%%% -*-BibTeX-*-
%%% ====================================================================
%%%  BibTeX-file{
%%%     author          = "Nelson H. F. Beebe",
%%%     version         = "1.58",
%%%     date            = "04 November 2025",
%%%     time            = "11:34:51 MDT",
%%%     filename        = "future-internet.bib",
%%%     address         = "University of Utah
%%%                        Department of Mathematics, 110 LCB
%%%                        155 S 1400 E RM 233
%%%                        Salt Lake City, UT 84112-0090
%%%                        USA",
%%%     telephone       = "+1 801 581 5254",
%%%     URL             = "https://www.math.utah.edu/~beebe",
%%%     checksum        = "38939 131410 732909 7072876",
%%%     email           = "beebe at math.utah.edu, beebe at acm.org,
%%%                        beebe at computer.org (Internet)",
%%%     codetable       = "ISO/ASCII",
%%%     keywords        = "BibTeX; bibliography; Future Internet",
%%%     license         = "public domain",
%%%     supported       = "yes",
%%%     docstring       = "This is a COMPLETE bibliography of the
%%%                        open-access journal Future Internet (CODEN
%%%                        none, ISSN 1999-5903), published by MDPI
%%%                        (Basel, Switzerland).
%%%
%%%                        Publication began with volume 1, number 1, in
%%%                        December 2009, and the journal appeared once
%%%                        in volume 1, quarterly in volumes 2--9, and
%%%                        since then, 12 times yearly.
%%%
%%%                        The journal has World-Wide Web sites at
%%%
%%%                            https://www.mdpi.com/journal/futureinternet
%%%                            https://www.mdpi.com/1999-5903/
%%%                            https://www.mdpi.com/1999-5903/<VOLUME>
%%%                            https://www.mdpi.com/1999-5903/<VOLUME>/<NUMBER>/
%%%
%%%                        At version 1.58, the year coverage looked
%%%                        like this:
%%%
%%%                             2009 (   6)    2015 (  30)    2021 ( 313)
%%%                             2010 (  32)    2016 (  55)    2022 ( 327)
%%%                             2011 (  21)    2017 (  82)    2023 ( 360)
%%%                             2012 (  61)    2018 ( 125)    2024 ( 360)
%%%                             2013 (  35)    2019 ( 246)    2025 ( 362)
%%%                             2014 (  36)    2020 ( 219)
%%%
%%%                             Article:       2670
%%%
%%%                             Total entries: 2670
%%%
%%%                        Data for the bibliography has been collected
%%%                        primarily from the journal Web site.
%%%
%%%                        Numerous errors in the sources noted above
%%%                        have been corrected.   Spelling has been
%%%                        verified with the UNIX spell and GNU ispell
%%%                        programs using the exception dictionary
%%%                        stored in the companion file with extension
%%%                        .sok.
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%%%                        as name:year:abbrev, where name is the
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%%%                        year is a 4-digit number, and abbrev is a
%%%                        3-letter condensation of important title
%%%                        words. Citation tags were automatically
%%%                        generated by software developed for the
%%%                        BibNet Project.
%%%
%%%                        In this bibliography, entries are sorted in
%%%                        publication order, using ``bibsort -byvolume''.
%%%
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%%%                        checksum as the first value, followed by the
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%%%  }
%%% ====================================================================

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%%% ====================================================================
%%% Acknowledgement abbreviations:

@String{ack-nhfb = "Nelson H. F. Beebe,
                    University of Utah,
                    Department of Mathematics, 110 LCB,
                    155 S 1400 E RM 233,
                    Salt Lake City, UT 84112-0090, USA,
                    Tel: +1 801 581 5254,
                    e-mail: \path|beebe@math.utah.edu|,
                            \path|beebe@acm.org|,
                            \path|beebe@computer.org| (Internet),
                    URL: \path|https://www.math.utah.edu/~beebe/|"}

%%% ====================================================================
%%% Journal abbreviations:

@String{j-FUTURE-INTERNET       = "Future Internet"}

%%% ====================================================================
%%% Bibliography entries:

@Article{Hudson-Smith:2009:FI,
  author =       "Andrew Hudson-Smith",
  title =        "The Future {Internet}",
  journal =      j-FUTURE-INTERNET,
  volume =       "1",
  number =       "1",
  pages =        "1--2",
  day =          "17",
  month =        jul,
  year =         "2009",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi1010001",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:42 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/1/1/1",
  abstract =     "In 1995 technology analyst Gartner [1] developed a
                 hype cycle model for the adoption of technology. The
                 cycle comprises five stages from the initial technology
                 trigger through to a final plateau of productivity
                 along a with a peak of inflated expectations, a tough
                 of disillusionment and the slope of enlightenment. The
                 hype cycle is notable technique for plotting and
                 identifying waves of innovation and hype in technology
                 and digital communications. Yet, from where we stand,
                 we can see the waves of innovation becoming
                 increasingly shorter, the troughs less deep and the
                 peaks of expectations higher. The read-write
                 revolution, that is arguably known as Web 2.0, has
                 transformed our experience of using the Internet from a
                 source of information to a means of communication and
                 participation. It has introduced mirror worlds, the
                 cloud, wikitecture, social shaping, connected places,
                 folksonomies and many other terms that I am sure many
                 of us have used in recent grant applications and
                 papers. This is the here and now, all of these
                 technologies are past the technology trigger point and
                 rising up the peak of inflated expectations with a few
                 already heading towards the trough before becoming
                 mainstream and approaching mass adoption.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wheeler:2009:LSM,
  author =       "Steve Wheeler",
  title =        "Learning Space Mashups: Combining {Web 2.0} Tools to
                 Create Collaborative and Reflective Learning Spaces",
  journal =      j-FUTURE-INTERNET,
  volume =       "1",
  number =       "1",
  pages =        "3--13",
  day =          "13",
  month =        jul,
  year =         "2009",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi1010003",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:42 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/1/1/3",
  abstract =     "In this paper, Web 2.0 open content mashups or
                 combinations are explored. Two case studies of recent
                 initial teacher training programmes are reviewed where
                 blogs and wikis were blended to create new virtual
                 learning spaces. In two separate studies, students
                 offer their views about using these tools, and reflect
                 on the strengths and weaknesses of this approach. There
                 is also discussion about aggregation of content and a
                 theorization of how community and personal spaces can
                 create tension and conflict. A new `learning spaces'
                 model will be presented which aids visualization of the
                 processes, domains and territories that are brought
                 into play when content and Web 2.0 tools are mashed up
                 within the same space.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Data Mashups.",
}

@Article{Fiaidhi:2009:IMM,
  author =       "Jinan Fiaidhi and Sabah Mohammed and Lyle Chamarette
                 and David Thomas",
  title =        "Identifying Middlewares for Mashup Personal Learning
                 Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "1",
  number =       "1",
  pages =        "14--27",
  day =          "05",
  month =        aug,
  year =         "2009",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi1010014",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:42 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/1/1/14",
  abstract =     "The common understanding of e-learning has shifted
                 over the last decade from the traditional learning
                 objects portals to learning paradigms that enforces
                 constructivism, discovery learning and social
                 collaboration. Such type of learning takes place
                 outside the formal academic settings (e.g., seminars or
                 lectures) where a learning environment is created by
                 using some kind of web application mashup tools. The
                 use of these mashup tools moves the learning
                 environment further away from being a monolithic
                 platform towards providing an open set of learning
                 tools, an unrestricted number of actors, and an open
                 corpus of artifacts, either pre-existing or created by
                 the learning process - freely combinable and utilizable
                 by learners within their learning activities. However,
                 collaboration, mashup and contextualization can only be
                 supported through services, which can be created and
                 modified dynamically based on middlewares to suit the
                 current needs and situations of learners. This article
                 identifies middlewares suitable for creating effective
                 personal learning environment based on Web 2.0 mashup
                 tools. This article also proposed a general framework
                 for constructing such personal learning environments
                 based on Ambient Learning realized by learning agents
                 and the use of Enterprise Mashup servers.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Data Mashups.",
}

@Article{Batcheller:2009:MAG,
  author =       "James K. Batcheller and Bruce M. Gittings and Robert
                 I. Dunfey",
  title =        "A Method for Automating Geospatial Dataset Metadata",
  journal =      j-FUTURE-INTERNET,
  volume =       "1",
  number =       "1",
  pages =        "28--46",
  day =          "10",
  month =        nov,
  year =         "2009",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi1010028",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:42 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/1/1/28",
  abstract =     "Metadata have long been recognised as crucial to
                 geospatial asset management and discovery, and yet
                 undertaking their creation remains an unenviable task
                 often to be avoided. This paper proposes a practical
                 approach designed to address such concerns, decomposing
                 various data creation, management, update and
                 documentation process steps that are subsequently
                 leveraged to contribute towards metadata record
                 completion. Using a customised utility embedded within
                 a common GIS application, metadata elements are
                 computationally derived from an imposed feature
                 metadata standard, dataset geometry, an integrated
                 storage protocol and pre-prepared content, and
                 instantiated within a common geospatial discovery
                 convention. Yielding 27 out of a 32 total metadata
                 elements (or 15 out of 17 mandatory elements) the
                 approach demonstrably lessens the burden of metadata
                 authorship. It also encourages improved geospatial
                 asset management whilst outlining core requisites for
                 developing a more open metadata strategy not bound to
                 any particular application domain.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Metadata and Markup.",
}

@Article{Ebner:2009:CWM,
  author =       "Martin Ebner and Hermann Maurer",
  title =        "Can Weblogs and Microblogs Change Traditional
                 Scientific Writing?",
  journal =      j-FUTURE-INTERNET,
  volume =       "1",
  number =       "1",
  pages =        "47--58",
  day =          "18",
  month =        nov,
  year =         "2009",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi1010047",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:42 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/1/1/47",
  abstract =     "This paper describes a follow-up Web 2.0 approach to a
                 technology enhanced master course for students of Graz
                 University of Technology. The lecture ``Social Aspects
                 of Information Technology'' has a long tradition for
                 using new didactical scenarios as well as modern
                 e-Learning technologies. After using a blogosphere one
                 year ago, this year microblog channels helped to expand
                 the traditional lecture. Students choose (on a
                 voluntary basis) whether they want to participate in a
                 blogging/microblogging group instead of using
                 conventional methods called Scientific
                 Writer/Scientific Reviewer. This study addresses the
                 question whether this method can change the learning
                 outcome into a more reflective one. Furthermore,
                 peer-reviewing groups judge the quality of essays and
                 blog contributions. In this paper we examine if
                 microblogging can be an appropriate technology for
                 assisting the process. This publication comes to the
                 conclusion that an amazing potential and a new way to
                 work with information is opened when using
                 microblogging. Students seem to be more engaged,
                 reflective and critical in as much as they presented
                 much more personal statements and opinions than years
                 before.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Beemer:2009:MLR,
  author =       "Brandon Beemer and Dawn Gregg",
  title =        "Mashups: a Literature Review and Classification
                 Framework",
  journal =      j-FUTURE-INTERNET,
  volume =       "1",
  number =       "1",
  pages =        "59--87",
  day =          "22",
  month =        dec,
  year =         "2009",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi1010059",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:42 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/1/1/59",
  abstract =     "The evolution of the Web over the past few years has
                 fostered the growth of a handful of new technologies
                 (e.g. Blogs, Wiki's, Web Services). Recently web
                 mashups have emerged as the newest Web technology and
                 have gained lots of momentum and attention from both
                 academic and industry communities. Current mashup
                 literature focuses on a wide array of issues, which can
                 be partially explained by how new the topic is.
                 However, to date, mashup literature lacks an
                 articulation of the different subtopics of web mashup
                 research. This study presents a broad review of mashup
                 literature to help frame the 1subtopics in mashup
                 research.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Data Mashups.",
}

@Article{Beall:2010:MND,
  author =       "Jeffrey Beall",
  title =        "Metadata for Name Disambiguation and Collocation",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "1",
  pages =        "1--15",
  day =          "05",
  month =        jan,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2010001",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:44 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/1/1",
  abstract =     "Searching names of persons, families, and
                 organizations is often difficult in online databases
                 because different persons or organizations frequently
                 share the same name and because a single person's or
                 organization's name may appear in different forms in
                 various online documents. Databases and search engines
                 can use metadata as a tool to solve the problem of name
                 ambiguity and name variation in online databases. This
                 article describes the challenges names pose in
                 information retrieval and some emerging name metadata
                 databases that can help ameliorate the problems.
                 Effective name disambiguation and collocation increase
                 search precision and recall and can improve assessment
                 of scholarly work.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Metadata and Markup.",
}

@Article{Priscoli:2010:FCA,
  author =       "Francesco Delli Priscoli",
  title =        "A Fully Cognitive Approach for Future {Internet}",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "1",
  pages =        "16--29",
  day =          "22",
  month =        jan,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2010016",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:44 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/1/16",
  abstract =     "This paper deals with an autonomous cognitive network
                 management architecture which aims at achieving
                 inter-network (horizontal) and inter-layer (vertical)
                 cross-optimization. The proposed architecture is based
                 on the so-called Cognitive Managers transparently
                 embedded in properly selected network nodes. The core
                 of each Cognitive Manager are the so-called thinking
                 modules, which are in charge of taking consistent and
                 coordinated decisions according to a fully cognitive
                 approach. The thinking modules potentially avail of
                 information coming from both the transport and the
                 service/content layers of all networks and, based on
                 all this inter-layer and inter-network information,
                 take consistent and coordinated decisions impacting the
                 different layers, aiming at the overall inter-layer,
                 inter-network optimization.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future Network Architectures.",
}

@Article{Fiore:2010:SRR,
  author =       "Ugo Fiore",
  title =        "Selective Redundancy Removal: a Framework for Data
                 Hiding",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "1",
  pages =        "30--40",
  day =          "15",
  month =        feb,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2010030",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:44 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/1/30",
  abstract =     "Data hiding techniques have so far concentrated on
                 adding or modifying irrelevant information in order to
                 hide a message. However, files in widespread use, such
                 as HTML documents, usually exhibit high redundancy
                 levels, caused by code-generation programs. Such
                 redundancy may be removed by means of optimization
                 software. Redundancy removal, if applied selectively,
                 enables information hiding. This work introduces
                 Selective Redundancy Removal (SRR) as a framework for
                 hiding data. An example application of the framework is
                 given in terms of hiding information in HTML documents.
                 Non-uniformity across documents may raise alarms.
                 Nevertheless, selective application of optimization
                 techniques might be due to the legitimate use of
                 optimization software not supporting all the
                 optimization methods, or configured to not use all of
                 them.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security for Next Generation Wireless
                 and Decentralized Systems.",
}

@Article{Fuchs:2010:TFW,
  author =       "Christian Fuchs and Wolfgang Hofkirchner and Matthias
                 Schafranek and Celina Raffl and Marisol Sandoval and
                 Robert Bichler",
  title =        "Theoretical Foundations of the {Web}: Cognition,
                 Communication, and Co-Operation. Towards an
                 Understanding of {Web 1.0, 2.0, 3.0}",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "1",
  pages =        "41--59",
  day =          "19",
  month =        feb,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2010041",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:44 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/1/41",
  abstract =     "Currently, there is much talk of Web 2.0 and Social
                 Software. A common understanding of these notions is
                 not yet in existence. The question of what makes Social
                 Software social has thus far also remained
                 unacknowledged. In this paper we provide a theoretical
                 understanding of these notions by outlining a model of
                 the Web as a techno-social system that enhances human
                 cognition towards communication and co-operation.
                 According to this understanding, we identify three
                 qualities of the Web, namely Web 1.0 as a Web of
                 cognition, Web 2.0 as a Web of human communication, and
                 Web 3.0 as a Web of co-operation. We use the terms Web
                 1.0, Web 2.0, Web 3.0 not in a technical sense, but for
                 describing and characterizing the social dynamics and
                 information processes that are part of the Internet.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Benedetto:2010:DQE,
  author =       "Francesco Benedetto and Alberto Curcio and Gaetano
                 Giunta",
  title =        "Dynamic {QoS} Evaluation of Multimedia Contents in
                 Wireless Networks by {``Double-Boomerang''}
                 Watermarking",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "1",
  pages =        "60--73",
  day =          "08",
  month =        mar,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2010060",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:44 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/1/60",
  abstract =     "This work presents a cooperative network-aware
                 processing of multimedia content for dynamic quality of
                 service management in wireless IP networks. Our
                 technique can be also used for quality control in UMTS
                 environments, exploiting the tracing watermarking
                 recently introduced in literature. In this work, we use
                 the transmitted video-sequences to monitor the QoS in a
                 videoconference call. The video-sequence of every
                 active user travels on the communication link, one time
                 as video (transparent mode), one time as watermark
                 (hidden mode) describing a boomerang trajectory. The
                 results obtained through our simulation trials confirm
                 the validity of such approach. In fact, the advantages
                 of distributing the management process are (i) an
                 easier and more precise localization of the cause of
                 QoS problems, (ii) a better knowledge of local
                 situations, (iii) a lower complexity for a single QoS
                 agent and (iv) an increase in possible actions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue QoS in Wired and Wireless IP Networks.",
}

@Article{Ding:2010:MED,
  author =       "Lian Ding and Shaofeng Liu",
  title =        "Markup in Engineering Design: a Discourse",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "1",
  pages =        "74--95",
  day =          "11",
  month =        mar,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2010074",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:44 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/1/74",
  abstract =     "Today's engineering companies are facing unprecedented
                 competition in a global market place. There is now a
                 knowledge intensive shift towards whole product
                 lifecycle support, and collaborative environments. It
                 has become particularly important to capture
                 information, knowledge and experiences about previous
                 design and following stages during their product
                 lifecycle, so as to retrieve and reuse such information
                 in new and follow-on designs activities. Recently, with
                 the rapid development and adoption of digital
                 technologies, annotation and markup are becoming
                 important tools for information communication,
                 retrieval and management. Such techniques are being
                 increasingly applied to an array of applications and
                 different digital items, such as text documents, 2D
                 images and 3D models. This paper presents a
                 state-of-the-art review of recent research in markup
                 for engineering design, including a number of core
                 markup languages and main markup strategies. Their
                 applications and future utilization in engineering
                 design, including multi-viewpoint of product models,
                 capture of information and rationale across the whole
                 product lifecycle, integration of engineering design
                 processes, and engineering document management, are
                 comprehensively discussed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Metadata and Markup.",
}

@Article{Christin:2010:SWS,
  author =       "Delphine Christin and Parag S. Mogre and Matthias
                 Hollick",
  title =        "Survey on Wireless Sensor Network Technologies for
                 Industrial Automation: The Security and Quality of
                 Service Perspectives",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "2",
  pages =        "96--125",
  day =          "08",
  month =        apr,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2020096",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:44 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/2/96",
  abstract =     "Wireless Sensor Networks (WSNs) are gradually adopted
                 in the industrial world due to their advantages over
                 wired networks. In addition to saving cabling costs,
                 WSNs widen the realm of environments feasible for
                 monitoring. They thus add sensing and acting
                 capabilities to objects in the physical world and allow
                 for communication among these objects or with services
                 in the future Internet. However, the acceptance of WSNs
                 by the industrial automation community is impeded by
                 open issues, such as security guarantees and provision
                 of Quality of Service (QoS). To examine both of these
                 perspectives, we select and survey relevant WSN
                 technologies dedicated to industrial automation. We
                 determine QoS requirements and carry out a threat
                 analysis, which act as basis of our evaluation of the
                 current state-of-the-art. According to the results of
                 this evaluation, we identify and discuss open research
                 issues.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security for Next Generation Wireless
                 and Decentralized Systems.",
}

@Article{Maier:2010:QPT,
  author =       "Martin Maier and Navid Ghazisaidi",
  title =        "{QoS} Provisioning Techniques for Future
                 Fiber-Wireless ({FiWi}) Access Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "2",
  pages =        "126--155",
  day =          "29",
  month =        apr,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2020126",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:44 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/2/126",
  abstract =     "A plethora of enabling optical and wireless
                 access-metro network technologies have been emerging
                 that can be used to build future-proof bimodal
                 fiber-wireless (FiWi) networks. Hybrid FiWi networks
                 aim at providing wired and wireless quad-play services
                 over the same infrastructure simultaneously and hold
                 great promise to mitigate the digital divide and change
                 the way we live and work by replacing commuting with
                 teleworking. After overviewing enabling optical and
                 wireless network technologies and their QoS
                 provisioning techniques, we elaborate on enabling
                 radio-over-fiber (RoF) and radio-and-fiber (R\&F)
                 technologies. We describe and investigate new QoS
                 provisioning techniques for future FiWi networks,
                 ranging from traffic class mapping, scheduling, and
                 resource management to advanced aggregation techniques,
                 congestion control, and layer-2 path selection
                 algorithms.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue QoS in Wired and Wireless IP Networks.",
}

@Article{Taswell:2010:DIM,
  author =       "Carl Taswell",
  title =        "A Distributed Infrastructure for Metadata about
                 Metadata: The {HDMM} Architectural Style and
                 {PORTAL-DOORS} System",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "2",
  pages =        "156--189",
  day =          "01",
  month =        jun,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2020156",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:44 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/2/156",
  abstract =     "Both the IRIS-DNS System and the PORTAL-DOORS System
                 share a common architectural style for pervasive
                 metadata networks that operate as distributed metadata
                 management systems with hierarchical authorities for
                 entity registering and attribute publishing.
                 Hierarchical control of metadata redistribution
                 throughout the registry-directory networks constitutes
                 an essential characteristic of this architectural style
                 called Hierarchically Distributed Mobile Metadata
                 (HDMM) with its focus on moving the metadata for who
                 what where as fast as possible from servers in response
                 to requests from clients. The novel concept of
                 multilevel metadata about metadata has also been
                 defined for the PORTAL-DOORS System with the use of
                 entity, record, infoset, representation and message
                 metadata. Other new features implemented include the
                 use of aliases, priorities and metaresources.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Metadata and Markup.",
}

@Article{Ramstetter:2010:ASN,
  author =       "Jerry Rick Ramstetter and Yaling Yang and Danfeng
                 Yao",
  title =        "Applications and Security of Next-Generation,
                 User-Centric Wireless Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "3",
  pages =        "190--211",
  day =          "28",
  month =        jul,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2030190",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:45 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/3/190",
  abstract =     "Pervasive wireless systems have significantly improved
                 end-users' quality of life. As manufacturing costs
                 decrease, communications bandwidth increases, and
                 contextual information is made more readily available,
                 the role of next generation wireless systems in
                 facilitating users' daily activities will grow. Unique
                 security and privacy issues exist in these wireless,
                 context-aware, often decentralized systems. For
                 example, the pervasive nature of such systems allows
                 adversaries to launch stealthy attacks against them. In
                 this review paper, we survey several emergent personal
                 wireless systems and their applications. These systems
                 include mobile social networks, active implantable
                 medical devices, and consumer products. We explore each
                 system's usage of contextual information and provide
                 insight into its security vulnerabilities. Where
                 possible, we describe existing solutions for
                 defendingagainst these vulnerabilities. Finally, we
                 point out promising future research directions for
                 improving these systems' robustness and security",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security for Next Generation Wireless
                 and Decentralized Systems.",
}

@Article{Arkoulis:2010:MSC,
  author =       "Stamatios Arkoulis and Giannis F. Marias and Pantelis
                 A. Frangoudis and Jens Oberender and Alexandru Popescu
                 and Markus Fiedler and Hermann de Meer and George C.
                 Polyzos",
  title =        "Misbehavior Scenarios in Cognitive Radio Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "3",
  pages =        "212--237",
  day =          "29",
  month =        jul,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2030212",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:45 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/3/212",
  abstract =     "Recent advances in the fields of Cognitive Radio and
                 the proliferation of open spectrum access promise that
                 spectrum-agile wireless communication will be
                 widespread in the near future, and will bring
                 significant flexibility and potential utility
                 improvements for end users. With spectrum efficiency
                 being a key objective, most relevant research focuses
                 on smart coexistence mechanisms. However, wireless
                 nodes may behave selfishly and should be considered as
                 rational autonomous entities. Selfishness, pure malice
                 or even faulty equipment can lead to behavior that does
                 not conform to sharing protocols and etiquette. Thus,
                 there is a need to secure spectrum sharing mechanisms
                 against attacks in the various phases of the sharing
                 process. Identifying these attacks and possible
                 countermeasures is the focus of this work.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security for Next Generation Wireless
                 and Decentralized Systems.",
}

@Article{Granitzer:2010:OAS,
  author =       "Michael Granitzer and Vedran Sabol and Kow Weng Onn
                 and Dickson Lukose and Klaus Tochtermann",
  title =        "Ontology Alignment --- a Survey with Focus on Visually
                 Supported Semi-Automatic Techniques",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "3",
  pages =        "238--258",
  day =          "04",
  month =        aug,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2030238",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:45 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/3/238",
  abstract =     "Semantic technologies are of paramount importance to
                 the future Internet. The reuse and integration of
                 semantically described resources, such as data or
                 services, necessitates the bringing of ontologies into
                 mutual agreement. Ontology alignment deals with the
                 discovery of correspondences between concepts and
                 relations from different ontologies. Alignment provides
                 the key ingredient to semantic interoperability. This
                 paper gives an overview on the state of the art in the
                 field of visually supported semi-automatic alignment
                 techniques and presents recent trends and developments.
                 Particular attention is given to user interfaces and
                 visualization techniques supporting involvement of
                 humans in the alignment process. We derive and
                 summarize requirements for visual semi-automatic
                 alignment systems, provide an overview of existing
                 approaches, and discuss the possibilities for further
                 improvements and future research.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Metadata and Markup.",
}

@Article{Xie:2010:TFS,
  author =       "Iris Xie and Soohyung Joo",
  title =        "Tales from the Field: Search Strategies Applied in
                 {Web} Searching",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "3",
  pages =        "259--281",
  day =          "06",
  month =        aug,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2030259",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:45 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/3/259",
  abstract =     "In their web search processes users apply multiple
                 types of search strategies, which consist of different
                 search tactics. This paper identifies eight types of
                 information search strategies with associated cases
                 based on sequences of search tactics during the
                 information search process. Thirty-one participants
                 representing the general public were recruited for this
                 study. Search logs and verbal protocols offered rich
                 data for the identification of different types of
                 search strategies. Based on the findings, the authors
                 further discuss how to enhance web-based information
                 retrieval (IR) systems to support each type of search
                 strategy.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Information Behavior.",
}

@Article{Ho:2010:IVA,
  author =       "Yeh-Chin Ho and Yi-Bing Lin and Ren-Huang Liou and
                 Yuan-Kuang Tu",
  title =        "Implementing Value Added Applications in Next
                 Generation Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "3",
  pages =        "282--294",
  day =          "06",
  month =        aug,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2030282",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:45 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/3/282",
  abstract =     "One of the major issues in the future Internet is the
                 integration of telecom networks with the Internet. In
                 many countries, large Internet Service Providers (ISPs)
                 are also telecom operators that have been focusing on
                 providing Internet services through their telecom
                 networks with telecom-grade mechanisms. In this
                 article, we show that IP Multimedia Subsystem (IMS) is
                 a telecom-grade mechanism that addresses this important
                 issue. In Next Generation Network (NGN), IMS supports
                 IP-based multimedia services that can be accessed from
                 various wireless and wired access technologies through
                 fixed-mobile convergence. We show how to integrate
                 Internet Protocol Television (IPTV) with NGN/IMS to
                 offer enhanced IPTV services for subscribers with
                 set-top boxes or mobile phones. We specifically
                 describe the implementations of three services: weather
                 forecasts, short messages on TV screens and TV
                 shopping/food ordering for mobile users. Although these
                 services can be directly implemented in the Internet,
                 our commercial operation experiences indicate that the
                 NGN/IMS implementation has advantages in terms of
                 telecom-grade security, Quality of Service (QoS), and
                 flexible service creation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Network vs. Application Based Solutions
                 for NGN.",
}

@Article{Urushidani:2010:DRA,
  author =       "Shigeo Urushidani and Kensuke Fukuda and Michihiro
                 Koibuchi and Motonori Nakamura and Shunji Abe and
                 Yusheng Ji and Michihiro Aoki and Shigeki Yamada",
  title =        "Dynamic Resource Allocation and {QoS} Control
                 Capabilities of the {Japanese} Academic Backbone
                 Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "3",
  pages =        "295--307",
  day =          "09",
  month =        aug,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2030295",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:45 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/3/295",
  abstract =     "Dynamic resource control capabilities have become
                 increasingly important for academic networks that must
                 support big scientific research projects at the same
                 time as less data intensive research and educational
                 activities. This paper describes the dynamic resource
                 allocation and QoS control capabilities of the Japanese
                 academic backbone network, called SINET3, which
                 supports a variety of academic applications with a wide
                 range of network services. The article describes the
                 network architecture, networking technologies, resource
                 allocation, QoS control, and layer-1 bandwidth
                 on-demand services. It also details typical services
                 developed for scientific research, including the user
                 interface, resource control, and management functions,
                 and includes performance evaluations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue QoS in Wired and Wireless IP Networks.",
}

@Article{Mahfoudh:2010:EER,
  author =       "Saoucene Mahfoudh and Pascale Minet and Ichrak
                 Amdouni",
  title =        "Energy Efficient Routing and Node Activity Scheduling
                 in the {OCARI} Wireless Sensor Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "3",
  pages =        "308--340",
  day =          "17",
  month =        aug,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2030308",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:45 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/3/308",
  abstract =     "Sensor nodes are characterized by a small size, a low
                 cost, an advanced communication technology, but also a
                 limited amount of energy. Energy efficient strategies
                 are required in such networks to maximize network
                 lifetime. In this paper, we focus on a solution
                 integrating energy efficient routing and node activity
                 scheduling. The energy efficient routing we propose,
                 called EOLSR, selects the route and minimizes the
                 energy consumed by an end-to-end transmission, while
                 avoiding nodes with low residual energy. Simulation
                 results show that EOLSR outperforms the solution
                 selecting the route of minimum energy as well as the
                 solution based on node residual energy. Cross-layering
                 allows EOLSR to use information from the application
                 layer or the MAC layer to reduce its overhead and
                 increase network lifetime. Node activity scheduling is
                 based on the following observation: the sleep state is
                 the least power consuming state. So, to schedule node
                 active and sleeping periods, we propose SERENA that
                 colors all network nodes using a small number of
                 colors, such that two nodes with the same color can
                 transmit without interfering. The node color is mapped
                 into a time slot during which the node can transmit.
                 Consequently, each node is awake during its slot and
                 the slots of its one-hop neighbors, and sleeps in the
                 remaining time. We evaluate SERENA benefits obtained in
                 terms of bandwidth, delay and energy. We also show how
                 cross-layering with the application layer can improve
                 the end-to-end delays for data gathering
                 applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Networked Sensors and Actuators.",
}

@Article{Lux:2010:CGV,
  author =       "Mathias Lux and Arthur Pitman and Oge Marques",
  title =        "Can Global Visual Features Improve Tag Recommendation
                 for Image Annotation?",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "3",
  pages =        "341--362",
  day =          "27",
  month =        aug,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2030341",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:45 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/3/341",
  abstract =     "Recent advances in the fields of digital photography,
                 networking and computing, have made it easier than ever
                 for users to store and share photographs. However
                 without sufficient metadata, e.g., in the form of tags,
                 photos are difficult to find and organize. In this
                 paper, we describe a system that recommends tags for
                 image annotation. We postulate that the use of
                 low-level global visual features can improve the
                 quality of the tag recommendation process when compared
                 to a baseline statistical method based on tag
                 co-occurrence. We present results from experiments
                 conducted using photos and metadata sourced from the
                 Flickr photo website that suggest that the use of
                 visual features improves the mean average precision
                 (MAP) of the system and increases the system's ability
                 to suggest different tags, therefore justifying the
                 associated increase in complexity.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Topal:2010:TRA,
  author =       "Sebahattin Topal and Ismet Erkmen and Aydan M.
                 Erkmen",
  title =        "Towards the Robotic {``Avatar''}: An Extensive Survey
                 of the Cooperation between and within Networked Mobile
                 Sensors",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "3",
  pages =        "363--387",
  day =          "14",
  month =        sep,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2030363",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:45 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/3/363",
  abstract =     "Cooperation between networked mobile sensors, wearable
                 and sycophant sensor networks with parasitically
                 sticking agents, and also having human beings involved
                 in the loop is the ``Avatarization'' within the robotic
                 research community, where all networks are connected
                 and where you can connect/disconnect at any time to
                 acquire data from a vast unstructured world. This paper
                 extensively surveys the networked robotic foundations
                 of this robotic biological ``Avatar'' that awaits us in
                 the future. Cooperation between networked mobile
                 sensors as well as cooperation of nodes within a
                 network are becoming more robust, fault tolerant and
                 enable adaptation of the networks to changing
                 environment conditions. In this paper, we survey and
                 comparatively discuss the current state of networked
                 robotics via their critical application areas and their
                 design characteristics. We conclude by discussing
                 future challenges.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Networked Sensors and Actuators.",
}

@Article{Do:2010:SQM,
  author =       "Viet Thi Minh Do and Lars Landmark and {\O}ivind
                 Kure",
  title =        "A Survey of {QoS} Multicast in Ad Hoc Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "3",
  pages =        "388--416",
  day =          "14",
  month =        sep,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2030388",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:45 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/3/388",
  abstract =     "This survey on Quality of Service (QoS) in multicast
                 ad hoc networks uses a framework based on the
                 mechanisms in three important elements: resource
                 estimations, multicast tree/mesh administration, and
                 multicast routing. Our contribution is an exploration
                 of the design space and an identification of areas that
                 have not been fully explored. We discuss the design
                 space of central mechanisms and classify proposed QoS
                 multicast schemes according to the mechanisms they
                 used. In addition, we summarize the scenarios used for
                 evaluating their performance. Furthermore, we identify
                 issues, mechanisms, and scenarios that have not been
                 fully investigated in existing works. The paper
                 provides a coherent understanding of design principles,
                 conceptual operation, and evaluated scenarios of
                 schemes designed for QoS multicast application in
                 mobile ad hoc networks (MANETs). It also outlines new
                 areas for future research in this field.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue QoS in Wired and Wireless IP Networks.",
}

@Article{Pinart:2010:ATD,
  author =       "Carolina Pinart",
  title =        "Anticipation of Traffic Demands to Guarantee {QoS} in
                 {IP}\slash Optical Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "3",
  pages =        "417--430",
  day =          "21",
  month =        sep,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2030417",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:45 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/3/417",
  abstract =     "Traffic in the Internet backbone is expected to grow
                 above a few Tbit/s in 2020. To cope with this,
                 operators are moving to IP/optical network
                 architectures, where IP is the convergence layer for
                 all services. On the other hand, the quality of service
                 (QoS) requirements of future applications encompasses
                 the individualization of services and the assurance of
                 stricter quality parameters such as latency, jitter or
                 capacity. In other words, future optical networks will
                 not only transport more IP data, but they will also
                 have to offer differentiated QoS requirements to
                 services. Finally, some emerging applications, e.g.,
                 grid computing, need greater flexibility in the usage
                 of network resources, which involves establishing and
                 releasing connections as if they were virtualized
                 resources controlled by other elements or layers. In
                 this context, traffic-driven lightpath provisioning and
                 service-plane approaches arise as very interesting
                 candidate solutions to solve the main challenges
                 described above. This work reviews the concepts of
                 service-oriented and self-managed networks and relates
                 them to propose an integrated approach to assure QoS by
                 offering flow-aware networking in the sense that
                 traffic demands will be anticipated in a suitable way,
                 lightpaths will be established taking into account QoS
                 information (i.e., impairments) and complex services
                 will be decomposed into optical connections so that the
                 above techniques can be employed to assure QoS for any
                 service.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue QoS in Wired and Wireless IP Networks.",
}

@Article{Kulatunga:2010:ENC,
  author =       "Chamil Kulatunga and Jesse Kielthy and Dmitri Botvich
                 and William Donnelly",
  title =        "Exploiting the In-Network Capabilities of Multicast to
                 Discover Proximate {IPTV} Channels",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "4",
  pages =        "431--445",
  day =          "29",
  month =        sep,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2040431",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:45 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/4/431",
  abstract =     "IPTV has become the next generation of television due,
                 in part, to its ability to support features that have
                 been lacking in conventional broadcasting-for example,
                 end-user interactivity, personalisation and
                 localisation. Providers are also searching for the most
                 efficient delivery methods to provide the greatest
                 amount of contents at the lowest cost. At present IPTV
                 uses IP multicast to deliver live TV channels in an
                 over-provisioned walled-garden network due to issues of
                 deploying multicast and QoS challenges in the public
                 Internet. However, IPTV is likely to shift into some
                 parts of the public Internet in the future as a managed
                 service. Multicast routing is performed on a
                 per-session destination-address basis so each router
                 maintains a table of all of the multicast addresses to
                 which the content is being forwarded. We exploit this
                 information to discover and join the in-progress
                 channels of geographically proximate users and to
                 create a new incentivised premium service in future
                 IPTV networks called ProxyTV. This approach is expected
                 to minimise network bandwidth requirements as it
                 enables ISPs to optimise bandwidth on their edge
                 networks. This becomes increasingly significant as TV
                 content consumes more and more bandwidth, especially
                 with the onset of HD and 3D capabilities. In this
                 paper, we have presented in detail the concept with the
                 results of a survey and an analysis of network traffic
                 to justify the proposed approach.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Network vs. Application Based Solutions
                 for NGN.",
}

@Article{So-In:2010:DRR,
  author =       "Chakchai So-In and Raj Jain and Abdel-Karim {Al
                 Tamimi}",
  title =        "Deficit Round {Robin} with Fragmentation Scheduling to
                 Achieve Generalized Weighted Fairness for Resource
                 Allocation in {IEEE 802.16e} Mobile {WiMAX} Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "4",
  pages =        "446--468",
  day =          "12",
  month =        oct,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2040446",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:45 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/4/446",
  abstract =     "Deficit Round Robin (DRR) is a fair packet-based
                 scheduling discipline commonly used in wired networks
                 where link capacities do not change with time. However,
                 in wireless networks, especially wireless broadband
                 networks, i.e., IEEE 802.16e Mobile WiMAX, there are
                 two main considerations violate the packet-based
                 service concept for DRR. First, the resources are
                 allocated per Mobile WiMAX frame. To achieve full frame
                 utilization, Mobile WiMAX allows packets to be
                 fragmented. Second, due to a high variation in wireless
                 channel conditions, the link/channel capacity can
                 change over time and location. Therefore, we introduce
                 a Deficit Round Robin with Fragmentation (DRRF) to
                 allocate resources per Mobile WiMAX frame in a fair
                 manner by allowing for varying link capacity and for
                 transmitting fragmented packets. Similar to DRR and
                 Generalized Processor Sharing (GPS), DRRF achieves
                 perfect fairness. DRRF results in a higher throughput
                 than DRR (80\% improvement) while causing less overhead
                 than GPS (8 times less than GPS). In addition, in
                 Mobile WiMAX, the quality of service (QoS) offered by
                 service providers is associated with the price paid.
                 This is similar to a cellular phone system; the users
                 may be required to pay air-time charges. Hence, we have
                 also formalized a Generalized Weighted Fairness (GWF)
                 criterion which equalizes a weighted sum of service
                 time units or slots, called temporal fairness, and
                 transmitted bytes, called throughput fairness, for
                 customers who are located in a poor channel condition
                 or at a further distance versus for those who are near
                 the base stations, or have a good channel condition. We
                 use DRRF to demonstrate the application of GWF. These
                 fairness criteria are used to satisfy basic
                 requirements for resource allocation, especially for
                 non real-time traffic. Therefore, we also extend DRRF
                 to support other QoS requirements, such as minimum
                 reserved traffic rate, maximum sustained traffic rate,
                 and traffic priority. For real-time traffic, i.e.,
                 video traffic, we compare the performance of DRRF with
                 deadline enforcement to that of Earliest Deadline First
                 (EDF). The results show that DRRF outperforms EDF
                 (higher achievable throughput under the promised delay
                 latency) and maintains fairness under an overload
                 scenario.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue QoS in Wired and Wireless IP Networks.",
}

@Article{Mahfoudh:2010:NCC,
  author =       "Saoucene Mahfoudh and Gerard Chalhoub and Pascale
                 Minet and Michel Misson and Ichrak Amdouni",
  title =        "Node Coloring and Color Conflict Detection in Wireless
                 Sensor Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "4",
  pages =        "469--504",
  day =          "13",
  month =        oct,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2040469",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:45 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/4/469",
  abstract =     "In wireless sensor networks, energy efficiency is
                 mainly achieved by making nodes sleep. In this paper,
                 we present the combination of SERENA, a new node
                 activity scheduling algorithm based on node coloring,
                 with TDMA/CA, a collision avoidance MAC protocol. We
                 show that the combination of these two protocols
                 enables substantial bandwidth and energy benefits for
                 both general and data gathering applications. As a
                 first contribution, we prove that the three-hop node
                 coloring problem is NP-complete. As a second
                 contribution, the overhead induced by SERENA during
                 network coloring is reduced, making possible the use of
                 these protocols even in dense networks with limited
                 bandwidth. The third contribution of this paper is to
                 show that applying any slot assignment algorithm with
                 spatial reuse based on node neighborhood without taking
                 into account link quality can lead to poor performances
                 because of collisions. The use of good quality links
                 will prevent this phenomenon. The fourth contribution
                 consists of optimizing end-to-end delays for data
                 gathering applications, by means of cross-layering with
                 the application. However, color conflicts resulting
                 from topology changes, mobility and late node arrivals
                 can give rise to collisions. As a fifth contribution,
                 we show how the MAC layer can detect color conflicts,
                 and cope with them at the cost of a slightly reduced
                 throughput. Then, we discuss the tradeoff between
                 requesting SERENA to solve the color conflicts and
                 dealing with them at the MAC layer, our third
                 contribution. The combination of SERENA and TDMA/CA is
                 evaluated through simulations on realistic
                 topologies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Networked Sensors and Actuators.",
}

@Article{Gottron:2010:SSM,
  author =       "Christian Gottron and Andr{\'e} K{\"o}nig and Ralf
                 Steinmetz",
  title =        "A Survey on Security in Mobile Peer-to-Peer
                 Architectures-Overlay-Based vs. Underlay-Based
                 Approaches",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "4",
  pages =        "505--532",
  day =          "13",
  month =        oct,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2040505",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:45 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/4/505",
  abstract =     "Mobile Ad hoc networks (MANET) and Peer-to-Peer (P2P)
                 networks share central characteristics such as their
                 distributed and decentralized nature. Combining both
                 networking paradigms results in a Mobile Peer-to-Peer
                 (MP2P) system that operates independently from a
                 preexisting infrastructure. Securing MP2P networks in
                 terms of availability and robustness as basic demands
                 in envisioned application scenarios like first
                 responder operations is a challenging task. In this
                 article, we present a survey of selected threats and of
                 state of the art countermeasures for MANETs and P2P
                 networks. Further, we discuss the efficiency of MANET
                 and P2P security mechanisms when applied in MP2P
                 networks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Network vs. Application Based Solutions
                 for NGN.",
}

@Article{Calegari:2010:OBI,
  author =       "Silvia Calegari and Gabriella Pasi",
  title =        "Ontology-Based Information Behaviour to Improve {Web}
                 Search",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "4",
  pages =        "533--558",
  day =          "18",
  month =        oct,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2040533",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:45 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/4/533",
  abstract =     "Web Search Engines provide a huge number of answers in
                 response to a user query, many of which are not
                 relevant, whereas some of the most relevant ones may
                 not be found. In the literature several approaches have
                 been proposed in order to help a user to find the
                 information relevant to his/her real needs on the Web.
                 To achieve this goal the individual Information
                 Behavior can been analyzed to 'keep' track of the
                 user's interests. Keeping information is a type of
                 Information Behavior, and in several works researchers
                 have referred to it as the study on what people do
                 during a search on the Web. Generally, the user's
                 actions (e.g., how the user moves from one Web page to
                 another, or her/his download of a document, etc.) are
                 recorded in Web logs. This paper reports on research
                 activities which aim to exploit the information
                 extracted from Web logs (or query logs) in personalized
                 user ontologies, with the objective to support the user
                 in the process of discovering Web information relevant
                 to her/his information needs. Personalized ontologies
                 are used to improve the quality of Web search by
                 applying two main techniques: query reformulation and
                 re-ranking of query evaluation results. In this paper
                 we analyze various methodologies presented in the
                 literature aimed at using personalized ontologies,
                 defined on the basis of the observation of Information
                 Behaviour to help the user in finding relevant
                 information.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Barradas:2010:ITA,
  author =       "Alvaro L. Barradas and Maria do Carmo R. Medeiros",
  title =        "An Intrinsic {TE} Approach for End-to-End {QoS}
                 Provisioning in {OBS} Networks Using Static
                 Load-Balanced Routing Strategies",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "4",
  pages =        "559--586",
  day =          "22",
  month =        oct,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2040559",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:45 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/4/559",
  abstract =     "Optical burst switching provides a feasible paradigm
                 for the next IP over optical backbones. However its
                 burst loss performance can be highly affected by burst
                 contention. In this paper we discuss traffic
                 engineering approaches for path selection with the
                 objective tominimize contention using only topological
                 information. The discussed strategies are based on
                 balancing the traffic across the network in order to
                 reduce congestion without incurring into link state
                 protocol penalties. The routing strategies are
                 evaluated by simulation on an optical burst switching
                 model specifically developed for the purpose with
                 OMNeT++. Results show that our strategies outperform
                 the traditionally used shortest path routing to an
                 extent that depends on the network connectivity.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue QoS in Wired and Wireless IP Networks.",
}

@Article{Kolios:2010:LAS,
  author =       "Panayiotis Kolios and Vasilis Friderikos and Katerina
                 Papadaki",
  title =        "Look-Ahead Strategies Based on Store-Carry and Forward
                 Relaying for Energy Efficient Cellular Communications",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "4",
  pages =        "587--602",
  day =          "04",
  month =        nov,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2040587",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:45 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/4/587",
  abstract =     "With the increasing availability of Internet type
                 services on mobile devices and the attractive flat rate
                 all-you-can-eat billing system, cellular
                 telecommunication networks are experiencing a
                 tremendous growth in data usage demand. However, there
                 are increasing concerns that current network deployment
                 trends (including more efficient radio access
                 techniques and increased spectrum allocation
                 strategies), will be unable to support the increased
                 Internet traffic in a sustainable way. The delay
                 tolerant nature of mobile Internet traffic allows for a
                 large degree of flexibility in optimizing network
                 performance to meet different design objectives and
                 it's a feature that has mostly gone unexplored by the
                 research community. In this paper, we introduce a novel
                 message forwarding mechanism in cellular networks that
                 benefits from the inherent delay tolerance of Internet
                 type services to provide flexible and adjustable
                 forwarding strategies for efficient network operation
                 while guaranteeing timely deliveries. By capitalizing
                 on the elasticity of message delivery deadlines and the
                 actual mobility of nodes inside the cell, considerable
                 performance gains can be achieved by physically
                 propagating information messages within the network.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Network vs. Application Based Solutions
                 for NGN.",
}

@Article{Islam:2010:NEI,
  author =       "Salekul Islam and Jean-Charles Gr{\'e}goire",
  title =        "Network Edge Intelligence for the Emerging
                 Next-Generation {Internet}",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "4",
  pages =        "603--623",
  day =          "05",
  month =        nov,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2040603",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:45 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/4/603",
  abstract =     "The success of the Content Delivery Networks (CDN) in
                 the recent years has demonstrated the increased
                 benefits of the deployment of some form of
                 ``intelligence'' within the network. Cloud computing,
                 on the other hand, has shown the benefits of economies
                 of scale and the use of a generic infrastructure to
                 support a variety of services. Following that trend, we
                 propose to move away from the smart terminal-dumb
                 network dichotomy to a model where some degree of
                 intelligence is put back into the network, specifically
                 at the edge, with the support of Cloud technology. In
                 this paper, we propose the deployment of an Edge Cloud,
                 which integrates a variety of user-side and server-side
                 services. On the user side, surrogate, an application
                 running on top of the Cloud, supports a virtual client.
                 The surrogate hides the underlying network
                 infrastructure from the user, thus allowing for
                 simpler, more easily managed terminals. Network side
                 services supporting delivery of and exploiting content
                 are also deployed on this infrastructure, giving the
                 Internet Service Providers (ISP) many opportunities to
                 become directly involved in content and service
                 delivery.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Graham:2010:BMM,
  author =       "Jim Graham and Greg Newman and Sunil Kumar and
                 Catherine Jarnevich and Nick Young and Alycia Crall and
                 Thomas J. Stohlgren and Paul Evangelista",
  title =        "Bringing Modeling to the Masses: a {Web} Based System
                 to Predict Potential Species Distributions",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "4",
  pages =        "624--634",
  day =          "11",
  month =        nov,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2040624",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:45 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/4/624",
  abstract =     "Predicting current and potential species distributions
                 and abundance is critical for managing invasive
                 species, preserving threatened and endangered species,
                 and conserving native species and habitats. Accurate
                 predictive models are needed at local, regional, and
                 national scales to guide field surveys, improve
                 monitoring, and set priorities for conservation and
                 restoration. Modeling capabilities, however, are often
                 limited by access to software and environmental data
                 required for predictions. To address these needs, we
                 built a comprehensive web-based system that: (1)
                 maintains a large database of field data; (2) provides
                 access to field data and a wealth of environmental
                 data; (3) accesses values in rasters representing
                 environmental characteristics; (4) runs statistical
                 spatial models; and (5) creates maps that predict the
                 potential species distribution. The system is available
                 online at www.niiss.org, and provides web-based tools
                 for stakeholders to create potential species
                 distribution models and maps under current and future
                 climate scenarios.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kos:2010:CGS,
  author =       "Alexander Kos and Hans-J{\"u}rgen Himmler",
  title =        "{CWM Global Search} --- The {Internet} Search Engine
                 for Chemists and Biologists",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "4",
  pages =        "635--644",
  day =          "03",
  month =        dec,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2040635",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:45 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/4/635",
  abstract =     "CWM Global Search is a meta-search engine allowing
                 chemists and biologists to search the major chemical
                 and biological databases on the Internet, by structure,
                 synonyms, CAS Registry Numbers and free text. A
                 meta-search engine is a search tool that sends user
                 requests to several other search engines and/or
                 databases and aggregates the results into a single list
                 or displays them according to their source [1]. CWM
                 Global Search is a web application that has many of the
                 characteristics of desktop applications (also known as
                 Rich Internet Application, RIA), and it runs on both
                 Windows and Macintosh platforms. The application is one
                 of the first RIA for scientists. The application can be
                 started using the URL
                 http://cwmglobalsearch.com/gsweb.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Eichler:2010:SSW,
  author =       "Frederik Eichler and Wolfgang Reinhardt",
  title =        "Simplifying the Scientific Writing and Review Process
                 with {SciFlow}",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "4",
  pages =        "645--661",
  day =          "06",
  month =        dec,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2040645",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:45 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/4/645",
  abstract =     "Scientific writing is an essential part of a student's
                 and researcher's everyday life. In this paper we
                 investigate the particularities of scientific writing
                 and explore the features and limitations of existing
                 tools for scientific writing. Deriving from this
                 analysis and an online survey of the scientific writing
                 processes of students and researchers at the University
                 of Paderborn, we identify key principles to simplify
                 scientific writing and reviewing. Finally, we introduce
                 a novel approach to support scientific writing with a
                 tool called SciFlow that builds on these principles and
                 state of the art technologies like cloud computing.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Guthle:2010:IAD,
  author =       "Martin G{\"u}thle and Jochen K{\"o}gel and Stefan Wahl
                 and Matthias Kaschub and Christian M. Mueller",
  title =        "Improving Anomaly Detection for Text-Based Protocols
                 by Exploiting Message Structures",
  journal =      j-FUTURE-INTERNET,
  volume =       "2",
  number =       "4",
  pages =        "662--669",
  day =          "21",
  month =        dec,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi2040662",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:45 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/2/4/662",
  abstract =     "Service platforms using text-based protocols need to
                 be protected against attacks. Machine-learning
                 algorithms with pattern matching can be used to detect
                 even previously unknown attacks. In this paper, we
                 present an extension to known Support Vector Machine
                 (SVM) based anomaly detection algorithms for the
                 Session Initiation Protocol (SIP). Our contribution is
                 to extend the amount of different features used for
                 classification (feature space) by exploiting the
                 structure of SIP messages, which reduces the false
                 positive rate. Additionally, we show how combining our
                 approach with attribute reduction significantly
                 improves throughput.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Semantics in the Future Internet.",
}

@Article{Kinkelin:2011:UTS,
  author =       "Holger Kinkelin and Ralph Holz and Heiko Niedermayer
                 and Simon Mittelberger and Georg Carle",
  title =        "On Using {TPM} for Secure Identities in Future Home
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "3",
  number =       "1",
  pages =        "1--13",
  day =          "07",
  month =        jan,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi3010001",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:46 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/3/1/1",
  abstract =     "Security should be integrated into future networks
                 from the beginning, not as an extension. Secure
                 identities and authentication schemes are an important
                 step to fulfill this quest. In this article, we argue
                 that home networks are a natural trust anchor for such
                 schemes. We describe our concept of home networks as a
                 universal point of reference for authentication, trust
                 and access control, and show that our scheme can be
                 applied to any next generation network. As home
                 networks are no safe place, we apply Trusted Computing
                 technology to prevent the abuse of identities, i.e.,
                 identity theft.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Semantics in the Future Internet.",
}

@Article{Hanka:2011:DPK,
  author =       "Oliver Hanka and Michael Eichhorn and Martin
                 Pfannenstein and J{\"o}rg Ebersp{\"a}cher and Eckehard
                 Steinbach",
  title =        "A Distributed Public Key Infrastructure Based on
                 Threshold Cryptography for the {HiiMap} Next Generation
                 {Internet} Architecture",
  journal =      j-FUTURE-INTERNET,
  volume =       "3",
  number =       "1",
  pages =        "14--30",
  day =          "01",
  month =        feb,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi3010014",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:46 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/3/1/14",
  abstract =     "In this article, a security extension for the HiiMap
                 Next Generation Internet Architecture is presented. We
                 regard a public key infrastructure which is integrated
                 into the mapping infrastructure of the
                 locator/identifier-split addressing scheme. The
                 security approach is based on Threshold Cryptography
                 which enables a sharing of keys among the mapping
                 servers. Hence, a more trustworthy and fair approach
                 for a Next Generation Internet Architecture as compared
                 to the state of the art approach is fostered.
                 Additionally, we give an evaluation based on IETF AAA
                 recommendations for security-related systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Semantics in the Future Internet.",
}

@Article{Rifa-Pous:2011:CEC,
  author =       "Helena Rif{\`a}-Pous and Jordi
                 Herrera-Joancomart{\'\i}",
  title =        "Computational and Energy Costs of Cryptographic
                 Algorithms on Handheld Devices",
  journal =      j-FUTURE-INTERNET,
  volume =       "3",
  number =       "1",
  pages =        "31--48",
  day =          "14",
  month =        feb,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi3010031",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:46 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/3/1/31",
  abstract =     "Networks are evolving toward a ubiquitous model in
                 which heterogeneous devices are interconnected.
                 Cryptographic algorithms are required for developing
                 security solutions that protect network activity.
                 However, the computational and energy limitations of
                 network devices jeopardize the actual implementation of
                 such mechanisms. In this paper, we perform a wide
                 analysis on the expenses of launching symmetric and
                 asymmetric cryptographic algorithms, hash chain
                 functions, elliptic curves cryptography and pairing
                 based cryptography on personal agendas, and compare
                 them with the costs of basic operating system
                 functions. Results show that although cryptographic
                 power costs are high and such operations shall be
                 restricted in time, they are not the main limiting
                 factor of the autonomy of a device.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue The Internet of Things.",
}

@Article{Petrie:2011:ECI,
  author =       "Charles Petrie",
  title =        "Enterprise Coordination on the {Internet}",
  journal =      j-FUTURE-INTERNET,
  volume =       "3",
  number =       "1",
  pages =        "49--66",
  day =          "17",
  month =        feb,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi3010049",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:46 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/3/1/49",
  abstract =     "Enterprises are now connected internally and
                 externally to other Enterprises via the Internet in
                 ways that are increasingly difficult to manage,
                 especially as these interconnections become more
                 dynamic. Current methods of coordinating the effects of
                 change as they propagate through these networks of
                 connections are not likely to scale. What is needed is
                 a new paradigm for how the Internet supports such
                 coordination. Indeed, the Internet should and could
                 provide fundamental coordination functions that are
                 missing today. In this paper, we describe how such a
                 ``Coordinated Internet'' would work (this paper is an
                 expanded version of [1]). The key functionality of a
                 Coordinated Internet would be that the Internet
                 actively watches what people do (analogous to search
                 completion on desktops today), correlates these
                 activities, and actively notifies people when and how
                 their current tasks affect and are affected by the
                 activities of other people. This would be accomplished
                 by standard coordination functions implemented as a
                 common Internet layer that can be used as a utility by
                 more specialized applications. Such a Coordinated
                 Internet would revolutionize enterprise management, for
                 all enterprises, large and small, corporate and
                 personal. For example, static workflows would become
                 obsolete for all but the the most routine processes.
                 Some solutions provide existence proofs of such a
                 coordination substrate, such as the Redux solution in
                 concurrent engineering, which we describe herein.
                 However, foundational research remains to be done in
                 the new field of Coordination Engineering in order to
                 reach the goal of a future Internet in which
                 coordination functions are fundamental.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Semantics in the Future Internet.",
}

@Article{Mikoczy:2011:ECN,
  author =       "Eugen Mik{\'o}czy and Ivan Kotuliak and Oskar van
                 Deventer",
  title =        "Evolution of the Converged {NGN} Service Platforms
                 Towards Future Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "3",
  number =       "1",
  pages =        "67--86",
  day =          "04",
  month =        mar,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi3010067",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:46 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/3/1/67",
  abstract =     "This article presents a comparison of main
                 characteristics of the Next Generation Networks (NGN)
                 and Future Generation Internet (FGI). The aim is to
                 discuss and compare two approaches to Future Networks
                 (FN) and services: the evolution of NGN, and the
                 revolutionary approach of a new FGI. We present both
                 frameworks from the services point of view as they are
                 delivered to the end-user, as well as from the
                 architectural point of view. We compare selected
                 properties of both approaches to explain commonalities
                 and differences. Their challenges are similar: managing
                 the quality of experience, mobility, security,
                 scalability and providing openness to applications.
                 Based on this comparison, we evaluate possible areas
                 for future convergence in the approach of the two
                 architectures to the Future Network concept. Our
                 analysis shows that despite their different
                 backgrounds, the internet's FGI and telco's NGN are not
                 that different after all. The convergence of the two
                 approaches therefore seems the only logical way
                 forward.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Network vs. Application Based Solutions
                 for NGN.",
}

@Article{Tonnies:2011:SOA,
  author =       "Sascha T{\"o}nnies and Benjamin K{\"o}hncke and
                 Patrick Hennig and Ingo Brunkhorst and Wolf-Tilo
                 Balke",
  title =        "A Service Oriented Architecture for Personalized
                 Universal Media Access",
  journal =      j-FUTURE-INTERNET,
  volume =       "3",
  number =       "2",
  pages =        "87--116",
  day =          "01",
  month =        apr,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi3020087",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:46 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/3/2/87",
  abstract =     "Multimedia streaming means delivering continuous data
                 to a plethora of client devices. Besides the actual
                 data transport, this also needs a high degree of
                 content adaptation respecting the end users' needs
                 given by content preferences, transcoding constraints,
                 and device capabilities. Such adaptations can be
                 performed in many ways, usually on the media server.
                 However, when it comes to content editing, like mixing
                 in subtitles or picture-in-picture composition, relying
                 on third party service providers may be necessary. For
                 economic reasons this should be done in a
                 service-oriented way, because a lot of adaptation
                 modules can be reused within different adaptation
                 workflows. Although service-oriented architectures have
                 become widely accepted in the Web community, the
                 multimedia environment is still dominated by monolithic
                 systems. The main reason is the insufficient support
                 for working with continuous data: generally the
                 suitability of Web services for handling complex data
                 types and state-full applications is still limited. In
                 this paper we discuss extensions of Web service
                 frameworks, and present a first implementation of a
                 service-oriented framework for media streaming and
                 digital item adaptation. The focus lies on the
                 technical realization of the services. Our experimental
                 results show the practicality of the actual deployment
                 of service-oriented multimedia frameworks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future Network Architectures.",
}

@Article{Chay:2011:UOT,
  author =       "Sengtha Chay and Nophea Sasaki",
  title =        "Using Online Tools to Assess Public Responses to
                 Climate Change Mitigation Policies in {Japan}",
  journal =      j-FUTURE-INTERNET,
  volume =       "3",
  number =       "2",
  pages =        "117--129",
  day =          "01",
  month =        apr,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi3020117",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:46 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/3/2/117",
  abstract =     "As a member of the Annex 1 countries to the Kyoto
                 Protocol of the United Nations Framework Convention on
                 Climate Change, Japan is committed to reducing 6\% of
                 the greenhouse gas emissions. In order to achieve this
                 commitment, Japan has undertaken several major
                 mitigation measures, one of which is the domestic
                 measure that includes ecologically friendly lifestyle
                 programs, utilizing natural energy, participating in
                 local environmental activities, and amending
                 environmental laws. Mitigation policies could be
                 achieved if public responses were strong. As the
                 internet has increasingly become an online platform for
                 sharing environmental information, public responses to
                 the need for reducing greenhouse gas emissions may be
                 assessed using available online tools. We used Google
                 Insights for Search, Google AdWords Keyword Tool, and
                 Google Timeline View to assess public responses in
                 Japan based on the interest shown for five search terms
                 that define global climate change and its mitigation
                 policies. Data on online search interests from January
                 04, 2004 to July 18, 2010 were analyzed according to
                 locations and categories. Our study suggests that the
                 search interests for the five chosen search terms
                 dramatically increased, especially when new mitigation
                 policies were introduced or when climate change related
                 events were organized. Such a rapid increase indicates
                 that the Japanese public strongly responds to climate
                 change mitigation policies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Glassey:2011:MIM,
  author =       "Olivier Glassey",
  title =        "Metadata For Identity Management of Population
                 Registers",
  journal =      j-FUTURE-INTERNET,
  volume =       "3",
  number =       "2",
  pages =        "130--143",
  day =          "18",
  month =        apr,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi3020130",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:46 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/3/2/130",
  abstract =     "A population register is an inventory of residents
                 within a country, with their characteristics (date of
                 birth, sex, marital status, etc.) and other
                 socio-economic data, such as occupation or education.
                 However, data on population are also stored in numerous
                 other public registers such as tax, land, building and
                 housing, military, foreigners, vehicles, etc.
                 Altogether they contain vast amounts of personal and
                 sensitive information. Access to public information is
                 granted by law in many countries, but this transparency
                 is generally subject to tensions with data protection
                 laws. This paper proposes a framework to analyze data
                 access (or protection) requirements, as well as a model
                 of metadata for data exchange.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Brown:2011:MPB,
  author =       "Katie Brown and Scott W. Campbell and Rich Ling",
  title =        "Mobile Phones Bridging the Digital Divide for Teens in
                 the {US}?",
  journal =      j-FUTURE-INTERNET,
  volume =       "3",
  number =       "2",
  pages =        "144--158",
  day =          "13",
  month =        may,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi3020144",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:46 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/3/2/144",
  abstract =     "In 2009, just 27\% of American teens with mobile
                 phones reported using their devices to access the
                 internet. However, teens from lower income families and
                 minority teens were significantly more likely to use
                 their phones to go online. Together, these surprising
                 trends suggest a potential narrowing of the digital
                 divide, offering internet access to those without other
                 means of going online. This is an important move, as,
                 in today's society, internet access is central to
                 active citizenship in general and teen citizenship in
                 particular. Yet the cost of this move toward equal
                 access is absorbed by those who can least afford it:
                 Teenagers from low income households. Using survey and
                 focus group data from a national study of ``Teens and
                 Mobile Phone Use'' (released by Pew and the University
                 of Michigan in 2010), this article helps identify and
                 explain this and other emergent trends for teen use (as
                 well as non-use) of the internet through mobile
                 phones.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Social Transformations from the Mobile
                 Internet.",
}

@Article{Mugridge:2011:EWB,
  author =       "Rick Mugridge and Mark Utting and David Streader",
  title =        "Evolving {Web}-Based Test Automation into Agile
                 Business Specifications",
  journal =      j-FUTURE-INTERNET,
  volume =       "3",
  number =       "2",
  pages =        "159--174",
  day =          "03",
  month =        jun,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi3020159",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:46 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/3/2/159",
  abstract =     "Usually, test automation scripts for a web application
                 directly mirror the actions that the tester carries out
                 in the browser, but they tend to be verbose and
                 repetitive, making them expensive to maintain and
                 ineffective in an agile setting. Our research has
                 focussed on providing tool-support for business-level,
                 example-based specifications that are mapped to the
                 browser level for automatic verification. We provide
                 refactoring support for the evolution of existing
                 browser-level tests into business-level specifications.
                 As resulting business rule tables may be incomplete,
                 redundant or contradictory, our tool provides feedback
                 on coverage.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Agile Practices.",
}

@Article{Sempere:2011:ADV,
  author =       "Andrew Sempere",
  title =        "Architecture and Design for Virtual Conferences: a
                 Case Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "3",
  number =       "3",
  pages =        "175--184",
  day =          "06",
  month =        jul,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi3030175",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:47 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/3/3/175",
  abstract =     "This paper presents a case study of the design issues
                 facing a large multi-format virtual conference. The
                 conference took place twice in two different years,
                 each time using an avatar-based 3D world with
                 spatialized audio including keynote, poster and social
                 sessions. Between year 1 and 2, major adjustments were
                 made to the architecture and design of the space,
                 leading to improvement in the nature of interaction
                 between the participants. While virtual meetings will
                 likely never supplant the effectiveness of face-to-face
                 meetings, this paper seeks to outline a few design
                 principles learned from this experience, which can be
                 applied generally to make computer mediated
                 collaboration more effective.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Virtual Worlds.",
}

@Article{Graham:2011:IDP,
  author =       "Roderick Graham and Danielle Taana Smith",
  title =        "{Internet} as Digital Practice: Examining Differences
                 in {African American} {Internet} Usage",
  journal =      j-FUTURE-INTERNET,
  volume =       "3",
  number =       "3",
  pages =        "185--203",
  day =          "20",
  month =        jul,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi3030185",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:47 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/3/3/185",
  abstract =     "This study assesses differences within the African
                 American population with respect to internet activity.
                 Using survey data, we find wide variations within the
                 population. While some segments of African Americans
                 are indeed less likely to perform certain activities on
                 the internet, we note that certain segments of the
                 African American population are reporting more internet
                 activity than other racial groups. These `haves' score
                 high not just in comparison to their African American
                 peers, but to the US American population as a whole. We
                 suggest a move away from the digital divide/digital
                 inequality models and a move towards thinking of
                 greater or lesser Information and Communication
                 Technology (ICT) usage as conditioned by the
                 instrumental needs of population groups. We term this a
                 digital practice model.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Schroth:2011:TTV,
  author =       "Olaf Schroth and Ellen Pond and Cam Campbell and Petr
                 Cizek and Stephen Bohus and Stephen R. J. Sheppard",
  title =        "Tool or Toy? {Virtual} Globes in Landscape Planning",
  journal =      j-FUTURE-INTERNET,
  volume =       "3",
  number =       "4",
  pages =        "204--227",
  day =          "20",
  month =        oct,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi3040204",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:47 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/3/4/204",
  abstract =     "Virtual globes, i.e., geobrowsers that integrate
                 multi-scale and temporal data from various sources and
                 are based on a globe metaphor, have developed into
                 serious tools that practitioners and various
                 stakeholders in landscape and community planning have
                 started using. Although these tools originate from
                 Geographic Information Systems (GIS), they have become
                 a different, potentially interactive and public tool
                 set, with their own specific limitations and new
                 opportunities. Expectations regarding their utility as
                 planning and community engagement tools are high, but
                 are tempered by both technical limitations and ethical
                 issues [1,2]. Two grassroots campaigns and a
                 collaborative visioning process, the Kimberley Climate
                 Adaptation Project case study (British Columbia),
                 illustrate and broaden our understanding of the
                 potential benefits and limitations associated with the
                 use of virtual globes in participatory planning
                 initiatives. Based on observations, questionnaires and
                 in-depth interviews with stakeholders and community
                 members using an interactive 3D model of regional
                 climate change vulnerabilities, potential impacts, and
                 possible adaptation and mitigation scenarios in
                 Kimberley, the benefits and limitations of virtual
                 globes as a tool for participatory landscape planning
                 are discussed. The findings suggest that virtual globes
                 can facilitate access to geospatial information, raise
                 awareness, and provide a more representative virtual
                 landscape than static visualizations. However,
                 landscape is not equally representative at all scales,
                 and not all types of users seem to benefit equally from
                 the tool. The risks of misinterpretation can be managed
                 by integrating the application and interpretation of
                 virtual globes into face-to-face planning processes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Internet and Landscapes.",
}

@Article{Paar:2011:LCM,
  author =       "Philip Paar and J{\"o}rg Rekittke",
  title =        "Low-Cost Mapping and Publishing Methods for Landscape
                 Architectural Analysis and Design in Slum-Upgrading
                 Projects",
  journal =      j-FUTURE-INTERNET,
  volume =       "3",
  number =       "4",
  pages =        "228--247",
  day =          "20",
  month =        oct,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi3040228",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:47 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/3/4/228",
  abstract =     "The research project ``Grassroots GIS'' focuses on the
                 development of low-cost mapping and publishing methods
                 for slums and slum-upgrading projects in Manila. In
                 this project smartphones, collaborative mapping and 3D
                 visualization applications are systematically employed
                 to support landscape architectural analysis and design
                 work in the context of urban poverty and urban informal
                 settlements. In this paper we focus on the description
                 of the developed methods and present preliminary
                 results of this work-in-progress.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Internet and Landscapes.",
}

@Article{Imhof:2011:NRK,
  author =       "Mark Imhof and Matthew Cox and Angela Fadersen and
                 Wayne Harvey and Sonia Thompson and David Rees and
                 Christopher Pettit",
  title =        "Natural Resource Knowledge and Information Management
                 via the {Victorian} Resources Online {Website}",
  journal =      j-FUTURE-INTERNET,
  volume =       "3",
  number =       "4",
  pages =        "248--280",
  day =          "09",
  month =        nov,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi3040248",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:47 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/3/4/248",
  abstract =     "Since 1997, the Victorian Resources Online (VRO)
                 website (http://www.dpi.vic.gov.au/vro) has been a key
                 means for the dissemination of landscape-based natural
                 resources information via the internet in Victoria,
                 Australia. The website currently consists of
                 approximately 11,000 web pages, including 1900 maps and
                 1000 downloadable documents. Information is provided at
                 a range of scales-from statewide and regional overviews
                 to more detailed catchment and sub-catchment levels. At
                 all these levels of generalisation, information is
                 arranged in an organisationally agnostic way around key
                 knowledge ``domains'' (e.g., soil, landform, water).
                 VRO represents a useful model for the effective
                 dissemination of a wide range of natural resources
                 information; relying on partnerships with key subject
                 matter experts and data custodians, including a
                 ``knowledge network'' of retired land resource
                 assessment specialists. In this paper, case studies are
                 presented that illustrate various approaches to
                 information and knowledge management with a focus on
                 presentation of spatially contexted soil and landscape
                 information at different levels of generalisation.
                 Examples are provided of adapting site-based
                 information into clickable maps that reveal
                 site-specific details, as well as ``spatialising'' data
                 from specialist internal databases to improve
                 accessibility to a wider audience. Legacy information
                 sources have also been consolidated and spatially
                 referenced. More recent incorporation of interactive
                 visualisation products (such as landscape panoramas,
                 videos and animations) is providing interactive rich
                 media content. Currently the site attracts an average
                 of 1190 user visits per day and user evaluation has
                 indicated a wide range of users, including students,
                 teachers, consultants, researchers and extension staff.
                 The wide range of uses for information and, in
                 particular, the benefits for natural resource
                 education, research and extension has also been
                 identified.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Internet and Landscapes.",
}

@Article{Parsons:2011:TDD,
  author =       "David Parsons and Ramesh Lal and Manfred Lange",
  title =        "Test Driven Development: Advancing Knowledge by
                 Conjecture and Confirmation",
  journal =      j-FUTURE-INTERNET,
  volume =       "3",
  number =       "4",
  pages =        "281--297",
  day =          "14",
  month =        dec,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi3040281",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:47 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/3/4/281",
  abstract =     "Test Driven Development (TDD) is a critical agile
                 software development practice that supports innovation
                 in short development cycles. However, TDD is one of the
                 most challenging agile practices to adopt because it
                 requires changes to work practices and skill sets. It
                 is therefore important to gain an understanding of TDD
                 through the experiences of those who have successfully
                 adopted this practice. We collaborated with an agile
                 team to provide this experience report on their
                 adoption of TDD, using observations and interviews
                 within the product development environment. This
                 article highlights a number of practices that underlie
                 successful development with TDD. To provide a
                 theoretical perspective that can help to explain how
                 TDD supports a positive philosophy of software
                 development, we have revised Northover et al.'s
                 conceptual framework, which is based on a four stage
                 model of agile development, to reinterpret Popper's
                 theory of conjecture and falsification in the context
                 of agile testing strategies. As a result of our
                 findings, we propose an analytical model for TDD in
                 agile software development which provides a theoretical
                 basis for further investigations into the role of TDD
                 and related practices.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Agile Practices.",
}

@Article{Li:2011:SOA,
  author =       "Haifeng Li and Bo Wu",
  title =        "A Service-Oriented Architecture for Proactive
                 Geospatial Information Services",
  journal =      j-FUTURE-INTERNET,
  volume =       "3",
  number =       "4",
  pages =        "298--318",
  day =          "19",
  month =        dec,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi3040298",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:47 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/3/4/298",
  abstract =     "The advances in sensor network, linked data, and
                 service-oriented computing has indicated a trend of
                 information technology, i.e., toward an open, flexible,
                 and distributed architecture. However, the existing
                 information technologies show a lack of effective
                 sharing, aggregation, and cooperation services to
                 handle the sensors, data, and processing resources to
                 fulfill user's complicated tasks in near real-time.
                 This paper presents a service-orientated architecture
                 for proactive geospatial information services (PGIS),
                 which integrates the sensors, data, processing, and
                 human services. PGIS is designed to organize,
                 aggregate, and co-operate services by composing small
                 scale services into service chains to meet the
                 complicated user requirements. It is a platform to
                 provide real-time or near real-time data collection,
                 storage, and processing capabilities. It is a flexible,
                 reusable, and scalable system to share and interoperate
                 geospatial data, information, and services. The
                 developed PGIS framework has been implemented and
                 preliminary experiments have been performed to verify
                 its performance. The results show that the basic
                 functions such as task analysis, managing sensors for
                 data acquisition, service composition, service chain
                 construction and execution are validated, and the
                 important properties of PGIS, including
                 interoperability, flexibility, and reusability, are
                 achieved.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Internet and Landscapes.",
}

@Article{Sharma:2011:OLO,
  author =       "Subhash Sharma and Christopher Pettit and Ian Bishop
                 and Pang Chan and Falak Sheth",
  title =        "An Online Landscape Object Library to Support
                 Interactive Landscape Planning",
  journal =      j-FUTURE-INTERNET,
  volume =       "3",
  number =       "4",
  pages =        "319--343",
  day =          "20",
  month =        dec,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi3040319",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:47 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/3/4/319",
  abstract =     "Using landscape objects with geo-visualisation tools
                 to create 3D virtual environments is becoming one of
                 the most prominent communication techniques to
                 understand landscape form, function and processes.
                 Geo-visualisation tools can also provide useful
                 participatory planning support systems to explore
                 current and future environmental issues such as
                 biodiversity loss, crop failure, competing pressures on
                 water availability and land degradation. These issues
                 can be addressed by understanding them in the context
                 of their locality. In this paper we discuss some of the
                 technologies which facilitate our work on the issues of
                 sustainability and productivity, and ultimately support
                 for planning and decision-making. We demonstrate an
                 online Landscape Object Library application with a
                 suite of geo-visualisation tools to support landscape
                 planning. This suite includes: a GIS based Landscape
                 Constructor tool, a modified version of a 3D game
                 engine SIEVE (Spatial Information Exploration and
                 Visualisation Environment) and an interactive touch
                 table display. By integrating the Landscape Object
                 Library with this suite of geo-visualisation tools, we
                 believe we developed a tool that can support a
                 diversity of landscape planning activities. This is
                 illustrated by trial case studies in biolink design,
                 whole farm planning and renewable energy planning. We
                 conclude the paper with an evaluation of our Landscape
                 Object Library and the suite of geographical tools, and
                 outline some further research directions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Internet and Landscapes.",
}

@Article{Formosa:2011:SIS,
  author =       "Saviour Formosa and Vincent Magri and Julia Neuschmid
                 and Manfred Schrenk",
  title =        "Sharing Integrated Spatial and Thematic Data: The
                 {CRISOLA} Case for {Malta} and the {European Project
                 Plan4all} Process",
  journal =      j-FUTURE-INTERNET,
  volume =       "3",
  number =       "4",
  pages =        "344--361",
  day =          "20",
  month =        dec,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi3040344",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:47 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/3/4/344",
  abstract =     "Sharing data across diverse thematic disciplines is
                 only the next step in a series of hard-fought efforts
                 to ensure barrier-free data availability. The Plan4all
                 project is one such effort, focusing on the
                 interoperability and harmonisation of spatial planning
                 data as based on the INSPIRE protocols. The aims are to
                 support holistic planning and the development of a
                 European network of public and private actors as well
                 as Spatial Data Infrastructure (SDI). The Plan4all and
                 INSPIRE standards enable planners to publish and share
                 spatial planning data. The Malta case tackled the wider
                 scenario for sharing of data, through the investigation
                 of the availability, transformation and dissemination
                 of data using geoportals. The study is brought to the
                 fore with an analysis of the approaches taken to ensure
                 that data in the physical and social domains are
                 harmonised in an internationally-established process.
                 Through an analysis of the criminological theme, the
                 Plan4all process is integrated with the social and land
                 use themes as identified in the CRISOLA model. The
                 process serves as a basis for the need to view sharing
                 as one part of the datacycle rather than an end in
                 itself: without a solid protocol the foundations have
                 been laid for the implementation of the datasets in the
                 social and crime domains.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue NeoGeography and WikiPlanning.",
}

@Article{Lai:2011:OSE,
  author =       "Sabrina Lai and Corrado Zoppi",
  title =        "An Ontology of the Strategic Environmental Assessment
                 of City Masterplans",
  journal =      j-FUTURE-INTERNET,
  volume =       "3",
  number =       "4",
  pages =        "362--378",
  day =          "20",
  month =        dec,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi3040362",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:47 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/3/4/362",
  abstract =     "Following a discussion on the semantics of the term
                 ``ontology'', this paper discusses some key points
                 concerning the ontology of the Strategic Environmental
                 Assessment procedure applied to city Masterplans, using
                 sustainability as a reference point. It also assumes
                 the implementation of Guidelines of the Autonomous
                 Region of Sardinia as an experimental context, with the
                 objective of proposing the SEA ontology as an important
                 contribution to improve SEA's effectiveness.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue NeoGeography and WikiPlanning.",
}

@Article{Coltekin:2011:HQG,
  author =       "Arzu Coltekin and Tumasch Reichenbacher",
  title =        "High Quality Geographic Services and Bandwidth
                 Limitations",
  journal =      j-FUTURE-INTERNET,
  volume =       "3",
  number =       "4",
  pages =        "379--396",
  day =          "20",
  month =        dec,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi3040379",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:47 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/3/4/379",
  abstract =     "In this paper we provide a critical overview of the
                 state of the art in human-centric intelligent data
                 management approaches for geographic visualizations
                 when we are faced with bandwidth limitations. These
                 limitations often force us to rethink how we design
                 displays for geographic visualizations. We need ways to
                 reduce the amount of data to be visualized and
                 transmitted. This is partly because modern instruments
                 effortlessly produce large volumes of data and Web 2.0
                 further allows bottom-up creation of rich and diverse
                 content. Therefore, the amount of information we have
                 today for creating useful and usable cartographic
                 products is higher than ever before. However, how much
                 of it can we really use online? To answer this
                 question, we first calculate the bandwidth needs for
                 geographic data sets in terms of waiting times. The
                 calculations are based on various data volumes
                 estimated by scholars for different scenarios.
                 Documenting the waiting times clearly demonstrates the
                 magnitude of the problem. Following this, we summarize
                 the current hardware and software solutions, then the
                 current human-centric design approaches trying to
                 address the constraints such as various screen sizes
                 and information overload. We also discuss a limited set
                 of social issues touching upon the digital divide and
                 its implications. We hope that our systematic
                 documentation and critical review will help researchers
                 and practitioners in the field to better understand the
                 current state of the art.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Internet and Landscapes.",
}

@Article{Neis:2012:SNE,
  author =       "Pascal Neis and Dennis Zielstra and Alexander Zipf",
  title =        "The Street Network Evolution of Crowdsourced Maps:
                 {OpenStreetMap} in {Germany} 2007--2011",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "1",
  pages =        "1--21",
  day =          "29",
  month =        dec,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4010001",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:47 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/1/1",
  abstract =     "The OpenStreetMap (OSM) project is a prime example in
                 the field of Volunteered Geographic Information (VGI).
                 Worldwide, several hundred thousand people are
                 currently contributing information to the ``free''
                 geodatabase. However, the data contributions show a
                 geographically heterogeneous pattern around the globe.
                 Germany counts as one of the most active countries in
                 OSM; thus, the German street network has undergone an
                 extensive development in recent years. The question
                 that remains is this: How does the street network
                 perform in a relative comparison with a commercial
                 dataset? By means of a variety of studies, we show that
                 the difference between the OSM street network for car
                 navigation in Germany and a comparable proprietary
                 dataset was only 9\% in June 2011. The results of our
                 analysis regarding the entire street network showed
                 that OSM even exceeds the information provided by the
                 proprietary dataset by 27\%. Further analyses show on
                 what scale errors can be reckoned with in the topology
                 of the street network, and the completeness of turn
                 restrictions and street name information. In addition
                 to the analyses conducted over the past few years,
                 projections have additionally been made about the point
                 in time by which the OSM dataset for Germany can be
                 considered ``complete'' in relative comparison to a
                 commercial dataset.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue NeoGeography and WikiPlanning.",
}

@Article{Stenliden:2012:HCW,
  author =       "Linnea Stenliden and Mikael Jern",
  title =        "How Can We Study Learning with Geovisual Analytics
                 Applied to Statistics?",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "1",
  pages =        "22--41",
  day =          "30",
  month =        dec,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4010022",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:47 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/1/22",
  abstract =     "It is vital to understand what kind of processes for
                 learning that Geovisual Analytics creates, as certain
                 activities and conditions are produced when employing
                 Geovisual Anlytic tools in education. To understand
                 learning processes created by Geovisual Analytics,
                 first requires an understanding of the interactions
                 between the technology, the workplace where the
                 learning takes place, and learners' specific knowledge
                 formation. When studying these types of interaction it
                 demands a most critical consideration from theoretical
                 perspectives on research design and methods. This paper
                 first discusses common, and then a more uncommon,
                 theoretical approach used within the fields of learning
                 with multimedia environments and Geovisual Analytics,
                 the socio-cultural theoretical perspective. The paper
                 next advocates this constructivist theoretical and
                 empirical perspective when studying learning with
                 multiple representational Geovisual Analytic tools. To
                 illustrate, an outline of a study made within this
                 theoretical tradition is offered. The study is
                 conducted in an educational setting where the Open
                 Statistics eXplorer platform is used. Discussion of our
                 study results shows that the socio-cultural perspective
                 has much to offer in terms of what kind of
                 understanding can be reached in conducting this kind of
                 studies. Therefore, we argue that empirical research to
                 analyze how specific communities use various Geovisual
                 Analytics to evaluate information is best positioned in
                 a socio-cultural theoretical perspective.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Geovisual Analytics.",
}

@Article{Lowell:2012:EAS,
  author =       "Kim Lowell and Lindsay Smith and Ian Miller and
                 Christopher Pettit and Eloise Seymour",
  title =        "{Extension Activity Support System (EASY)}: a
                 {Web}-Based Prototype for Facilitating Farm
                 Management",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "1",
  pages =        "42--64",
  day =          "04",
  month =        jan,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4010042",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:47 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/1/42",
  abstract =     "In response to disparate advances in delivering
                 spatial information to support agricultural extension
                 activities, the Extension Activity Support System
                 (EASY) project was established to develop a vision
                 statement and conceptual design for such a system based
                 on a national needs assessment. Personnel from across
                 Australia were consulted and a review of existing farm
                 information/management software undertaken to ensure
                 that any system that is eventually produced from the
                 EASY vision will build on the strengths of existing
                 efforts. This paper reports on the collaborative
                 consultative process undertaken to create the EASY
                 vision as well as the conceptual technical design and
                 business models that could support a fully functional
                 spatially enabled online system.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Internet and Landscapes.",
}

@Article{Montenegro:2012:LUP,
  author =       "Nuno Montenegro and Jorge C. Gomes and Paulo Urbano
                 and Jos{\'e} P. Duarte",
  title =        "A Land Use Planning Ontology: {LBCS}",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "1",
  pages =        "65--82",
  day =          "06",
  month =        jan,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4010065",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:47 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/1/65",
  abstract =     "Urban planning has a considerable impact on the
                 economic performance of cities and on the quality of
                 life of their populations. Efficiency at this level has
                 been hampered by the lack of integrated tools to
                 adequately describe urban space in order to formulate
                 appropriate design solutions. This paper describes an
                 ontology called LBCS-OWL2 specifically developed to
                 overcome this flaw, based on the Land Based
                 Classification Standards (LBCS), a comprehensive and
                 detailed land use standard to describe the different
                 dimensions of urban space. The goal is to provide
                 semantic and computer-readable land use descriptions of
                 geo-referenced spatial data. This will help to make
                 programming strategies available to those involved in
                 the urban development process. There are several
                 advantages to transferring a land use standard to an
                 OWL2 land use ontology: it is modular, it can be shared
                 and reused, it can be extended and data consistency
                 maintained, and it is ready for integration, thereby
                 supporting the interoperability of different urban
                 planning applications. This standard is used as a basic
                 structure for the ``City Information Modelling'' (CIM)
                 model developed within a larger research project called
                 City Induction, which aims to develop a tool for urban
                 planning and design.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue NeoGeography and WikiPlanning.",
}

@Article{Jurgenson:2012:WAM,
  author =       "Nathan Jurgenson",
  title =        "When Atoms Meet Bits: Social Media, the Mobile {Web}
                 and Augmented Revolution",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "1",
  pages =        "83--91",
  day =          "23",
  month =        jan,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4010083",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:47 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/1/83",
  abstract =     "The rise of mobile phones and social media may come to
                 be historically coupled with a growing atmosphere of
                 dissent that is enveloping much of the globe. The Arab
                 Spring, UK Riots, Occupy and many other protests and
                 so-called ``flash-mobs'' are all massive gatherings of
                 digitally-connected individuals in physical space; and
                 they have recently become the new normal. The primary
                 role of technology in producing this atmosphere has, in
                 part, been to effectively link the on and the offline.
                 The trend to view these as separate spaces, what I call
                 ``digital dualism'', is faulty. Instead, I argue that
                 the digital and physical enmesh to form an ``augmented
                 reality''. Linking the power of the digital-creating
                 and disseminating networked information-with the power
                 of the physical-occupying geographic space with
                 flesh-and-blood bodies-is an important part of why we
                 have this current flammable atmosphere of augmented
                 revolution.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Social Transformations from the Mobile
                 Internet.",
}

@Article{Anisetti:2012:WSA,
  author =       "Marco Anisetti and Claudio A. Ardagna and Ernesto
                 Damiani and Fulvio Frati and Hausi A. M{\"u}ller and
                 Atousa Pahlevan",
  title =        "{Web} Service Assurance: The Notion and the Issues",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "1",
  pages =        "92--109",
  day =          "14",
  month =        feb,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4010092",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:47 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/1/92",
  abstract =     "Web service technology provides basic infrastructure
                 for deploying collaborative business processes. Web
                 Service security standards and protocols aim to provide
                 secure communication and conversation between service
                 providers and consumers. Still, for a client calling a
                 Web service it is difficult to ascertain that a
                 particular service instance satisfies-at execution
                 time-specific non-functional properties. In this paper
                 we introduce the notion of certified Web service
                 assurance, characterizing how service consumers can
                 specify the set of security properties that a service
                 should satisfy. Also, we illustrate a mechanism to
                 re-check non-functional properties when the execution
                 context changes. To this end, we introduce the concept
                 of context-aware certificate, and describe a dynamic,
                 context-aware service discovery environment.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Recent Advances in Web Services.",
}

@Article{Fehling:2012:PBD,
  author =       "Christoph Fehling and Frank Leymann and Jochen
                 R{\"u}tschlin and David Schumm",
  title =        "Pattern-Based Development and Management of Cloud
                 Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "1",
  pages =        "110--141",
  day =          "15",
  month =        feb,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4010110",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:47 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/1/110",
  abstract =     "Cloud-based applications require a high degree of
                 automation regarding their IT resource management, for
                 example, to handle scalability or resource failures.
                 This automation is enabled by cloud providers offering
                 management interfaces accessed by applications without
                 human interaction. The properties of clouds, especially
                 pay-per-use billing and low availability of individual
                 resources, demand such a timely system management. We
                 call the automated steps to perform one of these
                 management tasks a ``management flow''. Because the
                 emerging behavior of the overall system is comprised of
                 many such management flows and is often hard to
                 predict, we propose defining abstract management flows,
                 describing common steps handling the management tasks.
                 These abstract management flows may then be refined for
                 each individual use case. We cover abstract management
                 flows describing how to make an application elastic,
                 resilient regarding IT resource failure, and how to
                 move application components between different runtime
                 environments. The requirements of these management
                 flows for handled applications are expressed using
                 architectural patterns that have to be implemented by
                 the applications. These dependencies result in abstract
                 management flows being interrelated with architectural
                 patterns in a uniform pattern catalog. We propose a
                 method by use of a catalog to guide application
                 managers during the refinement of abstract management
                 flows at the design stage of an application. Following
                 this method, runtime-specific management functionality
                 and management interfaces are used to obtain automated
                 management flows for a developed application.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Recent Advances in Web Services.",
}

@Article{Bunting:2012:PAE,
  author =       "Ben S. {Bunting, Jr.} and Jacob Hughes and Tim
                 Hetland",
  title =        "The Player as Author: Exploring the Effects of Mobile
                 Gaming and the Location-Aware Interface on
                 Storytelling",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "1",
  pages =        "142--160",
  day =          "17",
  month =        feb,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4010142",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:47 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/1/142",
  abstract =     "The mobile internet expands the immersive potential of
                 storytelling by introducing electronic games powered by
                 portable, location-aware interfaces. Mobile gaming has
                 become the latest iteration in a decades-long evolution
                 of electronic games that seek to empower the player not
                 just as an avatar in a gameworld but also as a
                 co-author of that gameworld, alongside the game's
                 original designers. Location-aware interfaces allow
                 players to implicate places in the physical world as
                 part of their gameworld (and vice versa) for the first
                 time. In addition to empowering the player as a
                 co-author in the process of constructing a compelling
                 gameworld, then, mobile games eschew linear narrative
                 structures in favor of a cooperative storytelling
                 process that is reliant in part on the player's
                 experience of place. While such an author-player
                 ``worldmaking'' approach to storytelling is not new,
                 mobile games evolve the process beyond what has yet
                 been possible within the technical and physical
                 constraints of the traditional video gaming format.
                 Location-aware interfaces allow mobile games to extend
                 the worldmaking process beyond the screen and into the
                 physical world, co-opting the player's sensory
                 experiences of real-world places as potential
                 storytelling tools. In our essay, we theorize the
                 unique storytelling potential of mobile games while
                 describing our experience attempting to harness that
                 potential through the design and implementation of our
                 hybrid-reality game University of Death.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Social Transformations from the Mobile
                 Internet.",
}

@Article{Oie:2012:SNU,
  author =       "Kjetil Vaage {\O}ie",
  title =        "Sensing the News: User Experiences when Reading
                 Locative News",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "1",
  pages =        "161--178",
  day =          "21",
  month =        feb,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4010161",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:47 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/1/161",
  abstract =     "This article focuses on user experiences on reading
                 location-aware news on the mobile platform and aims to
                 explore what experiences this kind of locative
                 journalism generates and how such experiences change
                 the users' social interaction with news. We produced a
                 specially designed mobile application and tailored news
                 stories specific to this project called LocaNews in
                 order to explore participants' relation to the content
                 in this journalistic format. The result is generated
                 through a field study and a questionnaire of 32 people
                 to find out how they experience the news presented in
                 this format. The user participants' responses are
                 analyzed based on their news experiences,
                 contextualizing places and their social interaction
                 with the news within this form of journalism. Results
                 showed that the local, semi-local and non-local user
                 approaches the locative news in a different manner, but
                 that the average user found this kind of news more
                 interesting and more informative than ordinary news.
                 The participants also have a problem identifying this
                 as journalism, rather than an information service.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Social Transformations from the Mobile
                 Internet.",
}

@Article{Sorschag:2012:FOI,
  author =       "Robert Sorschag",
  title =        "A Flexible Object-of-Interest Annotation Framework for
                 Online Video Portals",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "1",
  pages =        "179--215",
  day =          "22",
  month =        feb,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4010179",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:47 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/1/179",
  abstract =     "In this work, we address the use of object recognition
                 techniques to annotate what is shown where in online
                 video collections. These annotations are suitable to
                 retrieve specific video scenes for object related text
                 queries which is not possible with the manually
                 generated metadata that is used by current portals. We
                 are not the first to present object annotations that
                 are generated with content-based analysis methods.
                 However, the proposed framework possesses some
                 outstanding features that offer good prospects for its
                 application in real video portals. Firstly, it can be
                 easily used as background module in any video
                 environment. Secondly, it is not based on a fixed
                 analysis chain but on an extensive recognition
                 infrastructure that can be used with all kinds of
                 visual features, matching and machine learning
                 techniques. New recognition approaches can be
                 integrated into this infrastructure with low
                 development costs and a configuration of the used
                 recognition approaches can be performed even on a
                 running system. Thus, this framework might also benefit
                 from future advances in computer vision. Thirdly, we
                 present an automatic selection approach to support the
                 use of different recognition strategies for different
                 objects. Last but not least, visual analysis can be
                 performed efficiently on distributed, multi-processor
                 environments and a database schema is presented to
                 store the resulting video annotations as well as the
                 off-line generated low-level features in a compact
                 form. We achieve promising results in an annotation
                 case study and the instance search task of the TRECVID
                 2011 challenge.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Visual Information Retrieval.",
}

@Article{Exter:2012:UWT,
  author =       "Kristin Den Exter and Stephen Rowe and William Boyd
                 and David Lloyd",
  title =        "Using {Web 2.0} Technologies for Collaborative
                 Learning in Distance Education-Case Studies from an
                 {Australian} {University}",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "1",
  pages =        "216--237",
  day =          "07",
  month =        mar,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4010216",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:47 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/1/216",
  abstract =     "This paper explores the use of Web 2.0 technologies
                 for collaborative learning in a higher education
                 context. A review of the literature exploring the
                 strengths and weaknesses of Web 2.0 technology is
                 presented, and a conceptual model of a Web 2.0
                 community of inquiry is introduced. Two Australian case
                 studies are described, with an ex-poste evaluation of
                 the use of Web 2.0 tools. Conclusions are drawn as to
                 the potential for the use of Web 2.0 tools for
                 collaborative e-learning in higher education. In
                 particular, design and integration of Web 2.0 tools
                 should be closely related to curriculum intent and
                 pedagogical requirements, care must be taken to provide
                 clear guidance on both expected student activity and
                 learning expectations, and there is a clear need to
                 develop, support and encourage strong interaction both
                 between teachers and students, and amongst the students
                 themselves.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue NeoGeography and WikiPlanning.",
}

@Article{Martin:2012:RW,
  author =       "Ludger Martin and Thomas Gottron",
  title =        "Readability and the {Web}",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "1",
  pages =        "238--252",
  day =          "12",
  month =        mar,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4010238",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:47 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/1/238",
  abstract =     "Readability indices measure how easy or difficult it
                 is to read and comprehend a text. In this paper we look
                 at the relation between readability indices and web
                 documents from two different perspectives. On the one
                 hand we analyse how to reliably measure the readability
                 of web documents by applying content extraction
                 techniques and incorporating a bias correction. On the
                 other hand we investigate how web based corpus
                 statistics can be used to measure readability in a
                 novel and language independent way.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Selected Papers from ITA 11.",
}

@Article{Garside:2012:SMS,
  author =       "Debbie Garside and Arjun Ponnusamy and Steve Chan and
                 Richard Picking",
  title =        "Secure Military Social Networking and Rapid
                 Sensemaking in Domain Specific Concept Systems:
                 Research Issues and Future Solutions",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "1",
  pages =        "253--264",
  day =          "12",
  month =        mar,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4010253",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:47 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/1/253",
  abstract =     "This paper identifies the need for a secure military
                 social networking site and the underlying research
                 issues linked to the successful development of such
                 sites. The paper further proposes a solution to the
                 most basic issues by identifying and tackling known
                 potential security threats to military personnel and
                 their families. The paper further defines the base
                 platform for this development to facilitate rapid
                 sensemaking to inform critical communications and rapid
                 decision making processes during abrupt governance and
                 eco-system change, and how the plethora of information
                 (termed as Big Data) on social networking sites can be
                 analysed and harnessed. Underlying architectural
                 issues, efficiency and complexity are explored and
                 their future development is considered.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Selected Papers from ITA 11.",
}

@Article{Roche:2012:WBC,
  author =       "St{\'e}phane Roche and Boris Mericskay and Wided
                 Batita and Matthieu Bach and Mathieu Rondeau",
  title =        "{WikiGIS} Basic Concepts: {Web 2.0} for Geospatial
                 Collaboration",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "1",
  pages =        "265--284",
  day =          "13",
  month =        mar,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4010265",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:47 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/1/265",
  abstract =     "With the emergence of Web 2.0, new applications arise
                 and evolve into more interactive forms of collective
                 intelligence. These applications offer to both
                 professionals and citizens an open and expanded access
                 to geographic information. In this paper, we develop
                 the conceptual foundations of a new technology solution
                 called WikiGIS. WikiGIS's strength lies in its ability
                 to ensure the traceability of changes in
                 spatial-temporal geographic components (geometric
                 location and shape, graphics: iconography and
                 descriptive) generated by users. The final use case
                 highlights to what extent WikiGIS could be a relevant
                 and useful technological innovation in
                 Geocollaboration.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue NeoGeography and WikiPlanning.",
}

@Article{Mooney:2012:CHE,
  author =       "Peter Mooney and Padraig Corcoran",
  title =        "Characteristics of Heavily Edited Objects in
                 {OpenStreetMap}",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "1",
  pages =        "285--305",
  day =          "20",
  month =        mar,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4010285",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:47 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/1/285",
  abstract =     "This paper describes the results of an analysis of the
                 OpenStreetMap (OSM) database for the United Kingdom
                 (UK) and Ireland (correct to April 2011). 15, 640 OSM
                 ways (polygons and polylines), resulting in 316, 949
                 unique versions of these objects, were extracted and
                 analysed from the OSM database for the UK and Ireland.
                 In our analysis we only considered ``heavily edited''
                 objects in OSM: objects which have been edited 15 or
                 more times. Our results show that there is no strong
                 relationship between increasing numbers of contributors
                 to a given object and the number of tags (metadata)
                 assigned to it. 87\% of contributions/edits to these
                 objects are performed by 11\% of the total 4128
                 contributors. In 79\% of edits additional spatial data
                 (nodes) are added to objects. The results in this paper
                 do not attempt to evaluate the OSM data as good/poor
                 quality but rather informs potential consumers of OSM
                 data that the data itself is changing over time. In
                 developing a better understanding of the
                 characteristics of ``heavily edited'' objects there may
                 be opportunities to use historical analysis in working
                 towards quality indicators for OSM in the future.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Goggin:2012:DIM,
  author =       "Gerard Goggin",
  title =        "Driving the {Internet}: Mobile {Internets}, Cars, and
                 the Social",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "1",
  pages =        "306--321",
  day =          "20",
  month =        mar,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4010306",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:47 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/1/306",
  abstract =     "This paper looks at the tandem technologies of cars
                 and the Internet, and the new ways that they are
                 assembling the social with the mobile Internet. My
                 argument is two-fold: firstly, the advent of mobile
                 Internet in cars brings together new, widely divergent
                 trajectories of Internet; secondly, such developments
                 have social implications that vary widely depending on
                 whether or not we recognize the broader technological
                 systems and infrastructures, media practices, flows,
                 and mobilities in which vehicular mobile Internets are
                 being created.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Social Transformations from the Mobile
                 Internet.",
}

@Article{Nguyen:2012:BAS,
  author =       "Dinh Khoa Nguyen and Francesco Lelli and Mike P.
                 Papazoglou and Willem-Jan {Van den Heuvel}",
  title =        "Blueprinting Approach in Support of Cloud Computing",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "1",
  pages =        "322--346",
  day =          "21",
  month =        mar,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4010322",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:47 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/1/322",
  abstract =     "Current cloud service offerings, i.e.,
                 Software-as-a-service (SaaS), Platform-as-a-service
                 (PaaS) and Infrastructure-as-a-service (IaaS) offerings
                 are often provided as monolithic, one-size-fits-all
                 solutions and give little or no room for customization.
                 This limits the ability of Service-based Application
                 (SBA) developers to configure and syndicate offerings
                 from multiple SaaS, PaaS, and IaaS providers to address
                 their application requirements. Furthermore, combining
                 different independent cloud services necessitates a
                 uniform description format that facilitates the design,
                 customization, and composition. Cloud Blueprinting is a
                 novel approach that allows SBA developers to easily
                 design, configure and deploy virtual SBA payloads on
                 virtual machines and resource pools on the cloud. We
                 propose the Blueprint concept as a uniform abstract
                 description for cloud service offerings that may cross
                 different cloud computing layers, i.e., SaaS, PaaS and
                 IaaS. To support developers with the SBA design and
                 development in the cloud, this paper introduces a
                 formal Blueprint Template for unambiguously describing
                 a blueprint, as well as a Blueprint Lifecycle that
                 guides developers through the manipulation, composition
                 and deployment of different blueprints for an SBA.
                 Finally, the empirical evaluation of the blueprinting
                 approach within an EC's FP7 project is reported and an
                 associated blueprint prototype implementation is
                 presented.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Recent Advances in Web Services.",
}

@Article{Hanzl:2012:HGU,
  author =       "Ma{\l}gorzata Hanzl and Karol Dzik and Paulina
                 Kowalczyk and Krystian Kwieci{\'n}ski and Ewa
                 Stankiewicz and Agata L. Wierzbicka",
  title =        "Human Geomatics in Urban Design-Two Case Studies",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "1",
  pages =        "347--361",
  day =          "22",
  month =        mar,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4010347",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:47 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/1/347",
  abstract =     "The mapping of different aspects of urban phenomena
                 and their relation to the physical cityscape has been
                 greatly extended by the use of geomatics. The tradition
                 to base reasoning on ` understanding the world ' dates
                 from the time of Aristotle. The extension plan for
                 Barcelona (Eixample), developed by Cerd{\`a}, which
                 opened the era of modern urban planning, was preceded
                 by analyses of rich data, describing both detailed
                 demographic issues and physical structures. The
                 contemporary, postmodernist city planning continues
                 this tradition, although a shift towards analyses of
                 more human-related issues can be observed, covering,
                 inter alia, citizens' perception, cultural differences
                 and patterns of human activities with regard to
                 distinct social groups. The change towards a more
                 human-related perspective and the inclusion of urban
                 morphology analyses are direct consequences of this
                 trend. The required data may be gathered within a
                 crowd-sourcing participation process. According to
                 communicative planning theory, communication with the
                 wider public is indispensable in order to achieve the
                 best results, and can be realized with the use of
                 sophisticated IT tools. Evidence-based reasoning may be
                 supported by images of significant aesthetic values,
                 which inspire immediate reactions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue NeoGeography and WikiPlanning.",
}

@Article{Nilsen:2012:CBP,
  author =       "Line Lundvoll Nilsen",
  title =        "Collaboration between Professionals: The Use of
                 Videoconferencing for Delivering E-Health",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "2",
  pages =        "362--371",
  day =          "02",
  month =        apr,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4020362",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/2/362",
  abstract =     "This article explores the ways in which collaboration
                 between professionals using videoconferencing affects
                 the e-health delivered to patients. In Norway, general
                 practitioners (GPs) and specialists routinely hold
                 videoconferences. Observations of 42 VC meetings, each
                 lasting from 5 to 40 min, were analysed in terms of the
                 interactions. In addition, five semi-structured,
                 face-to-face interviews were conducted, each lasting
                 from 20 to 70 minutes. Statements were selected to
                 illustrate the content of the interactions and how
                 collaborative work affects the delivery of healthcare.
                 Successful collaborative work provides practitioners
                 with a new way of thinking: exchanging information and
                 knowledge between levels of care in order to provide
                 the best treatment for patients locally. The regularity
                 makes the collaborative work a two-way achievement. GPs
                 receive decision support and second opinions, and
                 specialists receive information and opportunities to
                 follow up. How the professionals manage their work
                 (i.e., collaborating) may benefit their patients. The
                 regular use of videoconferencing will furnish
                 professionals with enhanced resources for the meeting
                 of patients' demands in the future. Regularly informing
                 one another and exchanging knowledge, benefits the
                 professionals by providing increased certainty with
                 regard to their medical decisions, and it benefits the
                 patients because they will feel satisfied with the
                 competence of the specialists where they live.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future e-Health.",
}

@Article{Kennedy:2012:SAP,
  author =       "Sean Kennedy and Owen Molloy and Robert Stewart and
                 Paul Jacob and Maria Maleshkova and Frank Doheny",
  title =        "A Semantically Automated Protocol Adapter for Mapping
                 {SOAP} {Web} Services to {RESTful} {HTTP} Format to
                 Enable the {Web} Infrastructure, Enhance {Web} Service
                 Interoperability and Ease {Web} Service Migration",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "2",
  pages =        "372--395",
  day =          "11",
  month =        apr,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4020372",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/2/372",
  abstract =     "Semantic Web Services (SWS) are Web Service (WS)
                 descriptions augmented with semantic information. SWS
                 enable intelligent reasoning and automation in areas
                 such as service discovery, composition, mediation,
                 ranking and invocation. This paper applies SWS to a
                 previous protocol adapter which, operating within
                 clearly defined constraints, maps SOAP Web Services to
                 RESTful HTTP format. However, in the previous adapter,
                 the configuration element is manual and the latency
                 implications are locally based. This paper applies SWS
                 technologies to automate the configuration element and
                 the latency tests are conducted in a more realistic
                 Internet based setting.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Selected Papers from ITA 11.",
}

@Article{Zafiropoulos:2012:BCC,
  author =       "Kostas Zafiropoulos and Vasiliki Vrana and Dimitrios
                 Vagianos",
  title =        "Bloggers' Community Characteristics and Influence
                 within {Greek} Political Blogosphere",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "2",
  pages =        "396--412",
  day =          "19",
  month =        apr,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4020396",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/2/396",
  abstract =     "This paper investigates the properties of central or
                 core political blogs. They can be located as clusters
                 of blogs whose members have many incoming links. Other
                 blogs form clouds around them in the sense that they
                 link the core blogs. A case study records Greek
                 political blogs and their incoming links reported
                 through their blogrolls. The adjacency matrix from the
                 blogs' social network is analyzed and clusters are
                 located. Three of them, those with the larger numbers
                 of incoming links, may be considered to be central.
                 Next, four measures of influence are used to test the
                 influence of the central blogs. The findings suggest
                 that there are many kinds of central blogs, influential
                 and non-influential, and high influence does not always
                 involve high hyperlinking.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Government 2.0.",
}

@Article{Davies:2012:PEA,
  author =       "John N. Davies and Paul Comerford and Vic Grout",
  title =        "Principles of Eliminating Access Control Lists within
                 a Domain",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "2",
  pages =        "413--429",
  day =          "19",
  month =        apr,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4020413",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/2/413",
  abstract =     "The infrastructure of large networks is broken down
                 into areas that have a common security policy called a
                 domain. Security within a domain is commonly
                 implemented at all nodes. However this can have a
                 negative effect on performance since it introduces a
                 delay associated with packet filtering. When Access
                 Control Lists (ACLs) are used within a router for this
                 purpose then a significant overhead is introduced
                 associated with this process. It is likely that
                 identical checks are made at multiple points within a
                 domain prior to a packet reaching its destination.
                 Therefore by eliminating ACLs within a domain by
                 modifying the ingress/egress points with equivalent
                 functionality an improvement in the overall performance
                 can be obtained. This paper considers the effect of the
                 delays when using router operating systems offering
                 different levels of functionality. It considers factors
                 which contribute to the delay particularly due to ACLs
                 and by using theoretical principles modified by
                 practical calculation a model is created. Additionally
                 this paper provides an example of an optimized solution
                 which reduces the delay through network routers by
                 distributing the security rules to the ingress/egress
                 points of the domain without affecting the security
                 policy.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Selected Papers from ITA 11.",
}

@Article{Fernandez:2012:SPW,
  author =       "Eduardo B. Fernandez and Ola Ajaj and Ingrid Buckley
                 and Nelly Delessy-Gassant and Keiko Hashizume and Maria
                 M. Larrondo-Petrie",
  title =        "A Survey of Patterns for {Web} Services Security and
                 Reliability Standards",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "2",
  pages =        "430--450",
  day =          "20",
  month =        apr,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4020430",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/2/430",
  abstract =     "An important aspect for the acceptance of
                 Service-Oriented Architectures is having convenient
                 ways to help designers build secure applications.
                 Numerous standards define ways to apply security in web
                 services. However, these standards are rather complex
                 and sometimes overlap, which makes them hard to use and
                 may produce inconsistencies. Representing them as
                 patterns makes them easier to understand, to compare to
                 other patterns, to discover inconsistencies, and to use
                 them to build secure web services applications.
                 Security patterns abstract the key aspects of a
                 security mechanism and can thus be applied by
                 non-experts. We survey here our work on security
                 patterns for web services and their standards and we
                 put them in perspective with respect to each other and
                 to more fundamental patterns. We also consider other
                 patterns for web services security. All the patterns
                 described here have been previously published, we only
                 show here one of them in detail as an illustration of
                 our style for writing patterns. Our main purpose here
                 is to enumerate them, show their use, and show how they
                 relate to each other.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Recent Advances in Web Services.",
}

@Article{Pollino:2012:COS,
  author =       "Maurizio Pollino and Grazia Fattoruso and Luigi {La
                 Porta} and Antonio Bruno {Della Rocca} and Valentina
                 James",
  title =        "Collaborative Open Source Geospatial Tools and Maps
                 Supporting the Response Planning to Disastrous
                 Earthquake Events",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "2",
  pages =        "451--468",
  day =          "07",
  month =        may,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4020451",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/gnu.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/2/451",
  abstract =     "The latest improvements in geo-informatics offer new
                 opportunities in a wide range of territorial and
                 environmental applications. In this general framework,
                 a relevant issue is represented by earthquake early
                 warning and emergency management. This research work
                 presents the investigation and development of a simple
                 and innovative geospatial methodology and related
                 collaborative open source geospatial tools for
                 predicting and mapping the vulnerability to seismic
                 hazard in order to support the response planning to
                 disastrous events. The proposed geospatial methodology
                 and tools have been integrated into an open source
                 collaborative GIS system, designed and developed as an
                 integrated component of an earthquake early warning and
                 emergency management system.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue NeoGeography and WikiPlanning.",
}

@Article{Rosado:2012:SAM,
  author =       "David G. Rosado and Rafael G{\'o}mez and Daniel
                 Mellado and Eduardo Fern{\'a}ndez-Medina",
  title =        "Security Analysis in the Migration to Cloud
                 Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "2",
  pages =        "469--487",
  day =          "08",
  month =        may,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4020469",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/2/469",
  abstract =     "Cloud computing is a new paradigm that combines
                 several computing concepts and technologies of the
                 Internet creating a platform for more agile and
                 cost-effective business applications and IT
                 infrastructure. The adoption of Cloud computing has
                 been increasing for some time and the maturity of the
                 market is steadily growing. Security is the question
                 most consistently raised as consumers look to move
                 their data and applications to the cloud. We justify
                 the importance and motivation of security in the
                 migration of legacy systems and we carry out an
                 analysis of different approaches related to security in
                 migration processes to cloud with the aim of finding
                 the needs, concerns, requirements, aspects,
                 opportunities and benefits of security in the migration
                 process of legacy systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Recent Advances in Web Services.",
}

@Article{Muller:2012:DPM,
  author =       "Sebastian M{\"u}ller and Franziska Brecht and Benjamin
                 Fabian and Steffen Kunz and Dominik Kunze",
  title =        "Distributed Performance Measurement and Usability
                 Assessment of the {Tor} Anonymization Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "2",
  pages =        "488--513",
  day =          "15",
  month =        may,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4020488",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/2/488",
  abstract =     "While the Internet increasingly permeates everyday
                 life of individuals around the world, it becomes
                 crucial to prevent unauthorized collection and abuse of
                 personalized information. Internet anonymization
                 software such as Tor is an important instrument to
                 protect online privacy. However, due to the performance
                 overhead caused by Tor, many Internet users refrain
                 from using it. This causes a negative impact on the
                 overall privacy provided by Tor, since it depends on
                 the size of the user community and availability of
                 shared resources. Detailed measurements about the
                 performance of Tor are crucial for solving this issue.
                 This paper presents comparative experiments on Tor
                 latency and throughput for surfing to 500 popular
                 websites from several locations around the world during
                 the period of 28 days. Furthermore, we compare these
                 measurements to critical latency thresholds gathered
                 from web usability research, including our own user
                 studies. Our results indicate that without massive
                 future optimizations of Tor performance, it is unlikely
                 that a larger part of Internet users would adopt it for
                 everyday usage. This leads to fewer resources available
                 to the Tor community than theoretically possible, and
                 increases the exposure of privacy-concerned
                 individuals. Furthermore, this could lead to an
                 adoption barrier of similar privacy-enhancing
                 technologies for a Future Internet.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Privacy in the Future Internet.",
}

@Article{Nordfeldt:2012:YPV,
  author =       "Sam Nordfeldt and Carina Berter{\"o}",
  title =        "Young Patients' Views on the Open {Web 2.0} Childhood
                 Diabetes Patient Portal: a Qualitative Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "2",
  pages =        "514--527",
  day =          "18",
  month =        may,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4020514",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/2/514",
  abstract =     "Little is known about the views of young patients
                 themselves on interactive Web portal services provided
                 by pediatric practitioners. We aimed to explore their
                 perceptions of a real-world diabetes portal that offers
                 facts and contact with peers and practitioners; e.g.,
                 discussion forums, blog tools, self-care and treatment
                 information, research updates and news from local
                 practitioners. Twelve young patients (ages 12-21,
                 median 15 years), one boyfriend, 7 mothers and one
                 father each wrote an essay on their experience from use
                 of the portal. Their essays underwent qualitative
                 content analysis. A major theme was ``Helping and
                 facilitating daily life with diabetes'', the portal was
                 perceived as a place where contents are interesting,
                 inspiring and may trigger users' curiosity. There were
                 three subthemes; ``Ease of use in my everyday life,''
                 which includes the perception that the portal was
                 perceived as smooth and easy to enter and navigate
                 whenever needed; that information was easy to
                 understand for different groups of users. ``Support via
                 an exchange of experience,'' includes the ability to
                 contact peers being regarded advantageous. Some said
                 that just reading others' experiences can be helpful in
                 terms of persevering; children could find peers in the
                 same age group. ``Evidence based information,''
                 includes the perception of the portal being a useful
                 and trustworthy source of facts on e.g., physical
                 activity, blood glucose, medical devices, emotional
                 wellbeing, food and nutrition, and other aspects that
                 impact living with diabetes. Young users expressed
                 positive perceptions towards the interactive web
                 portal. Such services seem to have great potential for
                 supporting young patients and significant others -
                 intergrading for confidence.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future e-Health.",
}

@Article{Zafiropoulos:2012:AAG,
  author =       "Kostas Zafiropoulos and Ioannis Karavasilis and
                 Vasiliki Vrana",
  title =        "Assessing the Adoption of e-Government Services by
                 Teachers in {Greece}",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "2",
  pages =        "528--544",
  day =          "21",
  month =        may,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4020528",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/2/528",
  abstract =     "Technological developments and governments'
                 understanding of what citizens need usually determine
                 the design of public online services. For successful
                 implementation of e-Government services, governments
                 have to place the user in the center of future
                 developments, understand what citizens need and measure
                 what increases citizens' willingness to adopt
                 e-government services. The paper uses the Technology
                 Acceptance Model (TAM), the extended TAM, the Diffusion
                 of Innovations (DOI) theory and the important
                 determinants of user acceptance perceived risk and
                 trust, in order to describe teachers' behavioral
                 intensions to adopt e-Government services. A model
                 containing trust and risk, along with cognitive, social
                 and intrinsic factors is used to study the intentions
                 of e-Government use by Greek primary and secondary
                 education teachers. Two hundred and thirty teachers
                 responded to an online survey. Findings reveal that
                 cognitive and intrinsic factors have significant
                 effects on intentions to use e-Government websites.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Farman:2012:IST,
  author =       "Jason Farman",
  title =        "Introduction to the Social Transformations from the
                 Mobile {Internet} Special Issue",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "2",
  pages =        "545--550",
  day =          "23",
  month =        may,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4020545",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/2/545",
  abstract =     "The social transformations brought about by the mobile
                 internet are extensive. In discussing the broad range
                 of these transformations-positioned as a shift from
                 personal computing to pervasive computing-this
                 editorial elaborates on the key contributions addressed
                 by the articles in this special issue of Future
                 Internet. These articles touch on topics such as the
                 digital divide, the role of the mobile internet in
                 revolutions like the Arab Spring and the Occupy Wall
                 Street movement, the development of site-specific and
                 context-aware news, the incorporation of the internet
                 into existing technologies like the automobile, and the
                 utilization of the mobile internet to transform
                 everyday spaces into game spaces.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Social Transformations from the Mobile
                 Internet.",
}

@Article{Newell:2012:CSC,
  author =       "David A. Newell and Margaret M. Pembroke and William
                 E. Boyd",
  title =        "Crowd Sourcing for Conservation: {Web 2.0} a Powerful
                 Tool for Biologists",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "2",
  pages =        "551--562",
  day =          "24",
  month =        may,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4020551",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/2/551",
  abstract =     "The advent and adoption of Web 2.0 technologies offers
                 a powerful approach to enhancing the capture of
                 information in natural resource ecology, notably
                 community knowledge of species distributions. Such
                 information has previously been collected using, for
                 example, postal surveys; these are typically
                 inefficient, with low response rates, high costs, and
                 requiring respondents to be spatially literate. Here we
                 describe an example, using the Google Maps Application
                 Programming Interface, to discuss the opportunities
                 such tools provide to conservation biology. Toad
                 Tracker was created as a prototype to demonstrate the
                 utility of this technology to document the distribution
                 of an invasive vertebrate pest species, the cane toad,
                 within Australia. While the technological aspects of
                 this tool are satisfactory, manager resistance towards
                 its use raises issues around the public nature of the
                 technology, the collaborative (non-expert) role in data
                 collection, and data ownership. We conclude in
                 suggesting that, for such tools to be accepted by
                 non-innovation adopters, work is required on both the
                 technological aspects and, importantly, a cultural
                 change is required to create an environment of
                 acceptance of the shifting relationship between
                 authority, expertise and knowledge.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue NeoGeography and WikiPlanning.",
}

@Article{Rotondo:2012:UCP,
  author =       "Francesco Rotondo",
  title =        "The {U-City} Paradigm: Opportunities and Risks for
                 E-Democracy in Collaborative Planning",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "2",
  pages =        "563--574",
  day =          "05",
  month =        jun,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4020563",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/2/563",
  abstract =     "Volunteered Geographic Information (VGI) tools appear
                 to enhance the possibilities offered by a collaborative
                 approach to planning. The present paper analyzes both
                 the results of experiences of the author and of those
                 available in the literature, highlighting possible
                 advantages and disadvantages. After a brief
                 introduction to the meaning of e-democracy, the second
                 part focuses on the role of ICT in collaborative
                 planning, proceeding in the third part to an
                 illustration of an initial panorama of knowledge
                 gathered using ICT in such processes, while discussing
                 criticisms and opportunities. The fourth part discusses
                 the U-city paradigm as a driver of change in urban
                 planning participation processes. Research perspectives
                 are then outlined in the final part.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue NeoGeography and WikiPlanning.",
}

@Article{Goetz:2012:UCI,
  author =       "Marcus Goetz",
  title =        "Using Crowdsourced Indoor Geodata for the Creation of
                 a Three-Dimensional Indoor Routing {Web} Application",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "2",
  pages =        "575--591",
  day =          "06",
  month =        jun,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4020575",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/2/575",
  abstract =     "Routing services for outdoor areas are omnipresent and
                 also three-dimensional (3D) visualization is quite
                 common within this area. Recent research efforts are
                 now trying to adapt well known outdoor routing services
                 to complex indoor environments. However, most of the
                 current indoor routing systems only focus on
                 two-dimensional visualization, thus only one level can
                 be depicted. Especially multi-level routes therefore
                 lack visualization. Also, most of the (few) existing 3D
                 indoor routing services utilize proprietary software or
                 plugins, thus a widespread accessibility for those
                 services by using common computers or mobile devices is
                 not feasible. Therefore this paper describes the
                 development of a web-based 3D routing system based on a
                 new HTML extension. The visualization of rooms as well
                 as the computed routes is realized with XML3D. Since
                 this emerging technology is based on WebGL and will
                 likely be integrated into the HTML5 standard, the
                 developed system is already compatible with most common
                 browsers such as Google Chrome or Firefox. Another key
                 difference of the approach presented in this paper is
                 that all utilized data is actually crowdsourced geodata
                 from OpenStreetMap (OSM). Such data is collaboratively
                 collected by both amateurs and professionals and can be
                 used at no charge under the Open Data Commons Open
                 Database License (ODbL). Our research combines
                 user-generated geo content of the Web 2.0 with future
                 Internet technology for the provision of a ubiquitously
                 accessible 3D indoor routing application.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Garau:2012:FCP,
  author =       "Chiara Garau",
  title =        "Focus on Citizens: Public Engagement with Online and
                 Face-to-Face Participation --- a Case Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "2",
  pages =        "592--606",
  day =          "15",
  month =        jun,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4020592",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/2/592",
  abstract =     "The main objective of this paper is to focus on how an
                 integrated system based on Information Communication
                 Technology (ICT) and face-to-face communication can
                 increase participation in order to have a positive
                 effect on quality of life, plans and decisions, and to
                 discuss the many benefits which web-based public
                 participation can bring to the planning process through
                 a set of improvements to relations, quality and
                 structure of cities in general and in this case example
                 specifically. With the development of a transparent
                 support system for collaborative decision-making
                 processes, it is possible to identify a strategy for
                 addressing gaps to reach collaborative decisions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue NeoGeography and WikiPlanning.",
}

@Article{Le:2012:SHO,
  author =       "Quynh L{\^e} and Hoang Boi Nguyen and Tony Barnett",
  title =        "Smart Homes for Older People: Positive Aging in a
                 Digital World",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "2",
  pages =        "607--617",
  day =          "19",
  month =        jun,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4020607",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/2/607",
  abstract =     "Smart homes are homes with technologically advanced
                 systems to enable domestic task automation, easier
                 communication, and higher security. As an enabler of
                 health and well-being enhancement, smart homes have
                 been geared to accommodate people with special needs,
                 especially older people. This paper examines the
                 concept of ``smart home'' in a technologically driven
                 society and its multi-functional contribution to the
                 enhancement of older people's lives. Discussion then
                 focuses on the challenges in the use of smart homes
                 among older people such as accessibility and ethical
                 issues. Finally, some implications and recommendations
                 are provided.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future e-Health.",
}

@Article{Fernandez:2012:ISI,
  author =       "Eduardo B. Fernandez",
  title =        "Introduction to the Special Issue on Recent Advances
                 in {Web} Services",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "3",
  pages =        "618--620",
  day =          "27",
  month =        jun,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4030618",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/3/618",
  abstract =     "We have collected five papers describing different
                 aspects of web services and cloud computing. Cloud
                 computing is the next stage of application
                 interoperability and it is a logical extension of web
                 services, both approaches being a variety of
                 Service-Oriented Architecture. The papers cover
                 security, migration, certification, and application
                 development. Together, these papers provide a useful
                 panorama of some of the issues of these two
                 technologies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Recent Advances in Web Services.",
}

@Article{AbuKhousa:2012:HCO,
  author =       "Eman AbuKhousa and Nader Mohamed and Jameela
                 Al-Jaroodi",
  title =        "e-Health Cloud: Opportunities and Challenges",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "3",
  pages =        "621--645",
  day =          "04",
  month =        jul,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4030621",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/3/621",
  abstract =     "As the costs of healthcare services rise and
                 healthcare professionals are becoming scarce and hard
                 to find, it is imminent that healthcare organizations
                 consider adopting health information technology (HIT)
                 systems. HIT allows health organizations to streamline
                 many of their processes and provide services in a more
                 efficient and cost-effective manner. The latest
                 technological trends such as Cloud Computing (CC)
                 provide a strong infrastructure and offer a true
                 enabler for HIT services over the Internet. This can be
                 achieved on a pay-as-you-use model of the ``e-Health
                 Cloud'' to help the healthcare industry cope with
                 current and future demands yet keeping their costs to a
                 minimum. Despite its great potential, HIT as a CC model
                 has not been addressed extensively in the literature.
                 There are no apparent frameworks which clearly
                 encompass all viable schemes and interrelationships
                 between HIT and CC. Therefore, analyzing and comparing
                 the effectiveness of such schemes is important. In this
                 paper we introduce the concept of ``e-Health Cloud''
                 highlighting many of its constituents and proposing
                 building an e-health environment and elucidating many
                 of the challenges confronting the success of the
                 e-Health Cloud. We will also discuss different possible
                 solutions to address challenges such as security and
                 privacy.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future e-Health.",
}

@Article{Yerima:2012:AMB,
  author =       "Suleiman Y. Yerima and Gerard P. Parr and Sally I.
                 McClean and Philip J. Morrow",
  title =        "Adaptive Measurement-Based Policy-Driven {QoS}
                 Management with Fuzzy-Rule-based Resource Allocation",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "3",
  pages =        "646--671",
  day =          "04",
  month =        jul,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4030646",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/java2010.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/3/646",
  abstract =     "Fixed and wireless networks are increasingly
                 converging towards common connectivity with IP-based
                 core networks. Providing effective end-to-end resource
                 and QoS management in such complex heterogeneous
                 converged network scenarios requires unified, adaptive
                 and scalable solutions to integrate and co-ordinate
                 diverse QoS mechanisms of different access technologies
                 with IP-based QoS. Policy-Based Network Management
                 (PBNM) is one approach that could be employed to
                 address this challenge. Hence, a policy-based framework
                 for end-to-end QoS management in converged networks,
                 CNQF (Converged Networks QoS Management Framework) has
                 been proposed within our project. In this paper, the
                 CNQF architecture, a Java implementation of its
                 prototype and experimental validation of key elements
                 are discussed. We then present a fuzzy-based CNQF
                 resource management approach and study the performance
                 of our implementation with real traffic flows on an
                 experimental testbed. The results demonstrate the
                 efficacy of our resource-adaptive approach for
                 practical PBNM systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Selected Papers from ITA 11.",
}

@Article{Denning:2012:SWC,
  author =       "Dorothy E. Denning",
  title =        "{Stuxnet}: What Has Changed?",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "3",
  pages =        "672--687",
  day =          "16",
  month =        jul,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4030672",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/3/672",
  abstract =     "This paper considers the impact of Stuxnet on
                 cyber-attacks and cyber-defense. It first reviews
                 trends in cyber-weapons and how Stuxnet fits into these
                 trends. Because Stuxnet targeted an industrial control
                 system in order to wreak physical damage, the focus is
                 on weapons that target systems of that type and produce
                 physical effects. The paper then examines the impact of
                 Stuxnet on various domains of action where
                 cyber-attacks play a role, including state-level
                 conflict, terrorism, activism, crime, and pranks. For
                 each domain, it considers the potential for new types
                 of cyber-attacks, especially attacks against industrial
                 control systems, and whether such attacks would be
                 consistent with other trends in the domain. Finally,
                 the paper considers the impact of Stuxnet on
                 cyber-defense.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Aftermath of Stuxnet.",
}

@Article{Nilsen:2012:TPV,
  author =       "Line Lundvoll Nilsen and Terje Solvoll",
  title =        "Traditional Practice vs. New Tools and Routines in
                 Stroke Treatment",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "3",
  pages =        "688--699",
  day =          "06",
  month =        aug,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4030688",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/3/688",
  abstract =     "In Norway, it is a national goal to provide more
                 patients with thrombolytic treatment. A referring
                 hospital and a specialist hospital have implemented
                 videoconferencing (VC) equipment to share knowledge and
                 discuss stroke patients, regarding thrombolytic
                 treatment. VC has only been used four times within the
                 19 months that the service has been available. The
                 objective in this article is to increase the
                 understanding of the contradiction between the need for
                 knowledge-sharing through VC technology, as well as the
                 reasons for low frequency of use when discussing stroke
                 patients. Semi-structured interviews were conducted
                 with 13 professionals. The results illustrate how the
                 technology per se is not the reason for the low
                 frequency use. Health care is shaped by behavior,
                 traditional rules, standards and division of labor. By
                 using cultural historical activity theory (CHAT) as a
                 framework, we illustrate the importance of
                 understanding the historic way of performing an
                 activity to be able to expand the treatment activity in
                 the future.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future e-Health.",
}

@Article{Prandini:2012:RRA,
  author =       "Marco Prandini and Marco Ramilli",
  title =        "Raising Risk Awareness on the Adoption of {Web 2.0}
                 Technologies in Decision Making Processes",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "3",
  pages =        "700--718",
  day =          "09",
  month =        aug,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4030700",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/3/700",
  abstract =     "In the recent past, the so-called ``Web 2.0'' became a
                 powerful tool for decision making processes.
                 Politicians and managers, seeking to improve
                 participation, embraced this technology as if it simply
                 were a new, enhanced version of the WorldWideWeb,
                 better suited to retrieve information, opinions and
                 feedbacks from the general public on subjects like
                 laws, acts and policies. This approach was often naive,
                 neglecting the less-obvious aspects of the technology,
                 and thus bringing on significant security problems.
                 This paper shows how, in the end, the result could
                 easily be the opposite of what was desired. Malicious
                 attackers, in fact, could quite easily exploit the
                 vulnerabilities in these systems to hijack the process
                 and lead to wrong decisions, also causing the public to
                 lose trust in the systems themselves.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Government 2.0.",
}

@Article{Zafiropoulos:2012:CPA,
  author =       "Kostas Zafiropoulos",
  title =        "Connectivity Practices and Activity of {Greek}
                 Political Blogs",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "3",
  pages =        "719--736",
  day =          "14",
  month =        aug,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4030719",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/3/719",
  abstract =     "This paper uses Social Network Analysis indexes to
                 study Greek political blogs. The indexes describe
                 bloggers' community recommendations, centrality and
                 bloggers' attempt to form spheres of influence. Five
                 Social Network Analysis indexes are used: incoming
                 links, normalized betweenness, outgoing links, number
                 of 1-cliques a blog belongs to, and size of blog's
                 ego-network. By recording 127 Greek political blogs,
                 the paper finds that there are two distinct blog
                 performance properties regarding connectivity: Only a
                 few blogs serve as authority blogs having many incoming
                 links and centrality, while a few others try to expand
                 their influence territory by having many outgoing links
                 and forming larger 1-cliques and ego-networks. Next,
                 the paper associates the proposed indexes with blogs'
                 and users' community activity. Authority blogs present
                 high blog activity and users' community activity, as
                 well. These are recorded by large numbers of posts and
                 comments to the blog posts, respectively. It is shown
                 that blogs, which strive to expand their network by
                 using many outgoing links are more likely to link to
                 the authority blogs. Content analysis reveals that
                 authority blogs provide news and information and
                 promote discussion to a much higher degree compared to
                 the overall Greek political blogosphere.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Loskyll:2012:CBO,
  author =       "Matthias Loskyll and Ines Heck and Jochen Schlick and
                 Michael Schwarz",
  title =        "Context-Based Orchestration for Control of
                 Resource-Efficient Manufacturing Processes",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "3",
  pages =        "737--761",
  day =          "14",
  month =        aug,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4030737",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/3/737",
  abstract =     "The increasing competition between manufacturers, the
                 shortening of innovation cycles and the growing
                 importance of resource-efficient manufacturing demand a
                 higher versatility of factory automation.
                 Service-oriented approaches depict a promising
                 possibility to realize new control architectures by
                 encapsulating the functionality of mechatronic devices
                 into services. An efficient discovery, context-based
                 selection and dynamic orchestration of these services
                 are the key features for the creation of highly
                 adaptable manufacturing processes. We describe a
                 semantic service discovery and ad-hoc orchestration
                 system, which is able to react to new process variants
                 and changed contextual information (e.g., failure of
                 field devices, requirements on the consumption of
                 resources). Because a standardized vocabulary,
                 especially for the description of mechatronic
                 functionalities, is still missing in the manufacturing
                 domain, the semantic description of services, processes
                 and manufacturing plants as well as the semantic
                 interpretation of contextual information play an
                 important part.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Semantic Interoperability and Knowledge
                 Building.",
}

@Article{Subirats:2012:KRP,
  author =       "Laia Subirats and Luigi Ceccaroni and Felip Miralles",
  title =        "Knowledge Representation for Prognosis of Health
                 Status in Rehabilitation",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "3",
  pages =        "762--775",
  day =          "20",
  month =        aug,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4030762",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/3/762",
  abstract =     "In this article, key points are discussed concerning
                 knowledge representation for clinical decision support
                 systems in the domain of physical medicine and
                 rehabilitation. Information models, classifications and
                 terminologies, such as the ``virtual medical record''
                 (vMR), the ``international classification of
                 functioning, disability and health'' (ICF), the
                 ``international classification of diseases'' (ICD) and
                 the ``systematized nomenclature of medicine-clinical
                 terms'' (SNOMED CT), are used for knowledge integration
                 and reasoning. A system is described that supports the
                 measuring of functioning status, diversity, prognosis
                 and similarity between patients in the post-acute
                 stage, thus helping health professionals' prescription
                 of recommendations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future e-Health.",
}

@Article{Stojmenova:2012:AUC,
  author =       "Emilija Stojmenova and Bojan Imperl and Tomaz Zohar
                 and Dejan Dinevski",
  title =        "Adapted User-Centered Design: a Strategy for the
                 Higher User Acceptance of Innovative e-Health
                 Services",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "3",
  pages =        "776--787",
  day =          "27",
  month =        aug,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4030776",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/3/776",
  abstract =     "Being familiar with all the benefits of e-Health and
                 the strategic plan for the Slovenian health sector's
                 informatization, Telekom Slovenia and the Faculty of
                 Medicine from the University of Maribor, along with
                 other partners, have initiated an e-Health project. The
                 project group is developing various e-Health services
                 that are based on modern ICT (information and
                 communications technology) solutions and will be
                 available on several screens. In order to meet the
                 users' needs and expectations and, consequently,
                 achieve the high acceptance of e-Health services, the
                 user-centered design (UCD) approach was employed in the
                 e-Health project. However, during the research it was
                 found that conventional UCD methods are not completely
                 appropriate for older adults: the target population of
                 the e-Health services. That is why the selected UCD
                 methods were modified and adapted for older adults. The
                 modified UCD methods used in the research study are
                 presented in this paper. Using the results of the
                 adapted UCD methods, a prototype for a service named
                 MedReminder was developed. The prototype was evaluated
                 by a group of 12 study participants. The study
                 participants evaluated the MedReminder service as
                 acceptable with a good potential for a high adoption
                 rate among its target population, i.e., older adults.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future e-Health.",
}

@Article{Hunter:2012:TAE,
  author =       "Jane Hunter and Anna Gerber",
  title =        "Towards Annotopia-Enabling the Semantic
                 Interoperability of {Web}-Based Annotations",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "3",
  pages =        "788--806",
  day =          "30",
  month =        aug,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4030788",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/3/788",
  abstract =     "This paper describes the results of a collaborative
                 effort that has reconciled the Open Annotation
                 Collaboration (OAC) ontology and the Annotation
                 Ontology (AO) to produce a merged data model [the Open
                 Annotation (OA) data model] to describe Web-based
                 annotations-and hence facilitate the discovery, sharing
                 and re-use of such annotations. Using a number of case
                 studies that include digital scholarly editing, 3D
                 museum artifacts and sensor data streams, we evaluate
                 the OA model's capabilities. We also describe our
                 implementation of an online annotation server that
                 supports the storage, search and retrieval of
                 OA-compliant annotations across multiple applications
                 and disciplines. Finally we discuss outstanding problem
                 issues associated with the OA ontology, and the impact
                 that certain design decisions have had on the efficient
                 storage, indexing, search and retrieval of complex
                 structured annotations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Semantic Interoperability and Knowledge
                 Building.",
}

@Article{Schade:2012:SOI,
  author =       "Sven Schade and Frank Ostermann and Laura Spinsanti
                 and Werner Kuhn",
  title =        "Semantic Observation Integration",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "3",
  pages =        "807--829",
  day =          "03",
  month =        sep,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4030807",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/3/807",
  abstract =     "Although the integration of sensor-based information
                 into analysis and decision making has been a research
                 topic for many years, semantic interoperability has not
                 yet been reached. The advent of user-generated content
                 for the geospatial domain, Volunteered Geographic
                 Information (VGI), makes it even more difficult to
                 establish semantic integration. This paper proposes a
                 novel approach to integrating conventional sensor
                 information and VGI, which is exploited in the context
                 of detecting forest fires. In contrast to common
                 logic-based semantic descriptions, we present a formal
                 system using algebraic specifications to unambiguously
                 describe the processing steps from natural phenomena to
                 value-added information. A generic ontology of
                 observations is extended and profiled for forest fire
                 detection in order to illustrate how the sensing
                 process, and transformations between heterogeneous
                 sensing systems, can be represented as mathematical
                 functions and grouped into abstract data types. We
                 discuss the required ontological commitments and a
                 possible generalization.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Semantic Interoperability and Knowledge
                 Building.",
}

@Article{Bouzidi:2012:SWA,
  author =       "Khalil Riad Bouzidi and Bruno Fies and Catherine
                 Faron-Zucker and Alain Zarli and Nhan Le Thanh",
  title =        "{Semantic Web} Approach to Ease Regulation Compliance
                 Checking in Construction Industry",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "3",
  pages =        "830--851",
  day =          "11",
  month =        sep,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4030830",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/3/830",
  abstract =     "Regulations in the Building Industry are becoming
                 increasingly complex and involve more than one
                 technical area, covering products, components and
                 project implementations. They also play an important
                 role in ensuring the quality of a building, and to
                 minimize its environmental impact. Control or
                 conformance checking are becoming more complex every
                 day, not only for industrials, but also for
                 organizations charged with assessing the conformity of
                 new products or processes. This paper will detail the
                 approach taken by the CSTB (Centre Scientifique et
                 Technique du B{\^a}timent) in order to simplify this
                 conformance control task. The approach and the proposed
                 solutions are based on semantic web technologies. For
                 this purpose, we first establish a domain-ontology,
                 which defines the main concepts involved and the
                 relationships, including one based on OWL (Web Ontology
                 Language) [1]. We rely on SBVR (Semantics of Business
                 Vocabulary and Business Rules) [2] and SPARQL (SPARQL
                 Protocol and RDF Query Language) [3] to reformulate the
                 regulatory requirements written in natural language,
                 respectively, in a controlled and formal language. We
                 then structure our control process based on expert
                 practices. Each elementary control step is defined as a
                 SPARQL query and assembled into complex control
                 processes ``on demand'', according to the component
                 tested and its semantic definition. Finally, we
                 represent in RDF (Resource Description Framework) [4]
                 the association between the SBVR rules and SPARQL
                 queries representing the same regulatory constraints.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Semantic Interoperability and Knowledge
                 Building.",
}

@Article{Pileggi:2012:WSM,
  author =       "Salvatore F. Pileggi and Carlos Fernandez-Llatas and
                 Vicente Traver",
  title =        "When the Social Meets the Semantic: Social {Semantic
                 Web} or {Web} 2.5",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "3",
  pages =        "852--864",
  day =          "21",
  month =        sep,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4030852",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:48 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/3/852",
  abstract =     "The social trend is progressively becoming the key
                 feature of current Web understanding (Web 2.0). This
                 trend appears irrepressible as millions of users,
                 directly or indirectly connected through social
                 networks, are able to share and exchange any kind of
                 content, information, feeling or experience. Social
                 interactions radically changed the user approach.
                 Furthermore, the socialization of content around social
                 objects provides new unexplored commercial marketplaces
                 and business opportunities. On the other hand, the
                 progressive evolution of the web towards the Semantic
                 Web (or Web 3.0) provides a formal representation of
                 knowledge based on the meaning of data. When the social
                 meets semantics, the social intelligence can be formed
                 in the context of a semantic environment in which user
                 and community profiles as well as any kind of
                 interaction is semantically represented (Semantic
                 Social Web). This paper first provides a conceptual
                 analysis of the second and third version of the Web
                 model. That discussion is aimed at the definition of a
                 middle concept (Web 2.5) resulting in the convergence
                 and integration of key features from the current and
                 next generation Web. The Semantic Social Web (Web 2.5)
                 has a clear theoretical meaning, understood as the
                 bridge between the overused Web 2.0 and the not yet
                 mature Semantic Web (Web 3.0).",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Semantic Interoperability and Knowledge
                 Building.",
}

@Article{Groza:2012:PDL,
  author =       "Adrian Groza and Ioan Alfred Letia",
  title =        "Plausible Description Logic Programs for Stream
                 Reasoning",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "4",
  pages =        "865--881",
  day =          "17",
  month =        oct,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4040865",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:49 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/4/865",
  abstract =     "Sensor networks are estimated to drive the formation
                 of the future Internet, with stream reasoning
                 responsible for analysing sensor data. Stream reasoning
                 is defined as real time logical reasoning on large,
                 noisy, heterogeneous data streams, aiming to support
                 the decision process of large numbers of concurrent
                 querying agents. In this research we exploited
                 non-monotonic rule-based systems for handling
                 inconsistent or incomplete information and also
                 ontologies to deal with heterogeneity. Data is
                 aggregated from distributed streams in real time and
                 plausible rules fire when new data is available. The
                 advantages of lazy evaluation on data streams were
                 investigated in this study, with the help of a
                 prototype developed in Haskell.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Semantic Interoperability and Knowledge
                 Building.",
}

@Article{Gomes:2012:CDL,
  author =       "Rui Gomes and L{\'\i}gia Sousa",
  title =        "Contributions to the Development of Local e-Government
                 2.0",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "4",
  pages =        "882--899",
  day =          "22",
  month =        oct,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4040882",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:49 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/4/882",
  abstract =     "With the emergence of Web 2.0 (Blog, Wiki, RSS,
                 YouTube, Flickr, Podcast, Social Networks, and
                 Mashups), new ways of communicating, interacting and
                 being on the Web have arisen. These new communication
                 tools and strategies can radically change some specific
                 work processes in communities, such as the work
                 processes of an autarchy. Some authors emphasize the
                 advantages of using Web 2.0 tools in autarchies; thus,
                 we were interested in exploring the possibilities and
                 constraints of implementing these tools in our region
                 of Portugal, the Minho. Using a case study methodology,
                 we aimed to find out about the possibilities of
                 implementing Web 2.0 tools in autarchies through
                 exploring the interest and motivation of autarchic
                 collaborators in their use (our unit of analysis in
                 autarchies). Information was gathered with the help of
                 a questionnaire, the design of which was based on
                 previous exploratory interviews and applied to four
                 autarchic units in the Minho region. In each unit,
                 three different target-groups were surveyed
                 (Councilors, Information Systems (IS) Technicians, and
                 General Staff), so that we could triangulate the data.
                 Data analysis and results emphasized the interest and
                 motivation of the autarchies in using Web 2.0 tools, as
                 well as the main constraints that would be faced during
                 Web 2.0 implementation. It also allowed us to establish
                 some guidelines for adequate Web 2.0 implementation,
                 including an ``ideal'' profile of the person
                 responsible for the implementation process.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Government 2.0.",
}

@Article{Harrison:2012:COG,
  author =       "Teresa M. Harrison and Theresa A. Pardo and Meghan
                 Cook",
  title =        "Creating Open Government Ecosystems: a Research and
                 Development Agenda",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "4",
  pages =        "900--928",
  day =          "23",
  month =        oct,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4040900",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:49 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/4/900",
  abstract =     "In this paper, we propose to view the concept of open
                 government from the perspective of an ecosystem, a
                 metaphor often used by policy makers, scholars, and
                 technology gurus to convey a sense of the
                 interdependent social systems of actors, organizations,
                 material infrastructures, and symbolic resources that
                 can be created in technology-enabled,
                 information-intensive social systems. We use the
                 concept of an ecosystem to provide a framework for
                 considering the outcomes of a workshop organized to
                 generate a research and development agenda for open
                 government. The agenda was produced in discussions
                 among participants from the government (at the federal,
                 state, and local levels), academic and civil sector
                 communities at the Center for Technology in Government
                 (CTG) at the University at Albany, SUNY in April 2011.
                 The paper begins by discussing concepts central to
                 understanding what is meant by an ecosystem and some
                 principles that characterize its functioning. We then
                 apply this metaphor more directly to government,
                 proposing that policymakers engage in strategic
                 ecosystems thinking, which means being guided by the
                 goal of explicitly and purposefully constructing open
                 government ecosystems. From there, we present the
                 research agenda questions essential to the development
                 of this new view of government's interaction with users
                 and organizations. Our goal is to call attention to
                 some of the fundamental ways in which government must
                 change in order to evolve from outdated industrial
                 bureaucratic forms to information age networked and
                 interdependent systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Government 2.0.",
}

@Article{Hu:2012:SLP,
  author =       "Yuh-Jong Hu and Win-Nan Wu and Kua-Ping Cheng and
                 Ya-Ling Huang",
  title =        "Semantic Legal Policies for Data Exchange and
                 Protection across Super-Peer Domains in the Cloud",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "4",
  pages =        "929--954",
  day =          "25",
  month =        oct,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4040929",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:49 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/4/929",
  abstract =     "In semantic policy infrastructure, a Trusted Legal
                 Domain (TLD), designated as a Super-Peer Domain (SPD),
                 is a legal cage model used to circumscribe the legal
                 virtual boundary of data disclosure and usage in the
                 cloud. Semantic legal policies in compliance with the
                 law are enforced at the super-peer within an SPD to
                 enable Law-as-a-Service (LaaS) for cloud service
                 providers. In addition, cloud users could query
                 fragmented but protected outsourcing cloud data from a
                 law-aware super-peer, where each query is also
                 compliant with the law. Semantic legal policies are
                 logic-based formal policies, which are shown to be a
                 combination of OWL-DL ontologies and stratified Datalog
                 rules with negation, i.e., so-called non-monotonic
                 cq-programs, for policy representation and enforcement.
                 An agent at the super-peer is a unique law-aware
                 guardian that provides protected data integration
                 services for its peers within an SPD. Furthermore,
                 agents at the super-peers specify how law-compliant
                 legal policies are unified with each other to provide
                 protected data exchange services across SPDs in the
                 semantic data cloud.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Semantic Interoperability and Knowledge
                 Building.",
}

@Article{Davis:2012:SME,
  author =       "Jenny L. Davis",
  title =        "Social Media and Experiential Ambivalence",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "4",
  pages =        "955--970",
  day =          "26",
  month =        oct,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4040955",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:49 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/4/955",
  abstract =     "At once fearful and dependent, hopeful and
                 distrustful, our contemporary relationship with
                 technology is highly ambivalent. Using experiential
                 accounts from an ongoing Facebook-based qualitative
                 study (N = 231), I both diagnose and articulate this
                 ambivalence. I argue that technological ambivalence is
                 rooted primarily in the deeply embedded moral
                 prescription to lead a meaningful life, and a related
                 uncertainty about the role of new technologies in the
                 accomplishment of this task. On the one hand,
                 technology offers the potential to augment or even
                 enhance personal and public life. On the other hand,
                 technology looms with the potential to supplant or
                 replace real experience. I examine these polemic
                 potentialities in the context of personal experiences,
                 interpersonal relationships, and political activism. I
                 conclude by arguing that the pervasive integration and
                 non-optionality of technical systems amplifies utopian
                 hopes, dystopian fears, and ambivalent concerns in the
                 contemporary era.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Theorizing the Web 2012.",
}

@Article{Bencsath:2012:CSD,
  author =       "Boldizs{\'a}r Bencs{\'a}th and G{\'a}bor P{\'e}k and
                 Levente Butty{\'a}n and M{\'a}rk F{\'e}legyh{\'a}zi",
  title =        "The Cousins of {Stuxnet}: {Duqu}, {Flame}, and
                 {Gauss}",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "4",
  pages =        "971--1003",
  day =          "06",
  month =        nov,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4040971",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:49 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/4/971",
  abstract =     "Stuxnet was the first targeted malware that received
                 worldwide attention for causing physical damage in an
                 industrial infrastructure seemingly isolated from the
                 onlineworld. Stuxnet was a powerful targeted
                 cyber-attack, and soon other malware samples were
                 discovered that belong to this family. In this paper,
                 we will first present our analysis of Duqu, an
                 information-collecting malware sharing striking
                 similarities with Stuxnet. We describe our
                 contributions in the investigation ranging from the
                 original detection of Duquvia finding the dropper file
                 to the design of a Duqu detector toolkit. We then
                 continue with the analysis of the Flame advanced
                 information-gathering malware. Flame is unique in the
                 sense that it used advanced cryptographic techniques to
                 masquerade as a legitimate proxy and we are currently
                 collecting intelligence information to be able to break
                 its very specialencryption mechanism. Besides
                 explaining the operation of these pieces of malware, we
                 also examine if and how they could have been detected
                 by vigilant system administrators manually or in a
                 semi-automated manner using available tools. Finally,
                 we discuss lessons that the community can learn from
                 these incidents. We focus on technical issues, and
                 avoid speculations on the origin of these threats and
                 other geopolitical questions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Aftermath of Stuxnet.",
}

@Article{Lord:2012:TSH,
  author =       "Phillip Lord and Simon Cockell and Robert Stevens",
  title =        "Three Steps to Heaven: Semantic Publishing in a Real
                 World Workflow",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "4",
  pages =        "1004--1015",
  day =          "08",
  month =        nov,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4041004",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:49 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/4/1004",
  abstract =     "Semantic publishing offers the promise of computable
                 papers, enriched visualisation and a realisation of the
                 linked data ideal. In reality, however, the publication
                 process contrives to prevent richer semantics while
                 culminating in a ``lumpen'' PDF. In this paper, we
                 discuss a web-first approach to publication, and
                 describe a three-tiered approach that integrates with
                 the existing authoring tooling. Critically, although it
                 adds limited semantics, it does provide value to all
                 the participants in the process: the author, the reader
                 and the machine.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sarma:2012:STP,
  author =       "Amardeo Sarma and Joao Girao",
  title =        "Supporting Trust and Privacy with an Identity-Enabled
                 Architecture",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "4",
  pages =        "1016--1025",
  day =          "19",
  month =        nov,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4041016",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:49 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/4/1016",
  abstract =     "Cost reduction and a vastly increased potential to
                 create new services, such as via the proliferation of
                 the Cloud, have led to many more players and ``end
                 points''. With many of them being new entrants,
                 possibly short-lived, the question of how to handle
                 trust and privacy in this new context arises. In this
                 paper, we specifically look at the underlying
                 infrastructure that connects end-points served by these
                 players, which is an essential part of the overall
                 architecture to enable trust and privacy. We present an
                 enhanced architecture that allows real people, objects
                 and services to reliably interact via an infrastructure
                 providing assured levels of trust.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Privacy in the Future Internet.",
}

@Article{George:2012:TMB,
  author =       "Mathew George and Klaus-Peter Fischer-Hellmann and
                 Martin Knahl and Udo Bleimann and Shirley Atkinson",
  title =        "Traceability in Model-Based Testing",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "4",
  pages =        "1026--1036",
  day =          "26",
  month =        nov,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4041026",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:49 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/4/1026",
  abstract =     "The growing complexities of software and the demand
                 for shorter time to market are two important challenges
                 that face today's IT industry. These challenges demand
                 the increase of both productivity and quality of
                 software. Model-based testing is a promising technique
                 for meeting these challenges. Traceability modeling is
                 a key issue and challenge in model-based testing.
                 Relationships between the different models will help to
                 navigate from one model to another, and trace back to
                 the respective requirements and the design model when
                 the test fails. In this paper, we present an approach
                 for bridging the gaps between the different models in
                 model-based testing. We propose relation definition
                 markup language (RDML) for defining the relationships
                 between models.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Selected Papers from ITA 11.",
}

@Article{Antley:2012:TDA,
  author =       "Jeremy Antley",
  title =        "Textual Dualism and Augmented Reality in the {Russian}
                 Empire",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "4",
  pages =        "1037--1048",
  day =          "10",
  month =        dec,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4041037",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:49 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/4/1037",
  abstract =     "While the current focus on how digital technology
                 alters our conception of the self and its place in the
                 broader perceived reality yields fascinating insight
                 into modern issues, there is much to be gained by
                 analyzing the presence of dualist and augmented reality
                 discourses in a pre-digital era. This essay will
                 examine the ontological interplay of textual dualist
                 norms in the Russian and Soviet states of the 19th and
                 early 20th centuries and how those norms were
                 challenged by augmented claims embodied in rumors,
                 refrains, and the spelling of names. By utilizing the
                 informational concepts of mobility and asynchronicity,
                 three Russian historical vignettes --- the Emancipation
                 of the Serfs in 1861, the documentation of Jews in
                 Imperial Russia, and the attempts by Trotsky to realize
                 Soviet symchka --- demonstrate that not only are
                 dualist discourses prevalent in periods outside of the
                 contemporary, but also that the way in which those
                 conflicts framed themselves in the past directly
                 influences their deployment in today's digital world.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Theorizing the Web 2012.",
}

@Article{Wang:2012:VAS,
  author =       "Jue Wang and Keith J. Bennett and Edward A. Guinness",
  title =        "Virtual Astronaut for Scientific Visualization--- a
                 Prototype for {Santa Maria Crater} on {Mars}",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "4",
  pages =        "1049--1068",
  day =          "13",
  month =        dec,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4041049",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:49 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/4/1049",
  abstract =     "To support scientific visualization of
                 multiple-mission data from Mars, the Virtual Astronaut
                 (VA) creates an interactive virtual 3D environment
                 built on the Unity3D Game Engine. A prototype study was
                 conducted based on orbital and Opportunity Rover data
                 covering Santa Maria Crater in Meridiani Planum on
                 Mars. The VA at Santa Maria provides dynamic visual
                 representations of the imaging, compositional, and
                 mineralogical information. The VA lets one navigate
                 through the scene and provides geomorphic and geologic
                 contexts for the rover operations. User interactions
                 include in-situ observations visualization, feature
                 measurement, and an animation control of rover drives.
                 This paper covers our approach and implementation of
                 the VA system. A brief summary of the prototype system
                 functions and user feedback is also covered. Based on
                 external review and comments by the science community,
                 the prototype at Santa Maria has proven the VA to be an
                 effective tool for virtual geovisual analysis.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Geovisual Analytics.",
}

@Article{Sun:2012:WBG,
  author =       "Min Sun and Jing Li and Chaowei Yang and Gavin A.
                 Schmidt and Myra Bambacus and Robert Cahalan and
                 Qunying Huang and Chen Xu and Erik U. Noble and
                 Zhenlong Li",
  title =        "A {Web}-Based Geovisual Analytical System for Climate
                 Studies",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "4",
  pages =        "1069--1085",
  day =          "14",
  month =        dec,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4041069",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:49 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/4/1069",
  abstract =     "Climate studies involve petabytes of spatiotemporal
                 datasets that are produced and archived at distributed
                 computing resources. Scientists need an intuitive and
                 convenient tool to explore the distributed
                 spatiotemporal data. Geovisual analytical tools have
                 the potential to provide such an intuitive and
                 convenient method for scientists to access climate
                 data, discover the relationships between various
                 climate parameters, and communicate the results across
                 different research communities. However, implementing a
                 geovisual analytical tool for complex climate data in a
                 distributed environment poses several challenges. This
                 paper reports our research and development of a
                 web-based geovisual analytical system to support the
                 analysis of climate data generated by climate model.
                 Using the ModelE developed by the NASA Goddard
                 Institute for Space Studies (GISS) as an example, we
                 demonstrate that the system is able to (1) manage large
                 volume datasets over the Internet; (2) visualize
                 2D/3D/4D spatiotemporal data; (3) broker various
                 spatiotemporal statistical analyses for climate
                 research; and (4) support interactive data analysis and
                 knowledge discovery. This research also provides an
                 example for managing, disseminating, and analyzing Big
                 Data in the 21st century.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Geovisual Analytics.",
}

@Article{Cap:2012:TCN,
  author =       "Clemens H. Cap",
  title =        "Towards Content Neutrality in {Wiki} Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "4",
  number =       "4",
  pages =        "1086--1104",
  day =          "19",
  month =        dec,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi4041086",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:49 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/4/4/1086",
  abstract =     "The neutral point of view (NPOV) cornerstone of
                 Wikipedia (WP) is challenged for next generation
                 knowledge bases. A case is presented for content
                 neutrality as a new, every point of view (EPOV) guiding
                 principle. The architectural implications of content
                 neutrality are discussed and translated into novel
                 concepts of Wiki architectures. Guidelines for
                 implementing this architecture are presented. Although
                 NPOV is criticized, the contribution avoids ideological
                 controversy and focuses on the benefits of the novel
                 approach.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Selected Papers from ITA 11.",
}

@Article{Tomas-Gabarron:2013:OVT,
  author =       "Juan-Bautista Tomas-Gabarron and Esteban Egea-Lopez
                 and Joan Garcia-Haro",
  title =        "Optimization of Vehicular Trajectories under
                 {Gaussian} Noise Disturbances",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "1",
  pages =        "1--20",
  day =          "27",
  month =        dec,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5010001",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:49 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/1/1",
  abstract =     "Nowadays, research on Vehicular Technology aims at
                 automating every single mechanical element of vehicles,
                 in order to increase passengers' safety, reduce human
                 driving intervention and provide entertainment services
                 on board. Automatic trajectory tracing for vehicles
                 under especially risky circumstances is a field of
                 research that is currently gaining enormous attention.
                 In this paper, we show some results on how to develop
                 useful policies to execute maneuvers by a vehicle at
                 high speeds with the mathematical optimization of some
                 already established mobility conditions of the car. We
                 also study how the presence of Gaussian noise on
                 measurement sensors while maneuvering can disturb
                 motion and affect the final trajectories. Different
                 performance criteria for the optimization of such
                 maneuvers are presented, and an analysis is shown on
                 how path deviations can be minimized by using
                 trajectory smoothing techniques like the Kalman Filter.
                 We finalize the paper with a discussion on how
                 communications can be used to implement these
                 schemes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Vehicular Communications and
                 Networking.",
}

@Article{Paltrinieri:2013:PIE,
  author =       "Roberta Paltrinieri and Piergiorgio Degli Esposti",
  title =        "Processes of Inclusion and Exclusion in the Sphere of
                 Prosumerism",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "1",
  pages =        "21--33",
  day =          "10",
  month =        jan,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5010021",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:49 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/1/21",
  abstract =     "The term prosumer, first introduced by Toffler in the
                 1980s, has been developed by sociologists in response
                 to Web 2.0 (the set of technologies that has
                 transformed a predominantly static web into the
                 collaborative medium initially envisaged by Tim
                 Berners-Lee). The phenomena is now understood as a
                 process involving the creation of meanings on the part
                 of the consumer, who re-appropriates spaces that were
                 dominated by institutionalized production, and this
                 extends to the exploitation of consumer creativity on
                 the production side. Recent consumption literature can
                 be re-interpreted through the prosumer lens in order to
                 understand whether prosumers are more creative or
                 alienated in their activities. The peculiar typology of
                 prosumption introduced by Web 2.0 leads us to analyze
                 social capital as a key element in value creation, and
                 to investigate its different online and offline forms.
                 Our analysis then discusses the digital divide and
                 critical consumerism as forms of empowerment
                 impairment.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Theorizing the Web 2012.",
}

@Article{Fritsch:2013:CPE,
  author =       "Lothar Fritsch",
  title =        "The Clean Privacy Ecosystem of the Future {Internet}",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "1",
  pages =        "34--45",
  day =          "14",
  month =        jan,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5010034",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:49 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/1/34",
  abstract =     "This article speculates on the future of privacy and
                 electronic identities on the Internet. Based on a short
                 review of security models and the development of
                 privacy-enhancing technology, privacy and electronic
                 identities will be discussed as parts of a larger
                 context-an ecosystem of personal information and
                 electronic identities. The article argues for an
                 ecosystem view of personal information and electronic
                 identities, as both personal information and identity
                 information are basic required input for many
                 applications. Therefore, for both application owners
                 and users, a functioning ecosystem of personal
                 information and electronic identification is important.
                 For the future of the Internet, high-quality
                 information and controlled circulation of such
                 information is therefore argued as decisive for the
                 value of future Internet applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Privacy in the Future Internet.",
}

@Article{Desmet:2013:GAM,
  author =       "Antoine Desmet and Erol Gelenbe",
  title =        "Graph and Analytical Models for Emergency Evacuation",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "1",
  pages =        "46--55",
  day =          "21",
  month =        feb,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5010046",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:49 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/1/46",
  abstract =     "Cyber-Physical-Human Systems (CPHS) combine sensing,
                 communication and control to obtain desirable outcomes
                 in physical environments for human beings, such as
                 buildings or vehicles. A particularly important
                 application area is emergency management. While recent
                 work on the design and optimisation of emergency
                 management schemes has relied essentially on discrete
                 event simulation, which is challenged by the
                 substantial amount of programming or reprogramming of
                 the simulation tools and by the scalability and the
                 computing time needed to obtain useful performance
                 estimates, this paper proposes an approach that offers
                 fast estimates based on graph models and probability
                 models. We show that graph models can offer insight
                 into the critical areas in an emergency evacuation and
                 that they can suggest locations where sensor systems
                 are particularly important and may require hardening.
                 On the other hand, we also show that analytical models
                 based on queueing theory can provide useful estimates
                 of evacuation times and for routing optimisation. The
                 results are illustrated with regard to the evacuation
                 of a real-life building.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Emergency Management, Communications and
                 the Internet.",
}

@Article{Smith:2013:AAN,
  author =       "Danielle Taana Smith",
  title =        "{African Americans} and Network Disadvantage:
                 Enhancing Social Capital through Participation on
                 Social Networking Sites",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "1",
  pages =        "56--66",
  day =          "06",
  month =        mar,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5010056",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:49 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/1/56",
  abstract =     "This study examines the participation of African
                 Americans on social networking sites (SNS), and
                 evaluates the degree to which African Americans engage
                 in activities in the online environment to mitigate
                 social capital deficits. Prior literature suggests that
                 compared with whites, African Americans have less
                 social capital that can enhance their socio-economic
                 mobility. As such, my research question is: do African
                 Americans enhance their social capital through their
                 participation on SNS? I use nationally representative
                 data collected from the Pew Internet and American Life
                 Project to explore the research question. The results
                 suggest that the online environment is potentially a
                 space in which African Americans can lessen social
                 capital deficits.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Inequality in the Digital Environment.",
}

@Article{Menth:2013:GLL,
  author =       "Michael Menth and Matthias Hartmann and Dominik
                 Klein",
  title =        "Global Locator, Local Locator, and Identifier Split
                 ({GLI}-Split)",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "1",
  pages =        "67--94",
  day =          "11",
  month =        mar,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5010067",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:49 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/1/67",
  abstract =     "The locator/identifier split is an approach for a new
                 addressing and routing architecture to make routing in
                 the core of the Internet more scalable. Based on this
                 principle, we developed the GLI-Split framework, which
                 separates the functionality of current IP addresses
                 into a stable identifier and two independent locators,
                 one for routing in the Internet core and one for edge
                 networks. This makes routing in the Internet more
                 stable and provides more flexibility for edge networks.
                 GLI-Split can be incrementally deployed and it is
                 backward-compatible with the IPv6 Internet. We describe
                 its architecture, compare it to other approaches,
                 present its benefits, and finally present a
                 proof-of-concept implementation of GLI-Split.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Multisilta:2013:SLW,
  author =       "Jari Multisilta and Arttu Perttula",
  title =        "Supporting Learning with Wireless Sensor Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "1",
  pages =        "95--112",
  day =          "19",
  month =        mar,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5010095",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:49 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/1/95",
  abstract =     "In this article, learning is studied in in situ
                 applications that involve sensors. The main questions
                 are how to conceptualize experiential learning
                 involving sensors and what kinds of learning
                 applications using sensors already exist or could be
                 designed. It is claimed that experiential learning,
                 context information and sensor data supports twenty
                 first century learning. The concepts of context,
                 technology-mediated experiences, shared felt
                 experiences and experiential learning theory will be
                 used to describe a framework for sensor-based mobile
                 learning environments. Several scenarios and case
                 examples using sensors and sensor data will be
                 presented, and they will be analyzed using the
                 framework. Finally, the article contributes to the
                 discussion concerning the role of technology-mediated
                 learning experiences and collective sensor data in
                 developing twenty first century learning by
                 characterizing what kinds of skills and competences are
                 supported in learning situations that involve
                 sensors.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Scholz:2013:CSF,
  author =       "Markus Scholz and Dawud Gordon and Leonardo Ramirez
                 and Stephan Sigg and Tobias Dyrks and Michael Beigl",
  title =        "A Concept for Support of Firefighter Frontline
                 Communication",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "2",
  pages =        "113--127",
  day =          "16",
  month =        apr,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5020113",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:50 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/2/113",
  abstract =     "In an indoor firefighter mission, coordination and
                 communication support are of the utmost importance. We
                 present our experience from over five years of research
                 with current firefighter support technology. In
                 contrast to some large scale emergency response
                 research, our work is focused on the frontline
                 interaction between teams of firefighters and the
                 incident commander on a single site. In this paper we
                 investigate the flaws in firefighter communication
                 systems. Frequent technical failures and the high
                 cognitive costs incurred by communicating impede
                 coordination. We then extract a list of requirements
                 for an assistant emergency management technology from
                 expert interviews. Thirdly, we provide a system concept
                 and explore challenges for building a novel firefighter
                 support system based on our previous work. The system
                 has three key features: robust ad-hoc network,
                 telemetry and text messaging, as well as implicit
                 interaction. The result would provide a complementary
                 mode of communication in addition to the current
                 trunked radio.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Emergency Management, Communications and
                 the Internet.",
}

@Article{Gelenbe:2013:EQT,
  author =       "Erol Gelenbe and Ricardo Lent",
  title =        "Energy-{QoS} Trade-Offs in Mobile Service Selection",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "2",
  pages =        "128--139",
  day =          "19",
  month =        apr,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5020128",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:50 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/2/128",
  abstract =     "An attractive advantage of mobile networks is that
                 their users can gain easy access to different services.
                 In some cases, equivalent services could be fulfilled
                 by different providers, which brings the question of
                 how to rationally select the best provider among all
                 possibilities. In this paper, we investigate an answer
                 to this question from both quality-of-service (QoS) and
                 energy perspectives by formulating an optimisation
                 problem. We illustrate the theoretical results with
                 examples from experimental measurements of the
                 resulting energy and performance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Managing Quality-of-Service and Security
                 in Mobile Heterogeneous Environments.",
}

@Article{Uto:2013:MRI,
  author =       "Nelson Uto",
  title =        "A Methodology for Retrieving Information from Malware
                 Encrypted Output Files: {Brazilian} Case Studies",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "2",
  pages =        "140--167",
  day =          "25",
  month =        apr,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5020140",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:50 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/2/140",
  abstract =     "This article presents and explains a methodology based
                 on cryptanalytic and reverse engineering techniques
                 that can be employed to quickly recover information
                 from encrypted files generated by malware. The
                 objective of the methodology is to minimize the effort
                 with static and dynamic analysis, by using
                 cryptanalysis and related knowledge as much as
                 possible. In order to illustrate how it works, we
                 present three case studies, taken from a big Brazilian
                 company that was victimized by directed attacks focused
                 on stealing information from a special purpose hardware
                 they use in their environment.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security of Systems and Software
                 Resiliency.",
}

@Article{Kolding:2013:QSP,
  author =       "Troels Kolding and Pawel Ochal and Niels Terp
                 Kjeldgaard J{\o}rgensen and Klaus Pedersen",
  title =        "{QoS} Self-Provisioning and Interference Management
                 for Co-Channel Deployed {3G} Femtocells",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "2",
  pages =        "168--189",
  day =          "02",
  month =        may,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5020168",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:50 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/2/168",
  abstract =     "A highly efficient self-provisioning interference
                 management scheme is derived for 3G Home Node-Bs (HNB).
                 The proposed scheme comprises self-adjustment of the
                 HNB transmission parameters to meet the targeted QoS
                 (quality of service) requirements in terms of downlink
                 and uplink guaranteed minimum throughput and coverage.
                 This objective is achieved by means of an autonomous
                 HNB solution, where the transmit power of pilot and
                 data are adjusted separately, while also controlling
                 the uplink interference pollution towards the
                 macro-layer. The proposed scheme is evaluated by means
                 of extensive system level simulations and the results
                 show significant performance improvements in terms of
                 user throughput outage probability, power efficiency,
                 femtocell coverage, and impact on macro-layer
                 performance as compared to prior art baseline
                 techniques. The paper is concluded by also showing
                 corresponding measurements from live 3G high-speed
                 packet access (HSPA) HNB field-trials, confirming the
                 validity of major simulation results and assumptions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Managing Quality-of-Service and Security
                 in Mobile Heterogeneous Environments.",
}

@Article{Soderstrom:2013:DDY,
  author =       "Sylvia S{\"o}derstr{\"o}m",
  title =        "Digital Differentiation in Young People's {Internet}
                 Use --- Eliminating or Reproducing Disability
                 Stereotypes",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "2",
  pages =        "190--204",
  day =          "07",
  month =        may,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5020190",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:50 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/2/190",
  abstract =     "Norwegian authorities' policy aims at securing an
                 information society for all, emphasizing the importance
                 of accessible and usable Information and Communication
                 Technology (ICT) for everyone. While the body of
                 research on young people's use of ICT is quite
                 comprehensive, research addressing digital
                 differentiation in young people with disabilities' use
                 of ICT is still in its early days. This article
                 investigates how young people with disabilities' use,
                 or non-use, of assistive ICT creates digital
                 differentiations. The investigation elaborates on how
                 the anticipations and stereotypes of disability
                 establish an authoritative definition of assistive ICT,
                 and the consequence this creates for the use of the Web
                 by young people with disabilities. The object of the
                 article is to provide enhanced insight into the field
                 of technology and disability by illuminating how
                 assistive ICT sometimes eliminates and sometimes
                 reproduces stereotypes and digital differentiations.
                 The investigation draws on a qualitative interview
                 study with 23 young Norwegians with disabilities, aged
                 15-20 years. I draw on a theoretical perspective to
                 analyze the findings of the study, which employs the
                 concept of identity multiplicity. The article's closing
                 discussion expands on technology's significance in
                 young people's negotiations of impairment and of
                 perceptions of disability.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Inequality in the Digital Environment.",
}

@Article{Loukas:2013:RCT,
  author =       "George Loukas and Diane Gan and Tuan Vuong",
  title =        "A Review of Cyber Threats and Defence Approaches in
                 Emergency Management",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "2",
  pages =        "205--236",
  day =          "07",
  month =        may,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5020205",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:50 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/2/205",
  abstract =     "Emergency planners, first responders and relief
                 workers increasingly rely on computational and
                 communication systems that support all aspects of
                 emergency management, from mitigation and preparedness
                 to response and recovery. Failure of these systems,
                 whether accidental or because of malicious action, can
                 have severe implications for emergency management.
                 Accidental failures have been extensively documented in
                 the past and significant effort has been put into the
                 development and introduction of more resilient
                 technologies. At the same time researchers have been
                 raising concerns about the potential of cyber attacks
                 to cause physical disasters or to maximise the impact
                 of one by intentionally impeding the work of the
                 emergency services. Here, we provide a review of
                 current research on the cyber threats to communication,
                 sensing, information management and vehicular
                 technologies used in emergency management. We emphasise
                 on open issues for research, which are the cyber
                 threats that have the potential to affect emergency
                 management severely and for which solutions have not
                 yet been proposed in the literature.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Emergency Management, Communications and
                 the Internet.",
}

@Article{Ober:2013:SAB,
  author =       "Micha Ober and Stefan Katzenbeisser and Kay Hamacher",
  title =        "Structure and Anonymity of the {Bitcoin} Transaction
                 Graph",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "2",
  pages =        "237--250",
  day =          "07",
  month =        may,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5020237",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:50 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/2/237",
  abstract =     "The Bitcoin network of decentralized payment
                 transactions has attracted a lot of attention from both
                 Internet users and researchers in recent years. Bitcoin
                 utilizes a peer-to-peer network to issue anonymous
                 payment transactions between different users. In the
                 currently used Bitcoin clients, the full transaction
                 history is available at each node of the network to
                 prevent double spending without the need for a central
                 authority, forming a valuable source for empirical
                 research on network structure, network dynamics, and
                 the implied anonymity challenges, as well as guidance
                 on the future evolution of complex payment systems. We
                 found dynamical effects of which some increase
                 anonymity while others decrease it. Most importantly,
                 several parameters of the Bitcoin transaction graph
                 seem to have become stationary over the last 12-18
                 months. We discuss the implications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Digital Cash: Design and Impacts.",
}

@Article{West:2013:REO,
  author =       "Rebecca J. West and Bhoomi K. Thakore",
  title =        "Racial Exclusion in the Online World",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "2",
  pages =        "251--267",
  day =          "24",
  month =        may,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5020251",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:50 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/2/251",
  abstract =     "As the internet has become an integral part of
                 everyday life, it is understood that patterns of racial
                 stereotyping and discrimination found in the offline
                 world are often reproduced online. In our paper, we
                 examine two exclusionary practices in an online
                 environment for adult toy collectors: First, the
                 exclusion of non-white individuals who are expected to
                 form immediate friendships with other non-white
                 members; and second, the essentializing of racial
                 issues when concerns over the lack of racial diversity
                 in the toys are discussed. This dismissal is often
                 directly connected to non-white members' decisions to
                 no longer participate, resulting in a new form of
                 segregation within virtual space.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Inequality in the Digital Environment.",
}

@Article{Sakellari:2013:ITB,
  author =       "Georgia Sakellari and Christina Morfopoulou and Erol
                 Gelenbe",
  title =        "Investigating the Tradeoffs between Power Consumption
                 and Quality of Service in a Backbone Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "2",
  pages =        "268--281",
  day =          "24",
  month =        may,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5020268",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:50 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/2/268",
  abstract =     "Energy saving in networks has traditionally focussed
                 on reducing battery consumption through smart wireless
                 network design. Recently, researchers have turned their
                 attention to the energy cost and carbon emissions of
                 the backbone network that both fixed and mobile
                 communications depend on, proposing primarily
                 mechanisms that turn equipments OFF or put them into
                 deep sleep. This is an effective way of saving energy,
                 provided that the nodes can return to working condition
                 quickly, but it introduces increased delays and packet
                 losses that directly affect the quality of
                 communication experienced by the users. Here we
                 investigate the associated tradeoffs between power
                 consumption and quality of service in backbone networks
                 that employ deep sleep energy savings. We examine these
                 tradeoffs by conducting experiments on a real PC-based
                 network topology, where nodes are put into deep sleep
                 at random times and intervals, resulting in a
                 continuously changing network with reduced total power
                 consumption. The average power consumption, the packet
                 loss and the average delay of this network are examined
                 with respect to the average value of the ON rate and
                 the ON/OFF cycle of the nodes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Managing Quality-of-Service and Security
                 in Mobile Heterogeneous Environments.",
}

@Article{Neis:2013:CVG,
  author =       "Pascal Neis and Dennis Zielstra and Alexander Zipf",
  title =        "Comparison of Volunteered Geographic Information Data
                 Contributions and Community Development for Selected
                 World Regions",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "2",
  pages =        "282--300",
  day =          "03",
  month =        jun,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5020282",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:50 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/2/282",
  abstract =     "Volunteered Geographic Information (VGI) projects and
                 their crowdsourced data have been the focus of a number
                 of scientific analyses and investigations in recent
                 years. Oftentimes the results show that the
                 collaboratively collected geodata of one of the most
                 popular VGI projects, OpenStreetMap (OSM), provides
                 good coverage in urban areas when considering
                 particular completeness factors. However, results can
                 potentially vary significantly for different world
                 regions. In this article, we conduct an analysis to
                 determine similarities and differences in data
                 contributions and community development in OSM between
                 12 selected urban areas of the world. Our findings
                 showed significantly different results in data
                 collection efforts and local OSM community sizes.
                 European cities provide quantitatively larger amounts
                 of geodata and number of contributors in OSM, resulting
                 in a better representation of the real world in the
                 dataset. Although the number of volunteers does not
                 necessarily correlate with the general population
                 density of the urban areas, similarities could be
                 detected while comparing the percentage of different
                 contributor groups and the number of changes they made
                 to the OSM project. Further analyses show that
                 socio-economic factors, such as income, can have an
                 impact on the number of active contributors and the
                 data provided in the analyzed areas. Furthermore, the
                 results showed significant data contributions by
                 members whose main territory of interest lies more than
                 one thousand kilometers from the tested areas.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Marganski:2013:VRV,
  author =       "Alison Marganski",
  title =        "Virtual Relationship Violence and Perspectives on
                 Punishment: Do Gender or Nationality Matter?",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "3",
  pages =        "301--316",
  day =          "26",
  month =        jun,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5030301",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:50 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/3/301",
  abstract =     "Given the increasingly popular use of socially
                 interactive technology (SIT), it is believed that the
                 way in which individuals communicate and experience
                 relationships has drastically been changing. For those
                 who partake in this electronic world, damaging
                 behaviors akin to those found in the real world have
                 emerged. Yet, we know little about the extent of these
                 behaviors in the context of romantic relationships,
                 especially from a gender or cultural standpoint.
                 Research on dating violence generally indicates that
                 women experience in-person victimization at higher
                 rates than men, although some research has called this
                 into question. It also suggests that some national
                 groups experience higher rates of violence than others.
                 However, research is almost non-existent when it comes
                 to exploring violence in the digital world. This study
                 investigated gender and nationality in (1) the nature
                 and extent of socially interactive intimate violence,
                 and (2) perceptions of the seriousness of virtual
                 relationship violence. Using a sample of students from
                 the United States and Poland, findings revealed that
                 socially interactive technology may serve as a new
                 avenue for aggressing against partners, as virtual
                 relationship violence was not uncommon and reflected
                 some patterns present in the real world. Some
                 unexpected patterns also emerged. The results of this
                 research signal a possible transferability of covert
                 intimate violence and highlight ways in which
                 inequalities may exist in our virtual worlds.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Inequality in the Digital Environment.",
}

@Article{Imadali:2013:ESS,
  author =       "Sofiane Imadali and Athanasia Karanasiou and Alexandru
                 Petrescu and Ioannis Sifniadis and Eleftheria Velidou
                 and V{\'e}ronique V{\`e}que and Pantelis Angelidis",
  title =        "{eHealth} Service Support in Future {IPv6} Vehicular
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "3",
  pages =        "317--335",
  day =          "27",
  month =        jun,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5030317",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:50 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/3/317",
  abstract =     "Recent vehicular networking activities include novel
                 automotive applications, such as public vehicle to
                 vehicle/infrastructure (V2X), large scale deployments,
                 machine-to-machine (M2M) integration scenarios, and
                 more. The platform described in this paper focuses on
                 the integration of eHealth in a V2I setting. This is to
                 allow the use of Internet from a vehicular setting to
                 disseminate health-related information. From an eHealth
                 viewpoint, the use of remote healthcare solutions to
                 record and transmit a patient's vital signs is a
                 special telemedicine application that helps hospital
                 resident health professionals to optimally prepare the
                 patient's admittance. From the automotive perspective,
                 this is a typical vehicle-to-infrastructure (V2I)
                 communication scenario. This proposal provides an IPv6
                 vehicular platform, which integrates eHealth devices
                 and allows sending captured health-related data to a
                 personal health record (PHR) application server in the
                 IPv6 Internet. The collected data is viewed remotely by
                 a doctor and supports his diagnostic decision. In
                 particular, our work introduces the integration of
                 vehicular and eHealth testbeds, describes related work
                 and presents a lightweight auto-configuration method
                 based on a DHCPv6 extension to provide IPv6
                 connectivity with a few numbers of messages.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Vehicular Communications and
                 Networking.",
}

@Article{Gelenbe:2013:FRC,
  author =       "Erol Gelenbe and Fang-Jing Wu",
  title =        "Future Research on Cyber-Physical Emergency Management
                 Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "3",
  pages =        "336--354",
  day =          "27",
  month =        jun,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5030336",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:50 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/3/336",
  abstract =     "Cyber-physical systems that include human beings and
                 vehicles in a built environment, such as a building or
                 a city, together with sensor networks and decision
                 support systems have attracted much attention. In
                 emergencies, which also include mobile searchers and
                 rescuers, the interactions among civilians and the
                 environment become much more diverse, and the
                 complexity of the emergency response also becomes much
                 greater. This paper surveys current research on
                 sensor-assisted evacuation and rescue systems and
                 discusses the related research issues concerning
                 communication protocols for sensor networks, as well as
                 several other important issues, such as the integrated
                 asynchronous control of large-scale emergency response
                 systems, knowledge discovery for rescue and prototyping
                 platforms. Then, we suggest directions for further
                 research.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Emergency Management, Communications and
                 the Internet.",
}

@Article{Kotenko:2013:DIH,
  author =       "Igor Kotenko and Olga Polubelova and Andrey Chechulin
                 and Igor Saenko",
  title =        "Design and Implementation of a Hybrid
                 Ontological-Relational Data Repository for {SIEM}
                 Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "3",
  pages =        "355--375",
  day =          "09",
  month =        jul,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5030355",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:50 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/3/355",
  abstract =     "The technology of Security Information and Event
                 Management (SIEM) becomes one of the most important
                 research applications in the area of computer network
                 security. The overall functionality of SIEM systems
                 depends largely on the quality of solutions implemented
                 at the data storage level, which is purposed for the
                 representation of heterogeneous security events, their
                 storage in the data repository, and the extraction of
                 relevant data for analytical modules of SIEM systems.
                 The paper discusses the key issues of design and
                 implementation of a hybrid SIEM data repository, which
                 combines relational and ontological data
                 representations. Based on the analysis of existing SIEM
                 systems and standards, the ontological approach is
                 chosen as a core component of the repository, and an
                 example of the ontological data model for
                 vulnerabilities representation is outlined. The hybrid
                 architecture of the repository is proposed for
                 implementation in SIEM systems. Since the most of works
                 on the repositories of SIEM systems is based on the
                 relational data model, the paper focuses mainly on the
                 ontological part of the hybrid approach. To test the
                 repository we used the data model intended for attack
                 modeling and security evaluation, which includes both
                 ontological and relational dimensions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security of Systems and Software
                 Resiliency.",
}

@Article{Chadwick:2013:IAP,
  author =       "Darren Chadwick and Caroline Wesson and Chris
                 Fullwood",
  title =        "{Internet} Access by People with Intellectual
                 Disabilities: Inequalities and Opportunities",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "3",
  pages =        "376--397",
  day =          "17",
  month =        jul,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5030376",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:50 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/3/376",
  abstract =     "This review gives an overview of the societal
                 inequalities faced by people with intellectual
                 disabilities, before focusing specifically on
                 challenges people face accessing the Internet. Current
                 access will be outlined along with the societal,
                 support and attitudinal factors that can hinder access.
                 Discussion of carer views of Internet use by people
                 with intellectual disabilities will be covered
                 incorporating consideration of the tension between
                 protection, self-determination and lifestyle issues and
                 gaining Internet access. We will address how impairment
                 related factors may impede access and subsequently
                 discuss how supports may be used to obfuscate
                 impairments and facilitate access. We will move on from
                 this to critically describe some of the potential
                 benefits the Internet could provide to people with
                 intellectual disabilities, including the potential for
                 self-expression, advocacy and developing friendships.
                 Finally, strategies to better include people with
                 intellectual disabilities online will be given along
                 with future research suggestions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Inequality in the Digital Environment.",
}

@Article{Busanelli:2013:CNI,
  author =       "Stefano Busanelli and Filippo Rebecchi and Marco
                 Picone and Nicola Iotti and Gianluigi Ferrari",
  title =        "Cross-Network Information Dissemination in Vehicular
                 Ad hoc Networks ({VANETs}): Experimental Results from a
                 {Smartphone}-Based Testbed",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "3",
  pages =        "398--428",
  day =          "05",
  month =        aug,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5030398",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:50 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/3/398",
  abstract =     "In this work, we present an innovative approach for
                 effective cross-network information dissemination, with
                 applications to vehicular ad hoc networks (VANETs). The
                 proposed approach, denoted as ``Cross-Network Effective
                 Traffic Alert Dissemination'' (X-NETAD), leverages on
                 the spontaneous formation of local WiFi (IEEE 802.11b)
                 VANETs, with direct connections between neighboring
                 vehicles, in order to disseminate, very quickly and
                 inexpensively, traffic alerts received from the
                 cellular network. The proposed communication
                 architecture has been implemented on Android
                 smartphones. The obtained experimental results show
                 that an effective cross-network information
                 dissemination service can entirely rely on
                 smartphone-based communications. This paves the way to
                 future Internet architectures, where vehicles will play
                 a key role as information destinations and sources.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Vehicular Communications and
                 Networking.",
}

@Article{Teets:2013:LRC,
  author =       "Michael Teets and Matthew Goldner",
  title =        "Libraries' Role in Curating and Exposing Big Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "3",
  pages =        "429--438",
  day =          "20",
  month =        aug,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5030429",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:50 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/3/429",
  abstract =     "This article examines how one data hub is working to
                 become a relevant and useful source in the Web of big
                 data and cloud computing. The focus is on OCLC's
                 WorldCat database of global library holdings and
                 includes work by other library organizations to expose
                 their data using big data concepts and standards.
                 Explanation is given of how OCLC has begun work on the
                 knowledge graph for this data and its active
                 involvement with Schema.org in working to make this
                 data useful throughout the Web.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Server Technologies in Cloud Computing
                 and Big Data.",
}

@Article{Gupta:2013:PLN,
  author =       "Smrati Gupta and M. A. V{\'a}zquez-Castro",
  title =        "Physical Layer Network Coding Based on Integer Forcing
                 Precoded Compute and Forward",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "3",
  pages =        "439--459",
  day =          "28",
  month =        aug,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5030439",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:50 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/3/439",
  abstract =     "In this paper, we address the implementation of
                 physical layer network coding (PNC) based on compute
                 and forward (CF) in relay networks. It is known that
                 the maximum achievable rates in CF-based transmission
                 is limited due to the channel approximations at the
                 relay. In this work, we propose the integer forcing
                 precoder (IFP), which bypasses this maximum rate
                 achievability limitation. Our precoder requires channel
                 state information (CSI) at the transmitter, but only
                 that of the channel between the transmitter and the
                 relay, which is a feasible assumption. The overall
                 contributions of this paper are three-fold. Firstly, we
                 propose an implementation of CF using IFP and prove
                 that this implementation achieves higher rates as
                 compared to traditional relaying schemes. Further, the
                 probability of error from the proposed scheme is shown
                 to have up to 2 dB of gain over the existent lattice
                 network coding-based implementation of CF. Secondly, we
                 analyze the two phases of transmission in the CF
                 scheme, thereby characterizing the end-to-end behavior
                 of the CF and not only one-phase behavior, as in
                 previous proposals. Finally, we develop decoders for
                 both the relay and the destination. We use a
                 generalization of Bezout's theorem to justify the
                 construction of these decoders. Further, we make an
                 analytical derivation of the end-to-end probability of
                 error for cubic lattices using the proposed scheme.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Vehicular Communications and
                 Networking.",
}

@Article{Mantere:2013:NTF,
  author =       "Matti Mantere and Mirko Sailio and Sami Noponen",
  title =        "Network Traffic Features for Anomaly Detection in
                 Specific Industrial Control System Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "4",
  pages =        "460--473",
  day =          "25",
  month =        sep,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5040460",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:51 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/4/460",
  abstract =     "The deterministic and restricted nature of industrial
                 control system networks sets them apart from more open
                 networks, such as local area networks in office
                 environments. This improves the usability of network
                 security, monitoring approaches that would be less
                 feasible in more open environments. One of such
                 approaches is machine learning based anomaly detection.
                 Without proper customization for the special
                 requirements of the industrial control system network
                 environment, many existing anomaly or misuse detection
                 systems will perform sub-optimally. A machine learning
                 based approach could reduce the amount of manual
                 customization required for different industrial control
                 system networks. In this paper we analyze a possible
                 set of features to be used in a machine learning based
                 anomaly detection system in the real world industrial
                 control system network environment under investigation.
                 The network under investigation is represented by
                 architectural drawing and results derived from network
                 trace analysis. The network trace is captured from a
                 live running industrial process control network and
                 includes both control data and the data flowing between
                 the control network and the office network. We limit
                 the investigation to the IP traffic in the traces.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security of Systems and Software
                 Resiliency.",
}

@Article{Ogul:2013:PAM,
  author =       "Murat Ogul and Sel{\c{c}}uk Baktir",
  title =        "Practical Attacks on Mobile Cellular Networks and
                 Possible Countermeasures",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "4",
  pages =        "474--489",
  day =          "30",
  month =        sep,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5040474",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:51 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/4/474",
  abstract =     "Due to widespread adoption of mobile communications
                 devices and increasingly high throughput capacity of
                 cellular networks, Third-Generation (3G) and Long Term
                 Evolution (LTE) are becoming ever more popular.
                 Millions of smart phones with 3G capabilities are sold
                 every year and used for mostly browsing the Internet.
                 Hence, mobile operators have been heavily investing in
                 their packet switched networks to meet customer demand
                 and stay ahead in the market. The widespread use of
                 broadband mobile Internet bring along also some IP
                 based threats such as the Denial of Service (DoS)
                 attacks, botnets and malwares. In this paper, we
                 performed DoS and flooding attacks on 3G mobile
                 networks and measured their effect on the most critical
                 elements of a network such as the Radio Network
                 Controller (RNC) and the Serving GPRS Support Node
                 (SGSN) devices. We carried out our experiments on a
                 real mobile network, not just a simulation environment,
                 and hence our findings depict a realistic picture of
                 the vulnerabilities existent in 3G mobile networks. We
                 propose alternative solutions to avoid these
                 vulnerabilities and mitigate the issues raised.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ziaimatin:2013:STD,
  author =       "Hasti Ziaimatin and Tudor Groza and Jane Hunter",
  title =        "Semantic and Time-Dependent Expertise Profiling Models
                 in Community-Driven Knowledge Curation Platforms",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "4",
  pages =        "490--514",
  day =          "11",
  month =        oct,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5040490",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:51 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/4/490",
  abstract =     "Online collaboration and web-based knowledge sharing
                 have gained momentum as major components of the Web 2.0
                 movement. Consequently, knowledge embedded in such
                 platforms is no longer static and continuously evolves
                 through experts' micro-contributions. Traditional
                 Information Retrieval and Social Network Analysis
                 techniques take a document-centric approach to
                 expertise modeling by creating a macro-perspective of
                 knowledge embedded in large corpus of static documents.
                 However, as knowledge in collaboration platforms
                 changes dynamically, the traditional macro-perspective
                 is insufficient for tracking the evolution of knowledge
                 and expertise. Hence, Expertise Profiling is presented
                 with major challenges in the context of dynamic and
                 evolving knowledge. In our previous study, we proposed
                 a comprehensive, domain-independent model for expertise
                 profiling in the context of evolving knowledge. In this
                 paper, we incorporate Language Modeling into our
                 methodology to enhance the accuracy of resulting
                 profiles. Evaluation results indicate a significant
                 improvement in the accuracy of profiles generated by
                 this approach. In addition, we present our profile
                 visualization tool, Profile Explorer, which serves as a
                 paradigm for exploring and analyzing time-dependent
                 expertise profiles in knowledge-bases where content
                 evolves overtime. Profile Explorer facilitates
                 comparative analysis of evolving expertise, independent
                 of the domain and the methodology used in creating
                 profiles.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Han:2013:MEO,
  author =       "Qing Han",
  title =        "Managing Emergencies Optimally Using a Random Neural
                 Network-Based Algorithm",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "4",
  pages =        "515--534",
  day =          "16",
  month =        oct,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5040515",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:51 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/4/515",
  abstract =     "Emergency rescues require that first responders
                 provide support to evacuate injured and other civilians
                 who are obstructed by the hazards. In this case, the
                 emergency personnel can take actions strategically in
                 order to rescue people maximally, efficiently and
                 quickly. The paper studies the effectiveness of a
                 random neural network (RNN)-based task assignment
                 algorithm involving optimally matching emergency
                 personnel and injured civilians, so that the emergency
                 personnel can aid trapped people to move towards
                 evacuation exits in real-time. The evaluations are run
                 on a decision support evacuation system using the
                 Distributed Building Evacuation Simulator (DBES)
                 multi-agent platform in various emergency scenarios.
                 The simulation results indicate that the RNN-based task
                 assignment algorithm provides a near-optimal solution
                 to resource allocation problems, which avoids resource
                 wastage and improves the efficiency of the emergency
                 rescue process.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Huang:2013:SSV,
  author =       "Jun Steed Huang and Oliver Yang and Funmilyo Lawal",
  title =        "Sending Safety Video over {WiMAX} in Vehicle
                 Communications",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "4",
  pages =        "535--567",
  day =          "31",
  month =        oct,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5040535",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:51 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/4/535",
  abstract =     "This paper reports on the design of an OPNET
                 simulation platform to test the performance of sending
                 real-time safety video over VANET (Vehicular Adhoc
                 NETwork) using the WiMAX technology. To provide a more
                 realistic environment for streaming real-time video, a
                 video model was created based on the study of video
                 traffic traces captured from a realistic vehicular
                 camera, and different design considerations were taken
                 into account. A practical controller over real-time
                 streaming protocol is implemented to control data
                 traffic congestion for future road safety development.
                 Our driving video model was then integrated with the
                 WiMAX OPNET model along with a mobility model based on
                 real road maps. Using this simulation platform,
                 different mobility cases have been studied and the
                 performance evaluated in terms of end-to-end delay,
                 jitter and visual experience.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Vehicular Communications and
                 Networking.",
}

@Article{Jang:2013:CIS,
  author =       "S. Mo Jang and Yong Jin Park",
  title =        "The Citizen as Issue Specialists in a Changing Media
                 Environment",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "4",
  pages =        "568--579",
  day =          "13",
  month =        nov,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5040568",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:51 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/4/568",
  abstract =     "Although recent research suggests that the selective
                 nature of new media helps foster issue specialists,
                 little empirical evidence has been documented, mostly
                 due to theoretical and methodological limitations.
                 Extending the concept of issue publics, the present
                 study proposes a method to estimate the degree to which
                 an individual is a specialist- or a generalist-type
                 citizen. Applying the method to the 2008 American
                 National Election Studies data, the study reveals
                 various characteristics of specialists and generalists.
                 The results indicate that specialist-type citizens are
                 positively associated with online news use, but
                 negatively associated with conventional news media,
                 such as television, newspaper, and radio. The
                 implications of the growth of specialists as well as
                 the validity of the proposed method are discussed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Graham:2013:ISI,
  author =       "Roderick Graham",
  title =        "Introduction to the Special Issue on Inequality in the
                 Digital Environment",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "4",
  pages =        "580--584",
  day =          "26",
  month =        nov,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5040580",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:51 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/4/580",
  abstract =     "The purpose of this special issue is to explore social
                 inequalities in the digital environment. The motivation
                 for this issue is derived from the disproportionate
                 focus on technological and economic aspects of the
                 Information Society to the detriment of sociological
                 and cultural aspects. The research presented here falls
                 along three dimensions of inequality. Two papers
                 explore the ways that race orders interaction online. A
                 second pair of papers explores the experiences of
                 technology users with physical and mental disabilities.
                 A final paper looks at gender, and the higher rates of
                 intimate partner violence experienced by women online.
                 Taken as a whole, these five papers highlight some of
                 the ways that the digital environment can reproduce or
                 mitigate inequalities that have been molded and
                 routinized in the physical environment.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Inequality in the Digital Environment.",
}

@Article{Pileggi:2013:ASG,
  author =       "Salvatore F. Pileggi and Robert Amor",
  title =        "Addressing Semantic Geographic Information Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "4",
  pages =        "585--590",
  day =          "26",
  month =        nov,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5040585",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:51 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/4/585",
  abstract =     "The progressive consolidation of information
                 technologies on a large scale has been facilitating and
                 progressively increasing the production, collection,
                 and diffusion of geographic data, as well as
                 facilitating the integration of a large amount of
                 external information into geographic information
                 systems (GIS). Traditional GIS is transforming into a
                 consolidated information infrastructure. This
                 consolidated infrastructure is affecting more and more
                 aspects of internet computing and services. Most
                 popular systems (such as social networks, GPS, and
                 decision support systems) involve complex GIS and
                 significant amounts of information. As a web service,
                 GIS is affected by exactly the same problems that
                 affect the web as a whole. Therefore, next generation
                 GIS solutions have to address further methodological
                 and data engineering challenges in order to accommodate
                 new applications' extended requirements (in terms of
                 scale, interoperability, and complexity). The
                 conceptual and semantic modeling of GIS, as well as the
                 integration of semantics into current GIS, provide
                 highly expressive environments that are capable of
                 meeting the needs and requirements of a wide range of
                 applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Semantic Geographic Information System
                 (Semantic GIS).",
}

@Article{Jeong:2013:FAA,
  author =       "Sooman Jeong and Kisung Lee and Jungwoo Hwang and
                 Seongjin Lee and Youjip Won",
  title =        "Framework for Analyzing {Android} {I/O} Stack
                 Behavior: From Generating the Workload to Analyzing the
                 Trace",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "4",
  pages =        "591--610",
  day =          "13",
  month =        dec,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5040591",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:51 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/4/591",
  abstract =     "Abstract: The existing I/O workload generators and
                 trace capturing tools are not adaptable to generating
                 nor capturing the I/O requests of Android apps. The
                 Android platform needs proper tools to capture and
                 replay real world workload in the Android platform to
                 verify the result of benchmark tools. This paper
                 introduces Android Storage Performance Analysis Tool,
                 AndroStep, which is specifically designed for
                 characterizing and analyzing the behavior of the I/O
                 subsystem in Android based devices. The AndroStep
                 consists of Mobibench (workload generator), MOST
                 (Mobile Storage Analyzer), and Mobigen (workload
                 replayer). Mobibench is an Android app that generates a
                 filesystem as well as SQLite database operations.
                 Mobibench can also vary the number of concurrent
                 threads to examining the filesystem scalability to
                 support concurrency, e.g., metadata updates, journal
                 file creation/deletion. MOST captures the trace and
                 extracts key filesystem access characteristics such as
                 access pattern with respect to file types, ratio
                 between random vs. sequential access, ratio between
                 buffered vs. synchronous I/O, fraction of metadata
                 accesses, etc. MOST implements reverse mapping feature
                 (finding an inode for a given block) and retrospective
                 reverse mapping (finding an inode for a deleted file).
                 Mobigen is a trace capturing and replaying tool that is
                 specifically designed to perform the user experiment
                 without actual human intervention. Mobigen records the
                 system calls generated from the user behavior and
                 sanitizes the trace for replayable form. Mobigen can
                 replay this trace on different Android platforms or
                 with different I/O stack configurations. As an example
                 of using AndroStep, we analyzed the performances of
                 twelve Android smartphones and the SQLite performances
                 on five different filesystems. AndroStep makes
                 otherwise time consuming I/O stack analysis extremely
                 versatile. AndroStep makes a significant contribution
                 in terms of shedding light on internal behavior of the
                 Android I/O stack.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Mobile Engineering.",
}

@Article{Wan:2013:LEC,
  author =       "Liangtian Wan and Lutao Liu and Guangjie Han and Joel
                 J. P. C. Rodrigues",
  title =        "A Low Energy Consumption {DOA} Estimation Approach for
                 Conformal Array in Ultra-Wideband",
  journal =      j-FUTURE-INTERNET,
  volume =       "5",
  number =       "4",
  pages =        "611--630",
  day =          "16",
  month =        dec,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi5040611",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:51 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/5/4/611",
  abstract =     "Most direction-of-arrival (DOA) estimation approaches
                 for conformal array suffer from high computational
                 complexity, which cause high energy loss for the
                 direction finding system. Thus, a low energy
                 consumption DOA estimation algorithm for conformal
                 array antenna is proposed in this paper. The arbitrary
                 baseline direction finding algorithm is extended to
                 estimate DOA for a conformal array in ultra-wideband.
                 The rotation comparison method is adopted to solve the
                 ambiguity of direction finding. The virtual baseline
                 approach is used to construct the virtual elements.
                 Theoretically, the virtual elements can be extended in
                 the space flexibility. Four elements (both actual and
                 virtual elements) can be used to obtain a group of
                 solutions. The space angle estimation can be obtained
                 by using sub-array divided technique and matrix
                 inversion method. The stability of the proposed
                 algorithm can be guaranteed by averaging the angles
                 obtained by different sub-arrays. Finally, the
                 simulation results verify the effectiveness of the
                 proposed method with high DOA estimation accuracy and
                 relatively low computational complexity.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Green Communications and Networking.",
}

@Article{Hermann:2014:CIP,
  author =       "Steffen Hermann and Benjamin Fabian",
  title =        "A Comparison of {Internet} Protocol ({IPv6}) Security
                 Guidelines",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "1",
  pages =        "1--60",
  day =          "10",
  month =        jan,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6010001",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:51 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/1/1",
  abstract =     "The next generation of the Internet Protocol (IPv6) is
                 currently about to be introduced in many organizations.
                 However, its security features are still a very novel
                 area of expertise for many practitioners. This study
                 evaluates guidelines for secure deployment of IPv6,
                 published by the U.S. NIST and the German federal
                 agency BSI, for topicality, completeness and depth. The
                 later two are scores defined in this paper and are
                 based on the Requests for Comments relevant for IPv6
                 that were categorized, weighted and ranked for
                 importance using an expert survey. Both guides turn out
                 to be of practical value, but have a specific focus and
                 are directed towards different audiences. Moreover,
                 recommendations for possible improvements are
                 presented. Our results could also support strategic
                 management decisions on security priorities as well as
                 for the choice of security guidelines for IPv6
                 roll-outs.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Branchi:2014:AMS,
  author =       "Pablo E. Branchi and Carlos Fern{\'a}ndez-Valdivielso
                 and Ignacio R. Matias",
  title =        "Analysis Matrix for Smart Cities",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "1",
  pages =        "61--75",
  day =          "22",
  month =        jan,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6010061",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:51 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/1/61",
  abstract =     "The current digital revolution has ignited the
                 evolution of communications grids and the development
                 of new schemes for productive systems. Traditional
                 technologic scenarios have been challenged, and Smart
                 Cities have become the basis for urban competitiveness.
                 The citizen is the one who has the power to set new
                 scenarios, and that is why a definition of the way
                 people interact with their cities is needed, as is
                 commented in the first part of the article. At the same
                 time, a lack of clarity has been detected in the way of
                 describing what Smart Cities are, and the second part
                 will try to set the basis for that. For all before, the
                 information and communication technologies that manage
                 and transform 21st century cities must be reviewed,
                 analyzing their impact on new social behaviors that
                 shape the spaces and means of communication, as is
                 posed in the experimental section, setting the basis
                 for an analysis matrix to score the different elements
                 that affect a Smart City environment. So, as the better
                 way to evaluate what a Smart City is, there is a need
                 for a tool to score the different technologies on the
                 basis of their usefulness and consequences, considering
                 the impact of each application. For all of that, the
                 final section describes the main objective of this
                 article in practical scenarios, considering how the
                 technologies are used by citizens, who must be the main
                 concern of all urban development.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Neis:2014:RDF,
  author =       "Pascal Neis and Dennis Zielstra",
  title =        "Recent Developments and Future Trends in Volunteered
                 Geographic Information Research: The Case of
                 {OpenStreetMap}",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "1",
  pages =        "76--106",
  day =          "27",
  month =        jan,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6010076",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:51 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/1/76",
  abstract =     "User-generated content (UGC) platforms on the Internet
                 have experienced a steep increase in data contributions
                 in recent years. The ubiquitous usage of
                 location-enabled devices, such as smartphones, allows
                 contributors to share their geographic information on a
                 number of selected online portals. The collected
                 information is oftentimes referred to as volunteered
                 geographic information (VGI). One of the most utilized,
                 analyzed and cited VGI-platforms, with an increasing
                 popularity over the past few years, is OpenStreetMap
                 (OSM), whose main goal it is to create a freely
                 available geographic database of the world. This paper
                 presents a comprehensive overview of the latest
                 developments in VGI research, focusing on its
                 collaboratively collected geodata and corresponding
                 contributor patterns. Additionally, trends in the realm
                 of OSM research are discussed, highlighting which
                 aspects need to be investigated more closely in the
                 near future.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue NeoGeography and WikiPlanning 2014.",
}

@Article{Office:2014:ARF,
  author =       "Future Internet Editorial Office",
  title =        "Acknowledgement to Reviewers of Future {Internet} in
                 2013",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "1",
  pages =        "107--108",
  day =          "24",
  month =        feb,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6010107",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:51 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/1/107",
  abstract =     "The term ``crowdsourcing'' was initially introduced by
                 Howe in his article ``The Rise of Crowdsourcing'' [1].
                 During the last few years, crowdsourcing has become
                 popular among companies, institutions and universities,
                 as a crowd-centered modern ``tool'' for problem
                 solving. Crowdsourcing is mainly based on the idea of
                 an open-call publication of a problem, requesting the
                 response of the crowd for reaching the most appropriate
                 solution. The focus of this paper is on the role of
                 crowdsourcing in knowledge acquisition for planning
                 applications. The first part provides an introduction
                 to the origins of crowdsourcing in knowledge
                 generation. The second part elaborates on the concept
                 of crowdsourcing, while some indicative platforms
                 supporting the development of crowdsourcing
                 applications are also described. The third part focuses
                 on the integration of crowdsourcing with certain web
                 technologies and GIS (Geographic Information Systems),
                 for spatial planning applications, while in the fourth
                 part, a general framework of the rationale behind
                 crowdsourcing applications is presented. Finally, the
                 fifth part focuses on a range of case studies that
                 adopted several crowdsourcing techniques.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Papadopoulou:2014:CTK,
  author =       "Chrysaida-Aliki Papadopoulou and Maria Giaoutzi",
  title =        "Crowdsourcing as a Tool for Knowledge Acquisition in
                 Spatial Planning",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "1",
  pages =        "109--125",
  day =          "05",
  month =        mar,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6010109",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:51 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/1/109",
  abstract =     "The term ``crowdsourcing'' was initially introduced by
                 Howe in his article ``The Rise of Crowdsourcing'' [1].
                 During the last few years, crowdsourcing has become
                 popular among companies, institutions and universities,
                 as a crowd-centered modern ``tool'' for problem
                 solving. Crowdsourcing is mainly based on the idea of
                 an open-call publication of a problem, requesting the
                 response of the crowd for reaching the most appropriate
                 solution. The focus of this paper is on the role of
                 crowdsourcing in knowledge acquisition for planning
                 applications. The first part provides an introduction
                 to the origins of crowdsourcing in knowledge
                 generation. The second part elaborates on the concept
                 of crowdsourcing, while some indicative platforms
                 supporting the development of crowdsourcing
                 applications are also described. The third part focuses
                 on the integration of crowdsourcing with certain web
                 technologies and GIS (Geographic Information Systems),
                 for spatial planning applications, while in the fourth
                 part, a general framework of the rationale behind
                 crowdsourcing applications is presented. Finally, the
                 fifth part focuses on a range of case studies that
                 adopted several crowdsourcing techniques.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue NeoGeography and WikiPlanning 2014.",
}

@Article{Trinugroho:2014:IIP,
  author =       "Yohanes Baptista Dafferianto Trinugroho",
  title =        "Information Integration Platform for Patient-Centric
                 Healthcare Services: Design, Prototype and
                 Dependability Aspects",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "1",
  pages =        "126--154",
  day =          "06",
  month =        mar,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6010126",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:51 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/1/126",
  abstract =     "Technology innovations have pushed today's healthcare
                 sector to an unprecedented new level. Various portable
                 and wearable medical and fitness devices are being sold
                 in the consumer market to provide the self-empowerment
                 of a healthier lifestyle to society. Many vendors
                 provide additional cloud-based services for devices
                 they manufacture, enabling the users to visualize,
                 store and share the gathered information through the
                 Internet. However, most of these services are
                 integrated with the devices in a closed ``silo''
                 manner, where the devices can only be used with the
                 provided services. To tackle this issue, an information
                 integration platform (IIP) has been developed to
                 support communications between devices and
                 Internet-based services in an event-driven fashion by
                 adopting service-oriented architecture (SOA) principles
                 and a publish/subscribe messaging pattern. It follows
                 the ``Internet of Things'' (IoT) idea of connecting
                 everyday objects to various networks and to enable the
                 dissemination of the gathered information to the global
                 information space through the Internet. A
                 patient-centric healthcare service environment is
                 chosen as the target scenario for the deployment of the
                 platform, as this is a domain where IoT can have a
                 direct positive impact on quality of life enhancement.
                 This paper describes the developed platform, with
                 emphasis on dependability aspects, including
                 availability, scalability and security.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Toward people aware IoT.",
}

@Article{Lan:2014:NDE,
  author =       "Xiaoyu Lan and Liangtian Wan and Guangjie Han and Joel
                 J. P. C. Rodrigues",
  title =        "A Novel {DOA} Estimation Algorithm Using Array
                 Rotation Technique",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "1",
  pages =        "155--170",
  day =          "17",
  month =        mar,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6010155",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:51 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/1/155",
  abstract =     "The performance of traditional direction of arrival
                 (DOA) estimation algorithm based on uniform circular
                 array (UCA) is constrained by the array aperture.
                 Furthermore, the array requires more antenna elements
                 than targets, which will increase the size and weight
                 of the device and cause higher energy loss. In order to
                 solve these issues, a novel low energy algorithm
                 utilizing array base-line rotation for multiple targets
                 estimation is proposed. By rotating two elements and
                 setting a fixed time delay, even the number of elements
                 is selected to form a virtual UCA. Then, the received
                 data of signals will be sampled at multiple positions,
                 which improves the array elements utilization greatly.
                 2D-DOA estimation of the rotation array is accomplished
                 via multiple signal classification (MUSIC) algorithms.
                 Finally, the Cramer-Rao bound (CRB) is derived and
                 simulation results verified the effectiveness of the
                 proposed algorithm with high resolution and estimation
                 accuracy performance. Besides, because of the
                 significant reduction of array elements number, the
                 array antennas system is much simpler and less complex
                 than traditional array.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Green Communications and Networking.",
}

@Article{Motoyoshi:2014:MTF,
  author =       "Gen Motoyoshi and Kenji Leibnitz and Masayuki Murata",
  title =        "Mobility Tolerant Firework Routing for Improving
                 Reachability in {MANETs}",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "1",
  pages =        "171--189",
  day =          "24",
  month =        mar,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6010171",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:51 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/1/171",
  abstract =     "In this paper, we investigate our mobility-assisted
                 and adaptive broadcast routing mechanism, called
                 Mobility Tolerant Firework Routing (MTFR), which
                 utilizes the concept of potentials for routing and
                 improves node reachability, especially in situations
                 with high mobility, by including a broadcast mechanism.
                 We perform detailed evaluations by simulations in a
                 mobile environment and demonstrate the advantages of
                 MTFR over conventional potential-based routing. In
                 particular, we show that MTFR produces better
                 reachability in many aspects at the expense of a small
                 additional transmission delay and intermediate traffic
                 overhead, making MTFR a promising routing protocol and
                 feasible for future mobile Internet infrastructures.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lallie:2014:PCM,
  author =       "Harjinder Singh Lallie",
  title =        "The Problems and Challenges of Managing Crowd Sourced
                 Audio-Visual Evidence",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "2",
  pages =        "190--202",
  day =          "01",
  month =        apr,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6020190",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:51 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/2/190",
  abstract =     "A number of recent incidents, such as the Stanley Cup
                 Riots, the uprisings in the Middle East and the London
                 riots have demonstrated the value of crowd sourced
                 audio-visual evidence wherein citizens submit
                 audio-visual footage captured on mobile phones and
                 other devices to aid governmental institutions,
                 responder agencies and law enforcement authorities to
                 confirm the authenticity of incidents and, in the case
                 of criminal activity, to identify perpetrators. The use
                 of such evidence can present a significant logistical
                 challenge to investigators, particularly because of the
                 potential size of data gathered through such mechanisms
                 and the added problems of time-lining disparate sources
                 of evidence and, subsequently, investigating the
                 incident(s). In this paper we explore this problem and,
                 in particular, outline the pressure points for an
                 investigator. We identify and explore a number of
                 particular problems related to the secure receipt of
                 the evidence, imaging, tagging and then time-lining the
                 evidence, and the problem of identifying duplicate and
                 near duplicate items of audio-visual evidence.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Contemporary and Future Digital
                 Forensics.",
}

@Article{Bi:2014:RDE,
  author =       "Huibo Bi",
  title =        "Routing Diverse Evacuees with the Cognitive Packet
                 Network Algorithm",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "2",
  pages =        "203--222",
  day =          "17",
  month =        apr,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6020203",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:51 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/2/203",
  abstract =     "Regarding mobility, health conditions and personal
                 preferences, evacuees can be categorized into different
                 classes in realistic environments. Previous emergency
                 navigation algorithms that direct evacuees with a
                 single decision rule cannot fulfil civilians' distinct
                 service requirements and increase the likelihood of
                 inducing destructive crowd behaviours, such as
                 clogging, pushing and trampling, due to diverse
                 mobility. This paper explores a distributed emergency
                 navigation algorithm that employs the cognitive packet
                 network concept to tailor different quality of service
                 needs to different categories of evacuees. In addition,
                 a congestion-aware algorithm is presented to predict
                 the future congestion degree of a path with respect to
                 the observed population density, arrival rate and
                 service rate of each route segment. Experiments are
                 implemented in a simulated environment populated with
                 autonomous agents. Results show that our algorithm can
                 increase the number of survivors while providing
                 improved quality of service.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zoppi:2014:OAA,
  author =       "Corrado Zoppi and Sabrina Lai",
  title =        "An Ontology of the Appropriate Assessment of Municipal
                 Master Plans Related to {Sardinia} ({Italy})",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "2",
  pages =        "223--241",
  day =          "23",
  month =        apr,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6020223",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:51 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/2/223",
  abstract =     "This paper discusses some key points related to the
                 ontology of the ``appropriate assessment'' [1]
                 procedure concerning plans significantly affecting
                 Natura 2000 sites. We study this ontology by discussing
                 its implementation into the adjustment process of the
                 master plans of the regional municipalities of Sardinia
                 (Italy) to the Regional Landscape Plan (RLP) and put as
                 evidence some important general observations, coming
                 from the case study, concerning the utility and
                 effectiveness of the ontological conceptual framework
                 in order to help planners and decision-makers
                 understand and structure the assessment process of
                 plans.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue NeoGeography and WikiPlanning 2014.",
}

@Article{Hare:2014:EMC,
  author =       "Jonathon S. Hare and David P. Dupplaw and Paul H.
                 Lewis and Wendy Hall and Kirk Martinez",
  title =        "Exploiting Multimedia in Creating and Analysing
                 Multimedia {Web} Archives",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "2",
  pages =        "242--260",
  day =          "24",
  month =        apr,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6020242",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:51 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/2/242",
  abstract =     "The data contained on the web and the social web are
                 inherently multimedia and consist of a mixture of
                 textual, visual and audio modalities. Community
                 memories embodied on the web and social web contain a
                 rich mixture of data from these modalities. In many
                 ways, the web is the greatest resource ever created by
                 human-kind. However, due to the dynamic and distributed
                 nature of the web, its content changes, appears and
                 disappears on a daily basis. Web archiving provides a
                 way of capturing snapshots of (parts of) the web for
                 preservation and future analysis. This paper provides
                 an overview of techniques we have developed within the
                 context of the EU funded ARCOMEM (ARchiving COmmunity
                 MEMories) project to allow multimedia web content to be
                 leveraged during the archival process and for
                 post-archival analysis. Through a set of use cases, we
                 explore several practical applications of multimedia
                 analytics within the realm of web archiving, web
                 archive analysis and multimedia data on the web in
                 general.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Archiving Community Memories.",
}

@Article{Latvakoski:2014:THA,
  author =       "Juhani Latvakoski and Mahdi {Ben Alaya} and Herve
                 Ganem and Bashar Jubeh and Antti Iivari and Jeremie
                 Leguay and Jaume Martin Bosch and Niclas Granqvist",
  title =        "Towards Horizontal Architecture for Autonomic {M2M}
                 Service Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "2",
  pages =        "261--301",
  day =          "06",
  month =        may,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6020261",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:51 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/2/261",
  abstract =     "Today, increasing number of industrial application
                 cases rely on the Machine to Machine (M2M) services
                 exposed from physical devices. Such M2M services enable
                 interaction of physical world with the core processes
                 of company information systems. However, there are
                 grand challenges related to complexity and ``vertical
                 silos'' limiting the M2M market scale and
                 interoperability. It is here expected that horizontal
                 approach for the system architecture is required for
                 solving these challenges. Therefore, a set of
                 architectural principles and key enablers for the
                 horizontal architecture have been specified in this
                 work. A selected set of key enablers called as
                 autonomic M2M manager, M2M service capabilities, M2M
                 messaging system, M2M gateways towards energy
                 constrained M2M asset devices and creation of trust to
                 enable end-to-end security for M2M applications have
                 been developed. The developed key enablers have been
                 evaluated separately in different scenarios dealing
                 with smart metering, car sharing and electric bike
                 experiments. The evaluation results shows that the
                 provided architectural principles, and developed key
                 enablers establish a solid ground for future research
                 and seem to enable communication between objects and
                 applications, which are not initially been designed to
                 communicate together. The aim as the next step in this
                 research is to create a combined experimental system to
                 evaluate the system interoperability and performance in
                 a more detailed manner.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Toward people aware IoT.",
}

@Article{Braun:2014:SDN,
  author =       "Wolfgang Braun and Michael Menth",
  title =        "Software-Defined Networking Using {OpenFlow}:
                 Protocols, Applications and Architectural Design
                 Choices",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "2",
  pages =        "302--336",
  day =          "12",
  month =        may,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6020302",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:51 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/2/302",
  abstract =     "We explain the notion of software-defined networking
                 (SDN), whose southbound interface may be implemented by
                 the OpenFlow protocol. We describe the operation of
                 OpenFlow and summarize the features of specification
                 versions 1.0-1.4. We give an overview of existing
                 SDN-based applications grouped by topic areas. Finally,
                 we point out architectural design choices for SDN using
                 OpenFlow and discuss their performance implications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zafiropoulos:2014:SFG,
  author =       "Kostas Zafiropoulos and Konstantinos Antoniadis and
                 Vasiliki Vrana",
  title =        "Sharing Followers in e-Government {Twitter} Accounts:
                 The Case of {Greece}",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "2",
  pages =        "337--358",
  day =          "14",
  month =        may,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6020337",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:51 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/2/337",
  abstract =     "The recent emergence of e-government and online social
                 media offers opportunities for governments to meet the
                 demands and expectations of citizens, to provide
                 value-added services and overcome barriers of reduced
                 public budgets. Twitter is the most popular
                 microblogging platform that can facilitate interaction
                 and engagement. It is widely used by government
                 agencies, public affairs practitioners, non-government
                 organizations, members of Parliament and politicians.
                 The paper aims to explore the use of Twitter by
                 government agencies in Greece and record Twitter
                 followers' preferences regarding which accounts they
                 follow. The paper records 27 Greek e-government Twitter
                 accounts and their 107,107 followers. It uses a data
                 mining technique, association rules and two
                 multivariate statistical methods, multidimensional
                 scaling and cluster analysis and proposes the use of a
                 similarity measure, suitable for describing Twitter
                 account proximity. In this way, the paper locates
                 accounts that share followers. Groups of Twitter
                 accounts are located, and their common orientation is
                 described. The analysis not only describes Twitter
                 account similarities and group formation, but to some
                 extent, the followers' preferences and habits of
                 obtaining information through Twitter, as well.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Open Government Meets Social Data.",
}

@Article{Copeland:2014:UPV,
  author =       "Andrea Copeland",
  title =        "The Use of Personal Value Estimations to Select Images
                 for Preservation in Public Library Digital Community
                 Collections",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "2",
  pages =        "359--377",
  day =          "27",
  month =        may,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6020359",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:51 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/2/359",
  abstract =     "A considerable amount of information, particularly in
                 image form, is shared on the web through social
                 networking sites. If any of this content is worthy of
                 preservation, who decides what is to be preserved and
                 based on what criteria. This paper explores the
                 potential for public libraries to assume this role of
                 community digital repositories through the creation of
                 digital collections. Thirty public library users and
                 thirty librarians were solicited from the Indianapolis
                 metropolitan area to evaluate five images selected from
                 Flickr in terms of their value to public library
                 digital collections and their worthiness of long-term
                 preservation. Using a seven-point Likert scale,
                 participants assigned a value to each image in terms of
                 its importance to self, family and society.
                 Participants were then asked to explain the reasoning
                 behind their valuations. Public library users and
                 librarians had similar value estimations of the images
                 in the study. This is perhaps the most significant
                 finding of the study, given the importance of
                 collaboration and forming partnerships for building and
                 sustaining community collections and archives.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Archiving Community Memories.",
}

@Article{Mearns:2014:TMS,
  author =       "Graeme Mearns and Rebecca Simmonds and Ranald
                 Richardson and Mark Turner and Paul Watson and Paolo
                 Missier",
  title =        "Tweet My Street: a Cross-Disciplinary Collaboration
                 for the Analysis of Local {Twitter} Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "2",
  pages =        "378--396",
  day =          "27",
  month =        may,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6020378",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:51 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/2/378",
  abstract =     "Tweet My Street is a cross-disciplinary project
                 exploring the extent to which data derived from Twitter
                 can reveal more about spatial and temporal behaviours
                 and the meanings attached to these locally. This is
                 done with a longer-term view to supporting the
                 coproduction and delivery of local services, complaint
                 mechanisms and horizontal community support networks.
                 The project has involved the development of a web-based
                 software application capable of retrieving, storing and
                 visualising geo-located ``tweets'' (and associated
                 digital content) from Twitter's Firehose. This has been
                 piloted in Newcastle upon Tyne (UK) and has proven a
                 scalable tool that can aid the analysis of social media
                 data geographically. Beyond explaining efforts to
                 analyse pilot data via this software, this paper
                 elucidates three methodological challenges encountered
                 during early collaboration. These include issues
                 relating to ``proximity'' with subjects, ethics and
                 critical questions about scholars' digital
                 responsibilities during the neogeographic turn.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue NeoGeography and WikiPlanning 2014.",
}

@Article{Scassa:2014:POG,
  author =       "Teresa Scassa",
  title =        "Privacy and Open Government",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "2",
  pages =        "397--413",
  day =          "18",
  month =        jun,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6020397",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:51 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/2/397",
  abstract =     "The public-oriented goals of the open government
                 movement promise increased transparency and
                 accountability of governments, enhanced citizen
                 engagement and participation, improved service
                 delivery, economic development and the stimulation of
                 innovation. In part, these goals are to be achieved by
                 making more and more government information public in
                 reusable formats and under open licences. This paper
                 identifies three broad privacy challenges raised by
                 open government. The first is how to balance privacy
                 with transparency and accountability in the context of
                 ``public'' personal information. The second challenge
                 flows from the disruption of traditional approaches to
                 privacy based on a collapse of the distinctions between
                 public and private sector actors. The third challenge
                 is that of the potential for open government data-even
                 if anonymized-to contribute to the big data environment
                 in which citizens and their activities are increasingly
                 monitored and profiled.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Open Government Meets Social Data.",
}

@Article{Roy:2014:ODO,
  author =       "Jeffrey Roy",
  title =        "Open Data and Open Governance in {Canada}: a Critical
                 Examination of New Opportunities and Old Tensions",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "3",
  pages =        "414--432",
  day =          "27",
  month =        jun,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6030414",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:52 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/3/414",
  abstract =     "As governments develop open data strategies, such
                 efforts reflect the advent of the Internet, the
                 digitization of government, and the emergence of
                 meta-data as a wider socio-economic and societal
                 transformational. Within this context the purpose of
                 this article is twofold. First, we seek to both situate
                 and examine the evolution and effectiveness of open
                 data strategies in the Canadian public sector, with a
                 particular focus on municipal governments that have led
                 this movement. Secondly, we delve more deeply into-if
                 and how, open data can facilitate more open and
                 innovative forms of governance enjoining an
                 outward-oriented public sector (across all government
                 levels) with an empowered and participative society.
                 This latter vantage point includes four main and
                 inter-related dimensions: (i) conceptualizing public
                 value and public engagement; (ii) media
                 relations-across traditional intermediaries and
                 channels and new social media; (iii) political culture
                 and the politics of privacy in an increasingly
                 data-centric world; and (iv) federated architectures
                 and the alignment of localized, sub-national, and
                 national strategies and governance mechanisms. This
                 article demonstrates how each of these dimensions
                 includes important determinants of not only open data's
                 immediate impacts but also its catalytic ability to
                 forge wider and collective innovation and more holistic
                 governance renewal.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Open Government Meets Social Data.",
}

@Article{Demidova:2014:AEF,
  author =       "Elena Demidova and Nicola Barbieri and Stefan Dietze
                 and Adam Funk and Helge Holzmann and Diana Maynard and
                 Nikolaos Papailiou and Wim Peters and Thomas Risse and
                 Dimitris Spiliotopoulos",
  title =        "Analysing and Enriching Focused {Semantic Web}
                 Archives for {Parliament} Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "3",
  pages =        "433--456",
  day =          "30",
  month =        jul,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6030433",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:52 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/3/433",
  abstract =     "The web and the social web play an increasingly
                 important role as an information source for Members of
                 Parliament and their assistants, journalists, political
                 analysts and researchers. It provides important and
                 crucial background information, like reactions to
                 political events and comments made by the general
                 public. The case study presented in this paper is
                 driven by two European parliaments (the Greek and the
                 Austrian parliament) and targets an effective
                 exploration of political web archives. In this paper,
                 we describe semantic technologies deployed to ease the
                 exploration of the archived web and social web content
                 and present evaluation results.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Archiving Community Memories.",
}

@Article{Maynard:2014:SCA,
  author =       "Diana Maynard and Gerhard Gossen and Adam Funk and
                 Marco Fisichella",
  title =        "Should {I} Care about Your Opinion? {Detection} of
                 Opinion Interestingness and Dynamics in Social Media",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "3",
  pages =        "457--481",
  day =          "13",
  month =        aug,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6030457",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:52 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/3/457",
  abstract =     "In this paper, we describe a set of reusable text
                 processing components for extracting opinionated
                 information from social media, rating it for
                 interestingness, and for detecting opinion events. We
                 have developed applications in GATE to extract named
                 entities, terms and events and to detect opinions about
                 them, which are then used as the starting point for
                 opinion event detection. The opinions are then
                 aggregated over larger sections of text, to give some
                 overall sentiment about topics and documents, and also
                 some degree of information about interestingness based
                 on opinion diversity. We go beyond traditional opinion
                 mining techniques in a number of ways: by focusing on
                 specific opinion-target extraction related to key terms
                 and events, by examining and dealing with a number of
                 specific linguistic phenomena, by analysing and
                 visualising opinion dynamics over time, and by
                 aggregating the opinions in different ways for a more
                 flexible view of the information contained in the
                 documents.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Archiving Community Memories.",
}

@Article{Tsimpourla:2014:RDL,
  author =       "Clare Tsimpourla",
  title =        "{Rikki} Don't Lose That Number: Enumerated Human
                 Rights in a Society of Infinite Connections",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "3",
  pages =        "482--497",
  day =          "19",
  month =        aug,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6030482",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:52 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/3/482",
  abstract =     "The international Human Rights regime acknowledges a
                 certain number of rights. That number, albeit
                 increasing since its inception, does not seem able to
                 keep up with the pace of modern technology. Human
                 rights today are not only exercised in the tangible
                 world; they are also exercised on a daily basis in a
                 world of ubiquitous computing-as such they can be
                 easily breached with a mere click of a button. To make
                 matters worse, these rights are controlled largely by
                 multinational corporations that have little regard for
                 their value. In this paper we will attempt to explore
                 the difficulties the global human rights regime faces
                 today, the challenge that is its enforcement, and
                 whether it has come to a standstill in an age where
                 connections grow faster than the rule of law.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Digital Inequalities.",
}

@Article{Viscusi:2014:ASV,
  author =       "Gianluigi Viscusi and Marco Castelli and Carlo
                 Batini",
  title =        "Assessing Social Value in Open Data Initiatives: a
                 Framework",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "3",
  pages =        "498--517",
  day =          "19",
  month =        aug,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6030498",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:52 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/3/498",
  abstract =     "Open data initiatives are characterized, in several
                 countries, by a great extension of the number of data
                 sets made available for access by public
                 administrations, constituencies, businesses and other
                 actors, such as journalists, international institutions
                 and academics, to mention a few. However, most of the
                 open data sets rely on selection criteria, based on a
                 technology-driven perspective, rather than a focus on
                 the potential public and social value of data to be
                 published. Several experiences and reports confirm this
                 issue, such as those of the Open Data Census. However,
                 there are also relevant best practices. The goal of
                 this paper is to investigate the different dimensions
                 of a framework suitable to support public
                 administrations, as well as constituencies, in
                 assessing and benchmarking the social value of open
                 data initiatives. The framework is tested on three
                 initiatives, referring to three different countries,
                 Italy, the United Kingdom and Tunisia. The countries
                 have been selected to provide a focus on European and
                 Mediterranean countries, considering also the
                 difference in legal frameworks (civic law vs. common
                 law countries).",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Open Government Meets Social Data.",
}

@Article{Plachouras:2014:ACA,
  author =       "Vassilis Plachouras and Florent Carpentier and
                 Muhammad Faheem and Julien Masan{\`e}s and Thomas Risse
                 and Pierre Senellart and Patrick Siehndel and Yannis
                 Stavrakas",
  title =        "{ARCOMEM} Crawling Architecture",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "3",
  pages =        "518--541",
  day =          "19",
  month =        aug,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6030518",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:52 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/3/518",
  abstract =     "The World Wide Web is the largest information
                 repository available today. However, this information
                 is very volatile and Web archiving is essential to
                 preserve it for the future. Existing approaches to Web
                 archiving are based on simple definitions of the scope
                 of Web pages to crawl and are limited to basic
                 interactions with Web servers. The aim of the ARCOMEM
                 project is to overcome these limitations and to provide
                 flexible, adaptive and intelligent content acquisition,
                 relying on social media to create topical Web archives.
                 In this article, we focus on ARCOMEM's crawling
                 architecture. We introduce the overall architecture and
                 we describe its modules, such as the online analysis
                 module, which computes a priority for the Web pages to
                 be crawled, and the Application-Aware Helper which
                 takes into account the type of Web sites and
                 applications to extract structure from crawled content.
                 We also describe a large-scale distributed crawler that
                 has been developed, as well as the modifications we
                 have implemented to adapt Heritrix, an open source
                 crawler, to the needs of the project. Our experimental
                 results from real crawls show that ARCOMEM's crawling
                 architecture is effective in acquiring focused
                 information about a topic and leveraging the
                 information from social media.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Archiving Community Memories.",
}

@Article{Formosa:2014:NPR,
  author =       "Saviour Formosa",
  title =        "{NeoGeography} and Preparedness for Real-to-Virtual
                 World Knowledge Transfer: Conceptual Steps to
                 {Minecraft Malta}",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "3",
  pages =        "542--555",
  day =          "28",
  month =        aug,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6030542",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:52 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/3/542",
  abstract =     "Societies have rapidly morphed into complex entities
                 that are creating accessibility, yet, at the same time,
                 they are developing new forms of neogeographic-poverty
                 related to information uptake. Those that have managed
                 to partake in the opportunities provided by the web
                 have new vistas to survive in, in contrast to the new
                 poor who have limited or no access to information. New
                 forms of data in spatial format are accessible to all,
                 however few realize the implications of such a
                 transitional change in wellbeing: Whether entire
                 societies or individuals. The different generations
                 taking up the information access can face different
                 levels of accessibility that may be limited by access
                 to online data, knowledge of usage of tools and the
                 understanding of the results, all within the limits on
                 the spaces they are familiar with. This paper reviews a
                 conceptual process underlining the initial steps of a
                 long-term project in the Maltese Islands that seeks to
                 create an online series of tools that bring the concept
                 of ``physical place'' to the different generations
                 through the management of a major project, the creation
                 of a 3D virtuality, employing scanning processes, GIS,
                 conversion aspects, and a small block-based Minecraft
                 engine.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue NeoGeography and WikiPlanning 2014.",
}

@Article{Kaschesky:2014:DVF,
  author =       "Michael Kaschesky and Luigi Selmi",
  title =        "{7R} Data Value Framework for Open Data in Practice:
                 {Fusepool}",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "3",
  pages =        "556--583",
  day =          "08",
  month =        sep,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6030556",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:52 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/3/556",
  abstract =     "Based on existing literature, this article makes a
                 case for open (government) data as supporting political
                 efficiency, socio-economic innovation and
                 administrative efficiency, but also finds a lack of
                 measurable impact. It attributes the lack of impact to
                 shortcomings regarding data access (must be efficient)
                 and data usefulness (must be effective). To address
                 these shortcomings, seven key activities that add value
                 to data are identified and are combined into the 7R
                 Data Value Framework, which is an applied methodology
                 for linked data to systematically address both
                 technical and social shortcomings. The 7R Data Value
                 Framework is then applied to the international Fusepool
                 project that develops a set of integrated software
                 components to ease the publishing of open data based on
                 linked data and associated best practices. Real-life
                 applications for the Dutch Parliament and the Libraries
                 of Free University of Berlin are presented, followed by
                 a concluding discussion.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Open Government Meets Social Data.",
}

@Article{Irons:2014:DFI,
  author =       "Alastair Irons and Harjinder Singh Lallie",
  title =        "Digital Forensics to Intelligent Forensics",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "3",
  pages =        "584--596",
  day =          "12",
  month =        sep,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6030584",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:52 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/3/584",
  abstract =     "In this paper we posit that current investigative
                 techniques-particularly as deployed by law enforcement,
                 are becoming unsuitable for most types of crime
                 investigation. The growth in cybercrime and the
                 complexities of the types of the cybercrime coupled
                 with the limitations in time and resources, both
                 computational and human, in addressing cybercrime put
                 an increasing strain on the ability of digital
                 investigators to apply the processes of digital
                 forensics and digital investigations to obtain timely
                 results. In order to combat the problems, there is a
                 need to enhance the use of the resources available and
                 move beyond the capabilities and constraints of the
                 forensic tools that are in current use. We argue that
                 more intelligent techniques are necessary and should be
                 used proactively. The paper makes the case for the need
                 for such tools and techniques, and investigates and
                 discusses the opportunities afforded by applying
                 principles and procedures of artificial intelligence to
                 digital forensics intelligence and to intelligent
                 forensics and suggests that by applying new techniques
                 to digital investigations there is the opportunity to
                 address the challenges of the larger and more complex
                 domains in which cybercrimes are taking place.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Contemporary and Future Digital
                 Forensics.",
}

@Article{Perger:2014:GGW,
  author =       "Christoph Perger and Ellsworth LeDrew and Linda See
                 and Steffen Fritz",
  title =        "Geography {Geo-Wiki} in the Classroom: Using
                 Crowdsourcing to Enhance Geographical Teaching",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "4",
  pages =        "597--611",
  day =          "29",
  month =        sep,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6040597",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:52 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/4/597",
  abstract =     "Geo-Wiki is a crowdsourcing tool used to derive
                 information, based on satellite imagery, to validate
                 and enhance global land cover. Around 5000 users are
                 registered, who contribute to different campaigns to
                 collect data across various domains (e.g., agriculture,
                 biomass, human impact, etc.). However, seeing the
                 Earth's surface from above does not provide all of the
                 necessary information for understanding what is
                 happening on the ground. Instead, we need to enhance
                 this experience with local knowledge or with additional
                 information, such as geo-located photographs of surface
                 features with annotation. The latest development in
                 enhancing Geo-Wiki in this context has been achieved
                 through collaboration with the University of Waterloo
                 to set up a separate branch called Geography Geo-Wiki
                 for use in undergraduate teaching. We provide the
                 pedagogical objectives for this branch and describe two
                 modules that we have introduced in first and third year
                 Physical Geography classes. The majority of the
                 feedback was positive and in, many cases, was part of
                 what the student liked best about the course. Future
                 plans include the development of additional assignments
                 for the study of environmental processes using Geo-Wiki
                 that would engage students in a manner that is very
                 different from that of conventional teaching.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue NeoGeography and WikiPlanning 2014.",
}

@Article{Dalmau:2014:RDM,
  author =       "Francesc Valls Dalmau and Pilar Garcia-Almirall and
                 Ernest Redondo Dom{\'\i}nguez and David Fonseca
                 Escudero",
  title =        "From Raw Data to Meaningful Information: a
                 Representational Approach to Cadastral Databases in
                 Relation to Urban Planning",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "4",
  pages =        "612--639",
  day =          "24",
  month =        oct,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6040612",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:52 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/4/612",
  abstract =     "Digesting the data hose that cities are constantly
                 producing is complex; data is usually structured with
                 different criteria, which makes comparative analysis of
                 multiple cities challenging. However, the publicly
                 available data from the Spanish cadaster contains urban
                 information in a documented format with common
                 semantics for the whole territory, which makes these
                 analyses possible. This paper uses the information
                 about the 3D geometry of buildings, their use and their
                 year of construction, stored in cadastral databases, to
                 study the relation between the built environment (what
                 the city is) and the urban plan (what the city wants to
                 become), translating the concepts of the cadastral data
                 into the semantics of the urban plan. Different
                 representation techniques to better understand the city
                 from the pedestrians' point of view and to communicate
                 this information more effectively are also discussed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Semantic Geographic Information System
                 (Semantic GIS).",
}

@Article{Batita:2014:TCF,
  author =       "Wided Batita and St{\'e}phane Roche and Yvan
                 B{\'e}dard and Claude Caron",
  title =        "Towards a Conceptual Framework for {WikiGIS}",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "4",
  pages =        "640--672",
  day =          "29",
  month =        oct,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6040640",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:52 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/4/640",
  abstract =     "As an emerging complex concept, GeoDesign requires an
                 innovative theoretical basis, tools, supports and
                 practices. For this reason, we propose a new concept,
                 ``WikiGIS'', designed to answer some dimensions of the
                 GeoDesign process. WikiGIS focuses on the needs of
                 GeoDesign, but we leave the door open for future
                 improvement when tested in other areas that may have
                 additional needs. WikiGIS is built on Web 2.0
                 technologies-and primarily on wiki-to manage the
                 tracking of participants' editing (i.e., managing the
                 contributions history). It also offers GIS functions
                 for geoprocessing and a design-based approach for
                 sketching proposals. One of the main strengths of
                 WikiGIS is its ability to manage the traceability of
                 contributions with an easy and dynamical access, data
                 quality and deltification. The core of this paper
                 consists of presenting a conceptual framework for
                 WikiGIS using UML diagrams. A user interface is
                 presented later to show how our WikiGIS proposal works.
                 This interface is simply a means to illustrate the
                 concepts underlying WikiGIS.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue NeoGeography and WikiPlanning 2014.",
}

@Article{Antonio:2014:GDD,
  author =       "Amy Antonio and David Tuffley",
  title =        "The Gender Digital Divide in Developing Countries",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "4",
  pages =        "673--687",
  day =          "31",
  month =        oct,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6040673",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:52 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/4/673",
  abstract =     "Empirical studies clearly show that women in the
                 developing world have significantly lower technology
                 participation rates than men; a result of entrenched
                 socio-cultural attitudes about the role of women in
                 society. However, as studies are beginning to show,
                 when those women are able to engage with Internet
                 technology, a wide range of personal, family and
                 community benefits become possible. The key to these
                 benefits is on-line education, the access to which sets
                 up a positive feedback loop. This review gives an
                 overview of the digital divide, before focusing
                 specifically on the challenges women in developing
                 countries face in accessing the Internet. Current
                 gender disparities in Internet use will be outlined and
                 the barriers that potentially hinder women's access and
                 participation in the online world will be considered.
                 We will then look at the potential opportunities for
                 women's participation in a global digital society along
                 with a consideration of current initiatives that have
                 been developed to mitigate gender inequity in
                 developing countries. We will also consider a promising
                 avenue for future research.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Digital Inequalities.",
}

@Article{Risse:2014:AAS,
  author =       "Thomas Risse and Elena Demidova and Stefan Dietze and
                 Wim Peters and Nikolaos Papailiou and Katerina Doka and
                 Yannis Stavrakas and Vassilis Plachouras and Pierre
                 Senellart and Florent Carpentier and Amin Mantrach and
                 Bogdan Cautis and Patrick Siehndel and Dimitris
                 Spiliotopoulos",
  title =        "The {ARCOMEM} Architecture for Social- and
                 Semantic-Driven {Web} Archiving",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "4",
  pages =        "688--716",
  day =          "04",
  month =        nov,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6040688",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:52 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/4/688",
  abstract =     "The constantly growing amount ofWeb content and the
                 success of the SocialWeb lead to increasing needs for
                 Web archiving. These needs go beyond the pure
                 preservation of Web pages. Web archives are turning
                 into ``community memories'' that aim at building a
                 better understanding of the public view on, e.g.,
                 celebrities, court decisions and other events. Due to
                 the size of the Web, the traditional ``collect-all''
                 strategy is in many cases not the best method to build
                 Web archives. In this paper, we present the ARCOMEM
                 (From Future Internet 2014, 6 689 Collect-All Archives
                 to Community Memories) architecture and implementation
                 that uses semantic information, such as entities,
                 topics and events, complemented with information from
                 the Social Web to guide a novel Web crawler. The
                 resulting archives are automatically enriched with
                 semantic meta-information to ease the access and allow
                 retrieval based on conditions that involve high-level
                 concepts.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Archiving Community Memories.",
}

@Article{Hatlevik:2014:UMA,
  author =       "Ove Edvard Hatlevik and Karoline T{\o}mte",
  title =        "Using Multilevel Analysis to Examine the Relationship
                 between Upper Secondary Students {Internet} Safety
                 Awareness, Social Background and Academic Aspirations",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "4",
  pages =        "717--734",
  day =          "14",
  month =        nov,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6040717",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:52 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/4/717",
  abstract =     "Since 2009, most Norwegian students in upper secondary
                 have had access to their own personal computer at
                 school. Hence, with the increased access to technology,
                 the importance of online connectedness has increased
                 for adolescents' social interaction and communication.
                 It is, therefore, important to identify and understand
                 the concept of Internet safety among upper secondary
                 school students. A total of 4216 students from 238
                 classrooms in 23 upper secondary schools completed an
                 Internet safety assessment. The aim of the study was to
                 operationalize and measure Internet safety in a school
                 context, and to further examine the factors predicting
                 students' Internet safety awareness and responsibility.
                 Our analysis revealed substantial variation in Internet
                 safety awareness between schools, classrooms and
                 students. Overall, the findings indicate that students'
                 social backgrounds are determining for their
                 development and understanding of Internet safety
                 awareness.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Digital Inequalities.",
}

@Article{Somarakis:2014:PIT,
  author =       "Giorgos Somarakis and Anastasia Stratigea",
  title =        "Public Involvement in Taking Legislative Action as to
                 the Spatial Development of the Tourist Sector in
                 {Greece} --- The {``OpenGov''} Platform Experience",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "4",
  pages =        "735--759",
  day =          "25",
  month =        nov,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6040735",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:52 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/4/735",
  abstract =     "By the Aarhus Convention (1998) it is recognized the
                 right of citizens to get access to and influence
                 decision-making in respect to issues affecting the
                 state of the environment. More specifically, in Article
                 8 it is stated that public authorities are forced to
                 engage public participation when preparing regulations
                 or legally binding rules that have a significant
                 environmental impact. Towards this end, Information and
                 Communication Technologies (ICTs) and their
                 applications have considerably expanded the potential
                 of planners and decision makers to interact with
                 stakeholders and the public and engage them in
                 participatory processes through ICTs-enabled platforms.
                 The focus of the present paper is on the context of
                 public consultation in taking legislative action as to
                 the spatial development of the tourist sector in
                 Greece. It consists of three parts: the first part,
                 where the context of engaging the public in
                 governmental decision-making in Greece is discussed,
                 following the Open Government Partnership (OGP)
                 initiative; the second part, presenting the steps of
                 the ``OpenGov'' online platform, designed for gathering
                 public knowledge to further improve legislative efforts
                 and policy; and the third part, elaborating on the
                 experience gained by the use of the ``OpenGov''
                 platform for decision-making on the spatial development
                 of the tourist sector in Greece.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue NeoGeography and WikiPlanning 2014.",
}

@Article{Shepherd:2014:RRS,
  author =       "Lynsay A. Shepherd and Jacqueline Archibald and Robert
                 Ian Ferguson",
  title =        "Reducing Risky Security Behaviours: Utilising
                 Affective Feedback to Educate Users",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "4",
  pages =        "760--772",
  day =          "27",
  month =        nov,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6040760",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:52 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/4/760",
  abstract =     "Despite the number of tools created to help end-users
                 reduce risky security behaviours, users are still
                 falling victim to online attacks. This paper proposes a
                 browser extension utilising affective feedback to
                 provide warnings on detection of risky behaviour. The
                 paper provides an overview of behaviour considered to
                 be risky, explaining potential threats users may face
                 online. Existing tools developed to reduce risky
                 security behaviours in end-users have been compared,
                 discussing the success rates of various methodologies.
                 Ongoing research is described which attempts to educate
                 users regarding the risks and consequences of poor
                 security behaviour by providing the appropriate
                 feedback on the automatic recognition of risky
                 behaviour. The paper concludes that a solution
                 utilising a browser extension is a suitable method of
                 monitoring potentially risky security behaviour.
                 Ultimately, future work seeks to implement an affective
                 feedback mechanism within the browser extension with
                 the aim of improving security awareness.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Developments in Cybercrime and
                 Cybercrime Mitigation.",
}

@Article{Brainin:2014:ITO,
  author =       "Esther Brainin and Efrat Neter",
  title =        "Inside Technology: Opening the Black Box of Health ---
                 {Website} Configuration and Content Management",
  journal =      j-FUTURE-INTERNET,
  volume =       "6",
  number =       "4",
  pages =        "773--799",
  day =          "10",
  month =        dec,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi6040773",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:52 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/6/4/773",
  abstract =     "Given the existing divide related to Internet skills
                 and types of Internet use, it is safe to assume that a
                 large proportion of the population uses the Internet
                 for health purposes in a partially productive fashion.
                 We suggest that in addition to user characteristics,
                 another factor that inhibits productive Internet use,
                 and thus contributes to the existing gap, is related to
                 the ways in which the technology is configured. The
                 goal of this study was to explore the processes that
                 webmasters and content managers use for constructing
                 and producing, or selecting content, for health
                 websites. Interviews conducted with 23 website builders
                 and managers of websites that represent public and
                 non-public health organizations revealed that they do
                 not plan or conduct activities for content needs
                 elicitation, either in the design stage or on an
                 ongoing basis. Rather, these professionals rely on a
                 ``self-embodiment'' standard, whereby their and their
                 cohorts' expectations determine the quality and
                 functionality of the websites' structure and content.
                 Hence, target groups beyond their social sphere are
                 disregarded, and instead of new opportunities, new
                 cleavages are created. We recommended that government,
                 public and non-public stakeholders work to establish
                 construction standards, to ensure that health websites
                 meet the needs of varied end-user populations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Digital Inequalities.",
}

@Article{Laurini:2015:GOG,
  author =       "Robert Laurini",
  title =        "Geographic Ontologies, Gazetteers and
                 Multilingualism",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "1",
  pages =        "1--23",
  day =          "05",
  month =        jan,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7010001",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:53 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/1/1",
  abstract =     "Different languages imply different visions of space,
                 so that terminologies are different in geographic
                 ontologies. In addition to their geometric shapes,
                 geographic features have names, sometimes different in
                 diverse languages. In addition, the role of gazetteers,
                 as dictionaries of place names (toponyms), is to
                 maintain relations between place names and location.
                 The scope of geographic information retrieval is to
                 search for geographic information not against a
                 database, but against the whole Internet: but the
                 Internet stores information in different languages, and
                 it is of paramount importance not to remain stuck to a
                 unique language. In this paper, our first step is to
                 clarify the links between geographic objects as
                 computer representations of geographic features,
                 ontologies and gazetteers designed in various
                 languages. Then, we propose some inference rules for
                 matching not only types, but also relations in
                 geographic ontologies with the assistance of
                 gazetteers.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Semantic Geographic Information System
                 (Semantic GIS).",
}

@Article{Office:2015:ARF,
  author =       "Future Internet Editorial Office",
  title =        "Acknowledgement to Reviewers of {{\booktitle{Future
                 Internet}}} in 2014",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "1",
  pages =        "24--25",
  day =          "09",
  month =        jan,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7010024",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:53 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/1/24",
  abstract =     "The significance of approaches to technology-enhanced
                 learning (TEL) has increased rapidly during the last
                 few years. Nowadays in education different approaches
                 such as game-based learning, web-based learning,
                 video-based online courses, and many others are used on
                 a daily basis. However, what defines the success of
                 technology-enhanced learning approaches and how can
                 such approaches be developed in a structured way?
                 Furthermore, what different aspects have to be
                 considered while doing so? To answer these questions,
                 4567 publications were analyzed in this present
                 literature review in order to recognize the different
                 aspects of implementing technology-enhanced learning
                 approaches. Finally, 20 categories are defined in four
                 main areas that summarize all the aspects in the field
                 of technology-enhanced learning. Moreover, the study
                 also reveals research areas that are important but
                 hardly investigated in the observed journals of this
                 study.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Schweighofer:2015:ACW,
  author =       "Patrick Schweighofer and Martin Ebner",
  title =        "Aspects to Be Considered when Implementing
                 Technology-Enhanced Learning Approaches: a Literature
                 Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "1",
  pages =        "26--49",
  day =          "03",
  month =        feb,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7010026",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:53 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/1/26",
  abstract =     "The significance of approaches to technology-enhanced
                 learning (TEL) has increased rapidly during the last
                 few years. Nowadays in education different approaches
                 such as game-based learning, web-based learning,
                 video-based online courses, and many others are used on
                 a daily basis. However, what defines the success of
                 technology-enhanced learning approaches and how can
                 such approaches be developed in a structured way?
                 Furthermore, what different aspects have to be
                 considered while doing so? To answer these questions,
                 4567 publications were analyzed in this present
                 literature review in order to recognize the different
                 aspects of implementing technology-enhanced learning
                 approaches. Finally, 20 categories are defined in four
                 main areas that summarize all the aspects in the field
                 of technology-enhanced learning. Moreover, the study
                 also reveals research areas that are important but
                 hardly investigated in the observed journals of this
                 study.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Huang:2015:PDE,
  author =       "Yi-Ting Huang",
  title =        "Participatory Design to Enhance {ICT} Learning and
                 Community Attachment: a Case Study in Rural {Taiwan}",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "1",
  pages =        "50--66",
  day =          "02",
  month =        mar,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7010050",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:53 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/1/50",
  abstract =     "This study used observation and interviews with
                 participants in ``PunCar Action'' to understand how
                 participatory design methods can be applied to the
                 education of rural individuals in information and
                 communication technology (ICT). PunCar Action is a
                 volunteer program in which ICT educators tour the rural
                 communities of Taiwan, offering courses on the use of
                 digital technology. This paper makes three
                 contributions: First, we found that participatory
                 design is an excellent way to teach ICT and Web 2.0
                 skills, co-create community blogs, and sustain
                 intrinsic motivation to use Web applications. Second,
                 PunCar Action provides an innovative bottom-up
                 intergenerational ICT education model with high
                 penetrability capable of enhancing the confidence of
                 rural residents in the use of ICT. Third, the content
                 of basic courses was based on applications capable of
                 making the lives of elderly individuals more
                 convenient, and the advanced course was based on the
                 co-creation of community blogs aimed at reviving the
                 core functions of communities and expanding local
                 industry. Our research was conducted with the use of a
                 non-quantitative index to measure ICT learning
                 performance of participants from a rural community. The
                 results show that PunCar Action emphasizes
                 interpersonal communication and informational
                 applications and creates a collaborative process that
                 encourages rural residents to take action to close the
                 digital divide.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Digital Inequalities.",
}

@Article{Gan:2015:SNP,
  author =       "Diane Gan and Lily R. Jenkins",
  title =        "Social Networking Privacy --- Who's Stalking You?",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "1",
  pages =        "67--93",
  day =          "23",
  month =        mar,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7010067",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:53 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/1/67",
  abstract =     "This research investigates the privacy issues that
                 exist on social networking sites. It is reasonable to
                 assume that many Twitter users are unaware of the
                 dangers of uploading a tweet to their timeline which
                 can be seen by anyone. Enabling geo-location tagging on
                 tweets can result in personal information leakage,
                 which the user did not intend to be public and which
                 can seriously affect that user's privacy and anonymity
                 online. This research demonstrates that key information
                 can easily be retrieved using the starting point of a
                 single tweet with geo-location turned on. A series of
                 experiments have been undertaken to determine how much
                 information can be obtained about a particular
                 individual using only social networking sites and
                 freely available mining tools. The information gathered
                 enabled the target subjects to be identified on other
                 social networking sites such as Foursquare, Instagram,
                 LinkedIn, Facebook and Google+, where more personal
                 information was leaked. The tools used are discussed,
                 the results of the experiments are presented and the
                 privacy implications are examined.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Guillen:2015:IIS,
  author =       "Edward Guillen and Jeisson S{\'a}nchez and Rafael
                 Paez",
  title =        "Inefficiency of {IDS} Static Anomaly Detectors in
                 Real-World Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "2",
  pages =        "94--109",
  day =          "06",
  month =        may,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7020094",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:53 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/2/94",
  abstract =     "A wide range of IDS implementations with anomaly
                 detection modules have been deployed. In general, those
                 modules depend on intrusion knowledge databases, such
                 as Knowledge Discovery Dataset (KDD99), Center for
                 Applied Internet Data Analysis (CAIDA) or Community
                 Resource for Archiving Wireless Data at Dartmouth
                 (CRAWDAD), among others. Once the database is analyzed
                 and a machine learning method is employed to generate
                 detectors, some classes of new detectors are created.
                 Thereafter, detectors are supposed to be deployed in
                 real network environments in order to achieve detection
                 with good results for false positives and detection
                 rates. Since the traffic behavior is quite different
                 according to the user's network activities over
                 available services, restrictions and applications, it
                 is supposed that behavioral-based detectors are not
                 well suited to all kind of networks. This paper
                 presents the differences of detection results between
                 some network scenarios by applying traditional
                 detectors that were calculated with artificial neural
                 networks. The same detector is deployed in different
                 scenarios to measure the efficiency or inefficiency of
                 static training detectors.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Internet Security.",
}

@Article{Pahlevan:2015:DEC,
  author =       "Atousa Pahlevan and Jean-Luc Duprat and Alex Thomo and
                 Hausi M{\"u}ller",
  title =        "{Dynamis}: Effective Context-Aware {Web} Service
                 Selection Using Dynamic Attributes",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "2",
  pages =        "110--139",
  day =          "12",
  month =        may,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7020110",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:53 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/2/110",
  abstract =     "Quality web service discovery requires narrowing the
                 search space from an overwhelming set of services down
                 to the most relevant ones, while matching the
                 consumer's request. Today, the ranking of services only
                 considers static attributes or snapshots of current
                 attribute values, resulting in low-quality search
                 results. To satisfy the user's need for timely,
                 well-chosen web services, we ought to consider quality
                 of service attributes. The problem is that dynamic
                 attributes can be difficult to measure, frequently
                 fluctuate, are context-sensitive and depend on
                 environmental factors, such as network availability at
                 query time. In this paper, we propose the Dynamis
                 algorithm to address these challenges effectively.
                 Dynamis is based on well-established database
                 techniques, such as skyline and aggregation. We
                 illustrate our approach using observatory telescope web
                 services and experimentally evaluate it using stock
                 market data. In our evaluation, we show significant
                 improvement in service selection over existing
                 techniques.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Laneuville:2015:QAU,
  author =       "Odette Laneuville and Dorota Sikora",
  title =        "Quantitative Analysis of the Usage of a Pedagogical
                 Tool Combining Questions Listed as Learning Objectives
                 and Answers Provided as Online Videos",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "2",
  pages =        "140--151",
  day =          "15",
  month =        may,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7020140",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:53 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/2/140",
  abstract =     "To improve the learning of basic concepts in molecular
                 biology of an undergraduate science class, a
                 pedagogical tool was developed, consisting of learning
                 objectives listed at the end of each lecture and
                 answers to those objectives made available as videos
                 online. The aim of this study was to determine if the
                 pedagogical tool was used by students as instructed,
                 and to explore students' perception of its usefulness.
                 A combination of quantitative survey data and measures
                 of online viewing was used to evaluate the usage of the
                 pedagogical practice. A total of 77 short videos linked
                 to 11 lectures were made available to 71 students, and
                 64 completed the survey. Using online tracking tools, a
                 total of 7046 views were recorded. Survey data
                 indicated that most students (73.4\%) accessed all
                 videos, and the majority (98.4\%) found the videos to
                 be useful in assisting their learning. Interestingly,
                 approximately half of the students (53.1\%) always or
                 most of the time used the pedagogical tool as
                 recommended, and consistently answered the learning
                 objectives before watching the videos. While the
                 proposed pedagogical tool was used by the majority of
                 students outside the classroom, only half used it as
                 recommended limiting the impact on students'
                 involvement in the learning of the material presented
                 in class.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue eLearning.",
}

@Article{Yamashita:2015:RTH,
  author =       "Ryoma Yamashita and Kazumasa Takami",
  title =        "Receiver-Triggered Handshake Protocol for {DTN} in
                 Disaster Area",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "2",
  pages =        "152--169",
  day =          "27",
  month =        may,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7020152",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:53 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/2/152",
  abstract =     "When a disaster hits a wide area, communication
                 services for public use will be rendered unavailable.
                 This will make it difficult to confirm the safety of
                 people in the disaster area. A solution to this problem
                 is to form delay/disruption tolerant networks (DTN)
                 using mobile terminals of victims, those of rescuers,
                 who serve as information carriers, and terminals
                 (servers) in shelters. In this paper, we propose using
                 a receiver-triggered handshake protocol for
                 communication between these terminals. We have
                 developed the bundle layer protocol for this handshake
                 method. The proposed method has been implemented on a
                 network simulator to build an evaluation environment.
                 The disaster area has been modeled on an area around
                 Shinjuku Station in Tokyo. Victims are randomly
                 distributed in the area. We have compared the proposed
                 method with Epidemic Routing and Spray and Wait in
                 terms of the delivery rate at which messages reach
                 their destinations, and the length of time taken for
                 messages to reach their destinations. We have found
                 that the delivery rate of the three methods are, more
                 or less, the same, but that the proposed method is
                 superior to the other two methods in terms of storage
                 usage and battery consumption of terminals, and the
                 number of bundles generated in the network.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Smith:2015:OSP,
  author =       "Marlene A. Smith",
  title =        "Output from Statistical Predictive Models as Input to
                 {eLearning} Dashboards",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "2",
  pages =        "170--183",
  day =          "02",
  month =        jun,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7020170",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:53 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/2/170",
  abstract =     "We describe how statistical predictive models might
                 play an expanded role in educational analytics by
                 giving students automated, real-time information about
                 what their current performance means for eventual
                 success in eLearning environments. We discuss how an
                 online messaging system might tailor information to
                 individual students using predictive analytics. The
                 proposed system would be data-driven and quantitative;
                 e.g., a message might furnish the probability that a
                 student will successfully complete the certificate
                 requirements of a massive open online course. Repeated
                 messages would prod underperforming students and alert
                 instructors to those in need of intervention.
                 Administrators responsible for accreditation or
                 outcomes assessment would have ready documentation of
                 learning outcomes and actions taken to address
                 unsatisfactory student performance. The article's brief
                 introduction to statistical predictive models sets the
                 stage for a description of the messaging system.
                 Resources and methods needed to develop and implement
                 the system are discussed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue eLearning.",
}

@Article{Knapp:2015:UEM,
  author =       "Herschel Knapp and Sanjog Pangarkar",
  title =        "Utilizing the {ECHO} Model in the Veterans Health
                 Affairs System: Guidelines for Setup, Operations and
                 Preliminary Findings",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "2",
  pages =        "184--195",
  day =          "08",
  month =        jun,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7020184",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:53 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/2/184",
  abstract =     "Background: In 2011, the Veterans Health
                 Administration (VHA) consulted with the Project ECHO
                 (Extension for Community Healthcare Outcomes) team at
                 the University of New Mexico, Albuquerque, to reproduce
                 their successful model within the VHA. Methods: The VHA
                 launched SCAN-ECHO (Specialty Care Access
                 Network-Extension for Community Healthcare Outcomes), a
                 multisite videoconferencing system to conduct live
                 clinical consultations between specialists at a VHA
                 Medical Center (hospital) and primary care providers
                 stationed at satellite VHA CBOCs (Community-Based
                 Outpatient Clinic). Results: Analysis of the first
                 three years rendered a mean attendee satisfaction of
                 89.53\% and a consultation satisfaction score of
                 88.10\%. About half of the SCAN-ECHO consultations
                 resulted in patients receiving their treatment from
                 their local primary care providers; the remaining half
                 were referred to the VHA Medical Center when the
                 treatment involved equipment or services not available
                 at the CBOCs (e.g., MRI, surgery). Conclusion: This
                 paper details the setup, operation logistics and
                 preliminary findings, suggesting that SCAN-ECHO is a
                 viable model for providing quality specialty clinical
                 consultation service, prompter access to care, reduced
                 commutes and continuing education. Additionally, the
                 use of a secured Internet-based videoconferencing
                 system that supports connectivity to multiple (mobile)
                 devices could expand the utilization of this service.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue eLearning.",
}

@Article{Davaasambuu:2015:SOH,
  author =       "Battulga Davaasambuu and Keping Yu and Takuro Sato",
  title =        "Self-Optimization of Handover Parameters for Long-Term
                 Evolution with Dual Wireless Mobile Relay Nodes",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "2",
  pages =        "196--213",
  day =          "11",
  month =        jun,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7020196",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:53 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/2/196",
  abstract =     "In recent years, train passengers have been
                 transferring increasing amounts of data using mobile
                 devices. Wireless networks with mobile relay nodes
                 support broadband wireless communications for
                 passengers of such vehicles using backhaul links.
                 However, the mobility management entity reuses the
                 handover of existing user equipment, resulting in the
                 handover of the Long-Term Evolution network being
                 unsuitable for user equipment within the cabins of
                 vehicles traveling at high speed. In this paper, we
                 propose a self-optimizing handover hysteresis scheme
                 with dual mobile relay nodes for wireless networks in
                 high-speed mobile environments. The proposed mechanism
                 tunes the hysteresis and cell individual offset
                 handover parameters based on the velocity of the
                 vehicle and the handover performance indicator, which
                 affects the handover triggering decision and
                 performance. The results of simulations conducted in
                 which the performance of the proposed scheme was
                 compared to that of an existing scheme show that the
                 proposed scheme can reduce the number of radio link
                 failures and service interruptions during handover
                 procedures.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Cheng:2015:TPA,
  author =       "Xiu-Zhi Cheng and Da-Rong Zhu and Shen Zhang and Ping
                 He",
  title =        "Tracking Positioning Algorithm for Direction of
                 Arrival Based on Direction Lock Loop",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "3",
  pages =        "214--224",
  day =          "26",
  month =        jun,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7030214",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:54 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/3/214",
  abstract =     "In order to solve the problem of poor real-time
                 performance, low accuracy and high computational
                 complexity in the traditional process of locating and
                 tracking of Direction of Arrival (DOA) of moving
                 targets, this paper proposes a DOA algorithm based on
                 the Direction Lock Loop (DILL) which adopts Lock Loop
                 structure to realize the estimation and location of DOA
                 and can adjust the direction automatically along with
                 the changes of a signal's angular variation to track
                 the position of the signal. Meanwhile, to reduce the
                 influence of nonlinearity and noise on its performance,
                 the UKF filter is designed for eliminating interference
                 of the estimated target signal to improve accuracy of
                 the signal tracking and stability of the system.
                 Simulation results prove that the algorithm can not
                 only get a high resolution DOA estimate signal, but can
                 also locate and track multiple mobile targets
                 effectively with enhanced accuracy, efficiency and
                 stability.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Aman:2015:EEP,
  author =       "Waqas Aman and Einar Snekkenes",
  title =        "{EDAS}: An Evaluation Prototype for Autonomic
                 Event-Driven Adaptive Security in the {Internet of
                 Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "3",
  pages =        "225--256",
  day =          "08",
  month =        jul,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7030225",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:54 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/3/225",
  abstract =     "In Internet of Things (IoT), the main driving
                 technologies are considered to be tiny sensory objects.
                 These objects cannot host traditional preventive and
                 detective technologies to provide protection against
                 the increasing threat sophistication. Furthermore,
                 these solutions are limited to analyzing particular
                 contextual information, for instance network
                 information or files, and do not provide holistic
                 context for risk analysis and response. Analyzing a
                 part of a situation may lead to false alarms and later
                 to unnecessary and incorrect configurations. To
                 overcome these concerns, we proposed an event-driven
                 adaptive security (EDAS) model for IoT. EDAS aims to
                 observe security events (changes) generated by various
                 things in the monitored IoT environment, investigates
                 any intentional or unintentional risks associated with
                 the events and adapts to it autonomously. It correlates
                 different events in time and space to reduce any false
                 alarms and provides a mechanism to predict attacks
                 before they are realized. Risks are responded to
                 autonomically by utilizing a runtime adaptation
                 ontology. The mitigation action is chosen after
                 assessing essential information, such as the risk
                 faced, user preferences, device capabilities and
                 service requirements. Thus, it selects an optimal
                 mitigation action in a particular adverse situation.
                 The objective of this paper is to investigate EDAS
                 feasibility and its aptitude as a real-world prototype
                 in a remote patient monitoring context. It details how
                 EDAS can be a practical choice for IoT-eHealth in terms
                 of the security, design and implementation features it
                 offers as compared to traditional security controls. We
                 have explained the prototype's major components and
                 have highlighted the key technical challenges.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Internet Security.",
}

@Article{Zaidi:2015:VIS,
  author =       "Kamran Zaidi and Muttukrishnan Rajarajan",
  title =        "Vehicular {Internet}: Security \& Privacy Challenges
                 and Opportunities",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "3",
  pages =        "257--275",
  day =          "24",
  month =        jul,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7030257",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:54 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/3/257",
  abstract =     "The vehicular internet will drive the future of
                 vehicular technology and intelligent transportation
                 systems (ITS). Whether it is road safety, infotainment,
                 or driver-less cars, the vehicular internet will lay
                 the foundation for the future of road travel.
                 Governments and companies are pursuing driver-less
                 vehicles as they are considered to be more reliable
                 than humans and, therefore, safer. The vehicles today
                 are not just a means of transportation but are also
                 equipped with a wide range of sensors that provide
                 valuable data. If vehicles are enabled to share data
                 that they collect with other vehicles or authorities
                 for decision-making and safer driving, they thereby
                 form a vehicular network. However, there is a lot at
                 stake in vehicular networks if they are compromised.
                 With the stakes so high, it is imperative that the
                 vehicular networks are secured and made resilient to
                 any attack or attempt that may have serious
                 consequences. The vehicular internet can also be the
                 target of a cyber attack, which can be devastating. In
                 this paper, the opportunities that the vehicular
                 internet offers are presented and then various security
                 and privacy aspects are discussed and some solutions
                 are presented.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Internet Security.",
}

@Article{Floris:2015:SMR,
  author =       "Roberta Floris and Corrado Zoppi",
  title =        "Social Media-Related Geographic Information in the
                 Context of Strategic Environmental Assessment of
                 Municipal Masterplans: a Case Study Concerning
                 {Sardinia} ({Italy})",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "3",
  pages =        "276--293",
  day =          "07",
  month =        aug,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7030276",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:54 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/3/276",
  abstract =     "This paper proposes a discussion concerning the use of
                 social media-related geographic information in the
                 context of the strategic environmental assessment (SEA)
                 of Sardinian Municipal masterplans (MMPs). We show that
                 this kind of information improves, substantially, the
                 SEA process since it provides planners, evaluators, and
                 the local communities with information retrieved from
                 social media that would have not been available
                 otherwise. This information integrates authoritative
                 data collection, which comes from official sources, and
                 enlightens tastes and preferences of the users of
                 services and infrastructure, and their expectations
                 concerning their spatial organization. A methodological
                 approach related to the collection of social
                 media-related geographic information is implemented and
                 discussed with reference to the urban context of the
                 city of Cagliari (Sardinia, Italy). The results are
                 very effective in terms of provision of information,
                 which may possibly increase the spatial knowledge
                 available for planning policy definition and
                 implementation. In this perspective, this kind of
                 information discloses opportunities for building
                 analytical scenarios related to urban and regional
                 planning and it offers useful suggestions for
                 sustainable development based on tourism strategies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tuffley:2015:EEO,
  author =       "David Tuffley and Amy Antonio",
  title =        "Enhancing Educational Opportunities with
                 Computer-Mediated Assessment Feedback",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "3",
  pages =        "294--306",
  day =          "11",
  month =        aug,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7030294",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:54 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/3/294",
  abstract =     "As internet technologies make their way into
                 developing areas, so too does the possibility of
                 education and training being delivered to the people
                 living in those previously unserved areas. The growing
                 catalogue of free, high quality courseware, when
                 combined with the newly acquired means of delivery,
                 creates the potential for millions of people in the
                 developing world to acquire a good education. Yet a
                 good education obviously requires more than simply
                 delivering information; students must also receive high
                 quality feedback on their assessments. They must be
                 told how their performance compares with the ideal, and
                 be shown how to close the gap between the two. However,
                 delivering high quality feedback is labor-intensive,
                 and therefore expensive, and has long been recognized
                 as a problematic issue by educators. This paper
                 outlines a case study that uses a Learning Management
                 System (LMS) to efficiently deliver detailed feedback
                 that is informed by the principles of best practice. We
                 make the case that the efficiencies of this method
                 allow for large-scale courses with thousands of
                 enrolments that are accessible to developing and
                 developed areas alike. We explore the question; is
                 computer-mediated feedback delivery efficient and
                 effective and might it be applied to large-scale
                 courses at low-cost?",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lu:2015:LJW,
  author =       "Cunbo Lu and Liangtian Wan",
  title =        "A Low-Jitter Wireless Transmission Based on Buffer
                 Management in Coding-Aware Routing",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "3",
  pages =        "307--328",
  day =          "31",
  month =        aug,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7030307",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:54 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/3/307",
  abstract =     "It is significant to reduce packet jitter for
                 real-time applications in a wireless network. Existing
                 coding-aware routing algorithms use the opportunistic
                 network coding (ONC) scheme in a packet coding
                 algorithm. The ONC scheme never delays packets to wait
                 for the arrival of a future coding opportunity. The
                 loss of some potential coding opportunities may degrade
                 the contribution of network coding to jitter
                 performance. In addition, most of the existing
                 coding-aware routing algorithms assume that all flows
                 participating in the network have equal rate. This is
                 unrealistic, since multi-rate environments often
                 appear. To overcome the above problem and expand
                 coding-aware routing to multi-rate scenarios, from the
                 view of data transmission, we present a low-jitter
                 wireless transmission algorithm based on buffer
                 management (BLJCAR), which decides packets in coding
                 node according to the queue-length based threshold
                 policy instead of the regular ONC policy as used in
                 existing coding-aware routing algorithms. BLJCAR is a
                 unified framework to merge the single rate case and
                 multiple rate case. Simulations results show that the
                 BLJCAR algorithm embedded in coding-aware routing
                 outperforms the traditional ONC policy in terms of
                 jitter, packet delivery delay, packet loss ratio and
                 network throughput in network congestion in any traffic
                 rates.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2015:DRM,
  author =       "Hua Li and Huan Wang and Wenqing Yin and Yongwei Li
                 and Yan Qian and Fei Hu",
  title =        "Development of a Remote Monitoring System for Henhouse
                 Environment Based on {IoT} Technology",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "3",
  pages =        "329--341",
  day =          "10",
  month =        sep,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7030329",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:54 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/3/329",
  abstract =     "To monitor multiple environmental factors of henhouses
                 in modern chicken farms, a henhouse online monitoring
                 system based on wireless sensor network was developed
                 using wireless sensor technology and computer network
                 technology. Sensor data compensation and correction
                 were designed to be achieved using software and data
                 fitting methods, data reliable transmission achieved
                 using a data loss recovery strategy, and data missing
                 during monitoring addressed using a self-decision and
                 online filling method. Operation test of the system
                 showed that: The system was economic and reliable; it
                 enabled wireless monitoring and Web display of the
                 environmental factors of a henhouse; and the root mean
                 square errors (RMSEs) between the estimated values from
                 the self-decision and on-line filling method and
                 experimental values of the four environmental factors
                 were 0.1698, 3.0859, 77 and 0.094, respectively,
                 indicative of high estimation accuracy. The system can
                 provide support for modern management of henhouses and
                 can be transplanted to related monitoring scenarios in
                 the agricultural field.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Internet of Things.",
}

@Article{Singh:2015:EST,
  author =       "Dilraj Singh and Amardeep Singh",
  title =        "Enhanced Secure Trusted {AODV} ({ESTA}) Protocol to
                 Mitigate Blackhole Attack in Mobile Ad Hoc Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "3",
  pages =        "342--362",
  day =          "23",
  month =        sep,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7030342",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:54 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/3/342",
  abstract =     "The self-organizing nature of the Mobile Ad hoc
                 Networks (MANETs) provide a communication channel
                 anywhere, anytime without any pre-existing network
                 infrastructure. However, it is exposed to various
                 vulnerabilities that may be exploited by the malicious
                 nodes. One such malicious behavior is introduced by
                 blackhole nodes, which can be easily introduced in the
                 network and, in turn, such nodes try to crumble the
                 working of the network by dropping the maximum data
                 under transmission. In this paper, a new protocol is
                 proposed which is based on the widely used Ad hoc
                 On-Demand Distance Vector (AODV) protocol, Enhanced
                 Secure Trusted AODV (ESTA), which makes use of multiple
                 paths along with use of trust and asymmetric
                 cryptography to ensure data security. The results,
                 based on NS-3 simulation, reveal that the proposed
                 protocol is effectively able to counter the blackhole
                 nodes in three different scenarios.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Heller:2015:SID,
  author =       "Alfred Heller",
  title =        "The Sensing {Internet}--- a Discussion on Its Impact
                 on Rural Areas",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "4",
  pages =        "363--371",
  day =          "28",
  month =        sep,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7040363",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:54 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/4/363",
  abstract =     "This paper is based on the experience of introducing
                 wireless sensor networks (WSNs) into the building
                 industry in Denmark and in a rural area of Greenland.
                 There are very real advantages in the application of
                 the technology and its consequences for the life cycle
                 operation of the building sector. Sensor networks can
                 be seen as an important part of the Internet of Things
                 and may even constitute an Internet of Sensors, since
                 the communication layers can differ from the Internet
                 standards. The current paper describes the case for
                 application, followed by a discussion of the observed
                 adaptive advantages and consequences of the technology.
                 Essentially, WSNs constitute a highly sophisticated
                 technology that is more robust in a rural context due
                 to its extremely simple installation procedures (plug
                 and play) allowing the use of local less-skilled
                 labour, and the possibility of reconfiguring and
                 repurposing its use remotely.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Internet of Things.",
}

@Article{Boulos:2015:TIF,
  author =       "Maged N. Kamel Boulos and Abdulslam Yassine and
                 Shervin Shirmohammadi and Chakkrit Snae Namahoot and
                 Michael Br{\"u}ckner",
  title =        "Towards an ``{Internet of Food}'': Food Ontologies for
                 the {Internet of Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "4",
  pages =        "372--392",
  day =          "01",
  month =        oct,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7040372",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:54 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/4/372",
  abstract =     "Automated food and drink recognition methods connect
                 to cloud-based lookup databases (e.g., food item
                 barcodes, previously identified food images, or
                 previously classified NIR (Near Infrared) spectra of
                 food and drink items databases) to match and identify a
                 scanned food or drink item, and report the results back
                 to the user. However, these methods remain of limited
                 value if we cannot further reason with the identified
                 food and drink items, ingredients and
                 quantities/portion sizes in a proposed meal in various
                 contexts; i.e., understand from a semantic perspective
                 their types, properties, and interrelationships in the
                 context of a given user's health condition and
                 preferences. In this paper, we review a number of
                 ``food ontologies'', such as the Food Products
                 Ontology/FOODpedia (by Kolchin and Zamula), Open Food
                 Facts (by Gigandet et al.), FoodWiki (Ontology-driven
                 Mobile Safe Food Consumption System by Celik),
                 FOODS-Diabetes Edition (A Food-Oriented Ontology-Driven
                 System by Snae Namahoot and Bruckner), and AGROVOC
                 multilingual agricultural thesaurus (by the UN Food and
                 Agriculture Organization-FAO). These food ontologies,
                 with appropriate modifications (or as a basis, to be
                 added to and further expanded) and together with other
                 relevant non-food ontologies (e.g., about
                 diet-sensitive disease conditions), can supplement the
                 aforementioned lookup databases to enable progression
                 from the mere automated identification of food and
                 drinks in our meals to a more useful application
                 whereby we can automatically reason with the identified
                 food and drink items and their details (quantities and
                 ingredients/bromatological composition) in order to
                 better assist users in making the correct, healthy food
                 and drink choices for their particular health
                 condition, age, body weight/BMI (Body Mass Index),
                 lifestyle and preferences, etc.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fiore:2015:EIB,
  author =       "Ugo Fiore and Francesco Rossi",
  title =        "Embedding an Identity-Based Short Signature as a
                 Digital Watermark",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "4",
  pages =        "393--404",
  day =          "23",
  month =        oct,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7040393",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:54 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/4/393",
  abstract =     "Digital watermarking aims at protecting multimedia
                 content by hiding into it some data that can be used
                 for such purposes as, for example, intellectual
                 property protection or integrity control. Sometimes,
                 the owner of an image would prefer to not transmit,
                 publish, or hand to a cloud service the original image,
                 but rather an encrypted version of it. Encrypted images
                 allow for less embedding room with respect to their
                 unencrypted counterparts, as there is less spatial
                 correlation to leverage upon. An architecture for
                 embedding as payload the digital signature of an
                 encrypted image, by means of a reversible watermarking
                 technique, is presented in this work. A noteworthy
                 point is the use of an identity-based cryptosystem to
                 avoid certificate management and improve performance.
                 In addition, the use of IBS-1, a recently proposed
                 signature scheme, allows for a reduction in the size of
                 the signature.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tian:2015:DTR,
  author =       "Bo Tian and Kecheng Liu and Yuanzhong Chen",
  title =        "Dynamical Trust and Reputation Computation Model for
                 {B2C} E-Commerce",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "4",
  pages =        "405--428",
  day =          "27",
  month =        oct,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7040405",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:54 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/4/405",
  abstract =     "Trust is one of the most important factors that
                 influence the successful application of network service
                 environments, such as e-commerce, wireless sensor
                 networks, and online social networks. Computation
                 models associated with trust and reputation have been
                 paid special attention in both computer societies and
                 service science in recent years. In this paper, a
                 dynamical computation model of reputation for B2C
                 e-commerce is proposed. Firstly, conceptions associated
                 with trust and reputation are introduced, and the
                 mathematical formula of trust for B2C e-commerce is
                 given. Then a dynamical computation model of reputation
                 is further proposed based on the conception of trust
                 and the relationship between trust and reputation. In
                 the proposed model, classical varying processes of
                 reputation of B2C e-commerce are discussed.
                 Furthermore, the iterative trust and reputation
                 computation models are formulated via a set of
                 difference equations based on the closed-loop feedback
                 mechanism. Finally, a group of numerical simulation
                 experiments are performed to illustrate the proposed
                 model of trust and reputation. Experimental results
                 show that the proposed model is effective in simulating
                 the dynamical processes of trust and reputation for B2C
                 e-commerce.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Freina:2015:SEI,
  author =       "Laura Freina and Rosa Bottino and Michela Ott and
                 Filippo Costa",
  title =        "Social Empowerment of Intellectually Impaired through
                 a Cloud Mobile System",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "4",
  pages =        "429--444",
  day =          "17",
  month =        nov,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7040429",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:54 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/4/429",
  abstract =     "There is not a unique definition of ``empowerment'',
                 nevertheless the idea that it involves, on the one
                 hand, people having control over their own lives and,
                 on the other, some social aspects seems to be a common
                 characteristic. Most authors recognize three levels of
                 empowerment: individual, group, and community level,
                 which are interconnected and changes at one level
                 influence the others. Enhancing individual competence
                 and self-esteem has a direct effect on the control of
                 one's own life and, in turn, on the social components
                 of empowerment. In this paper we present Smart Angel, a
                 project that aims at creating a network involving
                 families, caregivers, experts, and tutors, as well as
                 the final users and their friends, based on a mobile
                 cloud system in support of both everyday living and
                 urban mobility for people with medium-mild intellectual
                 disabilities, with particular attention to the Down
                 syndrome. The system can be seen as a tool to empower
                 its users to be more independent and therefore
                 increasing their possibility to have an active role in
                 their life and an active participation to the
                 community.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Buchanan:2015:FIW,
  author =       "William J. Buchanan and David Lanc and Elochukwu
                 Ukwandu and Lu Fan and Gordon Russell and Owen Lo",
  title =        "The Future {Internet}: a World of Secret Shares",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "4",
  pages =        "445--464",
  day =          "24",
  month =        nov,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7040445",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:54 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/4/445",
  abstract =     "The Public Key Infrastructure (PKI) is crumbling,
                 partially due to the lack of a strong understanding of
                 how encryption actually works, but also due to
                 weaknesses in its implementation. This paper outlines
                 an Internet storage technique using secret sharing
                 methods which could be used to overcome the problems
                 inherent with PKI, while supporting new types of
                 architectures incorporating such things as automated
                 failover and break-glass data recovery. The paper
                 outlines a novel architecture: SECRET, which supports a
                 robust cloud-based infrastructure with in-built privacy
                 and failover. In order to understand the performance
                 overhead of SECRET, the paper outlines a range of
                 experiments that investigate the overhead of this and
                 other secret share methods.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Internet Security.",
}

@Article{Gao:2015:DLB,
  author =       "Ren Gao and Juebo Wu",
  title =        "Dynamic Load Balancing Strategy for Cloud Computing
                 with Ant Colony Optimization",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "4",
  pages =        "465--483",
  day =          "26",
  month =        nov,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7040465",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:54 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/4/465",
  abstract =     "How to distribute and coordinate tasks in cloud
                 computing is a challenging issue, in order to get
                 optimal resource utilization and avoid overload. In
                 this paper, we present a novel approach on load
                 balancing via ant colony optimization (ACO), for
                 balancing the workload in a cloud computing platform
                 dynamically. Two strategies, forward-backward ant
                 mechanism and max-min rules, are introduced to quickly
                 find out the candidate nodes for load balancing. We
                 formulate pheromone initialization and pheromone update
                 according to physical resources under the cloud
                 computing environment, including pheromone evaporation,
                 incentive, and punishment rules, etc. Combined with
                 task execution prediction, we define the moving
                 probability of ants in two ways, that is, whether the
                 forward ant meets the backward ant, or not, in the
                 neighbor node, with the aim of accelerating searching
                 processes. Simulations illustrate that the proposed
                 strategy can not only provide dynamic load balancing
                 for cloud computing with less searching time, but can
                 also get high network performance under medium and
                 heavily loaded contexts.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Internet of Things.",
}

@Article{Kruger:2015:ITE,
  author =       "Dov Kruger and Sarah Inman and Zhiyu Ding and Yijin
                 Kang and Poornima Kuna and Yujie Liu and Xiakun Lu and
                 Stephen Oro and Yingzhu Wang",
  title =        "Improving Teacher Effectiveness: Designing Better
                 Assessment Tools in Learning Management Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "4",
  pages =        "484--499",
  day =          "18",
  month =        dec,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7040484",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:54 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/4/484",
  abstract =     "Current-generation assessment tools used in K-12 and
                 post-secondary education are limited in the type of
                 questions they support; this limitation makes it
                 difficult for instructors to navigate their assessment
                 engines. Furthermore, the question types tend to score
                 low on Bloom's Taxonomy. Dedicated learning management
                 systems (LMS) such as Blackboard, Moodle and Canvas are
                 somewhat better than informal tools as they offer more
                 question types and some randomization. Still, question
                 types in all the major LMS assessment engines are
                 limited. Additionally, LMSs place a heavy burden on
                 teachers to generate online assessments. In this study
                 we analyzed the top three LMS providers to identify
                 inefficiencies. These inefficiencies in LMS design,
                 point us to ways to ask better questions. Our findings
                 show that teachers have not adopted current tools
                 because they do not offer definitive improvements in
                 productivity. Therefore, we developed LiquiZ, a design
                 for a next-generation assessment engine that reduces
                 user effort and provides more advanced question types
                 that allow teachers to ask questions that can currently
                 only be asked in one-on-one demonstration. The initial
                 LiquiZ project is targeted toward STEM subjects, so the
                 question types are particularly advantageous in math or
                 science subjects.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue eLearning.",
}

@Article{Drogkaris:2015:HMA,
  author =       "Prokopios Drogkaris and Stefanos Gritzalis and
                 Christos Kalloniatis and Costas Lambrinoudakis",
  title =        "A Hierarchical Multitier Approach for Privacy Policies
                 in e-Government Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "4",
  pages =        "500--515",
  day =          "21",
  month =        dec,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7040500",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:54 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/4/500",
  abstract =     "The appeal of e-Government users to retain control
                 over their personal information, while making use of
                 advanced governmental electronic services through
                 interconnected and interoperable deployments, can be
                 assisted by the incorporation of privacy policy and
                 Preferences documents. This paper addresses the
                 formulation of light-weight and accurate privacy
                 policies, while preserving compliance with underlying
                 legal and regulatory framework. Through the
                 exploitation of existing governmental hierarchies, a
                 multitier approach is proposed able to support diverge
                 data needs and processing requests imposed by service
                 providers. The incorporation of this approach into
                 e-Government environments will reduce the
                 administrative workload, imposed by the inclusion of
                 privacy policy documents, and promote the
                 implementation and provision of user-centric and data
                 privacy aware electronic services.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Internet Security.",
}

@Article{Zhou:2015:ORR,
  author =       "Dan Zhou and Zhong Yao",
  title =        "Optimal Referral Reward Considering Customer's Budget
                 Constraint",
  journal =      j-FUTURE-INTERNET,
  volume =       "7",
  number =       "4",
  pages =        "516--529",
  day =          "21",
  month =        dec,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi7040516",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:54 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/7/4/516",
  abstract =     "Everyone likes Porsche but few can afford it. Budget
                 constraints always play a critical role in a customer's
                 decision-making. The literature disproportionally
                 focuses on how firms can induce customer valuations
                 toward the product, but does not address how to assess
                 the influence of budget constraints. We study these
                 questions in the context of a referral reward program
                 (RRP). RRP is a prominent marketing strategy that
                 utilizes recommendations passed from existing customers
                 to their friends and effectively stimulates word of
                 mouth (WoM). We build a stylized game-theoretical model
                 with a nested Stackelberg game involving three players:
                 a firm, an existing customer, and a potential customer
                 who is a friend of the existing customer. The budget is
                 the friend's private information. We show that RRPs
                 might be optimal when the friend has either a low or a
                 high valuation, but they work differently in each
                 situation because of the budget. Furthermore, there are
                 two budget thresholds, a fixed one and a variable one,
                 which limit a firm's ability to use rewards.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Computational Social Sciences:
                 Contagion, Collective Behaviors, and Networks.",
}

@Article{Chang:2016:PQF,
  author =       "Gary Chang and Chung-Chieh Lee",
  title =        "Priority Queues with Fractional Service for Tiered
                 Delay {QoS}",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "1",
  pages =        "1",
  day =          "29",
  month =        dec,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8010001",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/1/1",
  abstract =     "Packet scheduling is key to quality of service (QoS)
                 capabilities of broadband wired and wireless networks.
                 In a heterogeneous traffic environment, a comprehensive
                 QoS packet scheduler must strike a balance between flow
                 fairness and access delay. Many advanced packet
                 scheduling solutions have targeted fair bandwidth
                 allocation while protecting delay-constrained traffic
                 by adding priority queue(s) on top of a fair bandwidth
                 scheduler. Priority queues are known to cause
                 performance uncertainties and, thus, various
                 modifications have been proposed. In this paper, we
                 present a packet queueing engine dubbed Fractional
                 Service Buffer (FSB), which, when coupled with a
                 configurable flow scheduler, can achieve desired QoS
                 objectives, such as fair throughputs and differentiated
                 delay guarantees. Key performance metrics, such as
                 delay limit and probability of delay limit violation,
                 are derived as a function of key FSB parameters for
                 each delay class in the packet queueing engine using
                 diffusion approximations. OPNET simulations verify
                 these analytical results.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Managing QoS and QoE Levels in Wired and
                 Wireless Data Networks.",
}

@Article{Wang:2016:DII,
  author =       "Yun Wang and William Chu and Sarah Fields and Colleen
                 Heinemann and Zach Reiter",
  title =        "Detection of Intelligent Intruders in Wireless Sensor
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "1",
  pages =        "2",
  day =          "20",
  month =        jan,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8010002",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/1/2",
  abstract =     "Most of the existing research works on the intrusion
                 detection problem in a wireless sensor network (WSN)
                 assume linear or random mobility patterns in
                 abstracting intruders' models in traversing the WSN
                 field. However, in real-life WSN applications, an
                 intruder is usually an intelligent mobile robot with
                 environment learning and detection avoidance capability
                 (i.e., the capability to avoid surrounding sensors).
                 Due to this, the literature results based on the linear
                 or random mobility models may not be applied to the
                 real-life WSN design and deployment for efficient and
                 effective intrusion detection in practice. This
                 motivates us to investigate the impact of intruder's
                 intelligence on the intrusion detection problem in a
                 WSN for various applications. To be specific, we
                 propose two intrusion algorithms, the pinball and
                 flood-fill algorithms, to mimic the intelligent motion
                 and behaviors of a mobile intruder in detecting and
                 circumventing nearby sensors for detection avoidance
                 while heading for its destination. The two proposed
                 algorithms are integrated into a WSN framework for
                 intrusion detection analysis in various circumstances.
                 Monte Carlo simulations are conducted, and the results
                 indicate that: (1) the performance of a WSN drastically
                 changes as a result of the intruder's intelligence in
                 avoiding sensor detections and intrusion algorithms;
                 (2) network parameters, including node density, sensing
                 range and communication range, play a crucial part in
                 the effectiveness of the intruder's intrusion
                 algorithms; and (3) it is imperative to integrate
                 intruder's intelligence in the WSN research for
                 intruder detection problems under various application
                 circumstances.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Internet of Things.",
}

@Article{Office:2016:ARF,
  author =       "Future Internet Editorial Office",
  title =        "Acknowledgement to Reviewers of {{\booktitle{Future
                 Internet}}} in 2015",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "1",
  pages =        "3",
  day =          "22",
  month =        jan,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8010003",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/1/3",
  abstract =     "In this paper, we address the problem of energy
                 conservation and optimization in residential
                 environments by providing users with useful information
                 to solicit a change in consumption behavior. Taking
                 care to highly limit the costs of installation and
                 management, our work proposes a Non-Intrusive Load
                 Monitoring (NILM) approach, which consists of
                 disaggregating the whole-house power consumption into
                 the individual portions associated to each device.
                 State of the art NILM algorithms need monitoring data
                 sampled at high frequency, thus requiring high costs
                 for data collection and management. In this paper, we
                 propose an NILM approach that relaxes the requirements
                 on monitoring data since it uses total active power
                 measurements gathered at low frequency (about 1 Hz).
                 The proposed approach is based on the use of Factorial
                 Hidden Markov Models (FHMM) in conjunction with context
                 information related to the user presence in the house
                 and the hourly utilization of appliances. Through a set
                 of tests, we investigated how the use of these
                 additional context-awareness features could improve
                 disaggregation results with respect to the basic FHMM
                 algorithm. The tests have been performed by using
                 Tracebase, an open dataset made of data gathered from
                 real home environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Paradiso:2016:CBE,
  author =       "Francesca Paradiso and Federica Paganelli and Dino
                 Giuli and Samuele Capobianco",
  title =        "Context-Based Energy Disaggregation in Smart Homes",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "1",
  pages =        "4",
  day =          "27",
  month =        jan,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8010004",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/1/4",
  abstract =     "In this paper, we address the problem of energy
                 conservation and optimization in residential
                 environments by providing users with useful information
                 to solicit a change in consumption behavior. Taking
                 care to highly limit the costs of installation and
                 management, our work proposes a Non-Intrusive Load
                 Monitoring (NILM) approach, which consists of
                 disaggregating the whole-house power consumption into
                 the individual portions associated to each device.
                 State of the art NILM algorithms need monitoring data
                 sampled at high frequency, thus requiring high costs
                 for data collection and management. In this paper, we
                 propose an NILM approach that relaxes the requirements
                 on monitoring data since it uses total active power
                 measurements gathered at low frequency (about 1 Hz).
                 The proposed approach is based on the use of Factorial
                 Hidden Markov Models (FHMM) in conjunction with context
                 information related to the user presence in the house
                 and the hourly utilization of appliances. Through a set
                 of tests, we investigated how the use of these
                 additional context-awareness features could improve
                 disaggregation results with respect to the basic FHMM
                 algorithm. The tests have been performed by using
                 Tracebase, an open dataset made of data gathered from
                 real home environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Ecosystemic Evolution Feeded by Smart
                 Systems.",
}

@Article{Ismail:2016:FST,
  author =       "Umar Mukhtar Ismail and Shareeful Islam and Moussa
                 Ouedraogo and Edgar Weippl",
  title =        "A Framework for Security Transparency in Cloud
                 Computing",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "1",
  pages =        "5",
  day =          "17",
  month =        feb,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8010005",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/1/5",
  abstract =     "Individuals and corporate users are persistently
                 considering cloud adoption due to its significant
                 benefits compared to traditional computing
                 environments. The data and applications in the cloud
                 are stored in an environment that is separated, managed
                 and maintained externally to the organisation.
                 Therefore, it is essential for cloud providers to
                 demonstrate and implement adequate security practices
                 to protect the data and processes put under their
                 stewardship. Security transparency in the cloud is
                 likely to become the core theme that underpins the
                 systematic disclosure of security designs and practices
                 that enhance customer confidence in using cloud service
                 and deployment models. In this paper, we present a
                 framework that enables a detailed analysis of security
                 transparency for cloud based systems. In particular, we
                 consider security transparency from three different
                 levels of abstraction, i.e., conceptual, organisation
                 and technical levels, and identify the relevant
                 concepts within these levels. This allows us to provide
                 an elaboration of the essential concepts at the core of
                 transparency and analyse the means for implementing
                 them from a technical perspective. Finally, an example
                 from a real world migration context is given to provide
                 a solid discussion on the applicability of the proposed
                 framework.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security in Cloud Computing and Big
                 Data.",
}

@Article{Ma:2016:MDR,
  author =       "Tinghuai Ma and Xichao Xu and Meili Tang and Yuanfeng
                 Jin and Wenhai Shen",
  title =        "{MHBase}: a Distributed Real-Time Query Scheme for
                 Meteorological Data Based on {HBase}",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "1",
  pages =        "6",
  day =          "01",
  month =        mar,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8010006",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/1/6",
  abstract =     "Meteorological technology has evolved rapidly in
                 recent years to provide enormous, accurate and
                 personalized advantages in the public service. Large
                 volumes of observational data are generated gradually
                 by technologies such as geographical remote sensing,
                 meteorological radar satellite, etc. that makes data
                 analysis in weather forecasting more precise but also
                 poses a threat to the traditional method of data
                 storage. In this paper, we present MHBase,
                 Meteorological data based on HBase (Hadoop Database), a
                 distributed real-time query scheme for meteorological
                 data based on HBase. The calibrated data obtained from
                 terminal devices will be partitioned into HBase and
                 persisted to HDFS (the Hadoop Distributed File System).
                 We propose two algorithms (the Indexed Store and the
                 Indexed Retrieve Algorithms) to implement a secondary
                 index using HBase Coprocessors, which allow MHbase to
                 provide high performance data querying on columns other
                 than rowkey. Experimental results show that the
                 performance of MHBase can satisfy the basic demands of
                 meteorological business services.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lischke:2016:ABN,
  author =       "Matthias Lischke and Benjamin Fabian",
  title =        "Analyzing the {Bitcoin} Network: The First Four
                 Years",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "1",
  pages =        "7",
  day =          "07",
  month =        mar,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8010007",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/1/7",
  abstract =     "In this explorative study, we examine the economy and
                 transaction network of the decentralized digital
                 currency Bitcoin during the first four years of its
                 existence. The objective is to develop insights into
                 the evolution of the Bitcoin economy during this
                 period. For this, we establish and analyze a novel
                 integrated dataset that enriches data from the Bitcoin
                 blockchain with off-network data such as business
                 categories and geo-locations. Our analyses reveal the
                 major Bitcoin businesses and markets. Our results also
                 give insights on the business distribution by countries
                 and how businesses evolve over time. We also show that
                 there is a gambling network that features many very
                 small transactions. Furthermore, regional differences
                 in the adoption and business distribution could be
                 found. In the network analysis, the small world
                 phenomenon is investigated and confirmed for several
                 subgraphs of the Bitcoin network.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Deng:2016:ELF,
  author =       "Zhi-An Deng and Di Wu and Yiran Zhou and Zhenyu Na",
  title =        "Enhanced Local {Fisher} Discriminant Analysis for
                 Indoor Positioning in Wireless Local Area Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "2",
  pages =        "8",
  day =          "25",
  month =        mar,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8020008",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/2/8",
  abstract =     "Feature extraction methods have been used to extract
                 location features for indoor positioning in wireless
                 local area networks. However, existing methods, such as
                 linear discriminant analysis and principal component
                 analysis, all suffer from the multimodal property of
                 signal distribution. This paper proposes a novel
                 method, based on enhanced local fisher discriminant
                 analysis (LFDA). First, LFDA is proposed to extract
                 discriminative location features. It maximizes
                 between-class separability while preserving
                 within-class local structure of signal space, thereby
                 guaranteeing maximal discriminative information
                 involved in positioning. Then, the generalization
                 ability of LFDA is further enhanced using signal
                 perturbation, which generates more number of
                 representative training samples. Experimental results
                 in realistic indoor environment show that, compared
                 with previous feature extraction methods, the proposed
                 method reduces the mean and standard deviation of
                 positing error by 23.9\% and 33.0\%, respectively.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future Mobile Computing.",
}

@Article{Golbeck:2016:UPF,
  author =       "Jennifer Golbeck and Matthew Louis Mauriello",
  title =        "User Perception of {Facebook} App Data Access: a
                 Comparison of Methods and Privacy Concerns",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "2",
  pages =        "9",
  day =          "25",
  month =        mar,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8020009",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/2/9",
  abstract =     "Users share vast amounts of personal information
                 online, but are they fully aware of what information
                 they are sharing and with whom? In this paper, we
                 focused on Facebook apps and set out to understand how
                 concerned users are about privacy and how well-informed
                 they are about what personal data apps can access. We
                 found that initially, subjects were generally
                 under-informed about what data apps could access from
                 their profiles. After viewing additional information
                 about these permissions, subjects' concern about
                 privacy on Facebook increased. Subjects' understanding
                 of what data apps were able to access increased,
                 although even after receiving explicit information on
                 the topic, many subjects still did not fully understand
                 the extent to which apps could access their data.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Human-Computer Interaction and the
                 Social Web.",
}

@Article{Massa:2016:FEU,
  author =       "Daniele Massa and Lucio Davide Spano",
  title =        "{FaceMashup}: An End-User Development Tool for Social
                 Network Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "2",
  pages =        "10",
  day =          "29",
  month =        mar,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8020010",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/2/10",
  abstract =     "Every day, each active social network user produces
                 and shares texts, images and videos. While developers
                 can access such data through application programming
                 interfaces (APIs) for creating games, visualizations
                 and routines, end users have less control on such
                 information. Their access is mediated by the social
                 application features, which limits them in combining
                 sources, filtering results and performing actions on
                 groups of elements. In order to fill this gap, we
                 introduce FaceMashup, an end user development (EUD)
                 environment supporting the manipulation of the Facebook
                 graph. We describe the tool interface, documenting the
                 choices we made during the design iterations. Data
                 types are represented through widgets containing user
                 interface (UI) elements similar to those used in the
                 social network application. Widgets can be connected
                 with each other with the drag and drop of their inner
                 fields, and the application updates their content.
                 Finally, we report the results of a user-test on the
                 FaceMashup prototype, which shows a good acceptance of
                 the environment by end-users.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Human-Computer Interaction and the
                 Social Web.",
}

@Article{Golbeck:2016:EFA,
  author =       "Jennifer Golbeck and Carman Neustaedter",
  title =        "Environmental Factors Affecting Where People
                 Geocache",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "2",
  pages =        "11",
  day =          "12",
  month =        apr,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8020011",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/2/11",
  abstract =     "Outdoor leisure activities are important for public
                 health as well as family cohesiveness, yet
                 environmental factors may easily affect someone's
                 ability to participate in such activities. We explored
                 this with a focus on the social web-based treasure hunt
                 game called Geocaching. We collected data on all US and
                 Canadian geocaches from OpenCaching.com and conducted
                 an online survey with twenty geocachers as a follow-up
                 to our data analysis. Data analysis showed that
                 geocaches were more often found in areas that were
                 wealthier, better educated, younger, and more urban,
                 and had higher population density and better weather.
                 Survey results showed similar trends: Most people
                 actively thought about where they would cache and tried
                 to minimize risks, despite cache hiders thinking less
                 about these concerns. These results further emphasize
                 the importance of environmental factors when it comes
                 to participation in outdoor activities and leads to
                 Human-Computer Interaction design implications for
                 location-based online social activities.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Human-Computer Interaction and the
                 Social Web.",
}

@Article{Antoniadis:2016:MAP,
  author =       "Konstantinos Antoniadis and Kostas Zafiropoulos and
                 Vasiliki Vrana",
  title =        "A Method for Assessing the Performance of e-Government
                 {Twitter} Accounts",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "2",
  pages =        "12",
  day =          "18",
  month =        apr,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8020012",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/2/12",
  abstract =     "This paper introduces a method for assessing the
                 influence of Twitter accounts of central e-government
                 agencies. It first stresses the importance of activity
                 and popularity of the e-government accounts, and also
                 the importance of community formation among
                 followers-citizens, as the two main stages of
                 e-government adoption. The proposed approach combines
                 activity and popularity of the accounts and followers'
                 community characteristics in a ranking system, using an
                 idea originally introduced to measure blogosphere
                 authority. A Twitter Authority Index is produced. The
                 method is demonstrated through an extended example: 56
                 Twitter accounts of ministries of EU countries are
                 sorted according to their indexes in the proposed
                 ranking system. Detailed values for the ministries'
                 accounts and average values for the countries that the
                 ministries belong to are reported and commented.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Computational Social Sciences:
                 Contagion, Collective Behaviors, and Networks.",
}

@Article{Fernandez:2016:MSC,
  author =       "Eduardo B. Fernandez and Nobukazu Yoshioka and
                 Hironori Washizaki and Madiha H. Syed",
  title =        "Modeling and Security in Cloud Ecosystems",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "2",
  pages =        "13",
  day =          "20",
  month =        apr,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8020013",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/2/13",
  abstract =     "Clouds do not work in isolation but interact with
                 other clouds and with a variety of systems either
                 developed by the same provider or by external entities
                 with the purpose to interact with them; forming then an
                 ecosystem. A software ecosystem is a collection of
                 software systems that have been developed to coexist
                 and evolve together. The stakeholders of such a system
                 need a variety of models to give them a perspective of
                 the possibilities of the system, to evaluate specific
                 quality attributes, and to extend the system. A
                 powerful representation when building or using software
                 ecosystems is the use of architectural models, which
                 describe the structural aspects of such a system. These
                 models have value for security and compliance, are
                 useful to build new systems, can be used to define
                 service contracts, find where quality factors can be
                 monitored, and to plan further expansion. We have
                 described a cloud ecosystem in the form of a pattern
                 diagram where its components are patterns and reference
                 architectures. A pattern is an encapsulated solution to
                 a recurrent problem. We have recently expanded these
                 models to cover fog systems and containers. Fog
                 Computing is a highly-virtualized platform that
                 provides compute, storage, and networking services
                 between end devices and Cloud Computing Data Centers; a
                 Software Container provides an execution environment
                 for applications sharing a host operating system,
                 binaries, and libraries with other containers. We
                 intend to use this architecture to answer a variety of
                 questions about the security of this system as well as
                 a reference to design interacting combinations of
                 heterogeneous components. We defined a metamodel to
                 relate security concepts which is being expanded.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security in Cloud Computing and Big
                 Data.",
}

@Article{Heaberlin:2016:EWN,
  author =       "Bradi Heaberlin and Simon DeDeo",
  title =        "The Evolution of {Wikipedia}'s Norm Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "2",
  pages =        "14",
  day =          "20",
  month =        apr,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8020014",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/2/14",
  abstract =     "Social norms have traditionally been difficult to
                 quantify. In any particular society, their sheer number
                 and complex interdependencies often limit a
                 system-level analysis. One exception is that of the
                 network of norms that sustain the online Wikipedia
                 community. We study the fifteen-year evolution of this
                 network using the interconnected set of pages that
                 establish, describe, and interpret the community's
                 norms. Despite Wikipedia's reputation for ad hoc
                 governance, we find that its normative evolution is
                 highly conservative. The earliest users create norms
                 that both dominate the network and persist over time.
                 These core norms govern both content and interpersonal
                 interactions using abstract principles such as
                 neutrality, verifiability, and assume good faith. As
                 the network grows, norm neighborhoods decouple
                 topologically from each other, while increasing in
                 semantic coherence. Taken together, these results
                 suggest that the evolution of Wikipedia's norm network
                 is akin to bureaucratic systems that predate the
                 information age.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Computational Social Sciences:
                 Contagion, Collective Behaviors, and Networks.",
}

@Article{Okamoto:2016:RBI,
  author =       "Kazuaki Okamoto and Kazumasa Takami",
  title =        "Routing Based on Information about the Routes of
                 Fixed-Route Traveling Nodes and on Destination Areas
                 Aimed at Reducing the Load on the {DTN}",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "2",
  pages =        "15",
  day =          "27",
  month =        apr,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8020015",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/2/15",
  abstract =     "In recent years, the interest in delay/disruption
                 tolerant networking (DTN) is growing as a means of
                 communication in times of disaster. To ensure that a
                 DTN works well in an emergency, it is desirable to
                 promote general use of the DTN, so that it will also be
                 used in normal times. Since the DTN uses mobile
                 terminals and vehicles, which are not dedicated network
                 devices, as relay nodes, the routing method should be
                 such that it does not impose a large processing load on
                 relay nodes. This paper considers use of a DTN for a
                 day-to-day service of delivering content to a specific
                 area and proposes a new routing method that is based on
                 information about the routes of fixed-route traveling
                 nodes, such as public transportation vehicles. The
                 destination of a bundle is specified not by a terminal
                 identifier, but by an area, which is identified by its
                 location information. This paper presents an
                 outbound-type bundle protocol, which is used by relay
                 nodes when they have received a forwarding-bundle
                 request from a sending terminal and try to determine
                 whether the bundle can reach its destination area.
                 Using simulation, the superiority of the proposed
                 routing was confirmed by comparing it to existing
                 routing methods in terms of the bundle arrival rate and
                 factors that affect the network load, such as the
                 number of bundle copies, the number of hops and the
                 maximum required buffer size.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ibba:2016:DLC,
  author =       "Simona Ibba and Filippo Eros Pani",
  title =        "Digital Libraries: The Challenge of Integrating
                 {Instagram} with a Taxonomy for Content Management",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "2",
  pages =        "16",
  day =          "10",
  month =        may,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8020016",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/2/16",
  abstract =     "Interoperability and social implication are two
                 current challenges in the digital library (DL) context.
                 To resolve the problem of interoperability, our work
                 aims to find a relationship between the main metadata
                 schemas. In particular, we want to formalize knowledge
                 through the creation of a metadata taxonomy built with
                 the analysis and the integration of existing schemas
                 associated with DLs. We developed a method to integrate
                 and combine Instagram metadata and hashtags. The final
                 result is a taxonomy, which provides innovative
                 metadata with respect to the classification of
                 resources, as images of Instagram and the
                 user-generated content, that play a primary role in the
                 context of modern DLs. The possibility of Instagram to
                 localize the photos inserted by users allows us to
                 interpret the most relevant and interesting informative
                 content for a specific user type and in a specific
                 location and to improve access, visibility and
                 searching of library content.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Human-Computer Interaction and the
                 Social Web.",
}

@Article{Premnath:2016:SPC,
  author =       "Sriram Nandha Premnath and Zygmunt J. Haas",
  title =        "Supporting Privacy of Computations in Mobile Big Data
                 Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "2",
  pages =        "17",
  day =          "10",
  month =        may,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8020017",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/2/17",
  abstract =     "Cloud computing systems enable clients to rent and
                 share computing resources of third party platforms, and
                 have gained widespread use in recent years. Numerous
                 varieties of mobile, small-scale devices such as
                 smartphones, red e-health devices, etc., across users,
                 are connected to one another through the massive
                 internetwork of vastly powerful servers on the cloud.
                 While mobile devices store ``private information'' of
                 users such as location, payment, health data, etc.,
                 they may also contribute ``semi-public information''
                 (which may include crowdsourced data such as transit,
                 traffic, nearby points of interests, etc.) for data
                 analytics. In such a scenario, a mobile device may seek
                 to obtain the result of a computation, which may depend
                 on its private inputs, crowdsourced data from other
                 mobile devices, and/or any ``public inputs'' from other
                 servers on the Internet. We demonstrate a new method of
                 delegating real-world computations of
                 resource-constrained mobile clients using an encrypted
                 program known as the garbled circuit. Using the garbled
                 version of a mobile client's inputs, a server in the
                 cloud executes the garbled circuit and returns the
                 resulting garbled outputs. Our system assures privacy
                 of the mobile client's input data and output of the
                 computation, and also enables the client to verify that
                 the evaluator actually performed the computation. We
                 analyze the complexity of our system. We measure the
                 time taken to construct the garbled circuit as well as
                 evaluate it for varying number of servers. Using
                 real-world data, we evaluate our system for a
                 practical, privacy preserving search application that
                 locates the nearest point of interest for the mobile
                 client to demonstrate feasibility.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security in Cloud Computing and Big
                 Data.",
}

@Article{Carrino:2016:IIT,
  author =       "Francesco Carrino and Elena Mugellini and Omar Abou
                 Khaled and Nabil Ouerhani and Juergen Ehrensberger",
  title =        "{iNUIT}: {Internet of Things} for Urban Innovation",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "2",
  pages =        "18",
  day =          "11",
  month =        may,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8020018",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/2/18",
  abstract =     "Internet of Things (IoT) seems a viable way to enable
                 the Smart Cities of the future. iNUIT (Internet of
                 Things for Urban Innovation) is a multi-year research
                 program that aims to create an ecosystem that exploits
                 the variety of data coming from multiple sensors and
                 connected objects installed on the scale of a city, in
                 order to meet specific needs in terms of development of
                 new services (physical security, resource management,
                 etc.). Among the multiple research activities within
                 iNUIT, we present two projects: SmartCrowd and OpEc.
                 SmartCrowd aims at monitoring the crowd's movement
                 during large events. It focuses on real-time tracking
                 using sensors available in smartphones and on the use
                 of a crowd simulator to detect possible dangerous
                 scenarios. A proof-of-concept of the application has
                 been tested at the Pal{\'e}o Festival (Switzerland)
                 showing the feasibility of the approach. OpEc
                 (Optimisation de l'Eclairage public) aims at using IoT
                 to implement dynamic street light management and
                 control with the goal of reducing street light energy
                 consumption while guaranteeing the same level of
                 security of traditional illumination. The system has
                 been tested during two months in a street in St-Imier
                 (Switzerland) without interruption, validating its
                 stability and resulting in an overall energy saving of
                 about 56\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Ecosystemic Evolution Feeded by Smart
                 Systems.",
}

@Article{Lettieri:2016:CSS,
  author =       "Nicola Lettieri",
  title =        "Computational Social Science, the Evolution of Policy
                 Design and Rule Making in Smart Societies",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "2",
  pages =        "19",
  day =          "12",
  month =        may,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8020019",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/2/19",
  abstract =     "In the last 20 years, the convergence of different
                 factors-the rise of the complexity of science, the
                 ``data deluge'' and the advances in information
                 technologies-triggered a paradigm shift in the way we
                 understand complex social systems and their evolution.
                 Beyond shedding new light onto social dynamics, the
                 emerging research area of Computational Social Science
                 (CSS) is providing a new rationale for a more
                 scientifically-grounded and effective policy design.
                 The paper discusses the opportunities potentially
                 deriving from the intersection between policy design
                 issues and CSS methods. After a general introduction to
                 the limits of traditional policy-making and a brief
                 review of the most promising CSS methodologies, the
                 work deals with way in which the insights potentially
                 offered by CSS can concretely flow in policy choices.
                 The attention is focused, to this end, on the legal
                 mechanisms regulating the formulation and the
                 evaluation of public policies. Our goal is two-fold:
                 sketch how the project of a ``smart society'' is
                 connected to the evolution of social sciences and
                 emphasize the need for change in the way in which
                 public policies are conceived of, designed and
                 implemented.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Ecosystemic Evolution Feeded by Smart
                 Systems.",
}

@Article{Pandey:2016:UFI,
  author =       "Pankaj Pandey and Einar Snekkenes",
  title =        "Using Financial Instruments to Transfer the
                 Information Security Risks",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "2",
  pages =        "20",
  day =          "17",
  month =        may,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8020020",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/2/20",
  abstract =     "For many individuals and organizations,
                 cyber-insurance is the most practical and only way of
                 handling a major financial impact of an information
                 security event. However, the cyber-insurance market
                 suffers from the problem of information asymmetry, lack
                 of product diversity, illiquidity, high transaction
                 cost, and so on. On the other hand, in theory, capital
                 market-based financial instruments can provide a risk
                 transfer mechanism with the ability to absorb the
                 adverse impact of an information security event. Thus,
                 this article addresses the limitations in the
                 cyber-(re)insurance markets with a set of capital
                 market-based financial instruments. This article
                 presents a set of information security derivatives,
                 namely options, vanilla options, swap, and futures that
                 can be traded at an information security prediction
                 market. Furthermore, this article demonstrates the
                 usefulness of information security derivatives in a
                 given scenario and presents an evaluation of the same
                 in comparison with cyber-insurance. In our analysis, we
                 found that the information security derivatives can at
                 least be a partial solution to the problems in the
                 cyber-insurance markets. The information security
                 derivatives can be used as an effective tool for
                 information elicitation and aggregation, cyber risk
                 pricing, risk hedging, and strategic decision making
                 for information security risk management.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lerman:2016:IVO,
  author =       "Kristina Lerman",
  title =        "Information Is Not a Virus, and Other Consequences of
                 Human Cognitive Limits",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "2",
  pages =        "21",
  day =          "13",
  month =        may,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8020021",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/2/21",
  abstract =     "The many decisions that people make about what to pay
                 attention to online shape the spread of information in
                 online social networks. Due to the constraints of
                 available time and cognitive resources, the ease of
                 discovery strongly impacts how people allocate their
                 attention to social media content. As a consequence,
                 the position of information in an individual's social
                 feed, as well as explicit social signals about its
                 popularity, determine whether it will be seen, and the
                 likelihood that it will be shared with followers.
                 Accounting for these cognitive limits simplifies
                 mechanics of information diffusion in online social
                 networks and explains puzzling empirical observations:
                 (i) information generally fails to spread in social
                 media and (ii) highly connected people are less likely
                 to re-share information. Studies of information
                 diffusion on different social media platforms reviewed
                 here suggest that the interplay between human cognitive
                 limits and network structure differentiates the spread
                 of information from other social contagions, such as
                 the spread of a virus through a population.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Computational Social Sciences:
                 Contagion, Collective Behaviors, and Networks.",
}

@Article{Sanchez:2016:DES,
  author =       "Luis Enrique S{\'a}nchez and Antonio Santos-Olmo and
                 Esther {\'A}lvarez and Monica Huerta and Sara Camacho
                 and Eduardo Fern{\'a}ndez-Medina",
  title =        "Development of an Expert System for the Evaluation of
                 Students' Curricula on the Basis of Competencies",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "2",
  pages =        "22",
  day =          "18",
  month =        may,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8020022",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/2/22",
  abstract =     "The concept of competence, which emerged during the
                 reform of computer engineering degrees, has not brought
                 benefits to companies when attempting to select the
                 most suitable candidates for their jobs. This article
                 aims to show some of the research that has been
                 conducted to determine why companies have not found
                 these skills useful and how both can be aligned.
                 Finally, we show the development of an Expert System
                 that will enable companies to select the most suitable
                 candidates for their jobs, considering personal and
                 social skills, along with technical knowledge. This
                 prototype will serve as a basis to align the
                 competencies defined in the curricula with professional
                 requirements, thus allowing a true alignment between
                 degree courses and the needs of professional
                 companies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Collection Information Systems Security.",
}

@Article{Fantacci:2016:CSS,
  author =       "Romano Fantacci and Dania Marabissi",
  title =        "Cognitive Spectrum Sharing: An Enabling Wireless
                 Communication Technology for a Wide Use of Smart
                 Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "2",
  pages =        "23",
  day =          "20",
  month =        may,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8020023",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/2/23",
  abstract =     "A smart city is an environment where a pervasive,
                 multi-service network is employed to provide citizens
                 improved living conditions as well as better public
                 safety and security. Advanced communication
                 technologies are essential to achieve this goal. In
                 particular, an efficient and reliable communication
                 network plays a crucial role in providing continue,
                 ubiquitous, and reliable interconnections among users,
                 smart devices, and applications. As a consequence,
                 wireless networking appears as the principal enabling
                 communication technology despite the necessity to face
                 severe challenges to satisfy the needs arising from a
                 smart environment, such as explosive data volume,
                 heterogeneous data traffic, and support of quality of
                 service constraints. An interesting approach for
                 meeting the growing data demand due to smart city
                 applications is to adopt suitable methodologies to
                 improve the usage of all potential spectrum resources.
                 Towards this goal, a very promising solution is
                 represented by the Cognitive Radio technology that
                 enables context-aware capability in order to pursue an
                 efficient use of the available communication resources
                 according to the surrounding environment conditions. In
                 this paper we provide a review of the characteristics,
                 challenges, and solutions of a smart city communication
                 architecture, based on the Cognitive Radio technology,
                 by focusing on two new network paradigms-namely,
                 Heterogeneous Network and Machines-to-Machines
                 communications-that are of special interest to
                 efficiently support smart city applications and
                 services.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Ecosystemic Evolution Feeded by Smart
                 Systems.",
}

@Article{Martini:2016:SOA,
  author =       "Barbara Martini and Federica Paganelli",
  title =        "A Service-Oriented Approach for Dynamic Chaining of
                 Virtual Network Functions over Multi-Provider
                 Software-Defined Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "2",
  pages =        "24",
  day =          "01",
  month =        jun,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8020024",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/2/24",
  abstract =     "Emerging technologies such as Software-Defined
                 Networks (SDN) and Network Function Virtualization
                 (NFV) promise to address cost reduction and flexibility
                 in network operation while enabling innovative network
                 service delivery models. However, operational network
                 service delivery solutions still need to be developed
                 that actually exploit these technologies, especially at
                 the multi-provider level. Indeed, the implementation of
                 network functions as software running over a
                 virtualized infrastructure and provisioned on a service
                 basis let one envisage an ecosystem of network services
                 that are dynamically and flexibly assembled by
                 orchestrating Virtual Network Functions even across
                 different provider domains, thereby coping with
                 changeable user and service requirements and context
                 conditions. In this paper we propose an approach that
                 adopts Service-Oriented Architecture (SOA)
                 technology-agnostic architectural guidelines in the
                 design of a solution for orchestrating and dynamically
                 chaining Virtual Network Functions. We discuss how SOA,
                 NFV, and SDN may complement each other in realizing
                 dynamic network function chaining through service
                 composition specification, service selection, service
                 delivery, and placement tasks. Then, we describe the
                 architecture of a SOA-inspired NFV orchestrator, which
                 leverages SDN-based network control capabilities to
                 address an effective delivery of elastic chains of
                 Virtual Network Functions. Preliminary results of
                 prototype implementation and testing activities are
                 also presented. The benefits for Network Service
                 Providers are also described that derive from the
                 adaptive network service provisioning in a
                 multi-provider environment through the orchestration of
                 computing and networking services to provide end users
                 with an enhanced service experience.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Ecosystemic Evolution Feeded by Smart
                 Systems.",
}

@Article{Garcia-Martinez:2016:MAE,
  author =       "Ant{\'o}n Garc{\'\i}a-Mart{\'\i}nez and Jos{\'e}
                 Rivas-Rangel and Jaime Rangel-Quintos and Jos{\'e}
                 Antonio Espinosa and Cecilio Barba and Carmen
                 De-Pablos-Heredero",
  title =        "A Methodological Approach to Evaluate Livestock
                 Innovations on Small-Scale Farms in Developing
                 Countries",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "2",
  pages =        "25",
  day =          "03",
  month =        jun,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8020025",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/2/25",
  abstract =     "The aim of the study was deepening the knowledge of
                 livestock innovations knowledge on small-scale farms in
                 developing countries. First, we developed a methodology
                 focused on identifying potential appropriate livestock
                 innovations for smallholders and grouped them in
                 innovation areas, defined as a set of well-organized
                 practices with a business purpose. Finally, a process
                 management program (PMP) was evaluated according to the
                 livestock innovation level and viability of the
                 small-scale farms. Logistic regression was used to
                 evaluate the impact of PMP on the economic viability of
                 the farm. Information from 1650 small-scale livestock
                 farms in Mexico was collected and the innovations were
                 grouped in five innovation areas: A1. Management, A2.
                 Feeding, A3. Genetic, A4. Reproduction and A5. Animal
                 Health. The resulting innovation level in the system
                 was low at 45.7\% and heterogeneous among areas. This
                 study shows the usefulness of the methodology described
                 and confirms that implementing a PMP allows improving
                 the viability an additional 21\%, due to a better
                 integration of processes, resulting in more efficient
                 management.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future Intelligent Systems and
                 Networks.",
}

@Article{Vovides:2016:ELU,
  author =       "Yianna Vovides and Sarah Inman",
  title =        "Elusive Learning-Using Learning Analytics to Support
                 Reflective Sensemaking of Ill-Structured Ethical
                 Problems: a Learner-Managed Dashboard Solution",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "2",
  pages =        "26",
  day =          "11",
  month =        jun,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8020026",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/2/26",
  abstract =     "Since the turn of the 21st century, we have seen a
                 surge of studies on the state of U.S. education
                 addressing issues such as cost, graduation rates,
                 retention, achievement, engagement, and curricular
                 outcomes. There is an expectation that graduates should
                 be able to enter the workplace equipped to take on
                 complex and ``messy'' or ill-structured problems as
                 part of their professional and everyday life. In the
                 context of online learning, we have identified two key
                 issues that are elusive (hard to capture and make
                 visible): learning with ill-structured problems and the
                 interaction of social and individual learning. We
                 believe that the intersection between learning and
                 analytics has the potential, in the long-term, to
                 minimize the elusiveness of deep learning. A proposed
                 analytics model is described in this article that is
                 meant to capture and also support further development
                 of a learner's reflective sensemaking.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue eLearning.",
}

@Article{Ye:2016:DSA,
  author =       "Ting Ye and Baowei Wang",
  title =        "Density Self-Adaptive Hybrid Clustering Routing
                 Protocol for Wireless Sensor Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "3",
  pages =        "27",
  day =          "29",
  month =        jun,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8030027",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/3/27",
  abstract =     "Energy efficiency is of major concern in wireless
                 sensor networks, especially in difficult node
                 deployment environments. Clustering is an effective
                 method to save energy consumption and prolong the
                 network lifetime. There are two kinds of clustering
                 methods in hierarchical routing protocols, namely
                 distributed control and centralized control. In the
                 distributed strategy, the algorithm has good
                 scalability, but it can easily lead to an uneven
                 distribution of cluster heads. When the centralized
                 strategy is used, the network is balanced and robust,
                 but the overhead of clustering is large and the network
                 latency is increased. In our proposed protocol, named
                 DAHC, a mixture algorithm of distributed and
                 centralized control is used to select a cluster head
                 (CH). Simultaneously, we propose a novel approach to
                 judge the cluster density and adjust according to the
                 preset threshold. The simulation results show that our
                 methods can evenly distribute the energy load on all
                 nodes, save the energy consumption of communication and
                 extend the network lifetime concurrently.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Strizhov:2016:SPS,
  author =       "Mikhail Strizhov and Zachary Osman and Indrajit Ray",
  title =        "Substring Position Search over Encrypted Cloud Data
                 Supporting Efficient Multi-User Setup",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "3",
  pages =        "28",
  day =          "04",
  month =        jul,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8030028",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/3/28",
  abstract =     "Existing Searchable Encryption (SE) solutions are able
                 to handle simple Boolean search queries, such as single
                 or multi-keyword queries, but cannot handle substring
                 search queries over encrypted data that also involve
                 identifying the position of the substring within the
                 document. These types of queries are relevant in areas
                 such as searching DNA data. In this paper, we propose a
                 tree-based Substring Position Searchable Symmetric
                 Encryption (SSP-SSE) to overcome the existing gap. Our
                 solution efficiently finds occurrences of a given
                 substring over encrypted cloud data. Specifically, our
                 construction uses the position heap tree data structure
                 and achieves asymptotic efficiency comparable to that
                 of an unencrypted position heap tree. Our encryption
                 takes O (k n) time, and the resulting ciphertext is of
                 size O (k n), where k is a security parameter and n is
                 the size of stored data. The search takes O (m 2 + o c
                 c) time and three rounds of communication, where m is
                 the length of the queried substring and o c c is the
                 number of occurrences of the substring in the document
                 collection. We prove that the proposed scheme is secure
                 against chosen-query attacks that involve an adaptive
                 adversary. Finally, we extend SSP-SSE to the multi-user
                 setting where an arbitrary group of cloud users can
                 submit substring queries to search the encrypted
                 data.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security in Cloud Computing and Big
                 Data.",
}

@Article{Haider:2016:WBD,
  author =       "Waqas Haider and Gideon Creech and Yi Xie and Jiankun
                 Hu",
  title =        "{Windows} Based Data Sets for Evaluation of Robustness
                 of Host Based Intrusion Detection Systems ({IDS}) to
                 Zero-Day and Stealth Attacks",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "3",
  pages =        "29",
  day =          "05",
  month =        jul,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8030029",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/3/29",
  abstract =     "The Windows Operating System (OS) is the most popular
                 desktop OS in the world, as it has the majority market
                 share of both servers and personal computing
                 necessities. However, as its default signature-based
                 security measures are ineffectual for detecting
                 zero-day and stealth attacks, it needs an intelligent
                 Host-based Intrusion Detection System (HIDS).
                 Unfortunately, a comprehensive data set that reflects
                 the modern Windows OS's normal and attack surfaces is
                 not publicly available. To fill this gap, in this paper
                 two open data sets generated by the cyber security
                 department of the Australian Defence Force Academy
                 (ADFA) are introduced, namely: Australian Defence Force
                 Academy Windows Data Set (ADFA-WD); and Australian
                 Defence Force Academy Windows Data Set with a Stealth
                 Attacks Addendum (ADFA-WD: SAA). Statistical analysis
                 results based on these data sets show that, due to the
                 low foot prints of modern attacks and high similarity
                 of normal and attacked data, both these data sets are
                 complex, and highly intelligent Host based Anomaly
                 Detection Systems (HADS) design will be required.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Cyber Warfare.",
}

@Article{Santos-Olmo:2016:ISC,
  author =       "Antonio Santos-Olmo and Luis Enrique S{\'a}nchez and
                 Ismael Caballero and Sara Camacho and Eduardo
                 Fernandez-Medina",
  title =        "The Importance of the Security Culture in {SMEs} as
                 Regards the Correct Management of the Security of Their
                 Assets",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "3",
  pages =        "30",
  day =          "07",
  month =        jul,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8030030",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/3/30",
  abstract =     "The information society is increasingly more dependent
                 on Information Security Management Systems (ISMSs), and
                 the availability of these kinds of systems is now vital
                 for the development of Small and Medium-Sized
                 Enterprises (SMEs). However, these companies require
                 ISMSs that have been adapted to their special features,
                 and which are optimized as regards the resources needed
                 to deploy and maintain them. This article shows how
                 important the security culture within ISMSs is for
                 SMEs, and how the concept of security culture has been
                 introduced into a security management methodology
                 (MARISMA is a Methodology for ``Information Security
                 Management System in SMEs'' developed by the Sicaman
                 Nuevas Tecnolog{\'\i}as Company, Research Group GSyA
                 and Alarcos of the University of Castilla-La Mancha.)
                 for SMEs. This model is currently being directly
                 applied to real cases, thus allowing a steady
                 improvement to be made to its implementation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Collection Information Systems Security.",
}

@Article{DeDeo:2016:CCW,
  author =       "Simon DeDeo",
  title =        "Conflict and Computation on {Wikipedia}: a
                 Finite-State Machine Analysis of {Editor}
                 Interactions",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "3",
  pages =        "31",
  day =          "08",
  month =        jul,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8030031",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/3/31",
  abstract =     "What is the boundary between a vigorous argument and a
                 breakdown of relations? What drives a group of
                 individuals across it? Taking Wikipedia as a test case,
                 we use a hidden Markov model to approximate the
                 computational structure and social grammar of more than
                 a decade of cooperation and conflict among its editors.
                 Across a wide range of pages, we discover a bursty
                 war/peace structure where the systems can become
                 trapped, sometimes for months, in a computational
                 subspace associated with significantly higher levels of
                 conflict-tracking ``revert'' actions. Distinct patterns
                 of behavior characterize the lower-conflict subspace,
                 including tit-for-tat reversion. While a fraction of
                 the transitions between these subspaces are associated
                 with top-down actions taken by administrators, the
                 effects are weak. Surprisingly, we find no statistical
                 signal that transitions are associated with the
                 appearance of particularly anti-social users, and only
                 weak association with significant news events outside
                 the system. These findings are consistent with
                 transitions being driven by decentralized processes
                 with no clear locus of control. Models of belief
                 revision in the presence of a common resource for
                 information-sharing predict the existence of two
                 distinct phases: a disordered high-conflict phase, and
                 a frozen phase with spontaneously-broken symmetry. The
                 bistability we observe empirically may be a consequence
                 of editor turn-over, which drives the system to a
                 critical point between them.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Computational Social Sciences:
                 Contagion, Collective Behaviors, and Networks.",
}

@Article{Guidi:2016:CSI,
  author =       "Gabriele Guidi and Roberto Miniati and Matteo Mazzola
                 and Ernesto Iadanza",
  title =        "Case Study: {IBM Watson} Analytics Cloud Platform as
                 Analytics-as-a-Service System for Heart Failure Early
                 Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "3",
  pages =        "32",
  day =          "13",
  month =        jul,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8030032",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/3/32",
  abstract =     "In the recent years the progress in technology and the
                 increasing availability of fast connections have
                 produced a migration of functionalities in Information
                 Technologies services, from static servers to
                 distributed technologies. This article describes the
                 main tools available on the market to perform Analytics
                 as a Service (AaaS) using a cloud platform. It is also
                 described a use case of IBM Watson Analytics, a cloud
                 system for data analytics, applied to the following
                 research scope: detecting the presence or absence of
                 Heart Failure disease using nothing more than the
                 electrocardiographic signal, in particular through the
                 analysis of Heart Rate Variability. The obtained
                 results are comparable with those coming from the
                 literature, in terms of accuracy and predictive power.
                 Advantages and drawbacks of cloud versus static
                 approaches are discussed in the last sections.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Ecosystemic Evolution Feeded by Smart
                 Systems.",
}

@Article{Florez:2016:ADC,
  author =       "Ang{\'e}lica Fl{\'o}rez and Lenin Serrano and Urbano
                 G{\'o}mez and Luis Su{\'a}rez and Alejandro Villarraga
                 and Hugo Rodr{\'\i}guez",
  title =        "Analysis of Dynamic Complexity of the Cyber Security
                 Ecosystem of {Colombia}",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "3",
  pages =        "33",
  day =          "19",
  month =        jul,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8030033",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/3/33",
  abstract =     "This paper presents two proposals for the analysis of
                 the complexity of the Cyber security Ecosystem of
                 Colombia (CEC). This analysis shows the available
                 knowledge about entities engaged in cyber security in
                 Colombia and the relationships between them, which
                 allow an understanding of the synergy between the
                 different existing components. The complexity of the
                 CEC is detailed from the view of the Influence Diagram
                 of System Dynamics and the Domain Diagram of Software
                 Engineering. The resulting model makes cyber security
                 evident as a strategic component of national
                 security.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Collection Information Systems Security.",
}

@Article{Merrick:2016:SGT,
  author =       "Kathryn Merrick and Medria Hardhienata and Kamran
                 Shafi and Jiankun Hu",
  title =        "A Survey of Game Theoretic Approaches to Modelling
                 Decision-Making in Information Warfare Scenarios",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "3",
  pages =        "34",
  day =          "22",
  month =        jul,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8030034",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/3/34",
  abstract =     "Our increasing dependence on information technologies
                 and autonomous systems has escalated international
                 concern for information- and cyber-security in the face
                 of politically, socially and religiously motivated
                 cyber-attacks. Information warfare tactics that
                 interfere with the flow of information can challenge
                 the survival of individuals and groups. It is
                 increasingly important that both humans and machines
                 can make decisions that ensure the trustworthiness of
                 information, communication and autonomous systems.
                 Subsequently, an important research direction is
                 concerned with modelling decision-making processes. One
                 approach to this involves modelling decision-making
                 scenarios as games using game theory. This paper
                 presents a survey of information warfare literature,
                 with the purpose of identifying games that model
                 different types of information warfare operations. Our
                 contribution is a systematic identification and
                 classification of information warfare games, as a basis
                 for modelling decision-making by humans and machines in
                 such scenarios. We also present a taxonomy of games
                 that map to information warfare and cyber crime
                 problems as a precursor to future research on
                 decision-making in such scenarios. We identify and
                 discuss open research questions including the role of
                 behavioural game theory in modelling human decision
                 making and the role of machine decision-making in
                 information warfare scenarios.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Cyber Warfare.",
}

@Article{Kou:2016:TVR,
  author =       "Weili Kou and Hui Li and Kailai Zhou",
  title =        "Turning Video Resource Management into Cloud
                 Computing",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "3",
  pages =        "35",
  day =          "21",
  month =        jul,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8030035",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/3/35",
  abstract =     "Big data makes cloud computing more and more popular
                 in various fields. Video resources are very useful and
                 important to education, security monitoring, and so on.
                 However, issues of their huge volumes, complex data
                 types, inefficient processing performance, weak
                 security, and long times for loading pose challenges in
                 video resource management. The Hadoop Distributed File
                 System (HDFS) is an open-source framework, which can
                 provide cloud-based platforms and presents an
                 opportunity for solving these problems. This paper
                 presents video resource management architecture based
                 on HDFS to provide a uniform framework and a five-layer
                 model for standardizing the current various algorithms
                 and applications. The architecture, basic model, and
                 key algorithms are designed for turning video resources
                 into a cloud computing environment. The design was
                 tested by establishing a simulation system prototype.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future Intelligent Systems and
                 Networks.",
}

@Article{Santos-Olmo:2016:AAR,
  author =       "Antonio Santos-Olmo and Luis Enrique S{\'a}nchez and
                 David G. Rosado and Eduardo Fern{\'a}ndez-Medina and
                 Mario Piattini",
  title =        "Applying the Action-Research Method to Develop a
                 Methodology to Reduce the Installation and Maintenance
                 Times of Information Security Management Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "3",
  pages =        "36",
  day =          "22",
  month =        jul,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8030036",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/3/36",
  abstract =     "Society is increasingly dependent on Information
                 Security Management Systems (ISMS), and having these
                 kind of systems has become vital for the development of
                 Small and Medium-Sized Enterprises (SMEs). However,
                 these companies require ISMS that have been adapted to
                 their special features and have been optimized as
                 regards the resources needed to deploy and maintain
                 them, with very low costs and short implementation
                 periods. This paper discusses the different cycles
                 carried out using the `Action Research (AR)' method,
                 which have allowed the development of a security
                 management methodology for SMEs that is able to
                 automate processes and reduce the implementation time
                 of the ISMS.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Collection Information Systems Security.",
}

@Article{Boulos:2016:IWH,
  author =       "Maged N. Kamel Boulos and Dean M. Giustini and Steve
                 Wheeler",
  title =        "{Instagram} and {WhatsApp} in Health and Healthcare:
                 an Overview",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "3",
  pages =        "37",
  day =          "26",
  month =        jul,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8030037",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/3/37",
  abstract =     "Instagram and WhatsApp are two social media and
                 networking services introduced in 2010. They are
                 currently subsidiaries of Facebook, Inc., California,
                 USA. Using evidence from the published literature and
                 case reports indexed in PubMed and other sources, we
                 present an overview of the various applications of
                 Instagram and WhatsApp in health and healthcare. We
                 also briefly describe the main issues surrounding the
                 uses of these two apps in health and medicine.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue e-Health.",
}

@Article{Yang:2016:NQP,
  author =       "Weijun Yang and Yuanfeng Chen",
  title =        "A Novel {QoS} Provisioning Algorithm for Optimal
                 Multicast Routing in {WMNs}",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "3",
  pages =        "38",
  day =          "01",
  month =        aug,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8030038",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/3/38",
  abstract =     "The problem of optimal multicast routing in Wireless
                 Mess Networks (WMNs) with Quality-of-Service (QoS)
                 provisioning, which is Non-Deterministic Polynomial
                 (NP)-complete, is studied in this paper. The existing
                 algorithms are not very efficient or effective. In
                 order to find an approximation optimal solution for
                 WMNs in feasible time from source to the set of
                 destination nodes, combining the previous deterministic
                 algorithm with the well-known Minimum Path Cost
                 Heuristic (MPH) algorithm, a novel multicast heuristic
                 approximation (NMHA) algorithm with QoS provisioning is
                 proposed in this paper to deal with it. The theoretical
                 validations for the proposed algorithm are presented to
                 show its performance and efficiency. After that, the
                 random static networks with different destination nodes
                 are evaluated. Simulations in these networks show that
                 the proposed algorithm can achieve the approximate
                 optimal solution with the approximation factor of 2(1 +
                 \epsilon)(1 - 1/ q) and the time complexity of O(qmn 2
                 \tau K-1).",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future Intelligent Systems and
                 Networks.",
}

@Article{Liu:2016:OBR,
  author =       "Xin Liu and Zhongfu Li and Shaohua Jiang",
  title =        "Ontology-Based Representation and Reasoning in
                 Building Construction Cost Estimation in {China}",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "3",
  pages =        "39",
  day =          "03",
  month =        aug,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8030039",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/3/39",
  abstract =     "Cost estimation is one of the most critical tasks for
                 building construction project management. The existing
                 building construction cost estimation methods of many
                 countries, including China, require information from
                 several sources, including material, labor, and
                 equipment, and tend to be manual, time-consuming, and
                 error-prone. To solve these problems, a building
                 construction cost estimation model based on ontology
                 representation and reasoning is established, which
                 includes three major components, i.e., concept model
                 ontology, work item ontology, and construction
                 condition ontology. Using this model, the cost
                 estimation information is modeled into OWL axioms and
                 SWRL rules that leverage the semantically rich ontology
                 representation to reason about cost estimation. Based
                 on OWL axioms and SWRL rules, the cost estimation
                 information can be translated into a set of concept
                 models, work items, and construction conditions
                 associated with the specific construction conditions.
                 The proposed method is demonstrated in Prot{\'e}g{\'e}
                 3.4.8 through case studies based on the Measurement
                 Specifications of Building Construction and Decoration
                 Engineering taken from GB 50500-2013 (the Chinese
                 national mandatory specifications). Finally, this
                 research discusses the limitations of the proposed
                 method and future research directions. The proposed
                 method can help a building construction cost estimator
                 extract information more easily and quickly.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Semantic Computing and Knowledge
                 Building.",
}

@Article{Chinnachodteeranun:2016:SOS,
  author =       "Rassarin Chinnachodteeranun and Kiyoshi Honda",
  title =        "Sensor Observation Service {API} for Providing Gridded
                 Climate Data to Agricultural Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "3",
  pages =        "40",
  day =          "09",
  month =        aug,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8030040",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/3/40",
  abstract =     "We developed a mechanism for seamlessly providing
                 weather data and long-term historical climate data from
                 a gridded data source through an international standard
                 web API, which was the Sensor Observation Service (SOS)
                 defined by the Open Geospatial Consortium (OGC). The
                 National Agriculture and Food Research Organization
                 (NARO) Japan has been providing gridded climate data
                 consisting of nine daily meteorological variables,
                 which are average, minimum, maximum of air temperature,
                 relative humidity, sunshine duration, solar radiant
                 exposure, downward longwave radiation, precipitation
                 and wind speed for 35 years covering Japan. The gridded
                 data structure is quite useful for spatial analysis,
                 such as developing crop suitability maps and monitoring
                 regional crop development. Individual farmers, however,
                 make decisions using historical climate information and
                 forecasts for an incoming cropping season of their
                 farms. In this regard, climate data at a point-based
                 structure are convenient for application development to
                 support farmers' decisions. Through the proposed
                 mechanism in this paper, the agricultural applications
                 and analysis can request point-based climate data from
                 a gridded data source through the standard API with no
                 need to deal with the complicated hierarchical data
                 structure of the gridded climate data source. Clients
                 can easily obtain data and metadata by only accessing
                 the service endpoint. The mechanism also provides
                 several web bindings and data encodings for the
                 clients' convenience. Caching, including the
                 pre-caching mechanism, was developed and evaluated to
                 secure an effective response time. The mechanism
                 enhances the accessibility and usability of the gridded
                 weather data source, as well as SOS API for
                 agricultural applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Diaz:2016:CAT,
  author =       "Paloma D{\'\i}az and John M. Carroll and Ignacio
                 Aedo",
  title =        "Coproduction as an Approach to Technology-Mediated
                 Citizen Participation in Emergency Management",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "3",
  pages =        "41",
  day =          "10",
  month =        aug,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8030041",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/3/41",
  abstract =     "Social and mobile computing open up new possibilities
                 for integrating citizens' information, knowledge, and
                 social capital in emergency management (EM). This
                 participation can improve the capacity of local
                 agencies to respond to unexpected events by involving
                 citizens not only as first line informants, but also as
                 first responders. This participation could contribute
                 to build resilient communities aware of the risks they
                 are threatened by and able to mobilize their social
                 capital to cope with them and, in turn, decrease the
                 impact of threats and hazards. However for this
                 participation to be possible organizations in charge of
                 EM need to realize that involving citizens does not
                 interfere with their protocols and that citizens are a
                 valuable asset that can contribute to the EM process
                 with specific skills and capabilities. In this paper we
                 discuss the design challenges of using social and
                 mobile computing to move to a more participatory EM
                 process that starts by empowering both citizens and
                 organizations in a coproduction service envisioned as a
                 partnership effort. As an example, we describe a case
                 study of a participatory design approach that involved
                 professional EM workers and decision makers in an
                 effort to understand the challenges of using
                 technology-based solutions to integrate citizen skills
                 and capabilities in their operation protocols. The case
                 study made it possible to identify specific roles that
                 citizens might play in a crisis or disaster and to
                 envision scenarios were technologies could be used to
                 integrate their skills into the EM process. In this way
                 the paper contributes to the roles and the scenarios of
                 theory-building about coproduction in EM services.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future Mobile Computing.",
}

@Article{Francese:2016:SEP,
  author =       "Rita Francese and Michele Risi",
  title =        "Supporting Elderly People by Ad Hoc Generated Mobile
                 Applications Based on Vocal Interaction",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "3",
  pages =        "42",
  day =          "25",
  month =        aug,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8030042",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/3/42",
  abstract =     "Mobile devices can be exploited for enabling people to
                 interact with Internet of Things (IoT) services. The
                 MicroApp Generator [1] is a service-composition tool
                 for supporting the generation of mobile applications
                 directly on the mobile device. The user interacts with
                 the generated app by using the traditional touch-based
                 interaction. This kind of interaction often is not
                 suitable for elderly and special needs people that
                 cannot see or touch the screen. In this paper, we
                 extend the MicroApp Generator with an interaction
                 approach enabling a user to interact with the generated
                 app only by using his voice, which can be very useful
                 to let special needs people live at home. To this aim,
                 once the mobile app has been generated and executed,
                 the system analyses and describes the user interface,
                 listens to the user speech and performs the associated
                 actions. A preliminary analysis has been conducted to
                 assess the user experience of the proposed approach by
                 a sample composed of elderly users by using a
                 questionnaire as a research instrument.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future Mobile Computing.",
}

@Article{Carta:2016:ISI,
  author =       "Salvatore Carta and Ludovico Boratto",
  title =        "Introduction to the Special Issue on Human-Computer
                 Interaction and the {Social Web}",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "3",
  pages =        "43",
  day =          "01",
  month =        sep,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8030043",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/3/43",
  abstract =     "Data is currently one of the most important assets for
                 companies in every field. The continuous growth in the
                 importance and volume of data has created a new
                 problem: it cannot be handled by traditional analysis
                 techniques. This problem was, therefore, solved through
                 the creation of a new paradigm: Big Data. However, Big
                 Data originated new issues related not only to the
                 volume or the variety of the data, but also to data
                 security and privacy. In order to obtain a full
                 perspective of the problem, we decided to carry out an
                 investigation with the objective of highlighting the
                 main issues regarding Big Data security, and also the
                 solutions proposed by the scientific community to solve
                 them. In this paper, we explain the results obtained
                 after applying a systematic mapping study to security
                 in the Big Data ecosystem. It is almost impossible to
                 carry out detailed research into the entire topic of
                 security, and the outcome of this research is,
                 therefore, a big picture of the main problems related
                 to security in a Big Data system, along with the
                 principal solutions to them proposed by the research
                 community.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Human-Computer Interaction and the
                 Social Web.",
}

@Article{Moreno:2016:MIB,
  author =       "Julio Moreno and Manuel A. Serrano and Eduardo
                 Fern{\'a}ndez-Medina",
  title =        "Main Issues in Big Data Security",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "3",
  pages =        "44",
  day =          "01",
  month =        sep,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8030044",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/3/44",
  abstract =     "Data is currently one of the most important assets for
                 companies in every field. The continuous growth in the
                 importance and volume of data has created a new
                 problem: it cannot be handled by traditional analysis
                 techniques. This problem was, therefore, solved through
                 the creation of a new paradigm: Big Data. However, Big
                 Data originated new issues related not only to the
                 volume or the variety of the data, but also to data
                 security and privacy. In order to obtain a full
                 perspective of the problem, we decided to carry out an
                 investigation with the objective of highlighting the
                 main issues regarding Big Data security, and also the
                 solutions proposed by the scientific community to solve
                 them. In this paper, we explain the results obtained
                 after applying a systematic mapping study to security
                 in the Big Data ecosystem. It is almost impossible to
                 carry out detailed research into the entire topic of
                 security, and the outcome of this research is,
                 therefore, a big picture of the main problems related
                 to security in a Big Data system, along with the
                 principal solutions to them proposed by the research
                 community.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security in Cloud Computing and Big
                 Data.",
}

@Article{Kosenkov:2016:CCN,
  author =       "Alexander Kosenkov",
  title =        "Cyber Conflicts as a New Global Threat",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "3",
  pages =        "45",
  day =          "09",
  month =        sep,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8030045",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:55 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/3/45",
  abstract =     "In this paper, an attempt is made to analyze the
                 potential threats and consequences of cyber conflicts
                 and, in particular, the risks of a global cyber
                 conflict. The material is based on a comprehensive
                 analysis of the nature of cyber conflict and its
                 elements from both technical and societal points of
                 view. The approach used in the paper considers the
                 societal component as an essential part of cyber
                 conflicts, allowing basics of cyber conflicts often
                 disregarded by researchers and the public to be
                 highlighted. Finally, the conclusion offers an
                 opportunity to consider cyber conflict as the most
                 advanced form of modern warfare, which imposes the most
                 serious threat and whose effect could be comparable to
                 weapons of mass destruction.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Cyber Warfare.",
}

@Article{Marti:2016:DED,
  author =       "Patrizia Marti and Carl Megens and Caroline Hummels",
  title =        "Data-Enabled Design for Social Change: Two Case
                 Studies",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "4",
  pages =        "46",
  day =          "23",
  month =        sep,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8040046",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:56 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/4/46",
  abstract =     "Smartness in contemporary society implies the use of
                 massive data to improve the experience of people with
                 connected services and products. The use of big data to
                 collect information about people's behaviours opens a
                 new concept of ``user-centred design'' where users are
                 remotely monitored, observed and profiled. In this
                 paradigm, users are considered as sources of
                 information and their participation in the design
                 process is limited to a role of data generators. There
                 is a need to identify methodologies that actively
                 involve people and communities at the core of
                 ecosystems of interconnected products and services. Our
                 contribution to designing for social innovation in
                 ecosystems relies on developing new methods and
                 approaches to transform data-driven design using a
                 participatory and co-creative data-enabled design
                 approach. To this end, we present one of the methods we
                 have developed to design ``smart'' systems called
                 Experiential Design Landscapes (EDL), and two sample
                 projects, Social Stairs and [Y]our Perspective. Social
                 Stairs faces the topic of behaviour change mediated by
                 sensing technologies. [Y]our Perspective is a social
                 platform to sustain processes of deliberative
                 democracy. Both projects exemplify our approach to
                 data-enabled design as a social proactive participatory
                 design approach.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Ecosystemic Evolution Feeded by Smart
                 Systems.",
}

@Article{Deng:2016:RCM,
  author =       "Ziyun Deng and Lei Chen and Tingqing He and Tao Meng",
  title =        "A Reliability Calculation Method for {Web} Service
                 Composition Using Fuzzy Reasoning Colored {Petri} Nets
                 and Its Application on Supercomputing Cloud Platform",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "4",
  pages =        "47",
  day =          "27",
  month =        sep,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8040047",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:56 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/4/47",
  abstract =     "In order to develop a Supercomputing Cloud Platform
                 (SCP) prototype system using Service-Oriented
                 Architecture (SOA) and Petri nets, we researched some
                 technologies for Web service composition. Specifically,
                 in this paper, we propose a reliability calculation
                 method for Web service compositions, which uses Fuzzy
                 Reasoning Colored Petri Net (FRCPN) to verify the Web
                 service compositions. We put forward a definition of
                 semantic threshold similarity for Web services and a
                 formal definition of FRCPN. We analyzed five kinds of
                 production rules in FRCPN, and applied our method to
                 the SCP prototype. We obtained the reliability value of
                 the end Web service as an indicator of the overall
                 reliability of the FRCPN. The method can test the
                 activity of FRCPN. Experimental results show that the
                 reliability of the Web service composition has a
                 correlation with the number of Web services and the
                 range of reliability transition values.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future Intelligent Systems and
                 Networks.",
}

@Article{Alti:2016:ASB,
  author =       "Adel Alti and Abderrahim Lakehal and S{\'e}bastien
                 Laborie and Philippe Roose",
  title =        "Autonomic Semantic-Based Context-Aware Platform for
                 Mobile Applications in Pervasive Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "4",
  pages =        "48",
  day =          "29",
  month =        sep,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8040048",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:56 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/4/48",
  abstract =     "Currently, the field of smart-* (home, city, health,
                 tourism, etc.) is naturally heterogeneous and
                 multimedia oriented. In such a domain, there is an
                 increasing usage of heterogeneous mobile devices, as
                 well as captors transmitting data (IoT). They are
                 highly connected and can be used for many different
                 services, such as to monitor, to analyze and to display
                 information to users. In this context, data management
                 and adaptation in real time are becoming a challenging
                 task. More precisely, at one time, it is necessary to
                 handle in a dynamic, intelligent and transparent
                 framework various data provided by multiple devices
                 with several modalities. This paper presents a
                 Kali-Smart platform, which is an autonomic
                 semantic-based context-aware platform. It is based on
                 semantic web technologies and a middleware providing
                 autonomy and reasoning facilities. Moreover, Kali-Smart
                 is generic and, as a consequence, offers to users a
                 flexible infrastructure where they can easily control
                 various interaction modalities of their own situations.
                 An experimental study has been made to evaluate the
                 performance and feasibility of the proposed platform.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future Mobile Computing.",
}

@Article{Huckle:2016:SB,
  author =       "Steve Huckle and Martin White",
  title =        "Socialism and the Blockchain",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "4",
  pages =        "49",
  day =          "18",
  month =        oct,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8040049",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:56 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/4/49",
  abstract =     "Bitcoin (BTC) is often cited as Libertarian. However,
                 the technology underpinning Bitcoin, blockchain, has
                 properties that make it ideally suited to Socialist
                 paradigms. Current literature supports the Libertarian
                 viewpoint by focusing on the ability of Bitcoin to
                 bypass central authority and provide anonymity; rarely
                 is there an examination of blockchain technology's
                 capacity for decentralised transparency and
                 auditability in support of a Socialist model. This
                 paper conducts a review of the blockchain,
                 Libertarianism, and Socialist philosophies. It then
                 explores Socialist models of public ownership and looks
                 at the unique cooperative properties of blockchain that
                 make the technology ideal for supporting Socialist
                 societies. In summary, this paper argues that
                 blockchain technologies are not just a Libertarian
                 tool, they also enhance Socialist forms of
                 governance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future Intelligent Systems and
                 Networks.",
}

@Article{Angelini:2016:SLL,
  author =       "Leonardo Angelini and Stefano Carrino and Omar Abou
                 Khaled and Susie Riva-Mossman and Elena Mugellini",
  title =        "Senior Living Lab: An Ecological Approach to {Foster}
                 Social Innovation in an Ageing Society",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "4",
  pages =        "50",
  day =          "21",
  month =        oct,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8040050",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:56 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/4/50",
  abstract =     "The Senior Living Lab (SLL) is a transdisciplinary
                 research platform created by four Universities that
                 aims at promoting ageing well at home through the
                 co-creation of innovative products, services and
                 practices with older adults. While most living labs for
                 ageing well are focused on Information and
                 Communication Technologies (ICTs), this social
                 laboratory adopts a transdisciplinary approach,
                 bringing together designers, economists, engineers and
                 healthcare professionals to develop multiple forms of
                 social innovation using participatory methods. The SLL
                 is based on an ecological approach, connecting
                 professionals and users in a cooperative network and
                 involving all of the stakeholders concerned with ageing
                 well, such as existing associations, business entities
                 and policy-makers. Three main themes for the co-design
                 of products and services were identified at the
                 beginning of the SLL conception, each sustained by a
                 major business partner: healthy nutrition to cope with
                 frailty, improved autonomous mobility to foster
                 independence and social communication to prevent
                 isolation. This article shows the innovative
                 transdisciplinary approach of the SLL and discusses the
                 particular challenges that emerged during the first
                 year of its creation, investigating the role of ICTs
                 when designing products and services for older
                 adults.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Ecosystemic Evolution Feeded by Smart
                 Systems.",
}

@Article{Ali:2016:OSD,
  author =       "Syed Mustafa Ali and Rachel Powers and Jeffrey Beorse
                 and Arif Noor and Farah Naureen and Naveed Anjum and
                 Muhammad Ishaq and Javariya Aamir and Richard
                 Anderson",
  title =        "{ODK} Scan: Digitizing Data Collection and Impacting
                 Data Management Processes in {Pakistan}'s Tuberculosis
                 Control Program",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "4",
  pages =        "51",
  day =          "24",
  month =        oct,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8040051",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:56 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/4/51",
  abstract =     "The present grievous tuberculosis situation can be
                 improved by efficient case management and timely
                 follow-up evaluations. With the advent of digital
                 technology, this can be achieved through quick
                 summarization of the patient-centric data. The aim of
                 our study was to assess the effectiveness of the ODK
                 Scan paper-to-digital system during a testing period of
                 three months. A sequential, explanatory mixed-method
                 research approach was employed to elucidate technology
                 use. Training, smartphones, the application and
                 3G-enabled SIMs were provided to the four field
                 workers. At the beginning, baseline measures of the
                 data management aspects were recorded and compared with
                 endline measures to determine the impact of ODK Scan.
                 Additionally, at the end of the study, users' feedback
                 was collected regarding app usability, user interface
                 design and workflow changes. A total of 122 patients'
                 records were retrieved from the server and analysed in
                 terms of quality. It was found that ODK Scan recognized
                 99.2\% of multiple choice fill-in bubble responses and
                 79.4\% of numerical digit responses correctly. However,
                 the overall quality of the digital data was decreased
                 in comparison to manually entered data. Using ODK Scan,
                 a significant time reduction is observed in data
                 aggregation and data transfer activities, but data
                 verification and form-filling activities took more
                 time. Interviews revealed that field workers saw value
                 in using ODK Scan, but they were more concerned about
                 the time-consuming aspects of the use of ODK Scan.
                 Therefore, it is concluded that minimal disturbance in
                 the existing workflow, continuous feedback and value
                 additions are the important considerations for the
                 implementing organization to ensure technology adoption
                 and workflow improvements.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue e-Health.",
}

@Article{Hoang:2016:RHI,
  author =       "Xuan Dau Hoang and Hong Ky Pham",
  title =        "A Review on Hot-{IP} Finding Methods and Its
                 Application in Early {DDoS} Target Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "4",
  pages =        "52",
  day =          "25",
  month =        oct,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8040052",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:56 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/4/52",
  abstract =     "On the high-speed connections of the Internet or
                 computer networks, the IP (Internet Protocol) packet
                 traffic passing through the network is extremely high,
                 and that makes it difficult for network monitoring and
                 attack detection applications. This paper reviews
                 methods to find the high-occurrence-frequency elements
                 in the data stream and applies the most efficient
                 methods to find Hot-IPs that are high-frequency IP
                 addresses of IP packets passing through the network.
                 Fast finding of Hot-IPs in the IP packet stream can be
                 effectively used in early detection of DDoS
                 (Distributed Denial of Service) attack targets and
                 spreading sources of network worms. Research results
                 show that the Count-Min method gives the best overall
                 performance for Hot-IP detection thanks to its low
                 computational complexity, low space requirement and
                 fast processing speed. We also propose an early
                 detection model of DDoS attack targets based on Hot-IP
                 finding, which can be deployed on the target network
                 routers.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Cyber Warfare.",
}

@Article{Zhu:2016:NMF,
  author =       "Zhiqin Zhu and Guanqiu Qi and Yi Chai and Yinong
                 Chen",
  title =        "A Novel Multi-Focus Image Fusion Method Based on
                 Stochastic Coordinate Coding and Local Density Peaks
                 Clustering",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "4",
  pages =        "53",
  day =          "11",
  month =        nov,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8040053",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:56 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/4/53",
  abstract =     "The multi-focus image fusion method is used in image
                 processing to generate all-focus images that have large
                 depth of field (DOF) based on original multi-focus
                 images. Different approaches have been used in the
                 spatial and transform domain to fuse multi-focus
                 images. As one of the most popular image processing
                 methods, dictionary-learning-based spare representation
                 achieves great performance in multi-focus image fusion.
                 Most of the existing dictionary-learning-based
                 multi-focus image fusion methods directly use the whole
                 source images for dictionary learning. However, it
                 incurs a high error rate and high computation cost in
                 dictionary learning process by using the whole source
                 images. This paper proposes a novel stochastic
                 coordinate coding-based image fusion framework
                 integrated with local density peaks. The proposed
                 multi-focus image fusion method consists of three
                 steps. First, source images are split into small image
                 patches, then the split image patches are classified
                 into a few groups by local density peaks clustering.
                 Next, the grouped image patches are used for
                 sub-dictionary learning by stochastic coordinate
                 coding. The trained sub-dictionaries are combined into
                 a dictionary for sparse representation. Finally, the
                 simultaneous orthogonal matching pursuit (SOMP)
                 algorithm is used to carry out sparse representation.
                 After the three steps, the obtained sparse coefficients
                 are fused following the max L1-norm rule. The fused
                 coefficients are inversely transformed to an image by
                 using the learned dictionary. The results and analyses
                 of comparison experiments demonstrate that fused images
                 of the proposed method have higher qualities than
                 existing state-of-the-art methods.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future Intelligent Systems and
                 Networks.",
}

@Article{He:2016:NFM,
  author =       "Jingsha He and Chengyue Chang and Peng He and Muhammad
                 Salman Pathan",
  title =        "Network Forensics Method Based on Evidence Graph and
                 Vulnerability Reasoning",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "4",
  pages =        "54",
  day =          "10",
  month =        nov,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8040054",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:56 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/4/54",
  abstract =     "As the Internet becomes larger in scale, more complex
                 in structure and more diversified in traffic, the
                 number of crimes that utilize computer technologies is
                 also increasing at a phenomenal rate. To react to the
                 increasing number of computer crimes, the field of
                 computer and network forensics has emerged. The general
                 purpose of network forensics is to find malicious users
                 or activities by gathering and dissecting firm
                 evidences about computer crimes, e.g., hacking.
                 However, due to the large volume of Internet traffic,
                 not all the traffic captured and analyzed is valuable
                 for investigation or confirmation. After analyzing some
                 existing network forensics methods to identify common
                 shortcomings, we propose in this paper a new network
                 forensics method that uses a combination of network
                 vulnerability and network evidence graph. In our
                 proposed method, we use vulnerability evidence and
                 reasoning algorithm to reconstruct attack scenarios and
                 then backtrack the network packets to find the original
                 evidences. Our proposed method can reconstruct attack
                 scenarios effectively and then identify multi-staged
                 attacks through evidential reasoning. Results of
                 experiments show that the evidence graph constructed
                 using our method is more complete and credible while
                 possessing the reasoning capability.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Cyber Warfare.",
}

@Article{Chinnachodteeranun:2016:DIW,
  author =       "Rassarin Chinnachodteeranun and Nguyen Duy Hung and
                 Kiyoshi Honda and Amor V. M. Ines and Eunjin Han",
  title =        "Designing and Implementing Weather Generators as {Web}
                 Services",
  journal =      j-FUTURE-INTERNET,
  volume =       "8",
  number =       "4",
  pages =        "55",
  day =          "15",
  month =        dec,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi8040055",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:56 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/8/4/55",
  abstract =     "Climate and weather realizations are essential inputs
                 for simulating crop growth and yields to analyze the
                 risks associated with future conditions. To simplify
                 the procedure of generating weather realizations and
                 make them available over the Internet, we implemented
                 novel mechanisms for providing weather generators as
                 web services, as well as a mechanism for sharing
                 identical weather realizations given a climatological
                 information. A web service for preparing long-term
                 climate data was implemented based on an international
                 standard, Sensor Observation Service (SOS). The weather
                 generator services, which are the core components of
                 the framework, analyze climatological data, and can
                 take seasonal climate forecasts as inputs for
                 generating weather realizations. The generated weather
                 realizations are encoded in a standard format, which
                 are ready for use to crop modeling. All outputs are
                 generated in SOS standard, which broadens the extent of
                 data sharing and interoperability with other sectoral
                 applications, e.g., water resources management. These
                 services facilitate the development of other
                 applications requiring input weather realizations, as
                 these can be obtained easily by just calling the
                 service. The workload of analysts related to data
                 preparation and handling of legacy weather generator
                 programs can be reduced. The architectural design and
                 implementation presented here can be used as a
                 prototype for constructing further services on top of
                 an interoperable sensor network system.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Communications and Computing for
                 Sustainable Development Goals.",
}

@Article{Lopez:2017:KTC,
  author =       "Lorena Isabel Barona L{\'o}pez and {\'A}ngel Leonardo
                 Valdivieso Caraguay and Marco Antonio Sotelo Monge and
                 Luis Javier Garc{\'\i}a Villalba",
  title =        "Key Technologies in the Context of Future Networks:
                 Operational and Management Requirements",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "1",
  pages =        "1",
  day =          "22",
  month =        dec,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9010001",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:56 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/1/1",
  abstract =     "The concept of Future Networks is based on the premise
                 that current infrastructures require enhanced control,
                 service customization, self-organization and
                 self-management capabilities to meet the new needs in a
                 connected society, especially of mobile users. In order
                 to provide a high-performance mobile system, three main
                 fields must be improved: radio, network, and operation
                 and management. In particular, operation and management
                 capabilities are intended to enable business agility
                 and operational sustainability, where the addition of
                 new services does not imply an excessive increase in
                 capital or operational expenditures. In this context, a
                 set of key-enabled technologies have emerged in order
                 to aid in this field. Concepts such as Software Defined
                 Network (SDN), Network Function Virtualization (NFV)
                 and Self-Organized Networks (SON) are pushing
                 traditional systems towards the next 5G network
                 generation.This paper presents an overview of the
                 current status of these promising technologies and
                 ongoing works to fulfill the operational and management
                 requirements of mobile infrastructures. This work also
                 details the use cases and the challenges, taking into
                 account not only SDN, NFV, cloud computing and SON but
                 also other paradigms.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Collection Information Systems Security.",
}

@Article{Office:2017:ARF,
  author =       "Future Internet Editorial Office",
  title =        "Acknowledgement to Reviewers of {{\booktitle{Future
                 Internet}}} in 2016",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "1",
  pages =        "2",
  day =          "12",
  month =        jan,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9010002",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:56 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/1/2",
  abstract =     "The fifth generation mobile network, or 5G, moves
                 towards bringing solutions to deploying faster
                 networks, with hundreds of thousands of simultaneous
                 connections and massive data transfer. For this
                 purpose, several emerging technologies are implemented,
                 resulting in virtualization and self-organization of
                 most of their components, which raises important
                 challenges related to safety. In order to contribute to
                 their resolution, this paper proposes a novel
                 architecture for incident management on 5G. The
                 approach combines the conventional risk management
                 schemes with the Endsley Situational Awareness model,
                 thus improving effectiveness in different aspects,
                 among them the ability to adapt to complex and
                 dynamical monitoring environments, and countermeasure
                 tracking or the role of context when decision-making.
                 The proposal takes into account all layers for
                 information processing in 5G mobile networks, ranging
                 from infrastructure to the actuators responsible for
                 deploying corrective measures.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lopez:2017:TIM,
  author =       "Lorena Isabel Barona L{\'o}pez and {\'A}ngel Leonardo
                 Valdivieso Caraguay and Jorge Maestre Vidal and Marco
                 Antonio Sotelo Monge and Luis Javier Garc{\'\i}a
                 Villalba",
  title =        "Towards Incidence Management in {5G} Based on
                 Situational Awareness",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "1",
  pages =        "3",
  day =          "17",
  month =        jan,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9010003",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:56 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/1/3",
  abstract =     "The fifth generation mobile network, or 5G, moves
                 towards bringing solutions to deploying faster
                 networks, with hundreds of thousands of simultaneous
                 connections and massive data transfer. For this
                 purpose, several emerging technologies are implemented,
                 resulting in virtualization and self-organization of
                 most of their components, which raises important
                 challenges related to safety. In order to contribute to
                 their resolution, this paper proposes a novel
                 architecture for incident management on 5G. The
                 approach combines the conventional risk management
                 schemes with the Endsley Situational Awareness model,
                 thus improving effectiveness in different aspects,
                 among them the ability to adapt to complex and
                 dynamical monitoring environments, and countermeasure
                 tracking or the role of context when decision-making.
                 The proposal takes into account all layers for
                 information processing in 5G mobile networks, ranging
                 from infrastructure to the actuators responsible for
                 deploying corrective measures.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Collection Information Systems Security.",
}

@Article{Martelli:2017:PVN,
  author =       "Cristina Martelli",
  title =        "A Point of View on New Education for Smart
                 Citizenship",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "1",
  pages =        "4",
  day =          "01",
  month =        feb,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9010004",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:56 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/1/4",
  abstract =     "Smart cities and intelligent communities have an
                 ever-growing demand for specialized smart services,
                 applications, and research-driven innovation. Knowledge
                 of users' profiles, behavior, and preferences are a
                 potentially dangerous side effect of smart services.
                 Citizens are usually not aware of the knowledge bases
                 generated by the IT services they use: this dimension
                 of the contemporary and digital era sheds new light on
                 the elements concerning the concept of citizenship
                 itself, as it affects dimensions like freedom and
                 privacy. This paper addresses this issue from an
                 education system perspective, and advances a
                 non-technical methodology for being aware and
                 recognizing knowledge bases generated by user-service
                 interaction. Starting from narratives, developed in
                 natural language by unskilled smart service users about
                 their experience, the proposed method advances an
                 original methodology, which is identified in the
                 conceptual models derived from these narratives, a
                 bridge towards a deeper understanding of the
                 informative implications of their behavior. The
                 proposal; which is iterative and scalable; has been
                 tested on the field and some examples of lesson
                 contents are presented and discussed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Ecosystemic Evolution Feeded by Smart
                 Systems.",
}

@Article{Park:2017:CMR,
  author =       "Kyungmo Park and Sanghyo Lee and Yonghan Ahn",
  title =        "{Construction Management Risk System (CMRS)} for
                 Construction Management ({CM}) Firms",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "1",
  pages =        "5",
  day =          "10",
  month =        feb,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9010005",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:56 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/1/5",
  abstract =     "After the global financial crisis of 2008, the need
                 for risk management arose because it was necessary to
                 minimize the losses in construction management (CM)
                 firms. This was caused by a decreased amount of orders
                 in the Korean CM market, which intensified order
                 competition between companies. However, research
                 results revealed that risks were not being
                 systematically managed owing to the absence of risk
                 management systems. Thus, it was concluded that it was
                 necessary to develop standard operating systems and
                 implement risk management systems in order to manage
                 risks effectively. Therefore, the purpose of this study
                 was to develop a construction risk management system
                 (CRMS) for systematically managing risks. For this
                 purpose, the field operation managers of CM firms were
                 interviewed and surveyed in order to define risk
                 factors. Upon this, a risk assessment priority analysis
                 was performed. Finally, a risk management system that
                 comprised seven modules and 20 sub-modules and was
                 capable of responding systematically to risks was
                 proposed. Furthermore, the effectiveness of this system
                 was verified through on-site inspection. This system
                 allows early response to risks, accountability
                 verification and immediate response to legal disputes
                 with clients by managing risk records.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Vidros:2017:ADO,
  author =       "Sokratis Vidros and Constantinos Kolias and Georgios
                 Kambourakis and Leman Akoglu",
  title =        "Automatic Detection of Online Recruitment Frauds:
                 Characteristics, Methods, and a Public Dataset",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "1",
  pages =        "6",
  day =          "03",
  month =        mar,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9010006",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:56 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/1/6",
  abstract =     "The critical process of hiring has relatively recently
                 been ported to the cloud. Specifically, the automated
                 systems responsible for completing the recruitment of
                 new employees in an online fashion, aim to make the
                 hiring process more immediate, accurate and
                 cost-efficient. However, the online exposure of such
                 traditional business procedures has introduced new
                 points of failure that may lead to privacy loss for
                 applicants and harm the reputation of organizations. So
                 far, the most common case of Online Recruitment Frauds
                 (ORF), is employment scam. Unlike relevant online fraud
                 problems, the tackling of ORF has not yet received the
                 proper attention, remaining largely unexplored until
                 now. Responding to this need, the work at hand defines
                 and describes the characteristics of this severe and
                 timely novel cyber security research topic. At the same
                 time, it contributes and evaluates the first to our
                 knowledge publicly available dataset of 17,880
                 annotated job ads, retrieved from the use of a
                 real-life system.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{He:2017:APP,
  author =       "Jingsha He and Qi Xiao and Peng He and Muhammad Salman
                 Pathan",
  title =        "An Adaptive Privacy Protection Method for Smart Home
                 Environments Using Supervised Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "1",
  pages =        "7",
  day =          "05",
  month =        mar,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9010007",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:56 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/1/7",
  abstract =     "In recent years, smart home technologies have started
                 to be widely used, bringing a great deal of convenience
                 to people's daily lives. At the same time, privacy
                 issues have become particularly prominent. Traditional
                 encryption methods can no longer meet the needs of
                 privacy protection in smart home applications, since
                 attacks can be launched even without the need for
                 access to the cipher. Rather, attacks can be
                 successfully realized through analyzing the frequency
                 of radio signals, as well as the timestamp series, so
                 that the daily activities of the residents in the smart
                 home can be learnt. Such types of attacks can achieve a
                 very high success rate, making them a great threat to
                 users' privacy. In this paper, we propose an adaptive
                 method based on sample data analysis and supervised
                 learning (SDASL), to hide the patterns of daily
                 routines of residents that would adapt to dynamically
                 changing network loads. Compared to some existing
                 solutions, our proposed method exhibits advantages such
                 as low energy consumption, low latency, strong
                 adaptability, and effective privacy protection.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Privacy in Wireless and
                 Mobile Networks.",
}

@Article{Rametta:2017:DSN,
  author =       "Corrado Rametta and Giovanni Schembra",
  title =        "Designing a Softwarized Network Deployed on a Fleet of
                 Drones for Rural Zone Monitoring",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "1",
  pages =        "8",
  day =          "20",
  month =        mar,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9010008",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:56 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/1/8",
  abstract =     "In the last decade, the differences in the information
                 communication technology (ICT) infrastructures between
                 urban and rural areas have registered a tremendous
                 increase. ICT infrastructures could strongly help rural
                 communities where many operations are time consuming,
                 labor-intensive and expensive due to limited access and
                 large distances to cover. One of the most attractive
                 solutions, which is widely recognized as promising for
                 filling this gap, is the use of drone fleets. In this
                 context, this paper proposes a video monitoring
                 platform as a service (VMPaaS) for wide rural areas not
                 covered by Internet access. The platform is realized
                 with a Software-Defined Network (SDN)/Network Functions
                 Virtualization (NFV)-based flying ad-hoc network
                 (FANET), whose target is providing a flexible and
                 dynamic connectivity backbone, and a set of drones
                 equipped with high-resolution cameras, each
                 transmitting a video stream of a portion of the
                 considered area. After describing the architecture of
                 the proposed platform, service chains to realize the
                 video delivery service are described, and an analytical
                 model is defined to evaluate the computational load of
                 the platform nodes in such a way so as to allow the
                 network orchestrator to decide the backbone drones
                 where running the virtual functions, and the relative
                 resources to be allocated. Numerical analysis is
                 carried out in a case study.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Communications and Computing for
                 Sustainable Development Goals.",
}

@Article{Tian:2017:IRB,
  author =       "Hao Tian and Peifeng Liang",
  title =        "Improved Recommendations Based on Trust Relationships
                 in Social Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "1",
  pages =        "9",
  day =          "21",
  month =        mar,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9010009",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:56 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/1/9",
  abstract =     "In order to alleviate the pressure of information
                 overload and enhance consumer satisfaction,
                 personalization recommendation has become increasingly
                 popular in recent years. As a result, various
                 approaches for recommendation have been proposed in the
                 past few years. However, traditional recommendation
                 methods are still troubled with typical issues such as
                 cold start, sparsity, and low accuracy. To address
                 these problems, this paper proposed an improved
                 recommendation method based on trust relationships in
                 social networks to improve the performance of
                 recommendations. In particular, we define trust
                 relationship afresh and consider several representative
                 factors in the formalization of trust relationships. To
                 verify the proposed approach comprehensively, this
                 paper conducted experiments in three ways. The
                 experimental results show that our proposed approach
                 leads to a substantial increase in prediction accuracy
                 and is very helpful in dealing with cold start and
                 sparsity.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chen:2017:DBS,
  author =       "Yongqun Chen and Huaibei Zhou and Ruoshan Kong and Li
                 Zhu and Huaqing Mao",
  title =        "Decentralized Blind Spectrum Selection in Cognitive
                 Radio Networks Considering Handoff Cost",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "2",
  pages =        "10",
  day =          "31",
  month =        mar,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9020010",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/2/10",
  abstract =     "Due to the spectrum varying nature of cognitive radio
                 networks, secondary users are required to perform
                 spectrum handoffs when the spectrum is occupied by
                 primary users, which will lead to a handoff delay. In
                 this paper, based on the multi-armed bandit framework
                 of medium access in decentralized cognitive radio
                 networks, we investigate blind spectrum selection
                 problem of secondary users whose sensing ability of
                 cognitive radio is limited and the channel statistics
                 are a priori unknown, taking the handoff delay as a
                 fixed handoff cost into consideration. In this
                 scenario, secondary users have to make the choice of
                 either staying foregoing spectrum with low availability
                 or handing off to another spectrum with higher
                 availability. We model the problem and investigate the
                 performance of three representative policies, i.e.,
                 \rho PRE, SL(K), k th-UCB1. The simulation results show
                 that, despite the inclusion of the fixed handoff cost,
                 these policies achieve the same asymptotic performance
                 as that without handoff cost. Moreover, through
                 comparison of these policies, we found the k th-UCB1
                 policy has better overall performance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Context-Awareness of Mobile Systems.",
}

@Article{Guazzini:2017:PPP,
  author =       "Andrea Guazzini and Ay{\c{c}}a Sara{\c{c}} and Camillo
                 Donati and Annalisa Nardi and Daniele Vilone and
                 Patrizia Meringolo",
  title =        "Participation and Privacy Perception in Virtual
                 Environments: The Role of Sense of Community, Culture
                 and Gender between {Italian} and {Turkish}",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "2",
  pages =        "11",
  day =          "07",
  month =        apr,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9020011",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/2/11",
  abstract =     "Advancements in information and communication
                 technologies have enhanced our possibilities to
                 communicate worldwide, eliminating borders and making
                 it possible to interact with people coming from other
                 cultures like never happened before. Such powerful
                 tools have brought us to reconsider our concept of
                 privacy and social involvement in order to make them
                 fit into this wider environment. It is possible to
                 claim that the information and communication
                 technologies (ICT) revolution is changing our world and
                 is having a core role as a mediating factor for social
                 movements (e.g., Arab spring) and political decisions
                 (e.g., Brexit), shaping the world in a faster and
                 shared brand new way. It is then interesting to explore
                 how the perception of this brand new environment (in
                 terms of social engagement, privacy perception and
                 sense of belonging to a community) differs even in
                 similar cultures separated by recent historical
                 reasons. Recent historical events may in effect have
                 shaped a different psychological representation of
                 Participation, Privacy and Sense of Community in ICT
                 environments, determining a different perception of
                 affordances and concerns of these complex behaviors.
                 The aim of this research is to examine the relation
                 between the constructs of Sense of Community,
                 Participation and Privacy compared with culture and
                 gender, considering the changes that have occurred in
                 the last few years with the introduction of the web
                 environment. A questionnaire, including ad hoc created
                 scales for Participation and Privacy, have been
                 administered to 180 participants from Turkey and Italy.
                 In order to highlight the cultural differences in the
                 perception of these two constructs, we have provided a
                 semantic differential to both sub-samples showing
                 interesting outcomes. The results are then discussed
                 while taking into account the recent history of both
                 countries in terms of the widespread of new
                 technologies, political actions and protest
                 movements.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Privacy in Wireless and
                 Mobile Networks.",
}

@Article{Wang:2017:SEE,
  author =       "Xinhua Wang",
  title =        "Spectrum and Energy Efficiency of Uplink Massive
                 {MIMO} System with {D2D} Underlay",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "2",
  pages =        "12",
  day =          "13",
  month =        apr,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9020012",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/2/12",
  abstract =     "In this paper, both the spectrum efficiency (SE) and
                 the energy efficiency (EE) are investigated for an
                 uplink massive multiple-input multiple-output (MIMO)
                 system coexisting with an underlay device-to-device
                 (D2D) system. The outage probability and the achievable
                 rates of the cellular user equipments (CUEs) and the
                 D2D link are derived in closed-form, respectively.
                 Constrained by the SE of the D2D link and the CUEs, the
                 EE of the massive MIMO system is maximized by jointly
                 optimizing the transmit power of CUEs and the number of
                 BS antennas. An algorithm with low complexity is
                 proposed to solve the optimization problem. Performance
                 results are provided to validate our derived
                 closed-from results and verify the efficiency of our
                 proposed scheme.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Communications and Computing for
                 Sustainable Development Goals.",
}

@Article{Zhang:2017:FBI,
  author =       "Yunpeng Zhang and Chengyou Wang and Xiaoli Wang and
                 Min Wang",
  title =        "Feature-Based Image Watermarking Algorithm Using {SVD}
                 and {APBT} for Copyright Protection",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "2",
  pages =        "13",
  day =          "19",
  month =        apr,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9020013",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/2/13",
  abstract =     "Watermarking techniques can be applied in digital
                 images to maintain the authenticity and integrity for
                 copyright protection. In this paper, scale-invariant
                 feature transform (SIFT) is combined with local digital
                 watermarking and a digital watermarking algorithm based
                 on SIFT, singular value decomposition (SVD), and all
                 phase biorthogonal transform (APBT) is proposed. It
                 describes the generation process of the SIFT algorithm
                 in detail and obtains a series of scale-invariant
                 feature points. A large amount of candidate feature
                 points are selected to obtain the neighborhood which
                 can be used to embed the watermark. For these selected
                 feature points, block-based APBT is carried out on
                 their neighborhoods. Moreover, a coefficients matrix of
                 certain APBT coefficients is generated for SVD to embed
                 the encrypted watermark. Experimental results
                 demonstrate that the proposed watermarking algorithm
                 has stronger robustness than some previous schemes. In
                 addition, APBT-based digital watermarking algorithm has
                 good imperceptibility and is more robust to different
                 combinations of attacks, which can be applied for the
                 purpose of copyright protection.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Collection Information Systems Security.",
}

@Article{Yu:2017:EEM,
  author =       "Qingyao Yu and Guangming Li and Xiaojie Hang and Kun
                 Fu and Tianqi Li",
  title =        "An Energy Efficient {MAC} Protocol for Wireless
                 Passive Sensor Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "2",
  pages =        "14",
  day =          "19",
  month =        apr,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9020014",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/2/14",
  abstract =     "Medium Access Control (MAC) protocol is one of the key
                 network protocols that ensure Wireless Sensor Networks
                 (WSNs) maintain high performance during communication.
                 MAC protocol design plays an important role in
                 improving the performances of the whole network. First,
                 Wireless Passive Sensor Networks (WPSNs) and MAC
                 protocols are introduced in this paper. Second, some
                 existing MAC protocols are introduced. Sensor MAC
                 (S-MAC) protocol is analyzed and existing improved
                 backoff algorithms are introduced. A new MAC protocol
                 called Improved Sensor MAC (IS-MAC) is then proposed to
                 solve the problem that the contention window (CW)
                 during carrier sense is fixed in S-MAC protocol. IS-MAC
                 protocol is able to adjust CW in terms of network load,
                 so energy consumption can be decreased. Finally,
                 according to the simulation results on NS2, the
                 proposed protocol has better performance in terms of
                 throughput and energy consumption.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sehra:2017:AOD,
  author =       "Sukhjit Singh Sehra and Jaiteg Singh and Hardeep Singh
                 Rai",
  title =        "Assessing {OpenStreetMap} Data Using Intrinsic Quality
                 Indicators: An Extension to the {QGIS} Processing
                 Toolbox",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "2",
  pages =        "15",
  day =          "21",
  month =        apr,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9020015",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/2/15",
  abstract =     "OpenStreetMap (OSM) is a recent emerging area in
                 computational science. There are several unexplored
                 issues in the quality assessment of OSM. Firstly,
                 researchers are using various established assessment
                 methods by comparing OSM with authoritative dataset.
                 However, these methods are unsuitable to assess OSM
                 data quality in the case of the non-availability of
                 authoritative data. In such a scenario, the intrinsic
                 quality indicators can be used to assess the quality.
                 Secondly, a framework for data assessment specific to
                 different geographic information system (GIS) domains
                 is not available. In this light, the current study
                 presents an extension of the Quantum GIS (QGIS)
                 processing toolbox by using existing functionalities
                 and writing new scripts to handle spatial data. This
                 would enable researchers to assess the completeness of
                 spatial data using intrinsic indicators. The study also
                 proposed a heuristic approach to test the road
                 navigability of OSM data. The developed models are
                 applied on Punjab (India) OSM data. The results suggest
                 that the OSM project in Punjab (India) is progressing
                 at a slow peace, and contributors' motivation is
                 required to enhance the fitness of data. It is
                 concluded that the scripts developed to provide an
                 intuitive method to assess the OSM data based on
                 quality indicators can be easily utilized for
                 evaluating the fitness-of-use of the data of any
                 region.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mamais:2017:PSD,
  author =       "Stylianos S. Mamais and George Theodorakopoulos",
  title =        "Private and Secure Distribution of Targeted
                 Advertisements to Mobile Phones",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "2",
  pages =        "16",
  day =          "01",
  month =        may,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9020016",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/2/16",
  abstract =     "Online Behavioural Advertising (OBA) enables promotion
                 companies to effectively target users with ads that
                 best satisfy their purchasing needs. This is highly
                 beneficial for both vendors and publishers who are the
                 owners of the advertising platforms, such as websites
                 and app developers, but at the same time creates a
                 serious privacy threat for users who expose their
                 consumer interests. In this paper, we categorize the
                 available ad-distribution methods and identify their
                 limitations in terms of security, privacy, targeting
                 effectiveness and practicality. We contribute our own
                 system, which utilizes opportunistic networking in
                 order to distribute targeted adverts within a social
                 network. We improve upon previous work by eliminating
                 the need for trust among the users (network nodes)
                 while at the same time achieving low memory and
                 bandwidth overhead, which are inherent problems of many
                 opportunistic networks. Our protocol accomplishes this
                 by identifying similarities between the consumer
                 interests of users and then allows them to share access
                 to the same adverts, which need to be downloaded only
                 once. Although the same ads may be viewed by multiple
                 users, privacy is preserved as the users do not learn
                 each other's advertising interests. An additional
                 contribution is that malicious users cannot alter the
                 ads in order to spread malicious content, and also,
                 they cannot launch impersonation attacks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Privacy in Wireless and
                 Mobile Networks.",
}

@Article{Chen:2017:TRU,
  author =       "Haibao Chen and Yuyan Zhao and Chuxiong Yan",
  title =        "Towards Rack Utilization in {Internet} Datacenters: An
                 Approach Based on Dynamic Programming",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "2",
  pages =        "17",
  day =          "06",
  month =        may,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9020017",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/2/17",
  abstract =     "In the datacenter rented to Internet Service Providers
                 (ISPs), the low utilization of racks can seriously
                 affect ISPs' benefit because the ISPs are charged by
                 ``rack per year'' rather than servers. Based on our
                 analysis about the utilization data from production
                 systems, we find that the over-provisioning of power
                 results in low power utilization, which potentially
                 decreases rack utilization as well as the ISPs'
                 benefit. To improve the rack utilization, maximizing
                 the number of servers in racks is an effective way. In
                 this paper, we propose a server placement algorithm to
                 minimize the power fragment in a rack. The experimental
                 results show that it can save more than 50\% leasing
                 cost (rack utilization improvement) in evaluation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Grout:2017:SAD,
  author =       "Vic Grout",
  title =        "A Simple Approach to Dynamic Optimisation of Flexible
                 Optical Networks with Practical Application",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "2",
  pages =        "18",
  day =          "23",
  month =        may,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9020018",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/2/18",
  abstract =     "This paper provides an initial introduction to, and
                 definition of, the `Dynamically Powered Relays for a
                 Flexible Optical Network' (DPR-FON) problem for
                 opto-electro-optical (OEO) regenerators used in optical
                 networks. In such networks, optical transmission
                 parameters can be varied dynamically as traffic
                 patterns change. This will provide different
                 bandwidths, but also change the regeneration limits as
                 a result. To support this flexibility, OEOs (`relays')
                 may be switched on and off as required, thus saving
                 power. DPR-FON is shown to be NP-complete;
                 consequently, solving such a dynamic problem in
                 real-time requires a fast heuristic capable of
                 delivering an acceptable approximation to the optimal
                 configuration with low complexity. In this paper, just
                 such an algorithm is developed, implemented, and
                 evaluated against more computationally-demanding
                 alternatives for two known cases. A number of
                 real-world extensions are considered as the paper
                 develops, combining to produce the `Generalised
                 Dynamically Powered Relays for a Flexible Optical
                 Network' (GDPR-FON) problem. This, too, is analysed and
                 an associated fast heuristic proposed, along with an
                 exploration of the further research that is required.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sun:2017:ABM,
  author =       "Peng Sun and Guangming Li and Fuqiang Wang",
  title =        "An Adaptive Back-Off Mechanism for Wireless Sensor
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "2",
  pages =        "19",
  day =          "01",
  month =        jun,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9020019",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/2/19",
  abstract =     "Wireless sensor networks (WSNs) have been extensively
                 applied in many domains such as smart homes and
                 Internet of Things (IoT). As part of WSNs'
                 communication protocols, back-off mechanisms play an
                 essential role in the deployment of wireless channels
                 for network nodes and have been at the core of ensuring
                 effective communication. The performance of many
                 back-off algorithms is excellent in light or middle
                 load networks. However, it degrades dramatically in
                 heavy load networks. In this paper, we propose an
                 adaptive contention window medium access control (MAC)
                 protocol to improve the throughput performance under
                 heavy load. By using the number of historical
                 collisions as the parameter in the back-off mechanism
                 to reflect the channel status, the size of the
                 contention window is adjusted automatically, and the
                 throughput of network is then improved. Simulation
                 results show that our optimized MAC protocol has higher
                 throughput and energy efficiency.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wu:2017:ACM,
  author =       "Jiang Wu and Zhou Lei and Shengbo Chen and Wenfeng
                 Shen",
  title =        "An Access Control Model for Preventing Virtual Machine
                 Escape Attack",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "2",
  pages =        "20",
  day =          "02",
  month =        jun,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9020020",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/2/20",
  abstract =     "With the rapid development of Internet, the
                 traditional computing environment is making a big
                 migration to the cloud-computing environment. However,
                 cloud computing introduces a set of new security
                 problems. Aiming at the virtual machine (VM) escape
                 attack, we study the traditional attack model and
                 attack scenarios in the cloud-computing environment. In
                 addition, we propose an access control model that can
                 prevent virtual machine escape (PVME) by adapting the
                 BLP (Bell-La Padula) model (an access control model
                 developed by D. Bell and J. LaPadula). Finally, the
                 PVME model has been implemented on full virtualization
                 architecture. The experimental results show that the
                 PVME module can effectively prevent virtual machine
                 escape while only incurring 4\% to 8\% time overhead.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2017:EEP,
  author =       "Xinhua Wang and Yan Yang and Jinlu Sheng",
  title =        "Energy Efficient Power Allocation for the Uplink of
                 Distributed Massive {MIMO} Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "2",
  pages =        "21",
  day =          "09",
  month =        jun,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9020021",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/2/21",
  abstract =     "In this paper, an energy efficient power allocation
                 scheme is proposed for a distributed massive
                 multiple-input multiple-output (MIMO) system with a
                 circular antenna array. Single-antenna users
                 simultaneously transmit signal to the base station (BS)
                 with a large number of distributed antennas. The tight
                 approximation of the energy efficiency (EE) is derived
                 in closed form expressions. Through jointly optimizing
                 the power allocation and the antenna number of BS, an
                 NP-hard problem is formulated to maximize the EE. The
                 equal power allocation is proved to be optimal given
                 the total transmit power and the number of antennas.
                 Finally, the optimal antenna number is determined by
                 one dimension search. It is noteworthy that the NP-hard
                 problem is solved by one dimension search. Simulation
                 results validate the accuracy and the low-complexity of
                 our proposed scheme.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Communications and Computing for
                 Sustainable Development Goals.",
}

@Article{Wang:2017:MIM,
  author =       "Weijun Wang and Ying Li and Yinghui Huang and Hui Liu
                 and Tingting Zhang",
  title =        "A Method for Identifying the Mood States of Social
                 Network Users Based on Cyber Psychometrics",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "2",
  pages =        "22",
  day =          "16",
  month =        jun,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9020022",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/2/22",
  abstract =     "Analyzing people's opinions, attitudes, sentiments,
                 and emotions based on user-generated content (UGC) is
                 feasible for identifying the psychological
                 characteristics of social network users. However, most
                 studies focus on identifying the sentiments carried in
                 the micro-blogging text and there is no ideal
                 calculation method for users' real emotional states. In
                 this study, the Profile of Mood State (POMS) is used to
                 characterize users' real mood states and a regression
                 model is built based on cyber psychometrics and a
                 multitask method. Features of users' online behavior
                 are selected through structured statistics and
                 unstructured text. Results of the correlation analysis
                 of different features demonstrate that users' real mood
                 states are not only characterized by the messages
                 expressed through texts, but also correlate with
                 statistical features of online behavior. The
                 sentiment-related features in different timespans
                 indicate different correlations with the real mood
                 state. The comparison among various regression
                 algorithms suggests that the multitask learning method
                 outperforms other algorithms in root-mean-square error
                 and error ratio. Therefore, this cyber psychometrics
                 method based on multitask learning that integrates
                 structural features and temporal emotional information
                 could effectively obtain users' real mood states and
                 could be applied in further psychological measurements
                 and predictions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liu:2017:NIT,
  author =       "Lingjun Liu and Zhonghua Xie and Cui Yang",
  title =        "A Novel Iterative Thresholding Algorithm Based on
                 Plug-and-Play Priors for Compressive Sampling",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "24",
  day =          "24",
  month =        jun,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030024",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/24",
  abstract =     "We propose a novel fast iterative thresholding
                 algorithm for image compressive sampling (CS) recovery
                 using three existing denoisers-i.e., TV (total
                 variation), wavelet, and BM3D (block-matching and 3D
                 filtering) denoisers. Through the use of the recently
                 introduced plug-and-play prior approach, we turn these
                 denoisers into CS solvers. Thus, our method can jointly
                 utilize the global and nonlocal sparsity of images. The
                 former is captured by TV and wavelet denoisers for
                 maintaining the entire consistency; while the latter is
                 characterized by the BM3D denoiser to preserve details
                 by exploiting image self-similarity. This composite
                 constraint problem is then solved with the fast
                 composite splitting technique. Experimental results
                 show that our algorithm outperforms several excellent
                 CS techniques.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Cocco:2017:BBC,
  author =       "Luisanna Cocco and Andrea Pinna and Michele Marchesi",
  title =        "Banking on Blockchain: Costs Savings Thanks to the
                 Blockchain Technology",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "25",
  day =          "27",
  month =        jun,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030025",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/25",
  abstract =     "This paper looks at the challenges and opportunities
                 of implementing blockchain technology across banking,
                 providing food for thought about the potentialities of
                 this disruptive technology. The blockchain technology
                 can optimize the global financial infrastructure,
                 achieving sustainable development, using more efficient
                 systems than at present. In fact, many banks are
                 currently focusing on blockchain technology to promote
                 economic growth and accelerate the development of green
                 technologies. In order to understand the potential of
                 blockchain technology to support the financial system,
                 we studied the actual performance of the Bitcoin
                 system, also highlighting its major limitations, such
                 as the significant energy consumption due to the high
                 computing power required, and the high cost of
                 hardware. We estimated the electrical power and the
                 hash rate of the Bitcoin network, over time, and, in
                 order to evaluate the efficiency of the Bitcoin system
                 in its actual operation, we defined three quantities:
                 ``economic efficiency'', ``operational efficiency'',
                 and ``efficient service''. The obtained results show
                 that by overcoming the disadvantages of the Bitcoin
                 system, and therefore of blockchain technology, we
                 could be able to handle financial processes in a more
                 efficient way than under the current system.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Menesidou:2017:CKM,
  author =       "Sofia Anna Menesidou and Vasilios Katos and Georgios
                 Kambourakis",
  title =        "Cryptographic Key Management in Delay Tolerant
                 Networks: a Survey",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "26",
  day =          "27",
  month =        jun,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030026",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/26",
  abstract =     "Since their appearance at the dawn of the second
                 millennium, Delay or Disruption Tolerant Networks
                 (DTNs) have gradually evolved, spurring the development
                 of a variety of methods and protocols for making them
                 more secure and resilient. In this context, perhaps,
                 the most challenging problem to deal with is that of
                 cryptographic key management. To the best of our
                 knowledge, the work at hand is the first to survey the
                 relevant literature and classify the various so far
                 proposed key management approaches in such a restricted
                 and harsh environment. Towards this goal, we have
                 grouped the surveyed key management methods into three
                 major categories depending on whether the particular
                 method copes with (a) security initialization, (b) key
                 establishment, and (c) key revocation. We have
                 attempted to provide a concise but fairly complete
                 evaluation of the proposed up-to-date methods in a
                 generalized way with the aim of offering a central
                 reference point for future research.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liu:2017:SFI,
  author =       "Xiruo Liu and Meiyuan Zhao and Sugang Li and Feixiong
                 Zhang and Wade Trappe",
  title =        "A Security Framework for the {Internet of Things} in
                 the Future {Internet} Architecture",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "27",
  day =          "28",
  month =        jun,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030027",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/27",
  abstract =     "The Internet of Things (IoT) is a recent trend that
                 extends the boundary of the Internet to include a wide
                 variety of computing devices. Connecting many
                 stand-alone IoT systems through the Internet introduces
                 many challenges, with security being front-and-center
                 since much of the collected information will be exposed
                 to a wide and often unknown audience. Unfortunately,
                 due to the intrinsic capability limits of low-end IoT
                 devices, which account for a majority of the IoT end
                 hosts, many traditional security methods cannot be
                 applied to secure IoT systems, which open a door for
                 attacks and exploits directed both against IoT services
                 and the broader Internet. This paper addresses this
                 issue by introducing a unified IoT framework based on
                 the MobilityFirst future Internet architecture that
                 explicitly focuses on supporting security for the IoT.
                 Our design integrates local IoT systems into the global
                 Internet without losing usability, interoperability and
                 security protection. Specifically, we introduced an IoT
                 middleware layer that connects heterogeneous hardware
                 in local IoT systems to the global MobilityFirst
                 network. We propose an IoT name resolution service
                 (IoT-NRS) as a core component of the middleware layer,
                 and develop a lightweight keying protocol that
                 establishes trust between an IoT device and the
                 IoT-NRS.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue IoT Security and Privacy.",
}

@Article{Rauniyar:2017:DDR,
  author =       "Ashish Rauniyar and Mohammad Irfan and Oka Danil
                 Saputra and Jin Woo Kim and Ah Ra Lee and Jae Min Jang
                 and Soo Young Shin",
  title =        "Design and Development of a Real-Time Monitoring
                 System for Multiple Lead-Acid Batteries Based on
                 {Internet of Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "28",
  day =          "29",
  month =        jun,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030028",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/csharp.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/28",
  abstract =     "In this paper, real-time monitoring of multiple
                 lead-acid batteries based on Internet of things is
                 proposed and evaluated. Our proposed system monitors
                 and stores parameters that provide an indication of the
                 lead acid battery's acid level, state of charge,
                 voltage, current, and the remaining charge capacity in
                 a real-time scenario. To monitor these lead-acid
                 battery parameters, we have developed a data
                 acquisition system by building an embedded system,
                 i.e., dedicated hardware and software. The wireless
                 local area network is used as the backbone network. The
                 information collected from all the connected battery
                 clients in the system is analyzed in an asynchronous
                 transmission control protocol/user datagram
                 protocol-based C\# server program running on a personal
                 computer (server) to determine important parameters
                 like the state of charge of the individual battery, and
                 if required, appropriate action can be taken in advance
                 to prevent excessive impairment to the battery.
                 Further, data are also displayed on an Android mobile
                 device and are stored in an SQL server database. We
                 have developed a real prototype to devise an end
                 product for our proposed system.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Big Data and Internet of Thing.",
}

@Article{Ebeid:2017:DEC,
  author =       "Emad Ebeid and Rune Heick and Rune Hylsberg Jacobsen",
  title =        "Deducing Energy Consumer Behavior from Smart Meter
                 Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "29",
  day =          "06",
  month =        jul,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030029",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/29",
  abstract =     "The ongoing upgrade of electricity meters to smart
                 ones has opened a new market of intelligent services to
                 analyze the recorded meter data. This paper introduces
                 an open architecture and a unified framework for
                 deducing user behavior from its smart main electricity
                 meter data and presenting the results in a natural
                 language. The framework allows a fast exploration and
                 integration of a variety of machine learning algorithms
                 combined with data recovery mechanisms for improving
                 the recognition's accuracy. Consequently, the framework
                 generates natural language reports of the user's
                 behavior from the recognized home appliances. The
                 framework uses open standard interfaces for exchanging
                 data. The framework has been validated through
                 comprehensive experiments that are related to an
                 European Smart Grid project.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Piezzo:2017:FSS,
  author =       "Chiara Piezzo and Kenji Suzuki",
  title =        "Feasibility Study of a Socially Assistive Humanoid
                 Robot for Guiding Elderly Individuals during Walking",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "30",
  day =          "08",
  month =        jul,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030030",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/30",
  abstract =     "The impact of the world-wide ageing population has
                 commenced with respect to society in developed
                 countries. Several researchers focused on exploring new
                 methods to improve the quality of life of elderly
                 individuals by allowing them to remain independent and
                 healthy to the maximum possible extent. For example,
                 new walking aids are designed to allow elderly
                 individuals to remain mobile in a safe manner because
                 the importance of walking is well-known. The aim of the
                 present study involves designing a humanoid robot guide
                 as a walking trainer for elderly individuals. It is
                 hypothesized that the same service robot provides an
                 assistive and social contribution with respect to
                 interaction between elderly users by motivating them to
                 walk more and simultaneously provides assistance, such
                 as physical assistance and gait monitoring, while
                 walking. This study includes a detailed statement of
                 the research problem as well as a literature review of
                 existing studies related to walking companion robots. A
                 user-centred design approach is adopted to report the
                 results of the current first feasibility study by using
                 a commercially available humanoid robot known as Pepper
                 developed by Softbank-Aldebaran. A quantitative
                 questionnaire was used to investigate all elements that
                 assess intrinsic motivation in users while performing a
                 given activity. Conversely, basic gait data were
                 acquired through a video analysis to test the
                 capability of the robot to modify the gait of human
                 users. The results in terms of the feedback received
                 from elderly subjects and the literature review improve
                 the design of the walking trainer for elderly
                 individuals.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Militano:2017:NID,
  author =       "Leonardo Militano and Antonino Orsino and Giuseppe
                 Araniti and Antonio Iera",
  title =        "{NB-IoT} for {D2D}-Enhanced Content Uploading with
                 Social Trustworthiness in {5G} Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "31",
  day =          "08",
  month =        jul,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030031",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/31",
  abstract =     "Future fifth-generation (5G) cellular systems are set
                 to give a strong boost to the large-scale deployment of
                 Internet of things (IoT). In the view of a future
                 converged 5G-IoT infrastructure, cellular IoT solutions
                 such as narrowband IoT (NB-IoT) and device-to-device
                 (D2D) communications are key technologies for
                 supporting IoT scenarios and applications. However,
                 some open issues still need careful investigation. An
                 example is the risk of threats to privacy and security
                 when IoT mobile services rely on D2D communications. To
                 guarantee efficient and secure connections to IoT
                 services involving exchange of sensitive data,
                 reputation-based mechanisms to identify and avoid
                 malicious devices are fast gaining ground. In order to
                 tackle the presence of malicious nodes in the network,
                 this paper introduces reliability and reputation
                 notions to model the level of trust among devices
                 engaged in an opportunistic hop-by-hop D2D-based
                 content uploading scheme. To this end, social awareness
                 of devices is considered as a means to enhance the
                 identification of trustworthy nodes. A performance
                 evaluation study shows that the negative effects due to
                 malicious nodes can be drastically reduced by adopting
                 the proposed solution. The performance metrics that
                 proved to benefit from the proposed solution are data
                 loss, energy consumption, and content uploading time.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Recent Advances in Cellular D2D
                 Communications.",
}

@Article{Gkioulos:2017:UMV,
  author =       "Vasileios Gkioulos and Gaute Wangen and Sokratis K.
                 Katsikas",
  title =        "User Modelling Validation over the Security Awareness
                 of Digital Natives",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "32",
  day =          "10",
  month =        jul,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030032",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/32",
  abstract =     "Young generations make extensive use of mobile
                 devices, such as smart-phones, tablets and laptops, for
                 a variety of daily tasks with potentially critical
                 impact, while the number of security breaches via
                 portable devices increases exponentially. A plethora of
                 security risks associated with these devices are
                 induced by design shortcomings and vulnerabilities
                 related to user behavior. Therefore, deploying suitable
                 risk treatments requires the investigation of how
                 security experts perceive the digital natives (young
                 people, born in the digital era), when utilizing their
                 user behavior models in the design and analysis of
                 related systems. In this article, we present the
                 results of a survey performed across a multinational
                 sample of security professionals, in comparison to our
                 earlier study over the security awareness of digital
                 natives. Through this study, we seek to identify
                 divergences between user behavior and the conceptual
                 user-models that security experts utilise in their
                 professional tasks. Our results indicate that the
                 experts understanding over the user behaviour does not
                 follow a solidified user-model, while influences from
                 personal perceptions and randomness are also
                 noticeable.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Privacy in Wireless and
                 Mobile Networks.",
}

@Article{Shivani:2017:RIE,
  author =       "J. L. Divya Shivani and Ranjan K. Senapati",
  title =        "Robust Image Embedded Watermarking Using {DCT} and
                 Listless {SPIHT}",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "33",
  day =          "12",
  month =        jul,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030033",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/33",
  abstract =     "This paper presents a DCT-based (DCT: discrete cosine
                 transform) listless set partitioning in hierarchical
                 trees (SPIHT) digital watermarking technique that is
                 robust against several common attacks such as cropping,
                 filtering, sharpening, noise, inversion, contrast
                 manipulation, and compression. The proposed technique
                 is made further robust by the incorporation of the
                 Chinese remainder theorem (CRT) encryption technique.
                 Our scheme is compared with the recently proposed
                 CRT-based DCT technique, CRT-based spatial domain
                 watermarking, and DCT-based inter block correlation
                 techniques. Extensive simulation experiments show
                 better robustness in common image manipulations and, at
                 the same time, the proposed technique successfully
                 makes the watermark perceptually invisible. A better
                 Tamper Assessment Function (TAF) value of 2-15\% and a
                 better Normalized Correlation (NC) is achieved compared
                 to some of the above techniques. In particular, the
                 proposed technique shows better robustness on
                 compression attacks at moderate to higher compression
                 ratios. It is possible to maintain the imperceptibility
                 and low TAF for various values by doubling the capacity
                 of the watermark.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fourneau:2017:GNA,
  author =       "Jean-Michel Fourneau and Erol Gelenbe",
  title =        "{G}-Networks with Adders",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "34",
  day =          "10",
  month =        jul,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030034",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/34",
  abstract =     "Abstract: Queueing networks are used to model the
                 performance of the Internet, of manufacturing and
                 job-shop systems, supply chains, and other networked
                 systems in transportation or emergency management.
                 Composed of service stations where customers receive
                 service, and then move to another service station till
                 they leave the network, queueing networks are based on
                 probabilistic assumptions concerning service times and
                 customer movement that represent the variability of
                 system workloads. Subject to restrictive assumptions
                 regarding external arrivals, Markovian movement of
                 customers, and service time distributions, such
                 networks can be solved efficiently with ``product form
                 solutions'' that reduce the need for software
                 simulators requiring lengthy computations. G-networks
                 generalise these models to include the effect of
                 ``signals'' that re-route customer traffic, or negative
                 customers that reject service requests, and also have a
                 convenient product form solution. This paper extends
                 G-networks by including a new type of signal, that we
                 call an ``Adder'', which probabilistically changes the
                 queue length at the service center that it visits,
                 acting as a load regulator. We show that this
                 generalisation of G-networks has a product form
                 solution.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sadik:2017:CAH,
  author =       "Ahmed R. Sadik and Bodo Urban",
  title =        "Combining Adaptive Holonic Control and {ISA-95}
                 Architectures to Self-Organize the Interaction in a
                 Worker-Industrial Robot Cooperative Workcell",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "35",
  day =          "14",
  month =        jul,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030035",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/35",
  abstract =     "Self-Organization is a spontaneous trend which exists
                 in nature among different organisms. Self-organization
                 refers to the process where some form of an overall
                 order arises in a group due to the local interaction
                 among the members of this group. In manufacturing, a
                 similar definition of a Reconfigurable Manufacturing
                 System (RMS) can be found. RMS is a system where the
                 production components and functions can be modified,
                 rearranged and/or interchanged in a timely and
                 cost-effective manner to quickly respond to the
                 production requirements. The definition of the RMS
                 concept implies that the self-organization is an
                 important key factor to fulfil that concept. A case
                 study where a cooperation among a variable number of
                 Industrial Robots (IRs) and workers is studied to show
                 the importance of the research problem. The goal of the
                 paper is to offer a suitable generic control and
                 interaction architecture solution model, which obtains
                 the self-organization from the RMS point of view.
                 Ultimately, applying the proposed solution concept to
                 the case study.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Binmad:2017:EFR,
  author =       "Ruchdee Binmad and Mingchu Li and Zhen Wang and Nakema
                 Deonauth and Chettupally Anil Carie",
  title =        "An Extended Framework for Recovering From Trust
                 Breakdowns in Online Community Settings",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "36",
  day =          "17",
  month =        jul,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030036",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/36",
  abstract =     "The violation of trust as a result of interactions
                 that do not proceed as expected gives rise to the
                 question as to whether broken trust can possibly be
                 recovered. Clearly, trust recovery is more complex than
                 trust initialization and maintenance. Trust recovery
                 requires a more complex mechanism to explore different
                 factors that cause the decline of trust and identify
                 the affected individuals of trust violation both
                 directly and indirectly. In this study, an extended
                 framework for recovering trust is presented. Aside from
                 evaluating whether there is potential for recovery
                 based on the outcome of a forgiveness mechanism after a
                 trust violation, encouraging cooperation between
                 interacting parties after a trust violation through
                 incentive mechanisms is also important. Furthermore, a
                 number of experiments are conducted to validate the
                 applicability of the framework and the findings show
                 that the e-marketplace incorporating our proposed
                 framework results in improved efficiency of trading,
                 especially in long-term interactions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lei:2017:NHC,
  author =       "Zhou Lei and Exiong Sun and Shengbo Chen and Jiang Wu
                 and Wenfeng Shen",
  title =        "A Novel Hybrid-Copy Algorithm for Live Migration of
                 Virtual Machine",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "37",
  day =          "18",
  month =        jul,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030037",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/37",
  abstract =     "Live migration of virtual machines is an important
                 approach for dynamic resource scheduling in cloud
                 environment. The hybrid-copy algorithm is an excellent
                 algorithm that combines the pre-copy algorithm with the
                 post-copy algorithm to remedy the defects of the
                 pre-copy algorithm and the post-copy algorithm.
                 Currently, the hybrid-copy algorithm only copies all
                 memory pages once in advance. In a write-intensive
                 workload, copy memory pages once may be enough.
                 However, more iterative copy rounds can significantly
                 reduce the page faults in a read-intensive workload. In
                 this paper, we propose a new parameter to decide the
                 appropriate time to stop the iterative copy phase based
                 on real-time situation. We use a Markov model to
                 forecast the memory access pattern. Based on the
                 predicted results and the analysis of the actual
                 situation, the memory page transfer order would be
                 adjusted to reduce the invalid transfers. The novel
                 hybrid-copy algorithm is implemented on the Xen
                 platform. The experimental results demonstrate that our
                 mechanism has good performance both on read-intensive
                 workloads and write-intensive workloads.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future Computing for Real Time
                 Intelligent Systems.",
}

@Article{Lee:2017:IAO,
  author =       "Il-Gu Lee",
  title =        "Interference-Aware Opportunistic Dynamic Energy Saving
                 Mechanism for {Wi-Fi} Enabled {IoTs}",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "38",
  day =          "18",
  month =        jul,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030038",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/38",
  abstract =     "The wireless local area network (WLAN) is one of the
                 most popular wireless technologies offering
                 connectivity today, and one of the candidates for the
                 internet of things (IoTs). However, WLAN's inefficiency
                 in terms of complexity and relatively large power
                 consumption compared with other wireless standards has
                 been reported as a major barrier for IoTs applications.
                 This paper proposes an interference-aware opportunistic
                 dynamic energy saving mechanism to improve energy
                 efficiency for Wi-Fi enabled IoTs. The proposed scheme
                 optimizes operating clock frequencies adaptively for
                 signal processing when the mobile station transmits
                 packets in partial sub-channels. Evaluation results
                 demonstrate that the proposed scheme improves energy
                 efficiency by approximately 34\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Big Data and Internet of Thing.",
}

@Article{Roychowdhury:2017:ABS,
  author =       "Sohini Roychowdhury and Paul Hage and Joseph Vasquez",
  title =        "{Azure}-Based Smart Monitoring System for Anemia-Like
                 Pallor",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "39",
  day =          "26",
  month =        jul,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030039",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/39",
  abstract =     "Increasing costs of diagnostic healthcare have
                 necessitated the development of hardware independent
                 non-invasive Point of Care (POC) systems. Although
                 anemia prevalence rates in global populations vary
                 between 10\% and 60\% in various demographic groups,
                 smart monitoring systems have not yet been developed
                 for screening and tracking anemia-like pallor. In this
                 work, we present two cloud platform-hosted POC
                 applications that are directed towards smart monitoring
                 of anemia-like pallor through eye and tongue pallor
                 site images. The applications consist of a front-end
                 graphical user interface (GUI) module and two different
                 back-end image processing and machine learning modules.
                 Both applications are hosted on a browser accessible
                 tomcat server ported to an Azure Virtual Machine (VM).
                 We observe that the first application spatially
                 segments regions of interest from pallor site images
                 with higher pallor classification accuracy and
                 relatively longer processing times when compared to the
                 lesser accurate yet faster second application. Also,
                 both applications achieve 65\%-98\% accuracy in
                 separating normal images from images with pallor or
                 abnormalities. The optimized front-end module is
                 significantly light-weight with a run-through time
                 ratio of 10-5 with respect to the back-end modules.
                 Thus, the proposed applications are portable and
                 hardware independent, allowing for their use in pallor
                 monitoring and screening tasks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bauman:2017:VIE,
  author =       "Brian Bauman and Patrick Seeling",
  title =        "Visual Interface Evaluation for Wearables Datasets:
                 Predicting the Subjective Augmented Vision Image {QoE}
                 and {QoS}",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "40",
  day =          "28",
  month =        jul,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030040",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/40",
  abstract =     "As Augmented Reality (AR) applications become
                 commonplace, the determination of a device operator's
                 subjective Quality of Experience (QoE) in addition to
                 objective Quality of Service (QoS) metrics gains
                 importance. Human subject experimentation is common for
                 QoE relationship determinations due to the subjective
                 nature of the QoE. In AR scenarios, the overlay of
                 displayed content with the real world adds to the
                 complexity. We employ Electroencephalography (EEG)
                 measurements as the solution to the inherent
                 subjectivity and situationality of AR content display
                 overlaid with the real world. Specifically, we evaluate
                 prediction performance for traditional image display
                 (AR) and spherical/immersive image display (SAR) for
                 the QoE and underlying QoS levels. Our approach
                 utilizing a four-position EEG wearable achieves high
                 levels of accuracy. Our detailed evaluation of the
                 available data indicates that less sensors would
                 perform almost as well and could be integrated into
                 future wearable devices. Additionally, we make our
                 Visual Interface Evaluation for Wearables (VIEW)
                 datasets from human subject experimentation publicly
                 available and describe their utilization.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sun:2017:SQE,
  author =       "Mao-hua Sun and Yuan-gang Li and Bing He",
  title =        "Study on a Quality Evaluation Method for College
                 {English} Classroom Teaching",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "41",
  day =          "30",
  month =        jul,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030041",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/41",
  abstract =     "A quality evaluation method is an important means and
                 the main basis on which to evaluate the college English
                 classroom teaching quality of teachers. To overcome the
                 one-sided subjectivity and resulting imprecision of the
                 traditional classroom teaching quality evaluation
                 method, a scientific and reasonable quality evaluation
                 index system for college English classroom teaching is
                 constructed. The fuzzy comprehensive evaluation method
                 and the analytic hierarchy process method are combined
                 to propose an improved multi-level fuzzy comprehensive
                 evaluation model for obtaining a new college English
                 classroom teaching quality evaluation method. In the
                 proposed method, according to the fuzzy characteristics
                 of a college English classroom teaching quality
                 evaluation, the fuzzy comprehensive evaluation method
                 is used to transform the qualitative evaluation indexes
                 into limited quantitative evaluation indexes, then a
                 judgment matrix is constructed to determine the weights
                 among different levels by using the analytic hierarchy
                 process method. Additionally, the college English
                 classroom teaching quality is evaluated in detail.
                 Finally, an actual case of college English classroom
                 teaching is used to verify the effectiveness of the
                 college English classroom teaching quality evaluation
                 method. The results show that the proposed college
                 English classroom teaching method can overcome the
                 subjectivity and randomness shortcomings of the
                 traditional classroom teaching quality evaluation
                 methods, and improve the reliability, accuracy, and
                 objectivity of fuzzy comprehensive evaluation. It is an
                 effective method to evaluate college English classroom
                 teaching quality.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue u- and e- Service, Science and
                 Technology.",
}

@Article{Cominelli:2017:MPF,
  author =       "Lorenzo Cominelli and Nicola Carbonaro and Daniele
                 Mazzei and Roberto Garofalo and Alessandro Tognetti and
                 Danilo {De Rossi}",
  title =        "A Multimodal Perception Framework for Users Emotional
                 State Assessment in Social Robotics",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "42",
  day =          "01",
  month =        aug,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030042",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/42",
  abstract =     "In this work, we present an unobtrusive and
                 non-invasive perception framework based on the synergy
                 between two main acquisition systems: the Touch-Me Pad,
                 consisting of two electronic patches for physiological
                 signal extraction and processing; and the Scene
                 Analyzer, a visual-auditory perception system
                 specifically designed for the detection of social and
                 emotional cues. It will be explained how the
                 information extracted by this specific kind of
                 framework is particularly suitable for social robotics
                 applications and how the system has been conceived in
                 order to be used in human-robot interaction
                 scenarios.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bonguet:2017:SDS,
  author =       "Adrien Bonguet and Martine Bellaiche",
  title =        "A Survey of Denial-of-Service and Distributed Denial
                 of Service Attacks and Defenses in Cloud Computing",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "43",
  day =          "05",
  month =        aug,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030043",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/43",
  abstract =     "Cloud Computing is a computing model that allows
                 ubiquitous, convenient and on-demand access to a shared
                 pool of highly configurable resources (e.g., networks,
                 servers, storage, applications and services).
                 Denial-of-Service (DoS) and Distributed
                 Denial-of-Service (DDoS) attacks are serious threats to
                 the Cloud services' availability due to numerous new
                 vulnerabilities introduced by the nature of the Cloud,
                 such as multi-tenancy and resource sharing. In this
                 paper, new types of DoS and DDoS attacks in Cloud
                 Computing are explored, especially the XML-DoS and
                 HTTP-DoS attacks, and some possible detection and
                 mitigation techniques are examined. This survey also
                 provides an overview of the existing defense solutions
                 and investigates the experiments and metrics that are
                 usually designed and used to evaluate their
                 performance, which is helpful for the future research
                 in the domain.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Collection Information Systems Security.",
}

@Article{Katsinis:2017:MIM,
  author =       "Georgios Katsinis and Eirini Eleni Tsiropoulou and
                 Symeon Papavassiliou",
  title =        "Multicell Interference Management in Device to Device
                 Underlay Cellular Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "44",
  day =          "07",
  month =        aug,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030044",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/44",
  abstract =     "In this paper, the problem of interference mitigation
                 in a multicell Device to Device (D2D) underlay cellular
                 network is addressed. In this type of network
                 architectures, cellular users and D2D users share
                 common Resource Blocks (RBs). Though such paradigms
                 allow potential increase in the number of supported
                 users, the latter comes at the cost of interference
                 increase that in turn calls for the design of efficient
                 interference mitigation methodologies. To treat this
                 problem efficiently, we propose a two step approach,
                 where the first step concerns the efficient RB
                 allocation to the users and the second one the
                 transmission power allocation. Specifically, the RB
                 allocation problem is formulated as a bilateral
                 symmetric interaction game. This assures the existence
                 of a Nash Equilibrium (NE) point of the game, while a
                 distributed algorithm, which converges to it, is
                 devised. The power allocation problem is formulated as
                 a linear programming problem per RB, and the
                 equivalency between this problem and the total power
                 minimization problem is shown. Finally, the operational
                 effectiveness of the proposed approach is evaluated via
                 numerical simulations, while its superiority against
                 state of the art approaches existing in the recent
                 literature is shown in terms of increased number of
                 supported users, interference reduction and power
                 minimization.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Recent Advances in Cellular D2D
                 Communications.",
}

@Article{Zhang:2017:RIW,
  author =       "Heng Zhang and Chengyou Wang and Xiao Zhou",
  title =        "A Robust Image Watermarking Scheme Based on {SVD} in
                 the Spatial Domain",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "45",
  day =          "07",
  month =        aug,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030045",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/45",
  abstract =     "With the development of image processing technology,
                 the copyright protection of digital images has become
                 an urgent problem to be solved. As an effective method,
                 the robust digital watermarking technique emerges at a
                 historic moment. Currently, most robust watermarking
                 schemes are performed in the transform domains, such as
                 the discrete cosine transform (DCT) and singular value
                 decomposition (SVD). Compared with spatial domain
                 watermarking schemes, these methods have achieved good
                 performance, such as better robustness and higher
                 security. However, the computational complexity
                 increases with the use of forward and reverse
                 transforms. In this paper, we analyze the SVD-based
                 watermarking scheme and its impact on the spatial
                 domain. Based on this analysis and the mathematical
                 characteristics of SVD, we present a robust image
                 watermarking scheme where a binary watermark is
                 embedded into the largest singular value of each image
                 block in the spatial domain. Several experiments are
                 conducted to verify the performance of the proposed
                 watermarking scheme. The experimental results show that
                 compared with the existing SVD domain watermarking
                 schemes, our proposed method has maintained good
                 robustness against various attacks. Moreover, it avoids
                 the false positive problem existing in traditional
                 SVD-based watermarking schemes and has lower
                 computational complexity.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lee:2017:DPD,
  author =       "Il-Gu Lee",
  title =        "Digital Pre-Distortion of Carrier Frequency Offset for
                 Reliable Wi-Fi Enabled {IoTs}",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "46",
  day =          "09",
  month =        aug,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030046",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/46",
  abstract =     "The Internet of Things (IoTs) will change the
                 requirements for wireless connectivity significantly,
                 mainly with regard to service coverage, data rate, and
                 energy efficiency. Therefore, to improve robustness and
                 reliability, WiFi-enabled IoT devices have been
                 developed to use narrowband communication. However,
                 narrowband transmission in WiFi such as IEEE 802.11ah
                 causes relatively higher frequency error due to the
                 reduced subcarrier space, which is larger than legacy
                 wireless local area networks (WLANs) in 2.4/5 GHz
                 frequencies. In a direct conversion receiver, this
                 error degrades the signal quality due to the presence
                 of direct current (DC) offset cancellation circuits. In
                 this paper, a digital carrier frequency offset (CFO)
                 predistortion scheme is proposed for a reliable
                 communication link in dense networks. Evaluation
                 results demonstrate that the proposed scheme can
                 improve received signal quality in terms of packet
                 error rate and error vector magnitude.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Big Data and Internet of Thing.",
}

@Article{Markus:2017:CAI,
  author =       "Andras Markus and Attila Kertesz and Gabor
                 Kecskemeti",
  title =        "Cost-Aware {IoT} Extension of {DISSECT-CF}",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "47",
  day =          "14",
  month =        aug,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030047",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/47",
  abstract =     "In the age of the Internet of Things (IoT), more and
                 more sensors, actuators and smart devices get connected
                 to the network. Application providers often combine
                 this connectivity with novel scenarios involving cloud
                 computing. Before implementing changes in these
                 large-scale systems, an in-depth analysis is often
                 required to identify governance models, bottleneck
                 situations, costs and unexpected behaviours.
                 Distributed systems simulators help in such analysis,
                 but they are often problematic to apply in this newly
                 emerging domain. For example, most simulators are
                 either too detailed (e.g., need extensive knowledge on
                 networking), or not extensible enough to support the
                 new scenarios. To overcome these issues, we discuss our
                 IoT cost analysis oriented extension of DIScrete event
                 baSed Energy Consumption simulaTor for Clouds and
                 Federations (DISSECT-CF). Thus, we present an in-depth
                 analysis of IoT and cloud related pricing models of the
                 most widely used commercial providers. Then, we show
                 how the fundamental properties (e.g., data production
                 frequency) of IoT entities could be linked to the
                 identified pricing models. To allow the adoption of
                 unforeseen scenarios and pricing schemes, we present a
                 declarative modelling language to describe these links.
                 Finally, we validate our extensions by analysing the
                 effects of various identified pricing models through
                 five scenarios coming from the field of weather
                 forecasting.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Big Data and Internet of Thing.",
}

@Article{Sadik:2017:FSS,
  author =       "Ahmed R. Sadik and Bodo Urban",
  title =        "Flow Shop Scheduling Problem and Solution in
                 Cooperative Robotics-Case-Study: One Cobot in
                 Cooperation with One Worker",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "48",
  day =          "16",
  month =        aug,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030048",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/48",
  abstract =     "This research combines between two different
                 manufacturing concepts. On the one hand, flow shop
                 scheduling is a well-known problem in production
                 systems. The problem appears when a group of jobs
                 shares the same processing sequence on two or more
                 machines sequentially. Flow shop scheduling tries to
                 find the appropriate solution to optimize the sequence
                 order of this group of jobs over the existing machines.
                 The goal of flow shop scheduling is to obtain the
                 continuity of the flow of the jobs over the machines.
                 This can be obtained by minimizing the delays between
                 two consequent jobs, therefore the overall makespan can
                 be minimized. On the other hand, collaborative robotics
                 is a relatively recent approach in production where a
                 collaborative robot (cobot) is capable of a close
                 proximity cooperation with the human worker to increase
                 the manufacturing agility and flexibility. The simplest
                 case-study of a collaborative workcell is one cobot in
                 cooperation with one worker. This collaborative
                 workcell can be seen as a special case of the shop flow
                 scheduling problem, where the required time from the
                 worker to perform a specific job is unknown and
                 variable. Therefore, during this research, we implement
                 an intelligent control solution which can optimize the
                 flow shop scheduling problem over the previously
                 mentioned case-study.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{De-Pablos-Heredero:2017:FIS,
  author =       "Carmen De-Pablos-Heredero",
  title =        "Future Intelligent Systems and Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "49",
  day =          "02",
  month =        sep,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030049",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/49",
  abstract =     "The expansion of telecommunication technologies
                 touches almost all aspects life that we are living
                 nowadays. Indeed, such technologies have emerged as a
                 fourth essential utility alongside the traditional
                 utilities of electricity, water, and gas. In this
                 context, Cloud Data Center Networks (cloud-DCNs) have
                 been proposed as a promising way to cope with such a
                 high-tech era and with any expected trends in future
                 computing networks. Resources of cloud-DCNs are leased
                 to the interested users in the form of services, such
                 services come in different models that vary between
                 software, platform, and infrastructure. The leasing
                 process of any service model starts with the users
                 (i.e., service tenants). A tenant asks for the service
                 resources, and the cloud-provider allocates the
                 resources with a charge that follows a predefined cost
                 policy. Cloud resources are limited, and those cloud
                 providers have profit objectives to be satisfied. Thus,
                 to comply with the aforementioned promise, the limited
                 resources need to be carefully allocated. Existing
                 allocation proposals in the literature dealt with this
                 problem in varying ways. However, none proposes a
                 win-win allocation model that satisfies both the
                 providers and tenants. This work proposes A Rational
                 Allocation Approach in Cloud Data Center Networks
                 (ARAAC) that efficiently allocates the available cloud
                 resources, in a way that allows for a win-win
                 environment to satisfy both parties: the providers and
                 tenants. To do so, ARAAC deploys the Second Best-Price
                 (SBP) mechanism along with a behavioral-based
                 reputation model. The reputation is built according to
                 the tenants' utilization history throughout their
                 previous service allocations. The reputation records
                 along with the adoption of the SBP mechanism allows for
                 a locally free-equilibrium approach that allocates the
                 available cloud-DCN resources in an efficient and fair
                 manner. In ARAAC, through an auction scenario, tenants
                 with positive reputation records are awarded by having
                 the required resources allocated at prices that are
                 lower than what they have offered. Compared to other
                 benchmark models, simulation results show that ARAAC
                 can efficiently adapt the behavior of those rational
                 service-tenants to provide for better use of the cloud
                 resources, with an increase in the providers'
                 profits.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future Intelligent Systems and
                 Networks.",
}

@Article{Quttoum:2017:ARA,
  author =       "Ahmad Nahar Quttoum and Ayoub Alsarhan and
                 Abidalrahman Moh'd",
  title =        "{ARAAC}: a Rational Allocation Approach in Cloud Data
                 Center Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "50",
  day =          "06",
  month =        sep,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030050",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/50",
  abstract =     "The expansion of telecommunication technologies
                 touches almost all aspects life that we are living
                 nowadays. Indeed, such technologies have emerged as a
                 fourth essential utility alongside the traditional
                 utilities of electricity, water, and gas. In this
                 context, Cloud Data Center Networks (cloud-DCNs) have
                 been proposed as a promising way to cope with such a
                 high-tech era and with any expected trends in future
                 computing networks. Resources of cloud-DCNs are leased
                 to the interested users in the form of services, such
                 services come in different models that vary between
                 software, platform, and infrastructure. The leasing
                 process of any service model starts with the users
                 (i.e., service tenants). A tenant asks for the service
                 resources, and the cloud-provider allocates the
                 resources with a charge that follows a predefined cost
                 policy. Cloud resources are limited, and those cloud
                 providers have profit objectives to be satisfied. Thus,
                 to comply with the aforementioned promise, the limited
                 resources need to be carefully allocated. Existing
                 allocation proposals in the literature dealt with this
                 problem in varying ways. However, none proposes a
                 win-win allocation model that satisfies both the
                 providers and tenants. This work proposes A Rational
                 Allocation Approach in Cloud Data Center Networks
                 (ARAAC) that efficiently allocates the available cloud
                 resources, in a way that allows for a win-win
                 environment to satisfy both parties: the providers and
                 tenants. To do so, ARAAC deploys the Second Best-Price
                 (SBP) mechanism along with a behavioral-based
                 reputation model. The reputation is built according to
                 the tenants' utilization history throughout their
                 previous service allocations. The reputation records
                 along with the adoption of the SBP mechanism allows for
                 a locally free-equilibrium approach that allocates the
                 available cloud-DCN resources in an efficient and fair
                 manner. In ARAAC, through an auction scenario, tenants
                 with positive reputation records are awarded by having
                 the required resources allocated at prices that are
                 lower than what they have offered. Compared to other
                 benchmark models, simulation results show that ARAAC
                 can efficiently adapt the behavior of those rational
                 service-tenants to provide for better use of the cloud
                 resources, with an increase in the providers'
                 profits.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhou:2017:LPP,
  author =       "Kaijun Zhou and Lingli Yu and Ziwei Long and Siyao
                 Mo",
  title =        "Local Path Planning of Driverless Car Navigation Based
                 on Jump Point Search Method Under Urban Environment",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "51",
  day =          "12",
  month =        sep,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030051",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/51",
  abstract =     "The Jump Point Search (JPS) algorithm is adopted for
                 local path planning of the driverless car under urban
                 environment, and it is a fast search method applied in
                 path planning. Firstly, a vector Geographic Information
                 System (GIS) map, including Global Positioning System
                 (GPS) position, direction, and lane information, is
                 built for global path planning. Secondly, the GIS map
                 database is utilized in global path planning for the
                 driverless car. Then, the JPS algorithm is adopted to
                 avoid the front obstacle, and to find an optimal local
                 path for the driverless car in the urban environment.
                 Finally, 125 different simulation experiments in the
                 urban environment demonstrate that JPS can search out
                 the optimal and safety path successfully, and
                 meanwhile, it has a lower time complexity compared with
                 the Vector Field Histogram (VFH), the Rapidly Exploring
                 Random Tree (RRT), A*, and the Probabilistic Roadmaps
                 (PRM) algorithms. Furthermore, JPS is validated
                 usefully in the structured urban environment.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lupetti:2017:DCP,
  author =       "Maria Luce Lupetti and Yuan Yao and Haipeng Mi and
                 Claudio Germak",
  title =        "Design for Children's Playful Learning with Robots",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "52",
  day =          "18",
  month =        sep,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030052",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/52",
  abstract =     "This article presents an investigation of the
                 implications of designing for children's playful
                 learning with robots. This study was carried out by
                 adopting a Research through Design approach that
                 resulted in the development of a novel
                 low-anthropomorphic robot called Shybo. The article
                 reports the main phases of the project: the preliminary
                 and exploratory research that was carried out to define
                 a list of design requirements; the design of the robot
                 and its supplementary materials for carrying out
                 playful learning experiences; and the evaluation of the
                 project that involved both parents and children. The
                 robot, in fact, was finally tested as part of a
                 two-hour experience that engaged children in activities
                 related to the associations between sounds and colours.
                 The article presents and discusses the results of this
                 evaluation to point out positive aspects of the
                 experience, emerging issues and hints for future works.
                 These are documented to share lessons learned that
                 might be supportive of the general development of
                 children's playful learning and cognitive experiences
                 with robots.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yang:2017:TND,
  author =       "Yao Yang",
  title =        "Towards a New Digital Era: Observing Local
                 E-Government Services Adoption in a {Chinese}
                 Municipality",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "3",
  pages =        "53",
  day =          "20",
  month =        sep,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9030053",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:57 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/3/53",
  abstract =     "As electronic government services (e-government)
                 evolve, traditional applications such as online portals
                 are encountering challenges in a new digital era in
                 which people thirst for more convenient, diverse
                 channels of communication with their government.
                 Despite the efforts devoted to the promotion of Social
                 Networking Service (SNS) use in e-government for the
                 past few years, empirical studies regarding this
                 ongoing trend are still insufficient. In the local
                 administration of China, a special collaboration
                 between local governments and private Internet
                 enterprises is happening: government services are
                 imported into commercial SNS platforms known as WeChat
                 and Weibo. This research conducts a case study of a
                 Chinese municipality premised upon survey data (N =
                 605) collected in Chongqing. It examines the
                 determinants of e-services adoption in four major local
                 applications: two traditional government-led services
                 ``Government website portal'' and ``Government official
                 app'' (traditional government-led services), and two
                 built-in government services on social networking
                 applications ``Weibo Government official account''
                 ``WeChat Public Services''. The paper aims to provide a
                 closer understanding of current trends in local
                 government e-services, or in this case, an innovative
                 trial of Chinese e-government practices.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue u- and e- Service, Science and
                 Technology.",
}

@Article{Rizvi:2017:DCB,
  author =       "Syed Tahir Hussain Rizvi and Denis Patti and Tomas
                 Bj{\"o}rklund and Gianpiero Cabodi and Gianluca
                 Francini",
  title =        "Deep Classifiers-Based License Plate Detection,
                 Localization and Recognition on {GPU}-Powered Mobile
                 Platform",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "66",
  day =          "21",
  month =        oct,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040066",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/66",
  abstract =     "The realization of a deep neural architecture on a
                 mobile platform is challenging, but can open up a
                 number of possibilities for visual analysis
                 applications. A neural network can be realized on a
                 mobile platform by exploiting the computational power
                 of the embedded GPU and simplifying the flow of a
                 neural architecture trained on the desktop workstation
                 or a GPU server. This paper presents an embedded
                 platform-based Italian license plate detection and
                 recognition system using deep neural classifiers. In
                 this work, trained parameters of a highly precise
                 automatic license plate recognition (ALPR) system are
                 imported and used to replicate the same neural
                 classifiers on a Nvidia Shield K1 tablet. A CUDA-based
                 framework is used to realize these neural networks. The
                 flow of the trained architecture is simplified to
                 perform the license plate recognition in real-time.
                 Results show that the tasks of plate and character
                 detection and localization can be performed in
                 real-time on a mobile platform by simplifying the flow
                 of the trained architecture. However, the accuracy of
                 the simplified architecture would be decreased
                 accordingly.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hanna:2017:SSD,
  author =       "Dalal Hanna and Prakash Veeraraghavan and Ben Soh",
  title =        "{SDMw}: Secure Dynamic Middleware for Defeating Port
                 and {OS} Scanning",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "67",
  day =          "21",
  month =        oct,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040067",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/67",
  abstract =     "Fingerprinting is a process of identifying the remote
                 network devices and services running on the devices,
                 including operating systems (OS) of the devices, and
                 hosts running different OSs. Several research proposals
                 and commercial products are available in the market to
                 defeat fingerprinting. However, they have performance
                 limitations and expose themselves to attackers. In this
                 paper, we utilize some real-time fault-tolerance
                 concepts (viz. real-time/dynamic, detection/locating,
                 confinement/localizing and masking/decoy) to propose a
                 plug-and-play adaptive middleware architecture called
                 Secure Dynamic Middleware (SDMw) with a view to defeat
                 attackers fingerprinting the network, without exposing
                 itself to the attackers. We verify that the proposed
                 scheme works seamlessly and requires zero-configuration
                 at the client side.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Colombo:2017:CWU,
  author =       "Bruna Armonas Colombo and Pedro Buck and Vinicius
                 Miana Bezerra",
  title =        "Challenges When Using Jurimetrics in {Brazil}--- a
                 Survey of Courts",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "68",
  day =          "25",
  month =        oct,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040068",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/68",
  abstract =     "Jurimetrics is the application of quantitative
                 methods, usually statistics, to law. An important step
                 to implement a jurimetric analysis is to extract raw
                 data from courts and organize that data in a way that
                 can be processed. Most of the raw data is unstructured
                 and written in natural language, which stands as a
                 challenge to Computer Science experts. As it requires
                 expertise in law, statistics, and computer science,
                 jurimetrics is a multidisciplinary field. When trying
                 to implement a jurimetric system in Brazil, additional
                 challenges were identified due to the heterogeneity of
                 the different court systems, the lack of standards, and
                 how the open data laws in Brazil are interpreted and
                 implemented. In this article, we present a survey of
                 Brazilian courts in terms of readiness to implement a
                 jurimetric system. Analyzing a sample of data, we have
                 found, in light of Brazil's open data regulation,
                 privacy issues and technical issues. Finally, we
                 propose a roadmap that encompasses both technology and
                 public policy to meet those challenges.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Computation, Law and the Net-The Future
                 of Law in the Computational Social Science Era.",
}

@Article{Li:2017:SCT,
  author =       "Dongyuan Li and Chengshuai Li and Zidong Wang and
                 Deqiang Wang and Jianping Xing and Bo Zhang",
  title =        "Signal Consensus in {TSP} of the Same Grid in Road
                 Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "69",
  day =          "24",
  month =        oct,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040069",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/69",
  abstract =     "In this paper, we propose a consensus algorithm with
                 input constraints for traffic light signals in transit
                 signal priority (TSP). TSP ensures control strategy of
                 traffic light signals can be adjusted and applied
                 according to the real-time traffic status, and provides
                 priority for buses. We give the convergence conditions
                 of the consensus algorithms with and without input
                 constraints in TSP respectively and analyze the
                 convergence performance of them by using matrix theory
                 and graph theory, and PTV-VISSIM is used to simulate
                 the traffic accident probability of three cases at
                 intersections. Simulation results are presented that a
                 consensus is asymptotically reached for all weights of
                 priority; the algorithm with input constraints is more
                 suitable for TSP than the algorithm without input
                 constraints, and the traffic accident rate is
                 reduced.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future Computing for Real Time
                 Intelligent Systems.",
}

@Article{Pruvost:2017:EDM,
  author =       "Hippolyte Pruvost and Peter Mooney",
  title =        "Exploring Data Model Relations in {OpenStreetMap}",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "70",
  day =          "24",
  month =        oct,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040070",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/70",
  abstract =     "The OpenStreetMap (OSM) geographic data model has
                 three principal object types: nodes (points), ways
                 (polygons and polylines), and relations (logical
                 grouping of all three object types to express
                 real-world geographical relationships). While there has
                 been very significant analysis of OSM over the past
                 decade or so, very little research attention has been
                 given to OSM relations. In this paper, we provide an
                 exploratory overview of relations in OSM for four
                 European cities. In this exploration, we undertake
                 analysis of relations to assess their complexity,
                 composition and flexibility within the OSM data model.
                 We show that some of the patterns discovered by
                 researchers related to OSM nodes and ways also exist in
                 relations. We find some other interesting aspects of
                 relations which we believe can act as a catalyst for a
                 more sustained future research effort on relations in
                 OSM. These aspects include: the potential influence of
                 bulk imports of geographical data to OSM, tagging of
                 relations, and contribution patterns of edits to OSM
                 relations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mazzenga:2017:FBF,
  author =       "Franco Mazzenga and Romeo Giuliano and Francesco
                 Vatalaro",
  title =        "{FttC}-Based Fronthaul for {5G} Dense\slash
                 Ultra-Dense Access Network: Performance and Costs in
                 Realistic Scenarios",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "71",
  day =          "27",
  month =        oct,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040071",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/71",
  abstract =     "One distinctive feature of the next 5G systems is the
                 presence of a dense/ultra-dense wireless access network
                 with a large number of access points (or nodes) at
                 short distances from each other. Dense/ultra-dense
                 access networks allow for providing very high
                 transmission capacity to terminals. However, the
                 deployment of dense/ultra-dense networks is slowed down
                 by the cost of the fiber-based infrastructure required
                 to connect radio nodes to the central processing units
                 and then to the core network. In this paper, we
                 investigate the possibility for existing FttC access
                 networks to provide fronthaul capabilities for
                 dense/ultra-dense 5G wireless networks. The analysis is
                 realistic in that it is carried out considering an
                 actual access network scenario, i.e., the Italian FttC
                 deployment. It is assumed that access nodes are
                 connected to the Cabinets and to the corresponding
                 distributors by a number of copper pairs. Different
                 types of cities grouped in terms of population have
                 been considered. Results focus on fronthaul transport
                 capacity provided by the FttC network and have been
                 expressed in terms of the available fronthaul bit rate
                 per node and of the achievable coverage.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Khan:2017:TAC,
  author =       "Muhidul Islam Khan and Muhammad Mahtab Alam and
                 Yannick {Le Moullec} and Elias Yaacoub",
  title =        "Throughput-Aware Cooperative Reinforcement Learning
                 for Adaptive Resource Allocation in Device-to-Device
                 Communication",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "72",
  day =          "01",
  month =        nov,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040072",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/72",
  abstract =     "Device-to-device (D2D) communication is an essential
                 feature for the future cellular networks as it
                 increases spectrum efficiency by reusing resources
                 between cellular and D2D users. However, the
                 performance of the overall system can degrade if there
                 is no proper control over interferences produced by the
                 D2D users. Efficient resource allocation among D2D User
                 equipments (UE) in a cellular network is desirable
                 since it helps to provide a suitable interference
                 management system. In this paper, we propose a
                 cooperative reinforcement learning algorithm for
                 adaptive resource allocation, which contributes to
                 improving system throughput. In order to avoid selfish
                 devices, which try to increase the throughput
                 independently, we consider cooperation between devices
                 as promising approach to significantly improve the
                 overall system throughput. We impose cooperation by
                 sharing the value function/learned policies between
                 devices and incorporating a neighboring factor. We
                 incorporate the set of states with the appropriate
                 number of system-defined variables, which increases the
                 observation space and consequently improves the
                 accuracy of the learning algorithm. Finally, we compare
                 our work with existing distributed reinforcement
                 learning and random allocation of resources. Simulation
                 results show that the proposed resource allocation
                 algorithm outperforms both existing methods while
                 varying the number of D2D users and transmission power
                 in terms of overall system throughput, as well as D2D
                 throughput by proper Resource block (RB)-power level
                 combination with fairness measure and improving the
                 Quality of service (QoS) by efficient controlling of
                 the interference level.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Recent Advances in Cellular D2D
                 Communications.",
}

@Article{Anwar:2017:QSB,
  author =       "Asim Anwar and Boon-Chong Seet and Xue Jun Li",
  title =        "Quality of Service Based {NOMA} Group {D2D}
                 Communications",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "73",
  day =          "01",
  month =        nov,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040073",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/73",
  abstract =     "Non-orthogonal multiple access (NOMA) provides
                 superior spectral efficiency and is considered as a
                 promising multiple access scheme for fifth generation
                 (5G) wireless systems. The spectrum efficiency can be
                 further enhanced by enabling device-to-device (D2D)
                 communications. In this work, we propose quality of
                 service (QoS) based NOMA (Q-NOMA) group D2D
                 communications in which the D2D receivers (DRs) are
                 ordered according to their QoS requirements. We discuss
                 two possible implementations of proposed Q-NOMA group
                 D2D communications based on the two power allocation
                 coefficient policies. In order to capture the key
                 aspects of D2D communications, which are device
                 clustering and spatial separation, we model the
                 locations of D2D transmitters (DTs) by Gauss-Poisson
                 process (GPP). The DRs are then considered to be
                 clustered around DTs. Multiple DTs can exist in
                 proximity of each other. In order to characterize the
                 performance, we derive the Laplace transform of the
                 interference at the probe D2D receiver and obtain a
                 closed-form expression of its outage probability using
                 stochastic geometry tools. The performance of proposed
                 Q-NOMA group D2D communications is then evaluated and
                 benchmarked against conventional paired D2D
                 communications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Recent Advances in Cellular D2D
                 Communications.",
}

@Article{Reddy:2017:ETE,
  author =       "Nalavala Ramanjaneya Reddy and Pakanati Chenna Reddy
                 and Mokkala Padmavathamma",
  title =        "Efficient Traffic Engineering Strategies for Improving
                 the Performance of {TCP} Friendly Rate Control
                 Protocol",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "74",
  day =          "01",
  month =        nov,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040074",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/74",
  abstract =     "Multimedia services will play a prominent role in the
                 next generation of internet. With increasing real time
                 requirements, internet technology has to provide
                 Quality of Service (QoS) for various kinds of real time
                 streaming services. When the bandwidth required exceeds
                 the available network resources, network paths can get
                 congested, which results in a delay in packet delivery
                 and packet loss. This situation leads to the design of
                 new strategies for congestion avoidance and control.
                 One of the popular and appropriate congestion control
                 mechanisms that is useful in transmitting multimedia
                 applications in the transport layer is TCP Friendly
                 Rate Control Protocol (TFRC). However, TFRC still
                 suffers from packet loss and delay due to long distance
                 heavy traffic and network fluctuations. This paper
                 introduces a number of key concerns like enhanced Round
                 Trip Time (RTT) and Retransmission Time Out (RTO)
                 calculations, Enhanced Average Loss Interval (ALI)
                 methods and improved Time to Live (TTL) features are
                 applied to TFRC to enhance the performance of TFRC over
                 wired networks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future Computing for Real Time
                 Intelligent Systems.",
}

@Article{Chikaraishi:2017:CSA,
  author =       "Takenobu Chikaraishi and Yuichiro Yoshikawa and Kohei
                 Ogawa and Oriza Hirata and Hiroshi Ishiguro",
  title =        "Creation and Staging of {Android} Theatre
                 ``{Sayonara}'' towards Developing Highly Human-Like
                 Robots",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "75",
  day =          "02",
  month =        nov,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040075",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/75",
  abstract =     "Even after long-term exposures, androids with a
                 strikingly human-like appearance evoke unnatural
                 feelings. The behavior that would induce human-like
                 feelings after long exposures is difficult to
                 determine, and it often depends on the cultural
                 background of the observers. Therefore, in this study,
                 we generate an acting performance system for the
                 android, in which an android and a human interact in a
                 stage play in the real world. We adopt the theatrical
                 theory called Contemporary Colloquial Theatre Theory to
                 give the android natural behaviors so that audiences
                 can comfortably observe it even after long-minute
                 exposure. A stage play is created and shown in various
                 locations, and the audiences are requested to report
                 their impressions of the stage and their cultural and
                 psychological backgrounds in a self-evaluating
                 questionnaire. Overall analysis indicates that the
                 audience had positive feelings, in terms of
                 attractiveness, towards the android on the stage even
                 after 20 min of exposure. The singularly high
                 acceptance of the android by Japanese audiences seems
                 to be correlated with a high animism tendency, rather
                 than to empathy. We also discuss how the stage play
                 approach is limited and could be extended to contribute
                 to realization of human-robot interaction in the real
                 world.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Engaging in Interaction with Robots.",
}

@Article{Saura:2017:UDM,
  author =       "Jos{\'e} Ram{\'o}n Saura and Pedro Palos-S{\'a}nchez
                 and Luis Manuel Cerd{\'a} Su{\'a}rez",
  title =        "Understanding the Digital Marketing Environment with
                 {KPIs} and {Web} Analytics",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "76",
  day =          "04",
  month =        nov,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040076",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/76",
  abstract =     "In the practice of Digital Marketing (DM), Web
                 Analytics (WA) and Key Performance Indicators (KPIs)
                 can and should play an important role in marketing
                 strategy formulation. It is the aim of this article to
                 survey the various DM metrics to determine and address
                 the following question: What are the most relevant
                 metrics and KPIs that companies need to understand and
                 manage in order to increase the effectiveness of their
                 DM strategies? Therefore, to achieve these objectives,
                 a Systematic Literature Review has been carried out
                 based on two main themes (i) Digital Marketing and (ii)
                 Web Analytics. The search terms consulted in the
                 databases have been (i) DM and (ii) WA obtaining a
                 result total of n = 378 investigations. The databases
                 that have been consulted for the extraction of data
                 were Scopus, PubMed, PsyINFO, ScienceDirect and Web of
                 Science. In this study, we define and identify the main
                 KPIs in measuring why, how and for what purpose users
                 interact with web pages and ads. The main contribution
                 of the study is to lay out and clarify quantitative and
                 qualitative KPIs and indicators for DM performance in
                 order to achieve a consensus on the use and measurement
                 of these indicators.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ali:2017:CSR,
  author =       "Ahmad Ali and Yu Ming and Sagnik Chakraborty and Saima
                 Iram",
  title =        "A Comprehensive Survey on Real-Time Applications of
                 {WSN}",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "77",
  day =          "07",
  month =        nov,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040077",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/77",
  abstract =     "Nowadays, the investigation of the Wireless Sensor
                 Network (WSN) has materialized its functional area
                 ubiquitously such as environmental engineering,
                 industrial and business applications, military,
                 feedstock and habitat, agriculture sector, seismic
                 detection, intelligent buildings, smart grids, and
                 predictive maintenance, etc. Although some challenges
                 still exist in the wireless sensor network, in spite of
                 the shortcoming, it has been gaining significant
                 attention among researchers and technologists due to
                 its versatility and robustness. WSN is subject to a
                 high potential technology that has been successfully
                 implemented and tested in real-time scenarios, as well
                 as deployed practically in various applications. In
                 this paper, we have carried out an extensive survey in
                 real-time applications of wireless sensor network
                 deployment in a practical scenario such as the
                 real-time intelligent monitoring of temperature,
                 criminal activity in borders and surveillance on
                 traffic monitoring, vehicular behavior on roads, water
                 level and pressure, and remote monitoring of patients.
                 The application of the Wireless Sensor Network in the
                 assorted field of research areas has been widely
                 deliberated. WSN is found to be the most effective
                 solution in remote areas which are not yet explored due
                 to its perilous nature and unreachable places. Here, in
                 this study, we have cited the recent and updated
                 research on the ubiquitous usage of WSN in diverse
                 fields in an extensive and comprehensive approach.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Communications and Computing for
                 Sustainable Development Goals.",
}

@Article{Kontogiannis:2017:PFN,
  author =       "Sotirios Kontogiannis and George Kokkonis and Soultana
                 Ellinidou and Stavros Valsamidis",
  title =        "Proposed Fuzzy-{NN} Algorithm with {LoRaCommunication}
                 Protocol for Clustered Irrigation Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "78",
  day =          "07",
  month =        nov,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040078",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/78",
  abstract =     "Modern irrigation systems utilize sensors and
                 actuators, interconnected together as a single entity.
                 In such entities, A.I. algorithms are implemented,
                 which are responsible for the irrigation process. In
                 this paper, the authors present an irrigation Open
                 Watering System (OWS) architecture that spatially
                 clusters the irrigation process into autonomous
                 irrigation sections. Authors' OWS implementation
                 includes a Neuro-Fuzzy decision algorithm called FITRA,
                 which originates from the Greek word for seed. In this
                 paper, the FITRA algorithm is described in detail, as
                 are experimentation results that indicate significant
                 water conservations from the use of the FITRA
                 algorithm. Furthermore, the authors propose a new
                 communication protocol over LoRa radio as an
                 alternative low-energy and long-range OWS clusters
                 communication mechanism. The experimental scenarios
                 confirm that the FITRA algorithm provides more
                 efficient irrigation on clustered areas than existing
                 non-clustered, time scheduled or threshold adaptive
                 algorithms. This is due to the FITRA algorithm's
                 frequent monitoring of environmental conditions, fuzzy
                 and neural network adaptation as well as adherence to
                 past irrigation preferences.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Big Data and Internet of Thing.",
}

@Article{Zhang:2017:MCU,
  author =       "Jingbo Zhang and Lili Cai and Shufang Zhang",
  title =        "Malicious Cognitive User Identification Algorithm in
                 Centralized Spectrum Sensing System",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "79",
  day =          "08",
  month =        nov,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040079",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/79",
  abstract =     "Collaborative spectral sensing can fuse the perceived
                 results of multiple cognitive users, and thus will
                 improve the accuracy of perceived results. However, the
                 multi-source features of the perceived results result
                 in security problems in the system. When there is a
                 high probability of a malicious user attack, the
                 traditional algorithm can correctly identify the
                 malicious users. However, when the probability of
                 attack by malicious users is reduced, it is almost
                 impossible to use the traditional algorithm to
                 correctly distinguish between honest users and
                 malicious users, which greatly reduces the perceived
                 performance. To address the problem above, based on the
                 \beta function and the feedback iteration mathematical
                 method, this paper proposes a malicious user
                 identification algorithm under multi-channel
                 cooperative conditions (\beta -MIAMC), which involves
                 comprehensively assessing the cognitive user's
                 performance on multiple sub-channels to identify the
                 malicious user. Simulation results show under the same
                 attack probability, compared with the traditional
                 algorithm, the \beta -MIAMC algorithm can more
                 accurately identify the malicious users, reducing the
                 false alarm probability of malicious users by more than
                 20\%. When the attack probability is greater than 7\%,
                 the proposed algorithm can identify the malicious users
                 with 100\% certainty.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Joshi:2017:FCB,
  author =       "Pusp Raj Joshi and Shareeful Islam and Syed Islam",
  title =        "A Framework for Cloud Based E-Government from the
                 Perspective of Developing Countries",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "80",
  day =          "09",
  month =        nov,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040080",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/80",
  abstract =     "Despite significant efforts to initiate electronic
                 government projects, developing countries are still
                 struggling to reap the benefits of using e-government
                 services. An effective implementation of e-government
                 infrastructure is necessary to increase the efficiency
                 and transparency of the government services. There are
                 several studies that observed causes like lack of
                 infrastructure support, lack of payment gateway and
                 improper e-government service delivery channel as main
                 barriers to a wider adoption of e-government services.
                 The main contribution of this research is to propose a
                 cloud-based G2G (Government-to-government) e-government
                 framework for a viable e-government solution from the
                 perspective of developing countries. We have introduced
                 a list of concepts and a systematic process to guide
                 the implementation of e-government project based on the
                 government's vision, goals, chosen services through the
                 service delivery channel to the appropriate cloud
                 service and deployment model. We have used Nepal as a
                 context of the case study and applied the framework to
                 a real e-government project of driving licensing
                 department using action research methodology. The
                 results from the study show that the G2G approach of
                 e-government implementation would be the best for
                 providing effective government services to the
                 stakeholders of developing countries. The proposed
                 framework also supports a smooth integration of
                 government services and reduces the time of the overall
                 project.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Shah:2017:NID,
  author =       "Reehan Ali Shah and Yuntao Qian and Dileep Kumar and
                 Munwar Ali and Muhammad Bux Alvi",
  title =        "Network Intrusion Detection through Discriminative
                 Feature Selection by Using Sparse Logistic Regression",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "81",
  day =          "10",
  month =        nov,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040081",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/81",
  abstract =     "Intrusion detection system (IDS) is a well-known and
                 effective component of network security that provides
                 transactions upon the network systems with security and
                 safety. Most of earlier research has addressed
                 difficulties such as overfitting, feature redundancy,
                 high-dimensional features and a limited number of
                 training samples but feature selection. We approach the
                 problem of feature selection via sparse logistic
                 regression (SPLR). In this paper, we propose a
                 discriminative feature selection and intrusion
                 classification based on SPLR for IDS. The SPLR is a
                 recently developed technique for data analysis and
                 processing via sparse regularized optimization that
                 selects a small subset from the original feature
                 variables to model the data for the purpose of
                 classification. A linear SPLR model aims to select the
                 discriminative features from the repository of datasets
                 and learns the coefficients of the linear classifier.
                 Compared with the feature selection approaches, like
                 filter (ranking) and wrapper methods that separate the
                 feature selection and classification problems, SPLR can
                 combine feature selection and classification into a
                 unified framework. The experiments in this
                 correspondence demonstrate that the proposed method has
                 better performance than most of the well-known
                 techniques used for intrusion detection.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Collection Information Systems Security.",
}

@Article{Yuan:2017:CBM,
  author =       "Peiyan Yuan and Hai Yu",
  title =        "A Combinational Buffer Management Scheme in Mobile
                 Opportunistic Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "82",
  day =          "14",
  month =        nov,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040082",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/82",
  abstract =     "Nodes in Mobile Opportunistic Network (MON) have to
                 cache packets to deal with the intermittent connection.
                 The buffer management strategy obviously impacts the
                 performance of MON, and it attracts more attention
                 recently. Due to the limited storage capacity of nodes,
                 traditional buffer management strategies just drop
                 messages based on the property of message, and they
                 neglect the collaboration between neighbors, resulting
                 in an ineffective performance improvement. Therefore,
                 effective buffer management strategies are necessary to
                 ensure that each node has enough buffer space to store
                 the message when the node buffer is close to
                 congestion. In this paper, we propose a buffer
                 management strategy by integrating the characteristics
                 of messages and nodes, and migrate the redundant
                 messages to the neighbor to optimize the total utility,
                 instead of deleting them. The simulation experiment
                 results show that it can obviously improve the delivery
                 ratio, the overhead ratio and the average delays, and
                 reduce the amount of hops compared with the traditional
                 ones.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2017:REI,
  author =       "Haipeng Li and Hidenori Nakazato and Syed Hassan
                 Ahmed",
  title =        "Request Expectation Index Based Cache Replacement
                 Algorithm for Streaming Content Delivery over {ICN}",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "83",
  day =          "14",
  month =        nov,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040083",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/83",
  abstract =     "Since the content delivery unit over
                 Information-Centric Networking (ICN) has shifted from
                 files to the segments of a file named chunks, solely
                 either file-level or chunk-level request probability is
                 insufficient for ICN cache management. In this paper, a
                 Request Expectation Index (RXI) based cache replacement
                 algorithm for streaming content delivery is proposed.
                 In this algorithm, RXI is introduced to serve as a
                 fine-grained and unified estimation criteria of
                 possible future request probability for cached chunks.
                 RXI is customized for streaming content delivery by
                 adopting both file-level and chunk-level request
                 probability and considering the dynamically varied
                 request status at each route as well. Compared to prior
                 work, the proposed algorithm evicts the chunk with the
                 minimum expectation of future request to maintain a
                 high cache utilization. Additionally, simulation
                 results demonstrate that the RXI-based algorithm can
                 remarkably enhance the streaming content delivery
                 performance and can be deployed in complex network
                 scenarios. The proposed results validate that, by
                 taking fine-grained request probability and request
                 status into consideration, the customized in-network
                 caching algorithm can improve the ICN streaming content
                 delivery performance by high cache utilization, fast
                 content delivery, and lower network traffic.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Jiang:2017:EER,
  author =       "Fan Jiang and Honglin Wang and Hao Ren and Shuai Xu",
  title =        "Energy-Efficient Resource and Power Allocation for
                 Underlay Multicast Device-to-Device Transmission",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "84",
  day =          "14",
  month =        nov,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040084",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/84",
  abstract =     "In this paper, we present an energy-efficient resource
                 allocation and power control scheme for D2D
                 (Device-to-Device) multicasting transmission. The
                 objective is to maximize the overall energy-efficiency
                 of D2D multicast clusters through effective resource
                 allocation and power control schemes, while considering
                 the quality of service (QoS) requirements of both
                 cellular users (CUs) and D2D clusters. We first build
                 the optimization model and a heuristic resource and
                 power allocation algorithm is then proposed to solve
                 the energy-efficiency problem with less computational
                 complexity. Numerical results indicate that the
                 proposed algorithm outperforms existing schemes in
                 terms of throughput per energy consumption.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Recent Advances in Cellular D2D
                 Communications.",
}

@Article{Hong:2017:BEF,
  author =       "Zhen Hong and Zehua Wang and Wei Cai and Victor C. M.
                 Leung",
  title =        "Blockchain-Empowered Fair Computational Resource
                 Sharing System in the {D2D} Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "85",
  day =          "17",
  month =        nov,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040085",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/85",
  abstract =     "Device-to-device (D2D) communication is becoming an
                 increasingly important technology in future networks
                 with the climbing demand for local services. For
                 instance, resource sharing in the D2D network features
                 ubiquitous availability, flexibility, low latency and
                 low cost. However, these features also bring along
                 challenges when building a satisfactory resource
                 sharing system in the D2D network. Specifically, user
                 mobility is one of the top concerns for designing a
                 cooperative D2D computational resource sharing system
                 since mutual communication may not be stably available
                 due to user mobility. A previous endeavour has
                 demonstrated and proven how connectivity can be
                 incorporated into cooperative task scheduling among
                 users in the D2D network to effectively lower average
                 task execution time. There are doubts about whether
                 this type of task scheduling scheme, though effective,
                 presents fairness among users. In other words, it can
                 be unfair for users who contribute many computational
                 resources while receiving little when in need. In this
                 paper, we propose a novel blockchain-based credit
                 system that can be incorporated into the
                 connectivity-aware task scheduling scheme to enforce
                 fairness among users in the D2D network. Users'
                 computational task cooperation will be recorded on the
                 public blockchain ledger in the system as transactions,
                 and each user's credit balance can be easily accessible
                 from the ledger. A supernode at the base station is
                 responsible for scheduling cooperative computational
                 tasks based on user mobility and user credit balance.
                 We investigated the performance of the credit system,
                 and simulation results showed that with a minor
                 sacrifice of average task execution time, the level of
                 fairness can obtain a major enhancement.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Recent Advances in Cellular D2D
                 Communications.",
}

@Article{Wang:2017:SME,
  author =       "Jinpeng Wang and G{\'e}rard Chalhoub",
  title =        "Study of Mobility Enhancements for {RPL} in
                 Convergecast Scenarios",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "86",
  day =          "17",
  month =        nov,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040086",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/86",
  abstract =     "In recent years, mobility support has become an
                 important requirement in various wireless sensor
                 network (WSN) applications. However, due to the strict
                 resource constraints of power, memory, and processing
                 resources in WSNs, routing protocols are mainly
                 designed without considering mobility. Low-Power and
                 Lossy Networks (LLNs) are a special type of WSNs that
                 tolerate data loss. The Routing Protocol for Low-Power
                 and Lossy Networks (RPL) is a routing protocol for LLNs
                 that adapts IPv6 (Internet Protocol version 6) and runs
                 on top of the IEEE (Institute of Electrical and
                 Electronics Engineers) 802.15.4 standard. RPL supports
                 multipoint-to-point traffic and point-to-multipoint
                 traffic. In this paper we propose a mobility
                 enhancement mechanism in order to improve data
                 collection applications in highly mobile scenarios. The
                 enhancement is based on signal strength monitoring and
                 depth updating in order to improve the routing protocol
                 performance in mobile scenarios. This enhancement helps
                 routing protocols to cope better with topology changes
                 and makes proactive decisions on updating next-hop
                 neighbours. We integrated this mechanism into the RPL
                 and compared it with other existing RPL mobility
                 support enhancements. Results obtained through
                 simulation using Cooja show that our work outperforms
                 other existing RPL mobility supports on different
                 performance metrics. Results also prove the efficiency
                 of our proposal in highly mobile scenarios.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yan:2017:HPE,
  author =       "Chengxin Yan and Ningjiang Chen and Zhang Shuo",
  title =        "High-Performance Elastic Management for Cloud
                 Containers Based on Predictive Message Scheduling",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "87",
  day =          "28",
  month =        nov,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040087",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/87",
  abstract =     "Containerized data centers can improve the
                 computational density of IaaS layers. This intensive
                 high-concurrency environment has high requirements for
                 message scheduling and container processing. In the
                 paper, an elastically scalable strategy for cloud
                 containers based on predictive message scheduling is
                 introduced, in order to reduce the delay of messages
                 and improve the response time of services and the
                 utilization of container resources. According to the
                 busy degree of different containers, a management
                 strategy of multiple containers at message-granularity
                 level is developed, which gives the containers better
                 elasticity. The simulation results show that the
                 proposed strategy improves service processing
                 efficiency and reduces response latency compared with
                 existing solutions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mamais:2017:BVP,
  author =       "Stylianos S. Mamais and George Theodorakopoulos",
  title =        "Behavioural Verification: Preventing Report Fraud in
                 Decentralized Advert Distribution Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "88",
  day =          "20",
  month =        nov,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040088",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/88",
  abstract =     "Service commissions, which are claimed by Ad-Networks
                 and Publishers, are susceptible to forgery as non-human
                 operators are able to artificially create fictitious
                 traffic on digital platforms for the purpose of
                 committing financial fraud. This places a significant
                 strain on Advertisers who have no effective means of
                 differentiating fabricated Ad-Reports from those which
                 correspond to real consumer activity. To address this
                 problem, we contribute an advert reporting system which
                 utilizes opportunistic networking and a
                 blockchain-inspired construction in order to identify
                 authentic Ad-Reports by determining whether they were
                 composed by honest or dishonest users. What constitutes
                 a user's honesty for our system is the manner in which
                 they access adverts on their mobile device. Dishonest
                 users submit multiple reports over a short period of
                 time while honest users behave as consumers who view
                 adverts at a balanced pace while engaging in typical
                 social activities such as purchasing goods online,
                 moving through space and interacting with other users.
                 We argue that it is hard for dishonest users to fake
                 honest behaviour and we exploit the behavioural
                 patterns of users in order to classify Ad-Reports as
                 real or fabricated. By determining the honesty of the
                 user who submitted a particular report, our system
                 offers a more secure reward-claiming model which
                 protects against fraud while still preserving the
                 user's anonymity.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Privacy in Wireless and
                 Mobile Networks.",
}

@Article{Nardini:2017:FRB,
  author =       "Giovanni Nardini and Giovanni Stea and Antonio
                 Virdis",
  title =        "A Fast and Reliable Broadcast Service for
                 {LTE}-Advanced Exploiting Multihop Device-to-Device
                 Transmissions",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "89",
  day =          "25",
  month =        nov,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040089",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/89",
  abstract =     "Several applications, from the Internet of Things for
                 smart cities to those for vehicular networks, need fast
                 and reliable proximity-based broadcast communications,
                 i.e., the ability to reach all peers in a geographical
                 neighborhood around the originator of a message, as
                 well as ubiquitous connectivity. In this paper, we
                 point out the inherent limitations of the LTE
                 (Long-Term Evolution) cellular network, which make it
                 difficult, if possible at all, to engineer such a
                 service using traditional infrastructure-based
                 communications. We argue, instead, that
                 network-controlled device-to-device (D2D)
                 communications, relayed in a multihop fashion, can
                 efficiently support this service. To substantiate the
                 above claim, we design a proximity-based broadcast
                 service which exploits multihop D2D. We discuss the
                 relevant issues both at the UE (User Equipment), which
                 has to run applications, and within the network (i.e.,
                 at the eNodeBs), where suitable resource allocation
                 schemes have to be enforced. We evaluate the
                 performance of a multihop D2D broadcasting using
                 system-level simulations, and demonstrate that it is
                 fast, reliable and economical from a resource
                 consumption standpoint.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Recent Advances in Cellular D2D
                 Communications.",
}

@Article{Sadik:2017:OBA,
  author =       "Ahmed R. Sadik and Bodo Urban",
  title =        "An Ontology-Based Approach to Enable Knowledge
                 Representation and Reasoning in Worker-Cobot Agile
                 Manufacturing",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "90",
  day =          "24",
  month =        nov,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040090",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/90",
  abstract =     "There is no doubt that the rapid development in
                 robotics technology has dramatically changed the
                 interaction model between the Industrial Robot (IR) and
                 the worker. As the current robotic technology has
                 afforded very reliable means to guarantee the physical
                 safety of the worker during a close proximity
                 interaction with the IR. Therefore, new forms of
                 cooperation between the robot and the worker can now be
                 achieved. Collaborative/Cooperative robotics is the new
                 branch of industrial robotics which empowers the idea
                 of cooperative manufacturing. Cooperative manufacturing
                 significantly depends on the existence of a
                 collaborative/cooperative robot (cobot). A cobot is
                 usually a Light-Weight Robot (LWR) which is capable of
                 operating safely with the human co-worker in a shared
                 work environment. This is in contrast with the
                 conventional IR which can only operate in isolation
                 from the worker workspace, due to the fact that the
                 conventional IR can manipulate very heavy objects,
                 which makes it so dangerous to operate in direct
                 contact with the worker. There is a slight difference
                 between the definition of collaboration and cooperation
                 in robotics. In cooperative robotics, both the worker
                 and the robot are performing tasks over the same
                 product in the same shared workspace but not
                 simultaneously. Collaborative robotics has a similar
                 definition, except that the worker and the robot are
                 performing a simultaneous task. Gathering the worker
                 and the cobot in the same manufacturing workcell can
                 provide an easy and cheap method to flexibly customize
                 the production. Moreover, to adapt with the production
                 demands in the real time of production, without the
                 need to stop or to modify the production operations.
                 There are many challenges and problems that can be
                 addressed in the cooperative manufacturing field.
                 However, one of the most important challenges in this
                 field is the representation of the cooperative
                 manufacturing environment and components. Thus, in
                 order to accomplish the cooperative manufacturing
                 concept, a proper approach is required to describe the
                 shared environment between the worker and the cobot.
                 The cooperative manufacturing shared environment
                 includes the cobot, the co-worker, and other production
                 components such as the product itself. Furthermore, the
                 whole cooperative manufacturing system components need
                 to communicate and share their knowledge, to reason and
                 process the shared information, which eventually gives
                 the control solution the capability of obtaining
                 collective manufacturing decisions. Putting into
                 consideration that the control solution should also
                 provide a natural language which is human readable and
                 in the same time can be understood by the machine
                 (i.e., the cobot). Accordingly, a distributed control
                 solution which combines an ontology-based Multi-Agent
                 System (MAS) and a Business Rule Management System
                 (BRMS) is proposed, in order to solve the mentioned
                 challenges in the cooperative manufacturing, which are:
                 manufacturing knowledge representation, sharing, and
                 reasoning.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kuang:2017:HTA,
  author =       "Zhufang Kuang and Gongqiang Li and Junshan Tan and
                 Zhigang Chen",
  title =        "High Throughput and Acceptance Ratio Multipath Routing
                 Algorithm in Cognitive Wireless Mesh Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "91",
  day =          "25",
  month =        nov,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040091",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/91",
  abstract =     "The link failure due to the secondary users exiting
                 the licensed channels when primary users reoccupy the
                 licensed channels is very important in cognitive
                 wireless mesh networks (CWMNs). A multipath routing and
                 spectrum allocation algorithm based on channel
                 interference and reusability with Quality of Service
                 (QoS) constraints in CWMNs (MRIR) was proposed.
                 Maximizing the throughput and the acceptance ratio of
                 the wireless service is the objective of the MRIR.
                 First, a primary path of resource conservation with QoS
                 constraints was constructed, then, a resource
                 conservation backup path based on channel interference
                 and reusability with QoS constraints was constructed.
                 The MRIR algorithm contains the primary path routing
                 and spectrum allocation algorithm, and the backup path
                 routing and spectrum allocation algorithm. The
                 simulation results showed that the MRIR algorithm could
                 achieve the expected goals and could achieve a higher
                 throughput and acceptance ratio.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chiti:2017:SAR,
  author =       "Francesco Chiti and Romano Fantacci and Laura
                 Pierucci",
  title =        "Social-Aware Relay Selection for Cooperative Multicast
                 Device-to-Device Communications",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "92",
  day =          "04",
  month =        dec,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040092",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/92",
  abstract =     "The increasing use of social networks such as
                 Facebook, Twitter, and Instagram to share photos, video
                 streaming, and music among friends has generated a huge
                 increase in the amount of data traffic over wireless
                 networks. This social behavior has triggered new
                 communication paradigms such as device-to-device (D2D)
                 and relaying communication schemes, which are both
                 considered as strong drivers for the next
                 fifth-generation (5G) cellular systems. Recently, the
                 social-aware layer and its relationship to and
                 influence on the physical communications layer have
                 gained great attention as emerging focus points. We
                 focus here on the case of relaying communications to
                 pursue the multicast data dissemination to a group of
                 users forming a social community through a relay node,
                 according to the extension of the D2D mode to the case
                 of device-to-many devices. Moreover, in our case, the
                 source selects the device to act as the relay among
                 different users of the multicast group by taking into
                 account both the propagation link conditions and the
                 relay social-trust level with the constraint of
                 minimizing the end-to-end content delivery delay. An
                 optimization procedure is also proposed in order to
                 achieve the best performance. Finally, numerical
                 results are provided to highlight the advantages of
                 considering the impact of social level on the
                 end-to-end delivery delay in the integrated
                 social-physical network in comparison with the
                 classical relay-assisted multicast communications for
                 which the relay social-trust level is not considered.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Recent Advances in Cellular D2D
                 Communications.",
}

@Article{Latif:2017:HWC,
  author =       "Siddique Latif and Junaid Qadir and Shahzad Farooq and
                 Muhammad Ali Imran",
  title =        "How {5G} Wireless (and Concomitant Technologies) Will
                 Revolutionize Healthcare?",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "93",
  day =          "11",
  month =        dec,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040093",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/93",
  abstract =     "The need to have equitable access to quality
                 healthcare is enshrined in the United Nations (UN)
                 Sustainable Development Goals (SDGs), which defines the
                 developmental agenda of the UN for the next 15 years.
                 In particular, the third SDG focuses on the need to
                 ``ensure healthy lives and promote well-being for all
                 at all ages''. In this paper, we build the case that 5G
                 wireless technology, along with concomitant emerging
                 technologies (such as IoT, big data, artificial
                 intelligence and machine learning), will transform
                 global healthcare systems in the near future. Our
                 optimism around 5G-enabled healthcare stems from a
                 confluence of significant technical pushes that are
                 already at play: apart from the availability of
                 high-throughput low-latency wireless connectivity,
                 other significant factors include the democratization
                 of computing through cloud computing; the
                 democratization of Artificial Intelligence (AI) and
                 cognitive computing (e.g., IBM Watson); and the
                 commoditization of data through crowdsourcing and
                 digital exhaust. These technologies together can
                 finally crack a dysfunctional healthcare system that
                 has largely been impervious to technological
                 innovations. We highlight the persistent deficiencies
                 of the current healthcare system and then demonstrate
                 how the 5G-enabled healthcare revolution can fix these
                 deficiencies. We also highlight open technical research
                 challenges, and potential pitfalls, that may hinder the
                 development of such a 5G-enabled health revolution.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Communications and Computing for
                 Sustainable Development Goals.",
}

@Article{Qadir:2017:ANU,
  author =       "Junaid Qadir and Arjuna Sathiaseelan and Umar Bin
                 Farooq and Muhammad Usama and Muhammad Ali Imran and
                 Muhammad Shafique",
  title =        "Approximate Networking for Universal {Internet}
                 Access",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "94",
  day =          "11",
  month =        dec,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040094",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/94",
  abstract =     "Despite the best efforts of networking researchers and
                 practitioners, an ideal Internet experience is
                 inaccessible to an overwhelming majority of people the
                 world over, mainly due to the lack of cost-efficient
                 ways of provisioning high-performance, global Internet.
                 In this paper, we argue that instead of an exclusive
                 focus on a utopian goal of universally accessible
                 ``ideal networking'' (in which we have a high
                 throughput and quality of service as well as low
                 latency and congestion), we should consider providing
                 ``approximate networking'' through the adoption of
                 context-appropriate trade-offs. In this regard, we
                 propose to leverage the advances in the emerging trend
                 of ``approximate computing'' that rely on relaxing the
                 bounds of precise/exact computing to provide new
                 opportunities for improving the area, power, and
                 performance efficiency of systems by orders of
                 magnitude by embracing output errors in resilient
                 applications. Furthermore, we propose to extend the
                 dimensions of approximate computing towards various
                 knobs available at network layers. Approximate
                 networking can be used to provision ``Global Access to
                 the Internet for All'' (GAIA) in a pragmatically tiered
                 fashion, in which different users around the world are
                 provided a different context-appropriate (but still
                 contextually functional) Internet experience.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Communications and Computing for
                 Sustainable Development Goals.",
}

@Article{Mahlous:2017:SES,
  author =       "Ahmed Redha Mahlous",
  title =        "{SCMC}: An Efficient Scheme for Minimizing Energy in
                 {WSNs} Using a Set Cover Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "9",
  number =       "4",
  pages =        "95",
  day =          "13",
  month =        dec,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi9040095",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/9/4/95",
  abstract =     "Energy-efficient clustering and routing are well known
                 optimization problems in the study of Wireless Sensor
                 Network (WSN) lifetime extension. In this paper, we
                 propose an intelligent hybrid optimization algorithm
                 based on a Set Cover approach to create clusters, and
                 min-cost max-flow for routing (SCMC) to increase the
                 lifetime of WSNs. In our method we used linear
                 programming (LP) to model the WSN optimization problem.
                 This model considers minimizing the energy for all
                 nodes in each set cover (cluster), and then minimizing
                 the routing energy between the nodes and the base
                 station through intermediate nodes, namely cluster
                 heads. To evaluate the performance of our scheme,
                 extensive simulations were conducted with different
                 scenarios. The results show that the set cover approach
                 combined with the min-cost max-flow algorithm reduces
                 energy consumption and increases the network's lifetime
                 and throughput.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Shehni:2018:NLW,
  author =       "Rezvan Almas Shehni and Karim Faez and Farshad Eshghi
                 and Manoochehr Kelarestaghi",
  title =        "A New Lightweight Watchdog-Based Algorithm for
                 Detecting {Sybil} Nodes in Mobile {WSNs}",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "1",
  pages =        "1",
  day =          "21",
  month =        dec,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10010001",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/1/1",
  abstract =     "Wide-spread deployment of Wireless Sensor Networks
                 (WSN) necessitates special attention to security
                 issues, amongst which Sybil attacks are the most
                 important ones. As a core to Sybil attacks, malicious
                 nodes try to disrupt network operations by creating
                 several fabricated IDs. Due to energy consumption
                 concerns in WSNs, devising detection algorithms which
                 release the sensor nodes from high computational and
                 communicational loads are of great importance. In this
                 paper, a new computationally lightweight watchdog-based
                 algorithm is proposed for detecting Sybil IDs in mobile
                 WSNs. The proposed algorithm employs watchdog nodes for
                 collecting detection information and a designated
                 watchdog node for detection information processing and
                 the final Sybil list generation. Benefiting from a
                 newly devised co-presence state diagram and adequate
                 detection rules, the new algorithm features low extra
                 communication overhead, as well as a satisfactory
                 compromise between two otherwise contradictory
                 detection measures of performance, True Detection Rate
                 (TDR) and False Detection Rate (FDR). Extensive
                 simulation results illustrate the merits of the new
                 algorithm compared to a couple of recent watchdog-based
                 Sybil detection algorithms.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Privacy in Wireless and
                 Mobile Networks.",
}

@Article{Zhou:2018:AOR,
  author =       "Zhibin Zhou and Pin Liu and Qin Liu and Guojun Wang",
  title =        "An Anonymous Offline {RFID} Grouping-Proof Protocol",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "1",
  pages =        "2",
  day =          "01",
  month =        jan,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10010002",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/1/2",
  abstract =     "As more and more items are tagged with RFID (Radio
                 Frequency Identification) tags, grouping-proof
                 technology is widely utilized to provide a coexistence
                 evidence for a group of related items. Due to the
                 wireless channel used in RFID systems, a security risk
                 exists in the communication between the reader and
                 tags. How to ensure the tag's information security and
                 to generate reliable grouping-proof becomes a hot
                 research topic. To protect the privacy of tags, the
                 verification of grouping-proof is traditionally
                 executed by the verifier, and the reader is only used
                 to collect the proof data. This approach can cause the
                 reader to submit invalid proof data to the verifier in
                 the event of DoP (Deny of Proof) attack. In this paper,
                 an ECC-based, off-line anonymous grouping-proof
                 protocol (EAGP) is proposed. The protocol authorizes
                 the reader to examine the validity of grouping-proof
                 without knowing the identities of tags. From the
                 security and performance analysis, the EAGP can protect
                 the security and privacy of RFID tags, and defence
                 impersonation and replay attacks. Furthermore, it has
                 the ability to reduce the system overhead caused by the
                 invalid submission of grouping-proofs. As a result, the
                 proposed EAGP equips practical application values.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Privacy in Wireless and
                 Mobile Networks.",
}

@Article{Hoyhtya:2018:RLA,
  author =       "Marko H{\"o}yhty{\"a} and Olli Apilo and Mika
                 Lasanen",
  title =        "Review of Latest Advances in {3GPP} Standardization:
                 {D2D} Communication in {5G} Systems and Its Energy
                 Consumption Models",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "1",
  pages =        "3",
  day =          "03",
  month =        jan,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10010003",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/1/3",
  abstract =     "Device-to-device (D2D) communication is an essential
                 part of the future fifth generation (5G) system that
                 can be seen as a ``network of networks,'' consisting of
                 multiple seamlessly-integrated radio access
                 technologies (RATs). Public safety communications,
                 autonomous driving, socially-aware networking, and
                 infotainment services are example use cases of D2D
                 technology. High data rate communications and use of
                 several active air interfaces in the described network
                 create energy consumption challenges for both base
                 stations and the end user devices. In this paper, we
                 review the status of 3rd Generation Partnership Project
                 (3GPP) standardization, which is the most important
                 standardization body for 5G systems. We define a set of
                 application scenarios for D2D communications in 5G
                 networks. We use the recent models of 3GPP long term
                 evolution (LTE) and WiFi interfaces in analyzing the
                 power consumption from both the infrastructure and user
                 device perspectives. The results indicate that with the
                 latest radio interfaces, the best option for energy
                 saving is the minimization of active interfaces and
                 sending the data with the best possible data rate.
                 Multiple recommendations on how to exploit the results
                 in future networks are given.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Recent Advances in Cellular D2D
                 Communications.",
}

@Article{Pecori:2018:VLA,
  author =       "Riccardo Pecori",
  title =        "A Virtual Learning Architecture Enhanced by Fog
                 Computing and Big Data Streams",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "1",
  pages =        "4",
  day =          "03",
  month =        jan,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10010004",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/1/4",
  abstract =     "In recent years, virtual learning environments are
                 gaining more and more momentum, considering both the
                 technologies deployed in their support and the sheer
                 number of terminals directly or indirectly interacting
                 with them. This essentially means that every day, more
                 and more smart devices play an active role in this
                 exemplary Web of Things scenario. This digital
                 revolution, affecting education, appears clearly
                 intertwined with the earliest forecasts of the Internet
                 of Things, envisioning around 50 billions heterogeneous
                 devices and gadgets to be active by 2020, considering
                 also the deployment of the fog computing paradigm,
                 which moves part of the computational power to the edge
                 of the network. Moreover, these interconnected objects
                 are expected to produce more and more significant
                 streams of data, themselves generated at unprecedented
                 rates, sometimes to be analyzed almost in real time.
                 Concerning educational environments, this translates to
                 a new type of big data stream, which can be labeled as
                 educational big data streams. Here, pieces of
                 information coming from different sources (such as
                 communications between students and instructors, as
                 well as students' tests, etc.) require accurate
                 analysis and mining techniques in order to retrieve
                 fruitful and well-timed insights from them. This
                 article presents an overview of the current state of
                 the art of virtual learning environments and their
                 limitations; then, it explains the main ideas behind
                 the paradigms of big data streams and of fog computing,
                 in order to introduce an e-learning architecture
                 integrating both of them. Such an action aims to
                 enhance the ability of virtual learning environments to
                 be closer to the needs of all the actors in an
                 educational scenario, as demonstrated by a preliminary
                 implementation of the envisioned architecture. We
                 believe that the proposed big stream and fog-based
                 educational framework may pave the way towards a better
                 understanding of students' educational behaviors and
                 foster new research directions in the field.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Big Data and Internet of Thing.",
}

@Article{Anwar:2018:ESS,
  author =       "Nazia Anwar and Huifang Deng",
  title =        "Elastic Scheduling of Scientific Workflows under
                 Deadline Constraints in Cloud Computing Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "1",
  pages =        "5",
  day =          "07",
  month =        jan,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10010005",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/1/5",
  abstract =     "Scientific workflow applications are collections of
                 several structured activities and fine-grained
                 computational tasks. Scientific workflow scheduling in
                 cloud computing is a challenging research topic due to
                 its distinctive features. In cloud environments, it has
                 become critical to perform efficient task scheduling
                 resulting in reduced scheduling overhead, minimized
                 cost and maximized resource utilization while still
                 meeting the user-specified overall deadline. This paper
                 proposes a strategy, Dynamic Scheduling of Bag of Tasks
                 based workflows (DSB), for scheduling scientific
                 workflows with the aim to minimize financial cost of
                 leasing Virtual Machines (VMs) under a user-defined
                 deadline constraint. The proposed model groups the
                 workflow into Bag of Tasks (BoTs) based on data
                 dependency and priority constraints and thereafter
                 optimizes the allocation and scheduling of BoTs on
                 elastic, heterogeneous and dynamically provisioned
                 cloud resources called VMs in order to attain the
                 proposed method's objectives. The proposed approach
                 considers pay-as-you-go Infrastructure as a Service
                 (IaaS) clouds having inherent features such as
                 elasticity, abundance, heterogeneity and VM
                 provisioning delays. A trace-based simulation using
                 benchmark scientific workflows representing real world
                 applications, demonstrates a significant reduction in
                 workflow computation cost while the workflow deadline
                 is met. The results validate that the proposed model
                 produces better success rates to meet deadlines and
                 cost efficiencies in comparison to adapted
                 state-of-the-art algorithms for similar problems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2018:IIS,
  author =       "Wenjuan Li and Weizhi Meng and Lam For Kwok",
  title =        "Investigating the Influence of Special On-Off Attacks
                 on Challenge-Based Collaborative Intrusion Detection
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "1",
  pages =        "6",
  day =          "08",
  month =        jan,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10010006",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/1/6",
  abstract =     "Intrusions are becoming more complicated with the
                 recent development of adversarial techniques. To boost
                 the detection accuracy of a separate intrusion
                 detector, the collaborative intrusion detection network
                 (CIDN) has thus been developed by allowing intrusion
                 detection system (IDS) nodes to exchange data with each
                 other. Insider attacks are a great threat for such
                 types of collaborative networks, where an attacker has
                 the authorized access within the network. In
                 literature, a challenge-based trust mechanism is
                 effective at identifying malicious nodes by sending
                 challenges. However, such mechanisms are heavily
                 dependent on two assumptions, which would cause CIDNs
                 to be vulnerable to advanced insider attacks in
                 practice. In this work, we investigate the influence of
                 advanced on-off attacks on challenge-based CIDNs, which
                 can respond truthfully to one IDS node but behave
                 maliciously to another IDS node. To evaluate the attack
                 performance, we have conducted two experiments under a
                 simulated and a real CIDN environment. The obtained
                 results demonstrate that our designed attack is able to
                 compromise the robustness of challenge-based CIDNs in
                 practice; that is, some malicious nodes can behave
                 untruthfully without a timely detection.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Privacy in Wireless and
                 Mobile Networks.",
}

@Article{Office:2018:ARF,
  author =       "Future Internet Editorial Office",
  title =        "Acknowledgement to Reviewers of {{\booktitle{Future
                 Internet}}} in 2017",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "1",
  pages =        "7",
  day =          "12",
  month =        jan,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10010007",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/1/7",
  abstract =     "Remote areas with sparse population, disaster areas in
                 the aftermath, and refugee camps all require
                 communication that is not forthcoming from commercial
                 vendors. Numerous communication system options are
                 available, but with widely varying cost and efficacy.
                 The goal of this work is to discuss a framework in
                 which to consider appropriate telecommunications
                 technology. The framework approaches sustainable
                 development as a business, under the assumption that
                 social/technical/environmental sustainability requires
                 economic sustainability. The framework incorporates
                 well known and accepted business canvas as a roadmap.
                 Information and Communication Technology (ICT)
                 interventions are then considered in terms of their
                 value proposition, markets, and perhaps most important
                 for the realm of sustainable development, the key
                 partners. To illustrate how the framework applies, we
                 consider three case studies and then apply the
                 resultant principles to the consideration of these ICT
                 projects. The case studies are chosen for their
                 diversity. Furthermore, after verifying the decision
                 framework, recommendations are made for three ongoing
                 intervention projects in limited-resource settings.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Brown:2018:DFC,
  author =       "Suzana Brown and Alan Mickelson",
  title =        "A Decision Framework for Choosing Telecommunication
                 Technologies in Limited-Resource Settings",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "1",
  pages =        "8",
  day =          "12",
  month =        jan,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10010008",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/1/8",
  abstract =     "Remote areas with sparse population, disaster areas in
                 the aftermath, and refugee camps all require
                 communication that is not forthcoming from commercial
                 vendors. Numerous communication system options are
                 available, but with widely varying cost and efficacy.
                 The goal of this work is to discuss a framework in
                 which to consider appropriate telecommunications
                 technology. The framework approaches sustainable
                 development as a business, under the assumption that
                 social/technical/environmental sustainability requires
                 economic sustainability. The framework incorporates
                 well known and accepted business canvas as a roadmap.
                 Information and Communication Technology (ICT)
                 interventions are then considered in terms of their
                 value proposition, markets, and perhaps most important
                 for the realm of sustainable development, the key
                 partners. To illustrate how the framework applies, we
                 consider three case studies and then apply the
                 resultant principles to the consideration of these ICT
                 projects. The case studies are chosen for their
                 diversity. Furthermore, after verifying the decision
                 framework, recommendations are made for three ongoing
                 intervention projects in limited-resource settings.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Inequality in the Digital Environment
                 2017.",
}

@Article{Mansour:2018:VAH,
  author =       "Asmae Ait Mansour and Nourddine Enneya and Mohamed
                 Ouadou",
  title =        "A Velocity-Aware Handover Trigger in Two-Tier
                 Heterogeneous Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "1",
  pages =        "9",
  day =          "15",
  month =        jan,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10010009",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/1/9",
  abstract =     "The unexpected change in user equipment (UE) velocity
                 is recognized as the primary explanation for poor
                 handover quality. In order to resolve this issue, while
                 limiting ping-pong (PP) events we carefully and
                 dynamically optimized handover parameters for each UE
                 unit according to its velocity and the coverage area of
                 the access point (AP). In order to recognize any
                 variations in velocity, we applied Allan variance
                 (AVAR) to the received signal strength (RSS) from the
                 serving AP. To assess our approach, it was essential to
                 configure a heterogeneous network context (LTE-WiFi)
                 and interconnect Media-Independent Handover (MIH) and
                 Proxy Mobile IPv6 (PMIPv6) for seamless handover.
                 Reproduction demonstrated that our approach does not
                 only result in a gain in relatively accurate velocity
                 but in addition reduces the number of PP and handover
                 failures (HOFs).",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Seet:2018:RAC,
  author =       "Boon-Chong Seet and Syed Faraz Hasan and Peter Han-Joo
                 Chong",
  title =        "Recent Advances on Cellular {D2D} Communications",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "1",
  pages =        "10",
  day =          "17",
  month =        jan,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10010010",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:58 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/1/10",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Recent Advances in Cellular D2D
                 Communications.",
}

@Article{Giuli:2018:AFI,
  author =       "Dino Giuli",
  title =        "Announcing the 2018 {{\booktitle{Future Internet}}}
                 Travel Award for {PhD} Students",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "2",
  pages =        "11",
  day =          "28",
  month =        jan,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10020011",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:59 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/2/11",
  abstract =     "In the field of cognitive radio spectrum sensing, the
                 adaptive silence period management mechanism (ASPM) has
                 improved the problem of the low time-resource
                 utilization rate of the traditional silence period
                 management mechanism (TSPM). However, in the case of
                 the low signal-to-noise ratio (SNR), the ASPM algorithm
                 will increase the probability of missed detection for
                 the primary user (PU). Focusing on this problem, this
                 paper proposes an improved adaptive silence period
                 management (IA-SPM) algorithm which can adaptively
                 adjust the sensing parameters of the current period in
                 combination with the feedback information from the data
                 communication with the sensing results of the previous
                 period. The feedback information in the channel is
                 achieved with frequency resources rather than time
                 resources in order to adapt to the parameter change in
                 the time-varying channel. The Monte Carlo simulation
                 results show that the detection probability of the
                 IA-SPM is 10-15\% higher than that of the ASPM under
                 low SNR conditions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhang:2018:IAS,
  author =       "Jingbo Zhang and Zhenyang Sun and Shufang Zhang",
  title =        "The Improved Adaptive Silence Period Algorithm over
                 Time-Variant Channels in the Cognitive Radio System",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "2",
  pages =        "12",
  day =          "29",
  month =        jan,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10020012",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:59 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/2/12",
  abstract =     "In the field of cognitive radio spectrum sensing, the
                 adaptive silence period management mechanism (ASPM) has
                 improved the problem of the low time-resource
                 utilization rate of the traditional silence period
                 management mechanism (TSPM). However, in the case of
                 the low signal-to-noise ratio (SNR), the ASPM algorithm
                 will increase the probability of missed detection for
                 the primary user (PU). Focusing on this problem, this
                 paper proposes an improved adaptive silence period
                 management (IA-SPM) algorithm which can adaptively
                 adjust the sensing parameters of the current period in
                 combination with the feedback information from the data
                 communication with the sensing results of the previous
                 period. The feedback information in the channel is
                 achieved with frequency resources rather than time
                 resources in order to adapt to the parameter change in
                 the time-varying channel. The Monte Carlo simulation
                 results show that the detection probability of the
                 IA-SPM is 10-15\% higher than that of the ASPM under
                 low SNR conditions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Loreti:2018:PAB,
  author =       "Pierpaolo Loreti and Lorenzo Bracciale and Alberto
                 Caponi",
  title =        "Push Attack: Binding Virtual and Real Identities Using
                 Mobile Push Notifications",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "2",
  pages =        "13",
  day =          "31",
  month =        jan,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10020013",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:59 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/2/13",
  abstract =     "Popular mobile apps use push notifications extensively
                 to offer an ``always connected'' experience to their
                 users. Social networking apps use them as a real-time
                 channel to notify users about new private messages or
                 new social interactions (e.g., friendship request,
                 tagging, etc.). Despite the cryptography used to
                 protect these communication channels, the strict
                 temporal binding between the actions that trigger the
                 notifications and the reception of the notification
                 messages in the mobile device may represent a privacy
                 issue. In this work, we present the push notification
                 attack designed to bind the physical owners of mobile
                 devices with their virtual identities, even if
                 pseudonyms are used. In an online attack, an active
                 attacker triggers a push notification and captures the
                 notification packets that transit in the network. In an
                 offline attack, a passive attacker correlates the
                 social network activity of a user with the received
                 push notification. The push notification attack
                 bypasses the standard ways of protecting user privacy
                 based on the network layer by operating at the
                 application level. It requires no additional software
                 on the victim's mobile device.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Privacy in Wireless and
                 Mobile Networks.",
}

@Article{Abbasi:2018:RVV,
  author =       "Irshad Ahmed Abbasi and Adnan Shahid Khan",
  title =        "A Review of Vehicle to Vehicle Communication Protocols
                 for {VANETs} in the Urban Environment",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "2",
  pages =        "14",
  day =          "31",
  month =        jan,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10020014",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:59 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/2/14",
  abstract =     "Vehicular Ad-hoc Networks (VANETs) have been gaining
                 significant attention from the research community due
                 to their increasing importance for building an
                 intelligent transportation system. The characteristics
                 of VANETs, such as high mobility, network partitioning,
                 intermittent connectivity and obstacles in city
                 environments, make routing a challenging task. Due to
                 these characteristics of VANETs, the performance of a
                 routing protocol is degraded. The position-based
                 routing is considered to be the most significant
                 approach in VANETs. In this paper, we present a brief
                 review of most significant position based unicast
                 routing protocols designed for vehicle to vehicle
                 communications in the urban environment. We provide
                 them with their working features for exchanging
                 information between vehicular nodes. We describe their
                 pros and cons. This study also provides a comparison of
                 the vehicle to vehicle communication based routing
                 protocols. The comparative study is based on some
                 significant factors such as mobility, traffic density,
                 forwarding techniques and method of junction selection
                 mechanism, and strategy used to handle a local optimum
                 situation. It also provides the simulation based study
                 of existing dynamic junction selection routing
                 protocols and a static junction selection routing
                 protocol. It provides a profound insight into the
                 routing techniques suggested in this area and the most
                 valuable solutions to advance VANETs. More importantly,
                 it can be used as a source of references to other
                 researchers in finding literature that is relevant to
                 routing in VANETs.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue New Perspectives in Intelligent
                 Transportation Systems and Mobile Communications
                 towards a Smart Cities Context.",
}

@Article{Pau:2018:SPC,
  author =       "Giovanni Pau and Tiziana Campisi and Antonino Canale
                 and Alessandro Severino and Mario Collotta and Giovanni
                 Tesoriere",
  title =        "Smart Pedestrian Crossing Management at Traffic Light
                 Junctions through a Fuzzy-Based Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "2",
  pages =        "15",
  day =          "01",
  month =        feb,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10020015",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:59 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/2/15",
  abstract =     "In the last few years, numerous research efforts have
                 been conducted to merge the Internet of Things (IoT)
                 with smart city environments. The goal to make a city
                 ``smart'' is arising as a possible solution to lessen
                 the issues caused by the urban population growth and
                 fast urbanization. Attention also has focused on the
                 pedestrian crossings because they are one of the most
                 dangerous places in the transport field. Information
                 and Communications Technologies (ICT) can undoubtedly
                 be an excellent support in developing infrastructures
                 that can best manage pedestrian crossing. For this
                 reason, this paper introduces a fuzzy logic-based
                 solution able to manage dynamically the traffic lights'
                 phases in signalized pedestrian crossings. The proposed
                 approach provides the possibility to change the phases
                 of the traffic light taking into account the time of
                 the day and the number of pedestrians about to cross
                 the road. The paper presents a thorough description of
                 the fuzzy logic controller configuration, an in-depth
                 analysis of the application scenario and simulative
                 assessments obtained through Vissim simulations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Pathan:2018:ETB,
  author =       "Muhammad Salman Pathan and Nafei Zhu and Jingsha He
                 and Zulfiqar Ali Zardari and Muhammad Qasim Memon and
                 Muhammad Iftikhar Hussain",
  title =        "An Efficient Trust-Based Scheme for Secure and Quality
                 of Service Routing in {MANETs}",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "2",
  pages =        "16",
  day =          "05",
  month =        feb,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10020016",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:59 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/2/16",
  abstract =     "Due to the dynamism of topology, sharing of bandwidth
                 and constraint of resources in wireless nodes, the
                 provision of quality of service (QoS) for routing in
                 mobile ad hoc networks (MANETs) presents a great
                 challenge. Security is another crucial aspect of
                 providing QoS since the existence of malicious nodes
                 present all kinds of threats to MANETs. Although a
                 number of mechanisms have been proposed for protecting
                 MANETs, most of the solutions are only effective for a
                 particular kind of attacks or provide security at the
                 cost of sacrificing QoS. In this paper, we propose a
                 trust-based secure QoS routing scheme by combining
                 social and QoS trust. The primary approach of the
                 proposed scheme relies on mitigating nodes that exhibit
                 various packet forwarding misbehavior and on
                 discovering the path that ensures reliable
                 communication through the trust mechanism. The scheme
                 would select the best forwarding node based on packet
                 forwarding behavior as well as capability in terms of
                 QoS parameters, such as residual energy, channel
                 quality, link quality, etc. We will present an
                 adversary model for packet dropping attack against
                 which we evaluate the proposed scheme. Simulation
                 experiment using Network Simulator-2 (NS2) and under
                 various network conditions show that mixing social and
                 QoS trust parameters can greatly improve security and
                 quality of service routing in terms of overhead, packet
                 delivery ratio and energy consumption.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rexha:2018:ITF,
  author =       "Blerim Rexha and Gresa Shala and Valon Xhafa",
  title =        "Increasing Trustworthiness of Face Authentication in
                 Mobile Devices by Modeling Gesture Behavior and
                 Location Using Neural Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "2",
  pages =        "17",
  day =          "05",
  month =        feb,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10020017",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:59 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/2/17",
  abstract =     "Personal mobile devices currently have access to a
                 significant portion of their user's private sensitive
                 data and are increasingly used for processing mobile
                 payments. Consequently, securing access to these mobile
                 devices is a requirement for securing access to the
                 sensitive data and potentially costly services. Face
                 authentication is one of the promising biometrics-based
                 user authentication mechanisms that has been widely
                 available in this era of mobile computing. With a
                 built-in camera capability on smartphones, tablets, and
                 laptops, face authentication provides an attractive
                 alternative of legacy passwords for its memory-less
                 authentication process, which is so sophisticated that
                 it can unlock the device faster than a fingerprint.
                 Nevertheless, face authentication in the context of
                 smartphones has proven to be vulnerable to attacks. In
                 most current implementations, a sufficiently
                 high-resolution face image displayed on another mobile
                 device will be enough to circumvent security measures
                 and bypass the authentication process. In order to
                 prevent such bypass attacks, gesture recognition
                 together with location is proposed to be additionally
                 modeled. Gestures provide a faster and more convenient
                 method of authentication compared to a complex
                 password. The focus of this paper is to build a secure
                 authentication system with face, location and gesture
                 recognition as components. User gestures and location
                 data are a sequence of time series; therefore, in this
                 paper we propose to use unsupervised learning in the
                 long short-term memory recurrent neural network to
                 actively learn to recognize, group and discriminate
                 user gestures and location. Moreover, a
                 clustering-based technique is also implemented for
                 recognizing gestures and location.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kambourakis:2018:SPW,
  author =       "Georgios Kambourakis and Felix Gomez Marmol and Guojun
                 Wang",
  title =        "Security and Privacy in Wireless and Mobile Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "2",
  pages =        "18",
  day =          "09",
  month =        feb,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10020018",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:59 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/2/18",
  abstract =     "The present work introduces virtual fairs,
                 particularly the perceived benefits, challenges, and
                 relevance of such fairs for recruitment and employer
                 branding. These aspects were explored in a
                 semi-structured interview with an organizer of virtual
                 fairs across Scandinavia, and a focus group composed of
                 Norwegian recruiters and exhibitors. The results of the
                 data collection can be summarized in the form of themes
                 that relate to web analytics, web services and
                 optimization. The benefits of virtual fairs pertain to
                 the (a) visibility and branding; (b) costs; and (c)
                 analytics-based customization. Challenges of virtual
                 career fairs pertain to the (a) lack of online
                 engagement, (b) preparation and staffing costs; (c)
                 lack of guidelines; (d) talent access and
                 identification; (e) security and infrastructure; (f)
                 long-term planning; (g) and inter-dependencies. The
                 discussion summarizes the implications of branding and
                 recruitment and the value they add to business, also
                 noting how context effects may come into play. The
                 article concludes by exploring the possibility that
                 virtual fairs will complement or become the new
                 standard in recruitment and outlines future avenues for
                 research and practice.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Privacy in Wireless and
                 Mobile Networks.",
}

@Article{Vik:2018:VCF,
  author =       "{\AA}dne Stenberg Vik and Bj{\o}rn Christian
                 N{\o}rbech and Debora Jeske",
  title =        "Virtual Career Fairs: Perspectives from {Norwegian}
                 Recruiters and Exhibitors",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "2",
  pages =        "19",
  day =          "12",
  month =        feb,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10020019",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:59 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/2/19",
  abstract =     "The present work introduces virtual fairs,
                 particularly the perceived benefits, challenges, and
                 relevance of such fairs for recruitment and employer
                 branding. These aspects were explored in a
                 semi-structured interview with an organizer of virtual
                 fairs across Scandinavia, and a focus group composed of
                 Norwegian recruiters and exhibitors. The results of the
                 data collection can be summarized in the form of themes
                 that relate to web analytics, web services and
                 optimization. The benefits of virtual fairs pertain to
                 the (a) visibility and branding; (b) costs; and (c)
                 analytics-based customization. Challenges of virtual
                 career fairs pertain to the (a) lack of online
                 engagement, (b) preparation and staffing costs; (c)
                 lack of guidelines; (d) talent access and
                 identification; (e) security and infrastructure; (f)
                 long-term planning; (g) and inter-dependencies. The
                 discussion summarizes the implications of branding and
                 recruitment and the value they add to business, also
                 noting how context effects may come into play. The
                 article concludes by exploring the possibility that
                 virtual fairs will complement or become the new
                 standard in recruitment and outlines future avenues for
                 research and practice.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue u- and e- Service, Science and
                 Technology.",
}

@Article{Gatteschi:2018:BSC,
  author =       "Valentina Gatteschi and Fabrizio Lamberti and Claudio
                 Demartini and Chiara Pranteda and V{\'\i}ctor
                 Santamar{\'\i}a",
  title =        "Blockchain and Smart Contracts for Insurance: Is the
                 Technology Mature Enough?",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "2",
  pages =        "20",
  day =          "20",
  month =        feb,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10020020",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:59 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/2/20",
  abstract =     "Blockchain is receiving increasing attention from
                 academy and industry, since it is considered a
                 breakthrough technology that could bring huge benefits
                 to many different sectors. In 2017, Gartner positioned
                 blockchain close to the peak of inflated expectations,
                 acknowledging the enthusiasm for this technology that
                 is now largely discussed by media. In this scenario,
                 the risk to adopt it in the wake of enthusiasm, without
                 objectively judging its actual added value is rather
                 high. Insurance is one the sectors that, among others,
                 started to carefully investigate the possibilities of
                 blockchain. For this specific sector, however, the hype
                 cycle shows that the technology is still in the
                 innovation trigger phase, meaning that the spectrum of
                 possible applications has not been fully explored yet.
                 Insurers, as with many other companies not necessarily
                 active only in the financial sector, are currently
                 requested to make a hard decision, that is, whether to
                 adopt blockchain or not, and they will only know if
                 they were right in 3-5 years. The objective of this
                 paper is to support actors involved in this decision
                 process by illustrating what a blockchain is, analyzing
                 its advantages and disadvantages, as well as discussing
                 several use cases taken from the insurance sector,
                 which could easily be extended to other domains.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{DAmico:2018:RCK,
  author =       "Antonella D'Amico and Domenico Guastella",
  title =        "Robotics Construction Kits: From {``Objects} to Think
                 with'' to {``Objects} to Think and to Emote with''",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "2",
  pages =        "21",
  day =          "24",
  month =        feb,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10020021",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:59 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/2/21",
  abstract =     "This paper discusses new ideas about the use of
                 educational robotics in social-emotional learning. In
                 particular, educational robotics could be a tool
                 intended to allow children to acquire some of the basic
                 aspects of human emotions and emotional functioning,
                 and to understand how these relate to the mind and
                 body. More specifically, by using robots such as the
                 LEGO Mindstorm construction kits-which allow users to
                 both construct the body of the robot and to provide it
                 with a behavioural repertory-children have the
                 opportunity to visualize (and manipulate) the
                 relationship between the robot's body and mind. This
                 allows them to simulate ``embodied emotional minds''
                 and to reflect on new neuroscientific concepts
                 regarding body-mind and cognition-emotion
                 relationships.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Engaging in Interaction with Robots.",
}

@Article{Oliveira:2018:LMP,
  author =       "Ewerton L. S. Oliveira and Davide Orr{\`u} and Luca
                 Morreale and Tiago P. Nascimento and Andrea Bonarini",
  title =        "Learning and Mining Player Motion Profiles in
                 Physically Interactive Robogames",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "3",
  pages =        "22",
  day =          "26",
  month =        feb,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10030022",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:59 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/3/22",
  abstract =     "Physically-Interactive RoboGames (PIRG) are an
                 emerging application whose aim is to develop robotic
                 agents able to interact and engage humans in a game
                 situation. In this framework, learning a model of
                 players' activity is relevant both to understand their
                 engagement, as well as to understand specific
                 strategies they adopted, which in turn can foster game
                 adaptation. Following such directions and given the
                 lack of quantitative methods for player modeling in
                 PIRG, we propose a methodology for representing players
                 as a mixture of existing player's types uncovered from
                 data. This is done by dealing both with the intrinsic
                 uncertainty associated with the setting and with the
                 agent necessity to act in real time to support the game
                 interaction. Our methodology first focuses on encoding
                 time series data generated from player-robot
                 interaction into images, in particular Gramian angular
                 field images, to represent continuous data. To these,
                 we apply latent Dirichlet allocation to summarize the
                 player's motion style as a probabilistic mixture of
                 different styles discovered from data. This approach
                 has been tested in a dataset collected from a real,
                 physical robot game, where activity patterns are
                 extracted by using a custom three-axis accelerometer
                 sensor module. The obtained results suggest that the
                 proposed system is able to provide a robust description
                 for the player interaction.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Engaging in Interaction with Robots.",
}

@Article{Hameed:2018:SBC,
  author =       "Sufian Hameed and Hassan Ahmed Khan",
  title =        "{SDN} Based Collaborative Scheme for Mitigation of
                 {DDoS} Attacks",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "3",
  pages =        "23",
  day =          "27",
  month =        feb,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10030023",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:59 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/3/23",
  abstract =     "Software Defined Networking (SDN) has proved itself to
                 be a backbone in the new network design and is quickly
                 becoming an industry standard. The idea of separation
                 of control plane and data plane is the key concept
                 behind SDN. SDN not only allows us to program and
                 monitor our networks but it also helps in mitigating
                 some key network problems. Distributed denial of
                 service (DDoS) attack is among them. In this paper we
                 propose a collaborative DDoS attack mitigation scheme
                 using SDN. We design a secure controller-to-controller
                 (C-to-C) protocol that allows SDN-controllers lying in
                 different autonomous systems (AS) to securely
                 communicate and transfer attack information with each
                 other. This enables efficient notification along the
                 path of an ongoing attack and effective filtering of
                 traffic near the source of attack, thus saving valuable
                 time and network resources. We also introduced three
                 different deployment approaches i.e., linear, central
                 and mesh in our testbed. Based on the experimental
                 results we demonstrate that our SDN based collaborative
                 scheme is fast and reliable in efficiently mitigating
                 DDoS attacks in real time with very small computational
                 footprints.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Collection Information Systems Security.",
}

@Article{Pilloni:2018:HDW,
  author =       "Virginia Pilloni",
  title =        "How Data Will Transform Industrial Processes:
                 Crowdsensing, Crowdsourcing and Big Data as Pillars of
                 {Industry 4.0}",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "3",
  pages =        "24",
  day =          "01",
  month =        mar,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10030024",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:59 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/3/24",
  abstract =     "We are living in the era of the fourth industrial
                 revolution, namely Industry 4.0. This paper presents
                 the main aspects related to Industry 4.0, the
                 technologies that will enable this revolution, and the
                 main application domains that will be affected by it.
                 The effects that the introduction of Internet of Things
                 (IoT), Cyber-Physical Systems (CPS), crowdsensing,
                 crowdsourcing, cloud computing and big data will have
                 on industrial processes will be discussed. The main
                 objectives will be represented by improvements in:
                 production efficiency, quality and cost-effectiveness;
                 workplace health and safety, as well as quality of
                 working conditions; products' quality and availability,
                 according to mass customisation requirements. The paper
                 will further discuss the common denominator of these
                 enhancements, i.e., data collection and analysis. As
                 data and information will be crucial for Industry 4.0,
                 crowdsensing and crowdsourcing will introduce new
                 advantages and challenges, which will make most of the
                 industrial processes easier with respect to traditional
                 technologies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Big Data and Internet of Thing.",
}

@Article{Hassan:2018:IMF,
  author =       "Tehseen {Ul Hassan} and Fei Gao and Babur Jalal and
                 Sheeraz Arif",
  title =        "Interference Management in Femtocells by the Adaptive
                 Network Sensing Power Control Technique",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "3",
  pages =        "25",
  day =          "01",
  month =        mar,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10030025",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:59 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/3/25",
  abstract =     "The overlay integration of low-power femtocells over
                 macrocells in a heterogeneous network (HetNet) plays an
                 important role in dealing with the increasing demand of
                 spectral efficiency, coverage and higher data rates, at
                 a nominal cost to network operators. However, the
                 downlink (DL) transmission power of an inadequately
                 deployed femtocell causes inter-cell interference
                 (ICI), which leads to severe degradation and sometimes
                 link failure for nearby macrocell users. In this paper,
                 we propose an adaptive network sensing (ANS) technique
                 for downlink power control to obviate the ICI. The
                 simulation results have shown that the ANS power
                 control technique successfully decreases the cell-edge
                 macro user's interference and enhances the throughput
                 performance of macro users, while also optimizing the
                 coverage and capacity of the femtocell. When compared
                 with the Femto User Equipment (FUE)-assisted and Macro
                 User Equipment (MUE)-assisted power control technique,
                 the proposed technique offers a good tradeoff in
                 reducing interference to macro users, while maintaining
                 the quality of service (QoS) requirement of the
                 femtocell users.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Massive MIMO Communication and
                 Networking Systems.",
}

@Article{Ruan:2018:TDS,
  author =       "Yibin Ruan and Jiazhu Dai",
  title =        "{TwinNet}: a Double Sub-Network Framework for
                 Detecting Universal Adversarial Perturbations",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "3",
  pages =        "26",
  day =          "06",
  month =        mar,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10030026",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:59 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/3/26",
  abstract =     "Deep neural network has achieved great progress on
                 tasks involving complex abstract concepts. However,
                 there exist adversarial perturbations, which are
                 imperceptible to humans, which can tremendously
                 undermine the performance of deep neural network
                 classifiers. Moreover, universal adversarial
                 perturbations can even fool classifiers on almost all
                 examples with just a single perturbation vector. In
                 this paper, we propose TwinNet, a framework for neural
                 network classifiers to detect such adversarial
                 perturbations. TwinNet makes no modification of the
                 protected classifier. It detects adversarially
                 perturbated examples by enhancing different types of
                 features in dedicated networks and fusing the output of
                 the networks later. The paper empirically shows that
                 our framework can identify adversarial perturbations
                 effectively with a slight loss in accuracy when
                 predicting normal examples, which outperforms
                 state-of-the-art works.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Suomalainen:2018:SAS,
  author =       "Jani Suomalainen and Kimmo Ahola and Mikko Majanen and
                 Olli M{\"a}mmel{\"a} and Pekka Ruuska",
  title =        "Security Awareness in Software-Defined Multi-Domain
                 {5G} Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "3",
  pages =        "27",
  day =          "08",
  month =        mar,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10030027",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:59 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/3/27",
  abstract =     "Fifth generation (5G) technologies will boost the
                 capacity and ease the management of mobile networks.
                 Emerging virtualization and softwarization technologies
                 enable more flexible customization of network services
                 and facilitate cooperation between different actors.
                 However, solutions are needed to enable users,
                 operators, and service providers to gain an up-to-date
                 awareness of the security and trustworthiness of 5G
                 systems. We describe a novel framework and enablers for
                 security monitoring, inferencing, and trust measuring.
                 The framework leverages software-defined networking and
                 big data technologies to customize monitoring for
                 different applications. We present an approach for
                 sharing security measurements across administrative
                 domains. We describe scenarios where the correlation of
                 multi-domain information improves the accuracy of
                 security measures with respect to two threats: end-user
                 location tracking and Internet of things (IoT)
                 authentication storms. We explore the security
                 characteristics of data flows in software networks
                 dedicated to different applications with a mobile
                 network testbed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Giuli:2018:EEF,
  author =       "Dino Giuli",
  title =        "Ecosystemic Evolution {Fed} by Smart Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "3",
  pages =        "28",
  day =          "10",
  month =        mar,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10030028",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:59 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/3/28",
  abstract =     "In recent years, software developers have started to
                 appropriate GitHub repositories to curate resources, in
                 order to systematically select, evaluate, and organize
                 existing artifacts for preservation and future use.
                 Curation behaviors in social media sites, such as
                 users' experiences to curate tweets from Twitter and
                 pins on Pinterest, are well documented. However,
                 GitHub, as a social coding platform, presents a new
                 context for this activity, raising questions about the
                 nature of curation on this task-driven online work
                 site. To explore and understand curation on GitHub, we
                 compared and contrasted curation repositories with
                 software repositories using activity logs and analyzed
                 the content of popular curation repositories. Our
                 results show that: (1) curation repositories have
                 become a favorite category of repositories in GitHub;
                 (2) curation repositories leverage collaborative
                 features and practices native to GitHub in new ways;
                 (3) curation repositories collect and preserve
                 high-quality resources for the software developers'
                 community. Our results suggest that curation is
                 becoming increasingly important to the software
                 developers' community, and current practices can be
                 better supported with tools designed specifically for
                 curation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Ecosystemic Evolution Feeded by Smart
                 Systems.",
}

@Article{Wu:2018:UHG,
  author =       "Yu Wu and Jessica Kropczynski and Raquel Prates and
                 John M. Carroll",
  title =        "Understanding How {GitHub} Supports Curation
                 Repositories",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "3",
  pages =        "29",
  day =          "10",
  month =        mar,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10030029",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:59 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/3/29",
  abstract =     "In recent years, software developers have started to
                 appropriate GitHub repositories to curate resources, in
                 order to systematically select, evaluate, and organize
                 existing artifacts for preservation and future use.
                 Curation behaviors in social media sites, such as
                 users' experiences to curate tweets from Twitter and
                 pins on Pinterest, are well documented. However,
                 GitHub, as a social coding platform, presents a new
                 context for this activity, raising questions about the
                 nature of curation on this task-driven online work
                 site. To explore and understand curation on GitHub, we
                 compared and contrasted curation repositories with
                 software repositories using activity logs and analyzed
                 the content of popular curation repositories. Our
                 results show that: (1) curation repositories have
                 become a favorite category of repositories in GitHub;
                 (2) curation repositories leverage collaborative
                 features and practices native to GitHub in new ways;
                 (3) curation repositories collect and preserve
                 high-quality resources for the software developers'
                 community. Our results suggest that curation is
                 becoming increasingly important to the software
                 developers' community, and current practices can be
                 better supported with tools designed specifically for
                 curation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sun:2018:ODD,
  author =       "Bo Sun and Ming Wei and Senlai Zhu",
  title =        "Optimal Design of Demand-Responsive Feeder Transit
                 Services with Passengers' Multiple Time Windows and
                 Satisfaction",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "3",
  pages =        "30",
  day =          "12",
  month =        mar,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10030030",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:59 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/3/30",
  abstract =     "This paper presents a mixed-integer linear programming
                 model for demand-responsive feeder transit services to
                 assign vehicles located at different depots to pick up
                 passengers at the demand points and transport them to
                 the rail station. The proposed model features
                 passengers' one or several preferred time windows for
                 boarding vehicles at the demand point and their
                 expected ride time. Moreover, passenger satisfaction
                 that was related only to expected ride time is fully
                 accounted for in the model. The objective is to
                 simultaneously minimize the operation costs of total
                 mileage and maximize passenger satisfaction. As the
                 problem is an extension of the nondeterministic
                 polynomial problem with integration of the vehicle
                 route problem, this study further develops an improved
                 bat algorithm to yield meta-optimal solutions for the
                 model in a reasonable amount of time. When this was
                 applied to a case study in Nanjing City, China, the
                 mileage and satisfaction of the proposed model were
                 reduced by 1.4 km and increased by 7.1\%, respectively,
                 compared with the traditional model. Sensitivity
                 analyses were also performed to investigate the impact
                 of the number of designed bus routes and weights of
                 objective functions on the model performance. Finally,
                 a comparison of Cplex, standard bat algorithm, and
                 group search optimizer is analyzed to verify the
                 validity of the proposed algorithm.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue New Perspectives in Intelligent
                 Transportation Systems and Mobile Communications
                 towards a Smart Cities Context.",
}

@Article{Chang:2018:SAI,
  author =       "Chia-Lin Chang and Michael McAleer and Yu-Chieh Wu",
  title =        "A Statistical Analysis of Industrial Penetration and
                 {Internet} Intensity in {Taiwan}",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "3",
  pages =        "31",
  day =          "16",
  month =        mar,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10030031",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:50:59 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/3/31",
  abstract =     "This paper is the first to investigate the effect of
                 industrial penetration (geographic concentration of
                 industries) and internet intensity (the proportion of
                 enterprises that uses the internet) for Taiwan
                 manufacturing firms, and analyses whether the
                 relationships are substitutes or complements. The
                 sample observations are based on a unique set of data,
                 namely 153,081 manufacturing plants, and covers 26
                 two-digit industry categories and 358 geographical
                 townships in Taiwan. The Heckman sample selection model
                 is used to accommodate sample selectivity for
                 unobservable data for firms that use the internet. The
                 empirical results from Heckman's two-stage estimation
                 show that: (1) a higher degree of industrial
                 penetration will not affect the probability that firms
                 will use the internet, but it will affect the total
                 expenditure on internet intensity; (2) for two-digit
                 SIC (Standard Industrial Classification) industries,
                 industrial penetration generally decreases the total
                 expenditure on internet intensity; and, (3) industrial
                 penetration and internet intensity are substitutes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Takasuka:2018:DSD,
  author =       "Hidenori Takasuka and Koichi Hirai and Kazumasa
                 Takami",
  title =        "Development of a Social {DTN} for Message
                 Communication between {SNS} Group Members",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "4",
  pages =        "32",
  day =          "04",
  month =        apr,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10040032",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:00 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/4/32",
  abstract =     "Smartphones have the ability to communicate with other
                 terminals through ad hoc connections. A variety of
                 applications have been developed to exploit this
                 ability. The authors have developed an Android OS
                 (operating system) application (called ``social DTN
                 manager'') that builds a DTN (delay, disruption,
                 disconnection tolerant networking) among members of a
                 social networking service (SNS) community using a
                 community token. The members can exchange messages over
                 this network. Control messages for building a DTN are
                 forwarded to only those nodes that use the same
                 community token in order to reduce flooding of message
                 copies. When a source node sends a communication
                 request to its destination node, they exchange control
                 messages to establish a communication route. Relay
                 nodes use these messages to create and hold routing
                 information for these nodes in their routing tables.
                 Thereafter, relay nodes can forward data messages based
                 on their routing tables. This again reduces flooding of
                 message copies. The social DTN manager incorporates
                 these functions, Facebook Graph API and Google Nearby
                 Connections API. The authors have installed it in
                 Android terminals and confirmed that a social DTN can
                 successfully be built using this application and that
                 data messages can be exchanged between terminals via
                 reactive routes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Safitri:2018:ICP,
  author =       "Cutifa Safitri and Yoshihide Yamada and Sabariah
                 Baharun and Shidrokh Goudarzi and Quang Ngoc Nguyen and
                 Keping Yu and Takuro Sato",
  title =        "An Intelligent Content Prefix Classification Approach
                 for Quality of Service Optimization in
                 Information-Centric Networking",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "4",
  pages =        "33",
  day =          "09",
  month =        apr,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10040033",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:00 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/4/33",
  abstract =     "This research proposes an intelligent classification
                 framework for quality of service (QoS) performance
                 improvement in information-centric networking (ICN).
                 The proposal works towards keyword classification
                 techniques to obtain the most valuable information via
                 suitable content prefixes in ICN. In this study, we
                 have achieved the intelligent function using Artificial
                 Intelligence (AI) implementation. Particularly, to find
                 the most suitable and promising intelligent approach
                 for maintaining QoS matrices, we have evaluated various
                 AI algorithms, including evolutionary algorithms (EA),
                 swarm intelligence (SI), and machine learning (ML) by
                 using the cost function to assess their classification
                 performances. With the goal of enabling a complete ICN
                 prefix classification solution, we also propose a
                 hybrid implementation to optimize classification
                 performances by integration of relevant AI algorithms.
                 This hybrid mechanism searches for a final minimum
                 structure to prevent the local optima from happening.
                 By simulation, the evaluation results show that the
                 proposal outperforms EA and ML in terms of network
                 resource utilization and response delay for QoS
                 performance optimization.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2018:RSC,
  author =       "Rongheng Li and Jian Zhang and Wenfeng Shen",
  title =        "Replicas Strategy and Cache Optimization of Video
                 Surveillance Systems Based on Cloud Storage",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "4",
  pages =        "34",
  day =          "10",
  month =        apr,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10040034",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:00 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/4/34",
  abstract =     "With the rapid development of video surveillance
                 technology, especially the popularity of cloud-based
                 video surveillance applications, video data begins to
                 grow explosively. However, in the cloud-based video
                 surveillance system, replicas occupy an amount of
                 storage space. Also, the slow response to video
                 playback constrains the performance of the system. In
                 this paper, considering the characteristics of video
                 data comprehensively, we propose a dynamic redundant
                 replicas mechanism based on security levels that can
                 dynamically adjust the number of replicas. Based on the
                 location correlation between cameras, this paper also
                 proposes a data cache strategy to improve the response
                 speed of data reading. Experiments illustrate that: (1)
                 our dynamic redundant replicas mechanism can save
                 storage space while ensuring data security; (2) the
                 cache mechanism can predict the playback behaviors of
                 the users in advance and improve the response speed of
                 data reading according to the location and time
                 correlation of the front-end cameras; and (3) in terms
                 of cloud-based video surveillance, our proposed
                 approaches significantly outperform existing methods.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mansour:2018:EMG,
  author =       "Asmae Ait Mansour and Nourddine Enneya and Mohamed
                 Ouadou",
  title =        "Enhanced Matching Game for Decoupled Uplink Downlink
                 Context-Aware Handover",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "4",
  pages =        "35",
  day =          "15",
  month =        apr,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10040035",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:00 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/4/35",
  abstract =     "In this paper, we address the problem of cell
                 association during a handover performed in a dense
                 heterogeneous network, where the preference of a mobile
                 user's equipment in terms of uplink traffic is not the
                 same as for the downlink traffic. Therefore, since
                 mobility is an intrinsic element of cellular networks,
                 designing a handover from the perspective of the uplink
                 and downlink is mandatory in the context of 5G cellular
                 networks. Based on this arena, we propose a decoupled
                 uplink-downlink handover scheme while making use of
                 femtocells in order to maximize the overall network
                 entity utilities and avoid overloading macrocells.
                 However, the fact that the handover process is
                 performed in a dense heterogeneous network makes the
                 issue NP-hard. Therefore, taking into account the need
                 for self-organizing solutions, we modeled the handover
                 process as a matching game with externalities. Thus, we
                 will provide an aspect of intelligence for the
                 execution of the handover process to mobile user's
                 equipment (UE). To make the proposition more efficient,
                 we integrate an assignment step to assist the matching
                 game. Hence, the base stations will be investigated and
                 filtered, keeping only the helpful base stations as the
                 players in terms of the quality of service for the
                 uplink and downlink. The numerical results verify the
                 superiority of the proposed context-aware algorithm
                 over traditional downlink handover and traditional
                 decoupled uplink and downlink handover schemes, by
                 improving the load balancing, increasing rates and
                 reducing delays.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Roffia:2018:DLD,
  author =       "Luca Roffia and Paolo Azzoni and Cristiano Aguzzi and
                 Fabio Viola and Francesco Antoniazzi and Tullio Salmon
                 Cinotti",
  title =        "Dynamic Linked Data: a {SPARQL} Event Processing
                 Architecture",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "4",
  pages =        "36",
  day =          "20",
  month =        apr,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10040036",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:00 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/4/36",
  abstract =     "This paper presents a decentralized Web-based
                 architecture designed to support the development of
                 distributed, dynamic, context-aware and interoperable
                 services and applications. The architecture enables the
                 detection and notification of changes over the Web of
                 Data by means of a content-based publish-subscribe
                 mechanism where the W3C SPARQL 1.1 Update and Query
                 languages are fully supported and used respectively by
                 publishers and subscribers. The architecture is built
                 on top of the W3C SPARQL 1.1 Protocol and introduces
                 the SPARQL 1.1 Secure Event protocol and the SPARQL 1.1
                 Subscribe Language as a means for conveying and
                 expressing subscription requests and notifications. The
                 reference implementation of the architecture offers to
                 developers a design pattern for a modular, scalable and
                 effective application development.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Big Data and Augmented Intelligence.",
}

@Article{Lettieri:2018:EMA,
  author =       "Nicola Lettieri and Antonio Altamura and Rosalba
                 Giugno and Alfonso Guarino and Delfina Malandrino and
                 Alfredo Pulvirenti and Francesco Vicidomini and Rocco
                 Zaccagnino",
  title =        "Ex Machina: Analytical platforms, Law and the
                 Challenges of Computational Legal Science",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "5",
  pages =        "37",
  day =          "26",
  month =        apr,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10050037",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:00 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/5/37",
  abstract =     "Over the years, computation has become a fundamental
                 part of the scientific practice in several research
                 fields that goes far beyond the boundaries of natural
                 sciences. Data mining, machine learning, simulations
                 and other computational methods lie today at the hearth
                 of the scientific endeavour in a growing number of
                 social research areas from anthropology to economics.
                 In this scenario, an increasingly important role is
                 played by analytical platforms: integrated environments
                 allowing researchers to experiment cutting-edge
                 data-driven and computation-intensive analyses. The
                 paper discusses the appearance of such tools in the
                 emerging field of computational legal science. After a
                 general introduction to the impact of computational
                 methods on both natural and social sciences, we
                 describe the concept and the features of an analytical
                 platform exploring innovative cross-methodological
                 approaches to the academic and investigative study of
                 crime. Stemming from an ongoing project involving
                 researchers from law, computer science and
                 bioinformatics, the initiative is presented and
                 discussed as an opportunity to raise a debate about the
                 future of legal scholarship and, inside of it, about
                 the challenges of computational legal science.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Computation, Law and the Net-The Future
                 of Law in the Computational Social Science Era.",
}

@Article{He:2018:MBF,
  author =       "Jingsha He and Jianan Wu and Nafei Zhu and Muhammad
                 Salman Pathan",
  title =        "{MinHash}-Based Fuzzy Keyword Search of Encrypted Data
                 across Multiple Cloud Servers",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "5",
  pages =        "38",
  day =          "01",
  month =        may,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10050038",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:00 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/hash.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/5/38",
  abstract =     "To enhance the efficiency of data searching, most data
                 owners store their data files in different cloud
                 servers in the form of cipher-text. Thus, efficient
                 search using fuzzy keywords becomes a critical issue in
                 such a cloud computing environment. This paper proposes
                 a method that aims at improving the efficiency of
                 cipher-text retrieval and lowering storage overhead for
                 fuzzy keyword search. In contrast to traditional
                 approaches, the proposed method can reduce the
                 complexity of Min-Hash-based fuzzy keyword search by
                 using Min-Hash fingerprints to avoid the need to
                 construct the fuzzy keyword set. The method will
                 utilize Jaccard similarity to rank the results of
                 retrieval, thus reducing the amount of calculation for
                 similarity and saving a lot of time and space overhead.
                 The method will also take consideration of multiple
                 user queries through re-encryption technology and
                 update user permissions dynamically. Security analysis
                 demonstrates that the method can provide better privacy
                 preservation and experimental results show that
                 efficiency of cipher-text using the proposed method can
                 improve the retrieval time and lower storage overhead
                 as well.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mousavi:2018:FCM,
  author =       "Seyed Davoud Mousavi and Rasool Sadeghi and
                 Mohamadreza Karimi and Erfan Karimian and Mohammad Reza
                 Soltan Aghaei",
  title =        "A Fair Cooperative {MAC} Protocol in {IEEE 802.11}
                 {WLAN}",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "5",
  pages =        "39",
  day =          "03",
  month =        may,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10050039",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:00 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/5/39",
  abstract =     "Cooperative communication techniques have recently
                 enabled wireless technologies to overcome their
                 challenges. The main objective of these techniques is
                 to improve resource allocation. In this paper, we
                 propose a new protocol in medium access control (MAC)
                 of the IEEE 802.11 standard. In our new protocol, which
                 is called Fair Cooperative MAC (FC-MAC), every relay
                 node participates in cooperation proportionally to its
                 provided cooperation gain. This technique improves
                 network resource allocation by exploiting the potential
                 capacity of all relay candidates. Simulation results
                 demonstrate that the FC-MAC protocol presents better
                 performance in terms of throughput, fairness, and
                 network lifetime.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2018:ECS,
  author =       "Baocheng Wang and Yafei Hu and Yu Xiao and Yi Li",
  title =        "An {EV} Charging Scheduling Mechanism Based on Price
                 Negotiation",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "5",
  pages =        "40",
  day =          "03",
  month =        may,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10050040",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:00 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/5/40",
  abstract =     "Scheduling EV user's charging behavior based on
                 charging price and applying renewable energy resources
                 are the effective methods to release the load pressure
                 of power grids brought about by the large-scale
                 popularity of electric vehicles (EVs). This paper
                 presents a novel approach for EV charging scheduling
                 based on price negotiation. Firstly, the EV charging
                 system framework based on price negotiation and
                 renewable energy resources is discussed. Secondly, the
                 price negotiation model is presented, including the
                 initial price models and the conditions of
                 transactions. Finally, an EV charging scheduling
                 mechanism based on price negotiation (CSM-PN),
                 including the price adjustment strategies of both the
                 operator and EV users is proposed to seek a final
                 transaction during multi-round price negotiation.
                 Simulation results show that this novel approach can
                 effectively improve the charging station operator's
                 income, reduce the EV users' costs, and balance the
                 load of the power grid while improving the efficiency
                 of the EV charging system.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yashima:2018:RAC,
  author =       "Tamotsu Yashima and Kazumasa Takami",
  title =        "Route Availability as a Communication Quality Metric
                 of a Mobile Ad Hoc Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "5",
  pages =        "41",
  day =          "04",
  month =        may,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10050041",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:00 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/5/41",
  abstract =     "Using ad hoc communication between mobile terminals,
                 MANETs (mobile ad hoc networks) are independent of any
                 communication infrastructure but their communication
                 quality can degrade because, as terminals move about in
                 the service area, routes are constantly disconnected
                 and then re-established. There has been no proposal for
                 a quality metric that models this unstable state, i.e.,
                 route nonuniformity. This paper proposes a new concept
                 of route availability (RA) as a metric of route
                 nonuniformity in a MANET and verifies how effectively
                 it represents the quality of service (QoS) of a network
                 or the quality of experience (QoE) of video streaming.
                 We have built an environment that emulates a MANET
                 capable of video streaming, and developed a method of
                 measuring RA for two representative MANET routing
                 methods: AODV (Ad hoc On-Demand Distance Vector) and
                 OLSR (Optimized Link State Routing). We have examined
                 the relationship between RA and conventional network
                 QoS metrics: packet loss rate and throughput. We have
                 also checked RA using a subjective quality assessment
                 test.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Guerrero-Narvaez:2018:TBS,
  author =       "Santiago Guerrero-Narv{\'a}ez and Miguel-{\'A}ngel
                 Ni{\~n}o-Zambrano and Dalila-Jhoana Riobamba-Calvache
                 and Gustavo-Adolfo Ram{\'\i}rez-Gonz{\'a}lez",
  title =        "Test Bed of Semantic Interaction of Smart Objects in
                 the {Web} of Things",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "5",
  pages =        "42",
  day =          "09",
  month =        may,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10050042",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:00 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/5/42",
  abstract =     "Semantic interaction in the Internet of Things (IoT)
                 is an important concept within current IoT development,
                 given that smart things require further autonomy with
                 greater processing, storage, and communication
                 capacities. The problem is now becoming one of how to
                 get these things to interact and collaborate with each
                 other; to form intelligent environments amongst
                 themselves and thus generate better services for users.
                 This article explores a solution approach that consists
                 in providing collaborative behavior to smart things,
                 through the incorporation of an ontology and an
                 architecture. It makes possible things that can
                 communicate and collaborate with each other, allowing
                 the generation of new services of interaction according
                 to user needs. For this task, a real test bed of smart
                 things was created, in which the proposed solution was
                 deployed (Smart Room). Finally, it was concluded that
                 the creation of these types of test bed is feasible,
                 taking into account that response times and the
                 information delivered by the different managed
                 processes are acceptable. New challenges were
                 encountered, however, such as problems of critical
                 region in test beds with conflicting services and
                 management of multiple users.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Big Data and Internet of Thing.",
}

@Article{Hoang:2018:BDB,
  author =       "Xuan Dau Hoang and Quynh Chi Nguyen",
  title =        "Botnet Detection Based On Machine Learning Techniques
                 Using {DNS} Query Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "5",
  pages =        "43",
  day =          "18",
  month =        may,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10050043",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:00 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/5/43",
  abstract =     "In recent years, botnets have become one of the major
                 threats to information security because they have been
                 constantly evolving in both size and sophistication. A
                 number of botnet detection measures, such as
                 honeynet-based and Intrusion Detection System
                 (IDS)-based, have been proposed. However, IDS-based
                 solutions that use signatures seem to be ineffective
                 because recent botnets are equipped with sophisticated
                 code update and evasion techniques. A number of studies
                 have shown that abnormal botnet detection methods are
                 more effective than signature-based methods because
                 anomaly-based botnet detection methods do not require
                 pre-built botnet signatures and hence they have the
                 capability to detect new or unknown botnets. In this
                 direction, this paper proposes a botnet detection model
                 based on machine learning using Domain Name Service
                 query data and evaluates its effectiveness using
                 popular machine learning techniques. Experimental
                 results show that machine learning algorithms can be
                 used effectively in botnet detection and the random
                 forest algorithm produces the best overall detection
                 accuracy of over 90\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Big Data and Augmented Intelligence.",
}

@Article{Zhou:2018:SST,
  author =       "Liang Zhou and Sheng-Ming Jiang and Chen-Lin Xiong",
  title =        "Studying Semi-{TCP} and Its Application in Marine
                 {Internet}",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "6",
  pages =        "44",
  day =          "25",
  month =        may,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10060044",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:00 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/6/44",
  abstract =     "TCP protocol has good performance on the Internet, but
                 its performance is significantly reduced when it is
                 applied to Marine Internet (MI). How to improve the
                 performance of TCP protocol in Marine Internet has
                 become an important research topic. In this paper, an
                 improved Semi-TCP is adopted for Marine Internet, and
                 the implementation scheme of Semi-TCP congestion
                 control is introduced. The exposed terminal problem and
                 congestion control problem of high load networks are
                 analyzed in detail. By using a timer, the congestion
                 control algorithm is improved. Performance analysis and
                 comparison of TCP-Lite, Semi-TCP-RTS, and improved
                 Semi-TCP (Semi-TCP-RTS-V2) are carried out on Exata
                 simulation platform, and the experimental results show
                 that Semi-TCP-RTS-V2 has better transmission
                 performance in ship ad hoc networks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue WSN and IoT in Smart Agriculture.",
}

@Article{Han:2018:MAP,
  author =       "Chong Han and Zilong Li and Jian Zhou and Lijuan Sun
                 and Siyu Chen",
  title =        "A Multiple Access Protocol Based on Gray Forecast for
                 Satellite Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "6",
  pages =        "45",
  day =          "01",
  month =        jun,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10060045",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:00 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/6/45",
  abstract =     "A satellite network's multiple access protocol must be
                 well designed to efficiently occupy channel resources
                 and meet various qualities of service requirements. In
                 this paper, a combined free/demand assignment multiple
                 access protocol based on gray forecast is proposed. In
                 terms of access, the adoption of the gray forecast
                 method allows the user to book the number of timeslots
                 to have more than the existing number of burst of
                 packets. In terms of bandwidth allocation, a user
                 priority allocation method is used to prioritize users
                 with high needs and focus on the allocation of
                 satellite resources. Experimental results show that the
                 proposed protocol can effectively improve the channel
                 utilization of the entire system. Thus, this protocol
                 has some advantages over existing protocols in network
                 throughput and end-to-end delay.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gunleifsen:2018:TCP,
  author =       "H{\aa}kon Gunleifsen and Vasileios Gkioulos and Thomas
                 Kemmerich",
  title =        "A Tiered Control Plane Model for Service Function
                 Chaining Isolation",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "6",
  pages =        "46",
  day =          "04",
  month =        jun,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10060046",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:00 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/6/46",
  abstract =     "This article presents an architecture for encryption
                 automation in interconnected Network Function
                 Virtualization (NFV) domains. Current NFV
                 implementations are designed for deployment within
                 trusted domains, where overlay networks with static
                 trusted links are utilized for enabling network
                 security. Nevertheless, within a Service Function Chain
                 (SFC), Virtual Network Function (VNF) flows cannot be
                 isolated and end-to-end encrypted because each VNF
                 requires direct access to the overall SFC data-flow.
                 This restricts both end-users and Service Providers
                 from enabling end-to-end security, and in extended VNF
                 isolation within the SFC data traffic. Encrypting data
                 flows on a per-flow basis results in an extensive
                 amount of secure tunnels, which cannot scale
                 efficiently in manual configurations. Additionally,
                 creating secure data plane tunnels between NFV
                 providers requires secure exchange of key parameters,
                 and the establishment of an east--west control plane
                 protocol. In this article, we present an architecture
                 focusing on these two problems, investigating how
                 overlay networks can be created, isolated, and secured
                 dynamically. Accordingly, we propose an architecture
                 for automated establishment of encrypted tunnels in
                 NFV, which introduces a novel, tiered east--west
                 communication channel between network controllers in a
                 multi-domain environment.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Software Defined Networking (SDN) and
                 Network Function Virtualization (NFV).",
}

@Article{Lee:2018:SIF,
  author =       "Il-Gu Lee",
  title =        "Secure Inter-Frame Space Communications for Wireless
                 {LANs}",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "6",
  pages =        "47",
  day =          "04",
  month =        jun,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10060047",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:00 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/6/47",
  abstract =     "The internet of things (IoTs) offers a wide range of
                 consumer benefits, from personal portable devices to
                 internet-connected infrastructure. The wireless local
                 area network (WLAN) is one of the potential candidates
                 for IoTs technology to connect billions of smart
                 devices. Long-range WLAN is widely deployed in dense
                 networks as an alternative to cellular networks or
                 satellite internet access because of its low cost, high
                 performance, and existing ecosystem. However, due to
                 the nature of unregulated communications in industrial,
                 scientific, and medical (ISM) bands, WLANs experience
                 interferences from other radios such as radars and
                 frequency hopping devices. Once interference is
                 detected at a WLAN device, the channel is avoided and
                 other channels become crowded. Thus, it degrades
                 network throughput and channel utilization. In this
                 paper, a secure inter-frame space communication system
                 design is proposed for WLANs to share the ISM bands
                 with other radio systems that generate periodic radio
                 signals. The proposed secure inter-frame communication
                 scheme achieves the goal by designing accurate radar
                 detection and secure inter-frame space communication.
                 The simulation results demonstrate that the proposed
                 scheme significantly increases the receiver sensitivity
                 and user datagram protocol throughput.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Francesconi:2018:FLP,
  author =       "Enrico Francesconi",
  title =        "On the Future of Legal Publishing Services in the
                 {Semantic Web}",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "6",
  pages =        "48",
  day =          "05",
  month =        jun,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10060048",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:00 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/6/48",
  abstract =     "The development of the Semantic Web represents an
                 essential precondition to the definition of new
                 scenarios for the future Internet. This perspective is
                 of particular interest in the legal information domain
                 for the specialized nature of legal information and the
                 peculiarities of the legal users' information needs. In
                 this paper, the evolution in recent years of the
                 Semantic Web in the legal domain is reviewed, with
                 particular emphasis to the most recent developments
                 related to Linked Open Data initiative and to the role,
                 in the legal Semantic Web, of the Publications Office
                 of the European Union in its two-fold role of public
                 institution and legal publisher.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Computation, Law and the Net-The Future
                 of Law in the Computational Social Science Era.",
}

@Article{Yang:2018:CPG,
  author =       "Hongbin Yang and Shuxiong Jiang and Wenfeng Shen and
                 Zhou Lei",
  title =        "Certificateless Provable Group Shared Data Possession
                 with Comprehensive Privacy Preservation for Cloud
                 Storage",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "6",
  pages =        "49",
  day =          "07",
  month =        jun,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10060049",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:00 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/6/49",
  abstract =     "Provable Data Possession (PDP) protocol makes it
                 possible for cloud users to check whether the cloud
                 servers possess their original data without downloading
                 all the data. However, most of the existing PDP schemes
                 are based on either public key infrastructure (PKI) or
                 identity-based cryptography, which will suffer from
                 issues of expensive certificate management or key
                 escrow. In this paper, we propose a new construction of
                 certificateless provable group shared data possession
                 (CL-PGSDP) protocol by making use of certificateless
                 cryptography, which will eliminate the above issues.
                 Meanwhile, by taking advantage of zero-knowledge
                 protocol and randomization method, the proposed
                 CL-PGSDP protocol leaks no information of the stored
                 data and the group user's identity to the verifiers
                 during the verifying process, which is of the property
                 of comprehensive privacy preservation. In addition, our
                 protocol also supports efficient user revocation from
                 the group. Security analysis and experimental
                 evaluation indicate that our CL-PGSDP protocol provides
                 strong security with desirable efficiency.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Big Data and Internet of Thing.",
}

@Article{Duradoni:2018:FTV,
  author =       "Mirko Duradoni and Mario Paolucci and Franco Bagnoli
                 and Andrea Guazzini",
  title =        "Fairness and Trust in Virtual Environments: The
                 Effects of Reputation",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "6",
  pages =        "50",
  day =          "09",
  month =        jun,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10060050",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:00 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/6/50",
  abstract =     "Reputation supports pro-social behaviors in a variety
                 of social settings and across different ages. When
                 re-encounters are possible, developing a positive
                 reputation can be a valuable asset that will result in
                 better outcomes. However, in real life, cooperative
                 acts are ambiguous and happen in noisy environments in
                 which individuals can have multiple goals, visibility
                 is reduced, and reputation systems may differ. This
                 study examined how reputation within a virtual
                 environment affects fairness in material allocations
                 and trust in information exchange, in a three-actors
                 interaction game in which each player had an incentive
                 to deceive the others. We compared the results of two
                 experimental conditions, one in which informers could
                 be evaluated, and one without reputational
                 opportunities. A reputational system appeared to
                 enhance both trust and fairness even within a virtual
                 environment under anonymous condition. We tested
                 adolescents and adults finding that they were
                 consistently more generous when visibility was
                 increased, but they showed significantly different
                 patterns in resources allocation and information
                 exchange. Male and female participants, across ages,
                 showed other interesting differences. These findings
                 suggest that reputational effects increase fairness and
                 trust even in a noisy, ambiguous and uncertain
                 environment, but this effect is modulated by age and
                 gender.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Techno-Social Smart Systems.",
}

@Article{Yu:2018:DBP,
  author =       "Lingli Yu and Decheng Kong and Xiaoxin Yan",
  title =        "A Driving Behavior Planning and Trajectory Generation
                 Method for Autonomous Electric Bus",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "6",
  pages =        "51",
  day =          "10",
  month =        jun,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10060051",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:00 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/6/51",
  abstract =     "A framework of path planning for autonomous electric
                 bus is presented. ArcGIS platform is utilized for
                 map-building and global path planning. Firstly, a
                 high-precision map is built based on GPS in ArcGIS for
                 global planning. Then the global optimal path is
                 obtained by network analysis tool in ArcGIS. To
                 facilitate local planning, WGS-84 coordinates in the
                 map are converted to local coordinates. Secondly, a
                 double-layer finite state machine (FSM) is devised to
                 plan driving behavior under different driving
                 scenarios, such as structured driving, lane changing,
                 turning, and so on. Besides, local optimal trajectory
                 is generated by cubic polynomial, which takes full
                 account of the safety and kinetics of the electric bus.
                 Finally, the simulation results show that the framework
                 is reliable and feasible for driving behavior planning
                 and trajectory generation. Furthermore, its validity is
                 proven with an autonomous bus platform 12 m in
                 length.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Xie:2018:NSA,
  author =       "Lei Xie and Shengbo Chen and Wenfeng Shen and Huaikou
                 Miao",
  title =        "A Novel Self-Adaptive {VM} Consolidation Strategy
                 Using Dynamic Multi-Thresholds in {IaaS} Clouds",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "6",
  pages =        "52",
  day =          "13",
  month =        jun,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10060052",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:00 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/6/52",
  abstract =     "With the rapid development of cloud computing, the
                 demand for infrastructure resources in cloud data
                 centers has further increased, which has already led to
                 enormous amounts of energy costs. Virtual machine (VM)
                 consolidation as one of the important techniques in
                 Infrastructure as a Service clouds (IaaS) can help
                 resolve energy consumption by reducing the number of
                 active physical machines (PMs). However, the necessity
                 of considering energy-efficiency and the obligation of
                 providing high quality of service (QoS) to customers is
                 a trade-off, as aggressive consolidation may lead to
                 performance degradation. Moreover, most of the existing
                 works of threshold-based VM consolidation strategy are
                 mainly focused on single CPU utilization, although the
                 resource request on different VMs are very diverse.
                 This paper proposes a novel self-adaptive VM
                 consolidation strategy based on dynamic
                 multi-thresholds (DMT) for PM selection, which can be
                 dynamically adjusted by considering future utilization
                 on multi-dimensional resources of CPU, RAM and
                 Bandwidth. Besides, the VM selection and placement
                 algorithm of VM consolidation are also improved by
                 utilizing each multi-dimensional parameter in DMT. The
                 experiments show that our proposed strategy has a
                 better performance than other strategies, not only in
                 high QoS but also in less energy consumption. In
                 addition, the advantage of its reduction on the number
                 of active hosts is much more obvious, especially when
                 it is under extreme workloads.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Dai:2018:PPF,
  author =       "Jiazhu Dai and Keke Qiao",
  title =        "A Privacy Preserving Framework for Worker's Location
                 in Spatial Crowdsourcing Based on Local Differential
                 Privacy",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "6",
  pages =        "53",
  day =          "14",
  month =        jun,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10060053",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:00 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/6/53",
  abstract =     "With the development of the mobile Internet,
                 location-based services are playing an important role
                 in everyday life. As a new location-based service,
                 Spatial Crowdsourcing (SC) involves collecting and
                 analyzing environmental, social, and other
                 spatiotemporal information of individuals, increasing
                 convenience for users. In SC, users (called requesters)
                 publish tasks and other users (called workers) are
                 required to physically travel to specified locations to
                 perform the tasks. However, with SC services, the
                 workers have to disclose their locations to untrusted
                 third parties, such as the Spatial Crowdsourcing Server
                 (SC-server), which could pose a considerable threat to
                 the privacy of workers. In this paper, we propose a new
                 location privacy protection framework based on local
                 difference privacy for spatial crowdsourcing, which
                 does not require the participation of trusted third
                 parties by adding noises locally to workers' locations.
                 The noisy locations of workers are submitted to the
                 SC-server rather than the real locations. Therefore,
                 the protection of workers' locations is achieved.
                 Experiments showed that this framework not only
                 preserves the privacy of workers in SC, but also has
                 modest overhead performance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wu:2018:SMI,
  author =       "Pin Wu and Yang Yang and Xiaoqiang Li",
  title =        "{StegNet}: Mega Image Steganography Capacity with Deep
                 Convolutional Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "6",
  pages =        "54",
  day =          "15",
  month =        jun,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10060054",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:00 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/6/54",
  abstract =     "Traditional image steganography often leans interests
                 towards safely embedding hidden information into cover
                 images with payload capacity almost neglected. This
                 paper combines recent deep convolutional neural network
                 methods with image-into-image steganography. It
                 successfully hides the same size images with a decoding
                 rate of 98.2\% or bpp (bits per pixel) of 23.57 by
                 changing only 0.76\% of the cover image on average. Our
                 method directly learns end-to-end mappings between the
                 cover image and the embedded image and between the
                 hidden image and the decoded image. We further show
                 that our embedded image, while with mega payload
                 capacity, is still robust to statistical analysis.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Guazzini:2018:SCC,
  author =       "Andrea Guazzini and Mirko Duradoni and Alessandro
                 Lazzeri and Giorgio Gronchi",
  title =        "Simulating the Cost of Cooperation: a Recipe for
                 Collaborative Problem-Solving",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "6",
  pages =        "55",
  day =          "19",
  month =        jun,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10060055",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:00 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/6/55",
  abstract =     "Collective problem-solving and decision-making, along
                 with other forms of collaboration online, are central
                 phenomena within ICT. There had been several attempts
                 to create a system able to go beyond the passive
                 accumulation of data. However, those systems often
                 neglect important variables such as group size, the
                 difficulty of the tasks, the tendency to cooperate, and
                 the presence of selfish individuals (free riders).
                 Given the complex relations among those variables,
                 numerical simulations could be the ideal tool to
                 explore such relationships. We take into account the
                 cost of cooperation in collaborative problem solving by
                 employing several simulated scenarios. The role of two
                 parameters was explored: the capacity, the group's
                 capability to solve increasingly challenging tasks
                 coupled with the collective knowledge of a group, and
                 the payoff, an individual's own benefit in terms of new
                 knowledge acquired. The final cooperation rate is only
                 affected by the cost of cooperation in the case of
                 simple tasks and small communities. In contrast, the
                 fitness of the community, the difficulty of the task,
                 and the groups sizes interact in a non-trivial way,
                 hence shedding some light on how to improve
                 crowdsourcing when the cost of cooperation is high.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Techno-Social Smart Systems.",
}

@Article{Sultan:2018:BDP,
  author =       "Kashif Sultan and Hazrat Ali and Zhongshan Zhang",
  title =        "Big Data Perspective and Challenges in Next Generation
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "7",
  pages =        "56",
  day =          "21",
  month =        jun,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10070056",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:01 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/7/56",
  abstract =     "With the development towards the next generation
                 cellular networks, i.e., 5G, the focus has shifted
                 towards meeting the higher data rate requirements,
                 potential of micro cells and millimeter wave spectrum.
                 The goals for next generation networks are very high
                 data rates, low latency and handling of big data. The
                 achievement of these goals definitely require newer
                 architecture designs, upgraded technologies with
                 possible backward support, better security algorithms
                 and intelligent decision making capability. In this
                 survey, we identify the opportunities which can be
                 provided by 5G networks and discuss the underlying
                 challenges towards implementation and realization of
                 the goals of 5G. This survey also provides a discussion
                 on the recent developments made towards
                 standardization, the architectures which may be
                 potential candidates for deployment and the energy
                 concerns in 5G networks. Finally, the paper presents a
                 big data perspective and the potential of machine
                 learning for optimization and decision making in 5G
                 networks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Big Data and Augmented Intelligence.",
}

@Article{Velusamy:2018:DCA,
  author =       "Gandhimathi Velusamy and Ricardo Lent",
  title =        "Dynamic Cost-Aware Routing of {Web} Requests",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "7",
  pages =        "57",
  day =          "21",
  month =        jun,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10070057",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:01 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/7/57",
  abstract =     "Work within next generation networks considers
                 additional network convergence possibilities and the
                 integration of new services to the web. This trend
                 responds to the ongoing growth of end-user demand for
                 services that can be delivered anytime, anywhere, on
                 any web-capable device, and of traffic generated by new
                 applications, e.g., the Internet of Things. To support
                 the massive traffic generated by the enormous user base
                 and number of devices with reliability and high
                 quality, web services run from redundant servers. As
                 new servers need to be regularly deployed at different
                 geographical locations, energy costs have become a
                 source of major concern for operators. We propose a
                 cost aware method for routing web requests across
                 replicated and distributed servers that can exploit the
                 spatial and temporal variations of both electricity
                 prices and the server network. The method relies on a
                 learning automaton that makes per-request decisions,
                 which can be computed much faster than regular global
                 optimization methods. Using simulation and testbed
                 measurements, we show the cost reductions that are
                 achievable with minimal impact on performance compared
                 to standard web routing algorithms.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Dechouniotis:2018:FMC,
  author =       "Dimitrios Dechouniotis and Ioannis Dimolitsas and
                 Konstantinos Papadakis-Vlachopapadopoulos and Symeon
                 Papavassiliou",
  title =        "Fuzzy Multi-Criteria Based Trust Management in
                 Heterogeneous Federated Future {Internet} Testbeds",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "7",
  pages =        "58",
  day =          "25",
  month =        jun,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10070058",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:01 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/7/58",
  abstract =     "A federation of heterogeneous testbeds, which provides
                 a wide range of services, attracts many experimenters
                 from academia and industry to evaluate novel future
                 Internet architectures and network protocols. The
                 candidate experimenter reserves the appropriate
                 testbeds' resources based on various diverse criteria.
                 Since several testbeds offer similar resources, a trust
                 mechanism between the users and the providers will
                 facilitate the proper selection of testbeds. This paper
                 proposes a fuzzy reputation-based trust framework that
                 is based on a modification of the fuzzy VIKOR
                 multi-criteria decision making method and combines the
                 user's opinion from previously-conducted experiments
                 with retrieved monitoring data from the utilized
                 testbeds, in order to quantify the reputation of each
                 testbed and the credibility of the experimenter. The
                 proposed framework can process various types of numeric
                 and linguistic data in an on-line fashion and can be
                 easily extended for new types of testbeds and services.
                 Data from active federated testbeds are used to
                 evaluate the performance of the fuzzy reputation-based
                 trust framework under dynamic conditions. Furthermore,
                 a comparison of the proposed framework with another
                 existing state of the art trust framework for federated
                 testbeds is presented, and its superiority is
                 demonstrated.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Diniz:2018:CRC,
  author =       "J{\'u}lio C{\'e}sar Medeiros Diniz and Francesco {Da
                 Ros} and Darko Zibar",
  title =        "Clock Recovery Challenges in {DSP}-Based Coherent
                 Single-Mode and Multi-Mode Optical Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "7",
  pages =        "59",
  day =          "26",
  month =        jun,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10070059",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:01 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/7/59",
  abstract =     "We present an analysis of clock recovery algorithms in
                 both polarization division multiplexing systems and
                 mode division multiplexing systems. The impact of
                 inter-polarization time skew and polarization mode
                 dispersion in single-mode fibers, as well as the
                 combined impact of mode mixing and mode group delay
                 spread in multi-mode fibers under different coupling
                 regimes are investigated. Results show that although
                 the clock tone vanishing has a known solution for
                 single-mode systems, in multi-mode systems even for low
                 group delay spread, strong coupling will cause clock
                 tone extinction, making it harder to implement an
                 effective clock recovery scheme.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Recent Advances in DSP-Based Optical
                 Communications.",
}

@Article{Quan:2018:NTL,
  author =       "Li Quan and Zhiliang Wang and Fuji Ren",
  title =        "A Novel Two-Layered Reinforcement Learning for Task
                 Offloading with Tradeoff between Physical Machine
                 Utilization Rate and Delay",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "7",
  pages =        "60",
  day =          "01",
  month =        jul,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10070060",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:01 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/7/60",
  abstract =     "Mobile devices could augment their ability via cloud
                 resources in mobile cloud computing environments. This
                 paper developed a novel two-layered reinforcement
                 learning (TLRL) algorithm to consider task offloading
                 for resource-constrained mobile devices. As opposed to
                 existing literature, the utilization rate of the
                 physical machine and the delay for offloaded tasks are
                 taken into account simultaneously by introducing a
                 weighted reward. The high dimensionality of the state
                 space and action space might affect the speed of
                 convergence. Therefore, a novel reinforcement learning
                 algorithm with a two-layered structure is presented to
                 address this problem. First, k clusters of the physical
                 machines are generated based on the k-nearest neighbors
                 algorithm (k-NN). The first layer of TLRL is
                 implemented by a deep reinforcement learning to
                 determine the cluster to be assigned for the offloaded
                 tasks. On this basis, the second layer intends to
                 further specify a physical machine for task execution.
                 Finally, simulation examples are carried out to verify
                 that the proposed TLRL algorithm is able to speed up
                 the optimal policy learning and can deal with the
                 tradeoff between physical machine utilization rate and
                 delay.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sun:2018:PCD,
  author =       "Bo Sun and Ming Wei and Chunfeng Yang and Zhihuo Xu
                 and Han Wang",
  title =        "Personalised and Coordinated Demand-Responsive Feeder
                 Transit Service Design: a Genetic Algorithms Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "7",
  pages =        "61",
  day =          "01",
  month =        jul,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10070061",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:01 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/7/61",
  abstract =     "The purpose of this work is to create an efficient
                 optimization framework for demand-responsive feeder
                 transit services to assign vehicles to cover all pickup
                 locations to transport passengers to a rail station.
                 The proposed methodology features passengers placing a
                 personalized travel order involving the subway schedule
                 chosen by passengers and windows of service time, etc.
                 Moreover, synchronous transfer between the shuttle and
                 feeder bus is fully accounted for in the problem. A
                 mixed-integer linear programming model is formulated to
                 minimize the total travel time for all passengers,
                 which consists of ride-time for vehicles from the
                 pickup locations to the rail station and wait-time for
                 passengers taking the subway beforehand. Different from
                 conventional methods, the proposed model benefits from
                 using a real distribution of passenger demand
                 aggregated from cellular data and travel time or the
                 distance matrix obtained from an open GIS tool. A
                 distributed genetic algorithm is further designed to
                 obtain meta-optimal solutions in a reasonable amount of
                 time. When applied to design a feeder bus system in
                 Nanjing City, China, case study results reveal that the
                 total travel time of the proposed model was reduced by
                 2.46\% compared to the traditional model. Sensitivity
                 analyses were also further performed to investigate the
                 impact of the number of vehicles on the output.
                 Finally, the difference in results of Cplex, standard
                 GA, and the proposed algorithm were compared to prove
                 the validity of the algorithm.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Vestoso:2018:GBP,
  author =       "Margherita Vestoso",
  title =        "The {GDPR} beyond Privacy: Data-Driven Challenges for
                 Social Scientists, Legislators and Policy-Makers",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "7",
  pages =        "62",
  day =          "06",
  month =        jul,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10070062",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:01 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/7/62",
  abstract =     "While securing personal data from privacy violations,
                 the new General Data Protection Regulation (GDPR)
                 explicitly challenges policymakers to exploit evidence
                 from social data-mining in order to build better
                 policies. Against this backdrop, two issues become
                 relevant: the impact of Big Data on social research,
                 and the potential intersection between social data
                 mining, rulemaking and policy modelling. The work aims
                 at contributing to the reflection on some of the
                 implications of the \&lsquo;knowledge-based' policy
                 recommended by the GDPR. The paper is thus split into
                 two parts: the first describes the data-driven
                 evolution of social sciences, raising methodological
                 and epistemological issues; the second focuses on the
                 interplay between data-driven social research,
                 rule-making and policy modelling, in the light of the
                 policy model fostered by GDPR. Some theoretical
                 reflections about the role of evidence in rule-making
                 will be considered to introduce a discussion on the
                 intersection between data-driven social research and
                 policy modelling and to sketch hypotheses on its future
                 evolutions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Computation, Law and the Net-The Future
                 of Law in the Computational Social Science Era.",
}

@Article{Karembai:2018:TPI,
  author =       "Anil Kumar Karembai and Jeffrey Thompson and Patrick
                 Seeling",
  title =        "Towards Prediction of Immersive Virtual Reality Image
                 Quality of Experience and Quality of Service",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "7",
  pages =        "63",
  day =          "07",
  month =        jul,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10070063",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:01 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/7/63",
  abstract =     "In this article, we evaluate the Quality of Service
                 (QoS) through media impairment levels and device
                 operators' subjective Quality of Experience (QoE). The
                 human-centered QoE determination commonly requires
                 human subject experimentation, which we combine with
                 Electroencephalography (EEG) measurements to move
                 towards automatized and generalized possibilities of
                 determining the QoE. We evaluate the prediction
                 performance for spherical/immersive images displayed
                 with a mobile device VR viewer (Spherical Virtual
                 Reality (SVR)) with the help of only four-position EEG
                 data gathered at the forehead, which correlates well
                 with practical applicability. We find that QoS levels
                 can be predicted more reliably (directly with R2=0.68
                 or based on profiles with R2=0.9) than the QoE, which
                 exhibits significant error levels. Additional
                 comparison with previous approaches for the Spherical
                 Augmented Reality (SAR) QoE indicates better
                 predictability in AR scenarios over VR.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sun:2018:DTS,
  author =       "Dong Sun and Kaixin Zhao and Yaming Fang and Jie Cui",
  title =        "Dynamic Traffic Scheduling and Congestion Control
                 across Data Centers Based on {SDN}",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "7",
  pages =        "64",
  day =          "09",
  month =        jul,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10070064",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:01 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/7/64",
  abstract =     "Software-defined Networking (SDN) and Data Center
                 Network (DCN) are receiving considerable attention and
                 eliciting widespread interest from both academia and
                 industry. When the traditionally shortest path routing
                 protocol among multiple data centers is used,
                 congestion will frequently occur in the shortest path
                 link, which may severely reduce the quality of network
                 services due to long delay and low throughput. The
                 flexibility and agility of SDN can effectively
                 ameliorate the aforementioned problem. However, the
                 utilization of link resources across data centers is
                 still insufficient, and has not yet been well
                 addressed. In this paper, we focused on this issue and
                 proposed an intelligent approach of real-time
                 processing and dynamic scheduling that could make full
                 use of the network resources. The traffic among the
                 data centers could be classified into different types,
                 and different strategies were proposed for these types
                 of real-time traffic. Considering the prolonged
                 occupation of the bandwidth by malicious flows, we
                 employed the multilevel feedback queue mechanism and
                 proposed an effective congestion control algorithm.
                 Simulation experiments showed that our scheme exhibited
                 the favorable feasibility and demonstrated a better
                 traffic scheduling effect and great improvement in
                 bandwidth utilization across data centers.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lodovisi:2018:PAH,
  author =       "Chiara Lodovisi and Pierpaolo Loreti and Lorenzo
                 Bracciale and Silvello Betti",
  title =        "Performance Analysis of Hybrid Optical-Acoustic {AUV}
                 Swarms for Marine Monitoring",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "7",
  pages =        "65",
  day =          "10",
  month =        jul,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10070065",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:01 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/7/65",
  abstract =     "Autonomous Underwater Vehicles (AUVs) are assuming an
                 important role in the monitoring and mapping of marine
                 ecosystems, especially for their ability to explore
                 harsh environments. AUV swarm can collect data
                 operating autonomously for long periods enabling new
                 applications in this field. However, the mission
                 duration is usually limited also by the high power
                 consumption required for acoustic transmissions. A new
                 generation of devices complements the acoustic modem
                 with an optical modem that can provide a communication
                 channel with higher capacity and lower power
                 consumption with respect to the acoustic channel.
                 However, the optical link that uses the visible light
                 is very sensitive to the water turbidity that can
                 strongly limit the link coverage. In this paper, we
                 evaluate the networking performances of the Venus
                 vessel, a real AUV prototype equipped with an
                 acoustical modem and an optical modem. The presented
                 analysis aims to evaluate key system parameters
                 allowing to select the best way to set up network
                 communications according to the surrounding conditions
                 (e.g., quality of water) and to the application
                 requirements. Simulation results account for the case
                 of ports or basins, where the water quality is poor and
                 the use of the optical modem is strongly limited by
                 distance. We evaluate system performance in terms of
                 transmission delay in the network and we also provide a
                 power--capacity trade-off.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Pizzi:2018:ETM,
  author =       "Sara Pizzi and Chiara Suraci and Leonardo Militano and
                 Antonino Orsino and Antonella Molinaro and Antonio Iera
                 and Giuseppe Araniti",
  title =        "Enabling Trustworthy Multicast Wireless Services
                 through {D2D} Communications in {5G} Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "7",
  pages =        "66",
  day =          "11",
  month =        jul,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10070066",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:01 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/7/66",
  abstract =     "Device-to-device (D2D) communication is considered as
                 one of the key enabling technologies for
                 fifth-generation (5G) networks as it allows data
                 offloading generated by the huge number of connected
                 devices. In this respect, group-oriented services are
                 among the most interesting usage scenarios. Indeed, D2D
                 can improve the performance of the conventional
                 multicast scheme (CMS) in cellular networks, which is
                 known to suffer from low spectral efficiency. Security
                 is a further key field of investigation for 5G systems,
                 as any threat to privacy and security may lead to both
                 deteriorated user experience and inefficient network
                 resources' utilization. Security issues are even more
                 in focus for D2D connections between devices that are
                 in mutual proximity. To improve the CMS performance and
                 also sustain security requirements of the 5G network,
                 this work proposes a secure D2D data transmission
                 algorithm. Making use of mechanisms such as encryption
                 and signature, this algorithm aims to protect the
                 exchanged data and the privacy of the devices involved
                 in the communication. A simulation campaign conducted
                 using MATLAB shows the ability of the proposed solution
                 to take advantage of the establishment of secure D2D
                 communications and efficiently utilize network
                 resources.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Peng:2018:NMP,
  author =       "Guang-Qian Peng and Guangtao Xue and Yi-Chao Chen",
  title =        "Network Measurement and Performance Analysis at Server
                 Side",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "7",
  pages =        "67",
  day =          "16",
  month =        jul,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10070067",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:01 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/7/67",
  abstract =     "Network performance diagnostics is an important topic
                 that has been studied since the Internet was invented.
                 However, it remains a challenging task, while the
                 network evolves and becomes more and more complicated
                 over time. One of the main challenges is that all
                 network components (e.g., senders, receivers, and relay
                 nodes) make decision based only on local information
                 and they are all likely to be performance bottlenecks.
                 Although Software Defined Networking (SDN) proposes to
                 embrace a centralize network intelligence for a better
                 control, the cost to collect complete network states in
                 packet level is not affordable in terms of collection
                 latency, bandwidth, and processing power. With the
                 emergence of the new types of networks (e.g., Internet
                 of Everything, Mission-Critical Control, data-intensive
                 mobile apps, etc.), the network demands are getting
                 more diverse. It is critical to provide finer
                 granularity and real-time diagnostics to serve various
                 demands. In this paper, we present EVA, a network
                 performance analysis tool that guides developers and
                 network operators to fix problems in a timely manner.
                 EVA passively collects packet traces near the server
                 (hypervisor, NIC, or top-of-rack switch), and pinpoints
                 the location of the performance bottleneck (sender,
                 network, or receiver). EVA works without detailed
                 knowledge of application or network stack and is
                 therefore easy to deploy. We use three types of
                 real-world network datasets and perform trace-driven
                 experiments to demonstrate EVA's accuracy and
                 generality. We also present the problems observed in
                 these datasets by applying EVA.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Miraz:2018:INT,
  author =       "Mahdi H. Miraz and Maaruf Ali and Peter S. Excell and
                 Richard Picking",
  title =        "{Internet of Nano-Things}, Things and Everything:
                 Future Growth Trends",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "8",
  pages =        "68",
  day =          "28",
  month =        jul,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10080068",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:01 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/8/68",
  abstract =     "The current statuses and future promises of the
                 Internet of Things (IoT), Internet of Everything (IoE)
                 and Internet of Nano-Things (IoNT) are extensively
                 reviewed and a summarized survey is presented. The
                 analysis clearly distinguishes between IoT and IoE,
                 which are wrongly considered to be the same by many
                 commentators. After evaluating the current trends of
                 advancement in the fields of IoT, IoE and IoNT, this
                 paper identifies the 21 most significant current and
                 future challenges as well as scenarios for the possible
                 future expansion of their applications. Despite
                 possible negative aspects of these developments, there
                 are grounds for general optimism about the coming
                 technologies. Certainly, many tedious tasks can be
                 taken over by IoT devices. However, the dangers of
                 criminal and other nefarious activities, plus those of
                 hardware and software errors, pose major challenges
                 that are a priority for further research. Major
                 specific priority issues for research are identified.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Internet of Things.",
}

@Article{Guo:2018:WBS,
  author =       "Jinyi Guo and Wei Ren and Yi Ren and Tianqing Zhu",
  title =        "A Watermark-Based In-Situ Access Control Model for
                 Image Big Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "8",
  pages =        "69",
  day =          "29",
  month =        jul,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10080069",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:01 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/8/69",
  abstract =     "When large images are used for big data analysis, they
                 impose new challenges in protecting image privacy. For
                 example, a geographic image may consist of several
                 sensitive areas or layers. When it is uploaded into
                 servers, the image will be accessed by diverse
                 subjects. Traditional access control methods regulate
                 access privileges to a single image, and their access
                 control strategies are stored in servers, which imposes
                 two shortcomings: (1) fine-grained access control is
                 not guaranteed for areas/layers in a single image that
                 need to maintain secret for different roles; and (2)
                 access control policies that are stored in servers
                 suffers from multiple attacks (e.g., transferring
                 attacks). In this paper, we propose a novel
                 watermark-based access control model in which access
                 control policies are associated with objects being
                 accessed (called an in-situ model). The proposed model
                 integrates access control policies as watermarks within
                 images, without relying on the availability of servers
                 or connecting networks. The access control for images
                 is still maintained even though images are
                 redistributed again to further subjects. Therefore,
                 access control policies can be delivered together with
                 the big data of images. Moreover, we propose a
                 hierarchical key-role-area model for fine-grained
                 encryption, especially for large size images such as
                 geographic maps. The extensive analysis justifies the
                 security and performance of the proposed model.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Big Data and Augmented Intelligence.",
}

@Article{Zhang:2018:MIP,
  author =       "Lijun Zhang and Kai Liu and Jian Liu",
  title =        "Multidiscipline Integrated Platform Based on
                 Probabilistic Analysis for Manufacturing Engineering
                 Processes",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "8",
  pages =        "70",
  day =          "30",
  month =        jul,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10080070",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:01 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/8/70",
  abstract =     "Researchers from different disciplines, such as
                 materials science, computer science, safety science,
                 mechanical engineering and controlling engineering,
                 have aimed to improve the quality of manufacturing
                 engineering processes. Considering the requirements of
                 research and development of advanced materials,
                 reliable manufacturing and collaborative innovation, a
                 multidiscipline integrated platform framework based on
                 probabilistic analysis for manufacturing engineering
                 processes is proposed. The proposed platform consists
                 of three logical layers: The requirement layer, the
                 database layer and the application layer. The platform
                 is intended to be a scalable system to gradually
                 supplement related data, models and approaches. The
                 main key technologies of the platform, encapsulation
                 methods, information fusion approaches and the
                 collaborative mechanism are also discussed. The
                 proposed platform will also be gradually improved in
                 the future. In order to exchange information for
                 manufacturing engineering processes, scientists and
                 engineers of different institutes of materials science
                 and manufacturing engineering should strengthen their
                 cooperation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Big Data and Augmented Intelligence.",
}

@Article{Johnson:2018:HAI,
  author =       "Shardrom Johnson and Jinwu Han and Yuanchen Liu and Li
                 Chen and Xinlin Wu",
  title =        "Hybrid Approach with Improved Genetic Algorithm and
                 Simulated Annealing for Thesis Sampling",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "8",
  pages =        "71",
  day =          "30",
  month =        jul,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10080071",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:01 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/8/71",
  abstract =     "Sampling inspection uses the sample characteristics to
                 estimate that of the population, and it is an important
                 method to describe the population, which has the
                 features of low cost, strong applicability and high
                 scientificity. This paper aims at the sampling
                 inspection of the master's degree thesis to ensure
                 their quality, which is commonly estimated by random
                 sampling. Since there are disadvantages in random
                 sampling, a hybrid algorithm combined with an improved
                 genetic algorithm and a simulated annealing algorithm
                 is proposed in this paper. Furthermore, a novel
                 mutation strategy is introduced according to the
                 specialty of Shanghai's thesis sampling to improve the
                 efficiency of sampling inspection; the acceleration of
                 convergence of the algorithm can also take advantage of
                 this. The new algorithm features the traditional
                 genetic algorithm, and it can obtain the global optimum
                 in the optimization process and provide the fairest
                 sampling plan under the constraint of multiple sampling
                 indexes. The experimental results on the master's
                 thesis dataset of Shanghai show that the proposed
                 algorithm well meets the requirements of the sampling
                 inspection in Shanghai with a lower time-complexity.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Goeke:2018:CAC,
  author =       "Ludger Goeke and Nazila Gol Mohammadi and Maritta
                 Heisel",
  title =        "Context Analysis of Cloud Computing Systems Using a
                 Pattern-Based Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "8",
  pages =        "72",
  day =          "31",
  month =        jul,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10080072",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:01 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/8/72",
  abstract =     "Cloud computing services bring new capabilities for
                 hosting and offering complex collaborative business
                 operations. However, these advances might bring
                 undesirable side-effects, e.g., introducing new
                 vulnerabilities and threats caused by collaboration and
                 data exchange over the Internet. Hence, users have
                 become more concerned about security and privacy
                 aspects. For secure provisioning of a cloud computing
                 service, security and privacy issues must be addressed
                 by using a risk assessment method. To perform a risk
                 assessment, it is necessary to obtain all relevant
                 information about the context of the considered cloud
                 computing service. The context analysis of a cloud
                 computing service and its underlying system is a
                 difficult task because of the variety of different
                 types of information that have to be considered. This
                 context information includes (i) legal, regulatory
                 and/or contractual requirements that are relevant for a
                 cloud computing service (indirect stakeholders); (ii)
                 relations to other involved cloud computing services;
                 (iii) high-level cloud system components that support
                 the involved cloud computing services; (iv) data that
                 is processed by the cloud computing services; and (v)
                 stakeholders that interact directly with the cloud
                 computing services and/or the underlying cloud system
                 components. We present a pattern for the contextual
                 analysis of cloud computing services and demonstrate
                 the instantiation of our proposed pattern with
                 real-life application examples. Our pattern contains
                 elements that represent the above-mentioned types of
                 contextual information. The elements of our pattern
                 conform to the General Data Protection Regulation.
                 Besides the context analysis, our pattern supports the
                 identification of high-level assets. Additionally, our
                 proposed pattern supports the documentation of the
                 scope and boundaries of a cloud computing service
                 conforming to the requirements of the ISO 27005
                 standard (information security risk management). The
                 results of our context analysis contribute to the
                 transparency of the achieved security and privacy level
                 of a cloud computing service. This transparency can
                 increase the trust of users in a cloud computing
                 service. We present results of the RestAssured project
                 related to the context analysis regarding cloud
                 computing services and their underlying cloud computing
                 systems. The context analysis is the prerequisite to
                 threat and control identification that are performed
                 later in the risk management process. The focus of this
                 paper is the use of a pattern at the time of design
                 systematic context analysis and scope definition for
                 risk management methods.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security Patterns in Industry.",
}

@Article{Lei:2018:JAA,
  author =       "Jianjun Lei and Jiarui Tao and Shanshan Yang",
  title =        "Joint {AP} Association and Bandwidth Allocation
                 Optimization Algorithm in High-Dense {WLANs}",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "8",
  pages =        "73",
  day =          "06",
  month =        aug,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10080073",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:01 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/8/73",
  abstract =     "Regarding access point (AP) overload and performance
                 anomaly which is caused by mobile terminals with
                 different bitrates, a joint AP association and
                 bandwidth allocation optimization algorithm is
                 presented in this paper. Meanwhile, load balancing and
                 proportional fairness are analyzed and formulated as an
                 optimization model. Then, we present a Fair Bandwidth
                 Allocation algorithm based on clients' Business
                 Priority (FBA-BP), which allocates bandwidth based on
                 the bandwidth demand of clients and their business
                 priority. Furthermore, we propose a Categorized AP
                 Association algorithm based on clients' demands
                 (CAA-BD), which classifies APs by different types of
                 clients and chooses an optimal associating AP for a new
                 client according to AP categories and the aggregated
                 demand transmission time that are calculated by the
                 FBA-BP algorithm. The CAA-BD can achieve load balance
                 and solve the performance anomaly caused by multi-rate
                 clients coexisting. The simulation results show that
                 our proposed algorithm obtains significant performance
                 in terms of AP utilization, throughput, transmission
                 delay and channel fairness in different client density
                 levels compared with the categorized and Strong Signal
                 First (SSF) algorithms.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Internet of Things.",
}

@Article{Liu:2018:PFE,
  author =       "Kanghuai Liu and Zhigang Chen and Jia Wu and Yutong
                 Xiao and Heng Zhang",
  title =        "Predict and Forward: An Efficient Routing-Delivery
                 Scheme Based on Node Profile in Opportunistic
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "8",
  pages =        "74",
  day =          "06",
  month =        aug,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10080074",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:01 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/8/74",
  abstract =     "In the social scene of opportunistic networks, message
                 applications find suitable relay nodes or certain
                 transmission destinations from the surrounding
                 neighbors through specific network addresses of users.
                 However, at the dawn of big data and 5G networks, the
                 variational location information of nodes is difficult
                 to be available to mobile devices all the time, and a
                 long wait for the destination may cause severe
                 end-to-end delay. To improve the transmission
                 environment, this study constructs an efficient
                 routing-delivery scheme (Predict and Forward) based on
                 node profile for the opportunistic networks. The node
                 profile effectively characterizes nodes by analyzing
                 and comparing their attributes instead of network
                 addresses, such as physical characteristics, places of
                 residence, workplaces, occupations or hobbies.
                 According to the optimal stopping theory, this
                 algorithm implements the optimal transmission for
                 Prelearn messages by dividing the complex data
                 transmission process into two different phases (Predict
                 and Forward). Through simulations and the comparison of
                 routing algorithms in opportunistic networks, the
                 proposed strategy increases the delivery ratio by 80\%
                 with the traditional methods on average, and the
                 average end-to-end delay in this algorithm is the
                 lowest.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liu:2018:HMS,
  author =       "Jianqiang Liu and Shuai Huo and Yi Wang",
  title =        "A Hierarchical Mapping System for Flat Identifier to
                 Locator Resolution Based on Active Degree",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "8",
  pages =        "75",
  day =          "08",
  month =        aug,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10080075",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:01 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/8/75",
  abstract =     "Overloading of IP address semantics appeals for a new
                 network architecture based on Identifier (ID)/Locator
                 separation. The challenge of Identifier (ID)/Locator
                 separation is how to solve the scalability and
                 efficiency challenges of identity-to-location
                 resolution. By analyzing the requirements of the
                 Identifier (ID)/Locator separation protocol, this paper
                 proposes a hierarchical mapping architecture on
                 active-degree (HMAA). This HMAA was divided into three
                 levels: active local level, neutral transfer level, and
                 inert global level. Each mapping item is dynamically
                 allocated to different levels to ensure minimizing
                 delay according to its activity characteristics. The
                 top layer CHORD is constructed by the Markov Decision
                 Process, which can keep consistency between the
                 physical topology and the logical topology. The
                 simulation results on delay time show that HMAA can
                 satisfy the scalability and efficiency requirements of
                 an Identifier (ID)/Locator separation network.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Teixeira:2018:SST,
  author =       "Marcio Andrey Teixeira and Tara Salman and Maede
                 Zolanvari and Raj Jain and Nader Meskin and Mohammed
                 Samaka",
  title =        "{SCADA} System Testbed for Cybersecurity Research
                 Using Machine Learning Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "8",
  pages =        "76",
  day =          "09",
  month =        aug,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10080076",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:01 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/8/76",
  abstract =     "This paper presents the development of a Supervisory
                 Control and Data Acquisition (SCADA) system testbed
                 used for cybersecurity research. The testbed consists
                 of a water storage tank's control system, which is a
                 stage in the process of water treatment and
                 distribution. Sophisticated cyber-attacks were
                 conducted against the testbed. During the attacks, the
                 network traffic was captured, and features were
                 extracted from the traffic to build a dataset for
                 training and testing different machine learning
                 algorithms. Five traditional machine learning
                 algorithms were trained to detect the attacks: Random
                 Forest, Decision Tree, Logistic Regression, Na{\"\i}ve
                 Bayes and KNN. Then, the trained machine learning
                 models were built and deployed in the network, where
                 new tests were made using online network traffic. The
                 performance obtained during the training and testing of
                 the machine learning models was compared to the
                 performance obtained during the online deployment of
                 these models in the network. The results show the
                 efficiency of the machine learning models in detecting
                 the attacks in real time. The testbed provides a good
                 understanding of the effects and consequences of
                 attacks on real SCADA environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Huang:2018:MIU,
  author =       "Yi-Ting Huang and Sheng-Fang Su",
  title =        "Motives for {Instagram} Use and Topics of Interest
                 among Young Adults",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "8",
  pages =        "77",
  day =          "09",
  month =        aug,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10080077",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:01 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/8/77",
  abstract =     "Instagram is currently the most popular social media
                 app among young people around the world. More than 70\%
                 of people between the ages of 12 and 24 are Instagram
                 users. The research framework of this study was
                 constructed based on smartphone addiction and the uses
                 and gratifications theory. We used 27 question items
                 divided into five factors, namely social interaction,
                 documentation, diversion, self-promotion, and
                 creativity, to investigate the motives for Instagram
                 use and topics of interest among university students in
                 Taiwan. A total of 307 valid questionnaires were
                 obtained. The results revealed that on the whole, the
                 motives for Instagram use were mostly to look at posts,
                 particularly involving social interaction and diversion
                 motives. The level of agreement expressed toward
                 motives for creating posts was lower. Gender,
                 professional training background, and level of
                 addiction to Instagram all exert influence on motives
                 for Instagram use. Over half of the students majoring
                 in design followed artisans and celebrities (including
                 designers), and female students noticed ads on
                 Instagram more than male students did.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Techno-Social Smart Systems.",
}

@Article{Ibadah:2018:SCR,
  author =       "Nisrine Ibadah and Khalid Minaoui and Mohammed Rziza
                 and Mohammed Oumsis and C{\'e}sar Benavente-Peces",
  title =        "Smart Collection of Real-Time Vehicular Mobility
                 Traces",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "8",
  pages =        "78",
  day =          "09",
  month =        aug,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10080078",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:01 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/8/78",
  abstract =     "Mobility trace techniques makes possible drawing the
                 behaviors of real-life movement which shape wireless
                 networks mobility whereabouts. In our investigation,
                 several trace mobility models have been collected after
                 the devices' deployment. The main issue of this
                 classical procedure is that it produces uncompleted
                 records due to several unpredictable problems occurring
                 during the deployment phase. In this paper, we propose
                 a new procedure aimed at collecting traces while
                 deployment phase failures are avoided, which improves
                 the reliability of data. The introduced procedure makes
                 possible the complete generation of traces with a
                 minimum amount of damage without the need to recover
                 mobile devices or lose them, as it is the case in
                 previous mobility traces techniques. Based on detecting
                 and correcting all accidental issues in real time, the
                 proposed trace scanning offers a set of relevant
                 information about the vehicle status which was
                 collected during seven months. Furthermore, the
                 proposed procedure could be applied to generate
                 vehicular traces. Likewise, it is suitable to
                 record/generate human and animal traces. The research
                 outcomes demonstrate the effectiveness and robustness
                 of the smart collection algorithm based on the proposed
                 trace mobility model.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ren:2018:QSM,
  author =       "Chuanxiang Ren and Wenbo Zhang and Lingqiao Qin and Bo
                 Sun",
  title =        "Queue Spillover Management in a Connected Vehicle
                 Environment",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "8",
  pages =        "79",
  day =          "10",
  month =        aug,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10080079",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:01 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/8/79",
  abstract =     "To alleviate the queue spillovers at intersections of
                 urban roads during rush hours, a solution to the
                 cross-spill problem based on vehicle networking
                 technologies is proposed. This involves using connected
                 vehicle technology, to realize the interactive
                 information on vehicle and intersection signal control.
                 The maximum control distance between intersections is
                 determined by how vehicles are controlled and would
                 travel in that connected environment. A method of
                 calculating overflow tendency towards intersection
                 queuing is also proposed, based on the maximum phase
                 control distance. By this method, the intersection
                 overflow is identified, and then the signal phases are
                 re-optimized according to the requirements of different
                 phases. Finally, overflow prevention control was also
                 performed in this study. The VISSIM simulation results
                 show that the method can better prevent the overflow of
                 queues at intersections.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhang:2018:FLM,
  author =       "Lei Zhang and Xiaoli Zhi",
  title =        "A Fast and Lightweight Method with Feature Fusion and
                 Multi-Context for Face Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "8",
  pages =        "80",
  day =          "17",
  month =        aug,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10080080",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:01 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/8/80",
  abstract =     "Convolutional neural networks (CNN for short) have
                 made great progress in face detection. They mostly take
                 computation intensive networks as the backbone in order
                 to obtain high precision, and they cannot get a good
                 detection speed without the support of high-performance
                 GPUs (Graphics Processing Units). This limits CNN-based
                 face detection algorithms in real applications,
                 especially in some speed dependent ones. To alleviate
                 this problem, we propose a lightweight face detector in
                 this paper, which takes a fast residual network as
                 backbone. Our method can run fast even on cheap and
                 ordinary GPUs. To guarantee its detection precision,
                 multi-scale features and multi-context are fully
                 exploited in efficient ways. Specifically, feature
                 fusion is used to obtain semantic strongly multi-scale
                 features firstly. Then multi-context including both
                 local and global context is added to these multi-scale
                 features without extra computational burden. The local
                 context is added through a depthwise separable
                 convolution based approach, and the global context by a
                 simple global average pooling way. Experimental results
                 show that our method can run at about 110 fps on VGA
                 (Video Graphics Array)-resolution images, while still
                 maintaining competitive precision on WIDER FACE and
                 FDDB (Face Detection Data Set and Benchmark) datasets
                 as compared with its state-of-the-art counterparts.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Viola:2018:IER,
  author =       "Fabio Viola and Luca Roffia and Francesco Antoniazzi
                 and Alfredo D'Elia and Cristiano Aguzzi and Tullio
                 Salmon Cinotti",
  title =        "Interactive {3D} Exploration of {RDF} Graphs through
                 Semantic Planes",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "8",
  pages =        "81",
  day =          "17",
  month =        aug,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10080081",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:01 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/8/81",
  abstract =     "This article presents Tarsier, a tool for the
                 interactive 3D visualization of RDF graphs. Tarsier is
                 mainly intended to support teachers introducing
                 students to Semantic Web data representation formalisms
                 and developers in the debugging of applications based
                 on Semantic Web knowledge bases. The tool proposes the
                 metaphor of semantic planes as a way to visualize an
                 RDF graph. A semantic plane contains all the RDF terms
                 sharing a common concept; it can be created, and
                 further split into several planes, through a set of UI
                 controls or through SPARQL 1.1 queries, with the full
                 support of OWL and RDFS. Thanks to the 3D
                 visualization, links between semantic planes can be
                 highlighted and the user can navigate within the 3D
                 scene to find the better perspective to analyze data.
                 Data can be gathered from generic SPARQL 1.1 protocol
                 services. We believe that Tarsier will enhance the
                 human friendliness of semantic technologies by: (1)
                 helping newcomers assimilate new data representation
                 formats; and (2) increasing the capabilities of
                 inspection to detect relevant situations even in
                 complex RDF graphs.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Safkhani:2018:SRO,
  author =       "Masoumeh Safkhani and Nasour Bagheri and Mahyar
                 Shariat",
  title =        "On the Security of Rotation Operation Based
                 Ultra-Lightweight Authentication Protocols for {RFID}
                 Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "9",
  pages =        "82",
  day =          "21",
  month =        aug,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10090082",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:02 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/9/82",
  abstract =     "Passive Radio Frequency IDentification (RFID) tags are
                 generally highly constrained and cannot support
                 conventional encryption systems to meet the required
                 security. Hence, designers of security protocols may
                 try to achieve the desired security only using limited
                 ultra-lightweight operations. In this paper, we show
                 that the security of such protocols is not provided by
                 using rotation functions. In the following, for an
                 example, we investigate the security of an RFID
                 authentication protocol that has been recently
                 developed using rotation function named ULRAS, which
                 stands for an Ultra-Lightweight RFID Authentication
                 Scheme and show its security weaknesses. More
                 precisely, we show that the ULRAS protocol is
                 vulnerable against de-synchronization attack. The given
                 attack has the success probability of almost
                 \&lsquo;1', with the complexity of only one session of
                 the protocol. In addition, we show that the given
                 attack can be used as a traceability attack against the
                 protocol if the parameters' lengths are an integer
                 power of 2, e.g., 128. Moreover, we propose a new
                 authentication protocol named UEAP, which stands for an
                 Ultra-lightweight Encryption based Authentication
                 Protocol, and then informally and formally, using
                 Scyther tool, prove that the UEAP protocol is secure
                 against all known active and passive attacks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue New Developments in RFID Technologies
                 and Applications and Their Integration into IoT.",
}

@Article{Wang:2018:HRA,
  author =       "Wentao Wang and Xuan Ke and Lingxia Wang",
  title =        "A {HMM-R} Approach to Detect {L-DDoS} Attack
                 Adaptively on {SDN} Controller",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "9",
  pages =        "83",
  day =          "23",
  month =        aug,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10090083",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:02 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/9/83",
  abstract =     "A data center network is vulnerable to suffer from
                 concealed low-rate distributed denial of service
                 (L-DDoS) attacks because its data flow has the
                 characteristics of data flow delay, diversity, and
                 synchronization. Several studies have proposed
                 addressing the detection of L-DDoS attacks, most of
                 them are only detect L-DDoS attacks at a fixed rate.
                 These methods cause low true positive and high false
                 positive in detecting multi-rate L-DDoS attacks.
                 Software defined network (SDN) is a new network
                 architecture that can centrally control the network. We
                 use an SDN controller to collect and analyze data
                 packets entering the data center network and calculate
                 the Renyi entropies base on IP of data packets, and
                 then combine them with the hidden Markov model to get a
                 probability model HMM-R to detect L-DDoS attacks at
                 different rates. Compared with the four common attack
                 detection algorithms (KNN, SVM, SOM, BP), HMM-R is
                 superior to them in terms of the true positive rate,
                 the false positive rate, and the adaptivity.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2018:UNL,
  author =       "Yanli Li and Lala Mei and Ran Li and Changan Wu",
  title =        "Using Noise Level to Detect Frame Repetition Forgery
                 in Video Frame Rate Up-Conversion",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "9",
  pages =        "84",
  day =          "24",
  month =        aug,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10090084",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:02 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/9/84",
  abstract =     "Frame repetition (FR) is a common temporal-domain
                 tampering operator, which is often used to increase the
                 frame rate of video sequences. Existing methods detect
                 FR forgery by analyzing residual variation or
                 similarity between video frames; however, these methods
                 are easily interfered with by noise, affecting the
                 stability of detection performance. This paper proposes
                 a noise-level based detection method which detects the
                 varying noise level over time to determine whether the
                 video is forged by FR. Wavelet coefficients are first
                 computed for each video frame, and median absolute
                 deviation (MAD) of wavelet coefficients is used to
                 estimate the standard deviation of Gaussian noise mixed
                 in each video frame. Then, fast Fourier transform (FFT)
                 is used to calculate the amplitude spectrum of the
                 standard deviation curve of the video sequence, and to
                 provide the peak-mean ratio (PMR) of the amplitude
                 spectrum. Finally, according to the PMR obtained, a
                 hard threshold decision is taken to determine whether
                 the standard deviation bears periodicity in the
                 temporal domain, in which way FR forgery can be
                 automatically identified. The experimental results show
                 that the proposed method ensures a large PMR for the
                 forged video, and presents a better detection
                 performance when compared with the existing detection
                 methods.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Collection Information Systems Security.",
}

@Article{Wu:2018:PPM,
  author =       "Yin Wu and Bowen Li and Fuquan Zhang",
  title =        "Predictive Power Management for Wind Powered Wireless
                 Sensor Node",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "9",
  pages =        "85",
  day =          "06",
  month =        sep,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10090085",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:02 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/9/85",
  abstract =     "A conventional Wireless Sensor Network (WSN) cannot
                 have an infinite lifetime without a battery recharge or
                 replacement. Energy Harvesting (EH), from environmental
                 energy sources, is a promising technology to provide
                 sustainable powering for a WSN. In this paper, we
                 propose and investigate a novel predictive energy
                 management framework that combines the Maximal Power
                 Transferring Tracking (MPTT) algorithm, a predictive
                 energy allocation strategy, and a high efficiency
                 transmission power control mechanism: First, the MPTT
                 optimal working point guarantees minimum power loss of
                 the EH-WSN system; Then, by exactly predicting the
                 upcoming available energy, the power allocation
                 strategy regulates EH-nodes' duty cycle accurately to
                 minimize the power failure time; Ultimately, the
                 transmission power control module further improves
                 energy efficiency by dynamically selecting the optimum
                 matching transmission power level with minimum energy
                 consumption. A wind energy powered wireless sensor
                 system has been equipped and tested to validate the
                 effectiveness of the proposed scheme. Results indicate
                 that compared with other predictive energy managers,
                 the proposed mechanism incurs relatively low power
                 failure time while maintaining a high-energy conversion
                 rate.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Internet of Things.",
}

@Article{Alshathri:2018:SLM,
  author =       "Samah Alshathri and Bogdan Ghita and Nathan Clarke",
  title =        "Sharing with Live Migration Energy Optimization
                 Scheduler for Cloud Computing Data Centers",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "9",
  pages =        "86",
  day =          "06",
  month =        sep,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10090086",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:02 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/9/86",
  abstract =     "The cloud-computing concept has emerged as a powerful
                 mechanism for data storage by providing a suitable
                 platform for data centers. Recent studies show that the
                 energy consumption of cloud computing systems is a key
                 issue. Therefore, we should reduce the energy
                 consumption to satisfy performance requirements,
                 minimize power consumption, and maximize resource
                 utilization. This paper introduces a novel algorithm
                 that could allocate resources in a cloud-computing
                 environment based on an energy optimization method
                 called Sharing with Live Migration (SLM). In this
                 scheduler, we used the Cloud-Sim toolkit to manage the
                 usage of virtual machines (VMs) based on a novel
                 algorithm that learns and predicts the similarity
                 between the tasks, and then allocates each of them to a
                 suitable VM. On the other hand, SLM satisfies the
                 Quality of Services (QoS) constraints of the hosted
                 applications by adopting a migration process. The
                 experimental results show that the algorithm exhibits
                 better performance, while saving power and minimizing
                 the processing time. Therefore, the SLM algorithm
                 demonstrates improved virtual machine efficiency and
                 resource utilization compared to an adapted
                 state-of-the-art algorithm for a similar problem.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sahajwani:2018:LLR,
  author =       "Manish Sahajwani and Alok Jain and Radheyshyam Gamad",
  title =        "Log Likelihood Ratio Based Relay Selection Scheme for
                 Amplify and Forward Relaying with Three State {Markov}
                 Channel",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "9",
  pages =        "87",
  day =          "06",
  month =        sep,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10090087",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:02 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/9/87",
  abstract =     "This paper presents log likelihood ratio (LLR) based
                 relay selection scheme for a cooperative amplify and
                 forward relaying system. To evaluate the performance of
                 the aforementioned system model, a three state Markov
                 chain based fading environment has been presented to
                 toggle among Rayleigh, Rician, and Nakagami-m fading
                 environment. A simulation is carried out while assuming
                 that there is no possibility of direct transmission
                 from the source and destination terminal. Simulation
                 results on the basis of Bit Error Rate (BER),
                 Instantaneous Channel Capacity, and Outage probability
                 have been presented and compared for different cases.
                 In each case, the best performance of the proposed
                 algorithm is obtained with a Binary Phase Shift Keying
                 (BPSK) modulation scheme.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gkioulos:2018:SLR,
  author =       "Vasileios Gkioulos and H{\aa}kon Gunleifsen and Goitom
                 Kahsay Weldehawaryat",
  title =        "A Systematic Literature Review on Military Software
                 Defined Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "9",
  pages =        "88",
  day =          "12",
  month =        sep,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10090088",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:02 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/9/88",
  abstract =     "Software Defined Networking (SDN) is an evolving
                 network architecture paradigm that focuses on the
                 separation of control and data planes. SDN receives
                 increasing attention both from academia and industry,
                 across a multitude of application domains. In this
                 article, we examine the current state of obtained
                 knowledge on military SDN by conducting a systematic
                 literature review (SLR). Through this work, we seek to
                 evaluate the current state of the art in terms of
                 research tracks, publications, methods, trends, and
                 most active research areas. Accordingly, we utilize
                 these findings for consolidating the areas of past and
                 current research on the examined application domain,
                 and propose directions for future research.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Software Defined Networking (SDN) and
                 Network Function Virtualization (NFV).",
}

@Article{Mambou:2018:NCV,
  author =       "Sebastien Mambou and Ondrej Krejcar and Kamil Kuca and
                 Ali Selamat",
  title =        "Novel Cross-View Human Action Model Recognition Based
                 on the Powerful View-Invariant Features Technique",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "9",
  pages =        "89",
  day =          "13",
  month =        sep,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10090089",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:02 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/9/89",
  abstract =     "One of the most important research topics nowadays is
                 human action recognition, which is of significant
                 interest to the computer vision and machine learning
                 communities. Some of the factors that hamper it include
                 changes in postures and shapes and the memory space and
                 time required to gather, store, label, and process the
                 pictures. During our research, we noted a considerable
                 complexity to recognize human actions from different
                 viewpoints, and this can be explained by the position
                 and orientation of the viewer related to the position
                 of the subject. We attempted to address this issue in
                 this paper by learning different special view-invariant
                 facets that are robust to view variations. Moreover, we
                 focused on providing a solution to this challenge by
                 exploring view-specific as well as view-shared facets
                 utilizing a novel deep model called the sample-affinity
                 matrix (SAM). These models can accurately determine the
                 similarities among samples of videos in diverse angles
                 of the camera and enable us to precisely fine-tune
                 transfer between various views and learn more detailed
                 shared facets found in cross-view action
                 identification. Additionally, we proposed a novel
                 view-invariant facets algorithm that enabled us to
                 better comprehend the internal processes of our
                 project. Using a series of experiments applied on INRIA
                 Xmas Motion Acquisition Sequences (IXMAS) and the
                 Northwestern--UCLA Multi-view Action 3D (NUMA)
                 datasets, we were able to show that our technique
                 performs much better than state-of-the-art
                 techniques.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Abbasi:2018:VMA,
  author =       "Aaqif Afzaal Abbasi and Hai Jin",
  title =        "{v-Mapper}: An Application-Aware Resource
                 Consolidation Scheme for Cloud Data Centers",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "9",
  pages =        "90",
  day =          "15",
  month =        sep,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10090090",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:02 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/9/90",
  abstract =     "Cloud computing systems are popular in computing
                 industry for their ease of use and wide range of
                 applications. These systems offer services that can be
                 used over the Internet. Due to their wide popularity
                 and usage, cloud computing systems and their services
                 often face issues resource management related
                 challenges. In this paper, we present v-Mapper, a
                 resource consolidation scheme which implements network
                 resource management concepts through software-defined
                 networking (SDN) control features. The paper makes
                 three major contributions: (1) We propose a virtual
                 machine (VM) placement scheme that can effectively
                 mitigate the VM placement issues for data-intensive
                 applications; (2) We propose a validation scheme that
                 will ensure that a cloud service is entertained only if
                 there are sufficient resources available for its
                 execution and (3) We present a scheduling policy that
                 aims to eliminate network load constraints. We tested
                 our scheme with other techniques in terms of average
                 task processing time, service delay and bandwidth
                 usage. Our results demonstrate that v-Mapper
                 outperforms other techniques and delivers significant
                 improvement in system's performance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Software Defined Networking (SDN) and
                 Network Function Virtualization (NFV).",
}

@Article{Bendjima:2018:ICW,
  author =       "Mostefa Bendjima and Mohammed Feham",
  title =        "Intelligent Communication in Wireless Sensor
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "9",
  pages =        "91",
  day =          "15",
  month =        sep,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10090091",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:02 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/9/91",
  abstract =     "Wireless sensor networks (WSN) are designed to collect
                 information by means of a large number of
                 energy-limited battery sensor nodes. Therefore, it is
                 important to minimize the energy consumed by each
                 sensor, in order to extend the network life. The goal
                 of this work is to design an intelligent WSN that
                 collects as much information as possible to process it
                 intelligently. To achieve this goal, an agent is sent
                 to each sensor in order to process the information and
                 to cooperate with neighboring sensors while mobile
                 agents (MA) can be used to reduce information shared
                 between source nodes (SN) and send them to the base
                 station (Sink). This work proposes to use communication
                 architecture for wireless sensor networks based on the
                 multi-agent system (MAS) to ensure optimal information
                 collection. The collaboration of these agents generates
                 a simple message that summarizes the important
                 information in order to transmit it by a mobile agent.
                 To reduce the size of the MA, the sensors of the
                 network have been grouped into sectors. For each MA, we
                 have established an optimal itinerary, consuming a
                 minimum amount of energy with data aggregation
                 efficiency in a minimum time. Successive simulations in
                 large-scale wireless sensor networks through the
                 SINALGO (published under a BSD license) simulator show
                 the performance of the proposed method, in terms of
                 energy consumption and package delivery rate.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Teng:2018:OAU,
  author =       "Qianru Teng and Yimin Chen and Chen Huang",
  title =        "Occlusion-Aware Unsupervised Learning of Monocular
                 Depth, Optical Flow and Camera Pose with Geometric
                 Constraints",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "10",
  pages =        "92",
  day =          "21",
  month =        sep,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10100092",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:02 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/10/92",
  abstract =     "We present an occlusion-aware unsupervised neural
                 network for jointly learning three low-level vision
                 tasks from monocular videos: depth, optical flow, and
                 camera motion. The system consists of three different
                 predicting sub-networks simultaneously coupled by
                 combined loss terms and is capable of computing each
                 task independently on test samples. Geometric
                 constraints extracted from scene geometry which have
                 traditionally been used in bundle adjustment or
                 pose-graph optimization are formed as various
                 self-supervisory signals during our end-to-end learning
                 approach. Different from prior works, our image
                 reconstruction loss also takes account of optical flow.
                 Moreover, we impose novel 3D flow consistency
                 constraints over the predictions of all the three
                 tasks. By explicitly modeling occlusion and taking
                 utilization of both 2D and 3D geometry relationships,
                 abundant geometric constraints are formed over
                 estimated outputs, enabling the system to capture both
                 low-level representations and high-level cues to infer
                 thinner scene structures. Empirical evaluation on the
                 KITTI dataset demonstrates the effectiveness and
                 improvement of our approach: (1) monocular depth
                 estimation outperforms state-of-the-art unsupervised
                 methods and is comparable to stereo supervised ones;
                 (2) optical flow prediction ranks top among prior works
                 and even beats supervised and traditional ones
                 especially in non-occluded regions; (3) pose estimation
                 outperforms established SLAM systems under comparable
                 input settings with a reasonable margin.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Said:2018:PCE,
  author =       "Anwar Said and Syed Waqas Haider Shah and Hasan Farooq
                 and Adnan Noor Mian and Ali Imran and Jon Crowcroft",
  title =        "Proactive Caching at the Edge Leveraging Influential
                 User Detection in Cellular {D2D} Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "10",
  pages =        "93",
  day =          "21",
  month =        sep,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10100093",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:02 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/10/93",
  abstract =     "Caching close to users in a radio access network (RAN)
                 has been identified as a promising method to reduce a
                 backhaul traffic load and minimize latency in 5G and
                 beyond. In this paper, we investigate a novel community
                 detection inspired by a proactive caching scheme for
                 device-to-device (D2D) enabled networks. The proposed
                 scheme builds on the idea that content
                 generated/accessed by influential users is more
                 probable to become popular and thus can be exploited
                 for pro-caching. We use a Clustering Coefficient based
                 Genetic Algorithm (CC-GA) for community detection to
                 discover a group of cellular users present in close
                 vicinity. We then use an Eigenvector Centrality measure
                 to identify the influential users with respect to the
                 community structure, and the content associated to it
                 is then used for pro-active caching using D2D
                 communications. The numerical results show that,
                 compared to reactive caching, where historically
                 popular content is cached, depending on cache size,
                 load and number of requests, up to 30\% more users can
                 be satisfied using a proposed scheme while achieving
                 significant reduction in backhaul traffic load.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yuan:2018:ICP,
  author =       "Peiyan Yuan and Xiaoxiao Pang and Xiaoyan Zhao",
  title =        "Influence of Crowd Participation Features on Mobile
                 Edge Computing",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "10",
  pages =        "94",
  day =          "25",
  month =        sep,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10100094",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:02 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/10/94",
  abstract =     "Mobile edge computing is a new communication paradigm,
                 which stores content close to the end users, so as to
                 reduce the backhaul delay and alleviate the traffic
                 load of the backbone networks. Crowd participation is
                 one of the most striking features of this technology,
                 and it enables numerous interesting applications. The
                 dynamics of crowd participation offer unprecedented
                 opportunities for both content caching and data
                 forwarding. In this paper, we investigate the influence
                 of the dynamics of crowd participation, from the
                 perspective of opportunistic caching and forwarding,
                 and discuss how we can exploit such opportunities to
                 allocate content and select relays efficiently. Some
                 existing issues in this emerging research area are also
                 discussed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wu:2018:CEE,
  author =       "Yue Wu and Junyi Zhang",
  title =        "{Chinese} Event Extraction Based on Attention and
                 Semantic Features: a Bidirectional Circular Neural
                 Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "10",
  pages =        "95",
  day =          "26",
  month =        sep,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10100095",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:02 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/10/95",
  abstract =     "Chinese event extraction uses word embedding to
                 capture similarity, but suffers when handling
                 previously unseen or rare words. From the test, we know
                 that characters may provide some information that we
                 cannot obtain in words, so we propose a novel
                 architecture for combining word representations:
                 character--word embedding based on attention and
                 semantic features. By using an attention mechanism, our
                 method is able to dynamically decide how much
                 information to use from word or character level
                 embedding. With the semantic feature, we can obtain
                 some more information about a word from the sentence.
                 We evaluate different methods on the CEC Corpus, and
                 this method is found to improve performance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Big Data and Augmented Intelligence.",
}

@Article{Hussein:2018:MBA,
  author =       "Isam A. Hussein and Basil H. Jasim and Ramzy S. Ali",
  title =        "A Modified {BA} Anti-Collision Protocol for Coping
                 with Capture Effect and Interference in {RFID}
                 Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "10",
  pages =        "96",
  day =          "01",
  month =        oct,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10100096",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:02 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/10/96",
  abstract =     "Radio frequency identification (RFID) technology has
                 widely been used in the last few years. Its
                 applications focus on auto identification, tracking,
                 and data capturing issues. However, RFID suffers from
                 the main problem of tags collision when multiple tags
                 simultaneously respond to the reader request. Many
                 protocols were proposed to solve the collision problems
                 with good identification efficiency and an acceptable
                 time delay, such as the blocking anti-collision
                 protocol (BA). Nevertheless, most of these protocols
                 assumed that the RFID reader could decode the tag's
                 signal only when there was one tag responding to the
                 reader request once each time. Hence, they ignored the
                 phenomenon of the capture effect, which results in
                 identifying the tag with the stronger signal as the
                 multiple tags simultaneously respond. As a result, many
                 tags will not be identified under the capture effect.
                 Therefore, the purpose of this paper is to take the
                 capture effect phenomenon into consideration in order
                 to modify the blocking BA protocol to ensure a full
                 read rate, i.e., identifying all the tags in the frame
                 without losing any tag. Moreover, the modifications
                 include distinguishing between collision and
                 interference responses (for the period of staying tags)
                 in the noisy environments, for the purpose of enhancing
                 the efficiency of the identification. Finally, the
                 simulation and analytical results show that our
                 modifications and MBA protocol outperform the previous
                 protocols in the same field, such as generalized query
                 tree protocols (GQT1 and GQT2), general binary tree
                 (GBT), and tweaked binary tree (TBT).",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue New Developments in RFID Technologies
                 and Applications and Their Integration into IoT.",
}

@Article{Zhang:2018:ECP,
  author =       "Yu Zhang and Bingjia Shao",
  title =        "The Effect of Customer Participation Types on Online
                 Recovery Satisfaction: a Mental Accounting
                 Perspective",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "10",
  pages =        "97",
  day =          "03",
  month =        oct,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10100097",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:02 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/10/97",
  abstract =     "With the high popularity of the Internet, online
                 trading has gradually replaced the traditional shopping
                 model and extended to every corner of social life.
                 However, online trading cannot avoid failures; thus,
                 understanding how firms can best recover customers in
                 online contexts to keep customer loyalty is very
                 important. This study investigates the mechanisms by
                 which customer participation types (physical, mental,
                 and emotional) promote customers' perceived justice and
                 post-recovery satisfaction from a mental accounting
                 perspective. Furthermore, the moderating effects of two
                 modes of online apology speech acts (direct and
                 indirect) on customer participation and perceived
                 justice are investigated. A total of 1083 Chinese
                 tourists who have purchased a Wi-Fi rental service in
                 the past year were contacted according to the database
                 provided by two travel agencies, and 329 stated having
                 experienced an online recovery service and participated
                 in the survey; 297 valid questionnaires were collected.
                 Among them, 48.82\% were males and 51.18\% females.
                 Most of the respondents were aged 20--35 years. By
                 carrying out data analysis by partial least squares
                 structural equation modeling (PLS-SEM) using SmartPLS,
                 the results show that, first, only mental and physical
                 participation can enhance perceived justice, while
                 emotional participation does not influence perceived
                 justice. Second, the positive influence of mental
                 participation on perceived justice is most significant.
                 Third, only when the service staff adopts the indirect
                 mode to express an online apology, mental and physical
                 participation can enhance perceived justice.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Techno-Social Smart Systems.",
}

@Article{Hardaha:2018:SDR,
  author =       "Prakash Narayan Hardaha and Shailendra Singh",
  title =        "Structured Data {REST} Protocol for End to End Data
                 Mashup",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "10",
  pages =        "98",
  day =          "04",
  month =        oct,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10100098",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:02 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/10/98",
  abstract =     "Due to the exponential growth of the data and its
                 services, visiting multiple webs/apps by a user raises
                 three issues-(1) consumption of extra bytes; (2) time
                 killing process of surfing inside the webs/apps; (3)
                 tedious task of remembering address of webs/apps with
                 their credentials. The data mashup is a set of
                 techniques and user-friendly approaches which not only
                 resolves above issues but also allows ordinary user to
                 fetch required data from multiple disparate data
                 sources and to create the integrated view in his
                 defined digital place. In this paper, we have proposed
                 an extension of existing REST protocol called
                 Structured Data REST (SDRest) protocol and
                 user-friendly novel approach which allows even ordinary
                 users to develop end to end data mashup, using the
                 innovative concept of Structured Data Mashup Box (SDMB)
                 and One Time Configuration (OTC)-Any Time Access (ATA)
                 models. Our implementation shows that pre-mashup
                 configuration can easily be performed by an ordinary
                 user and an integrated user interface view of end user
                 data mashup can be created without any technical
                 knowledge or programming. We have also evaluated the
                 proposed work by comparing it with some of the related
                 works and found that the proposed work has developed
                 user friendly configurable approach using the current
                 state of the art techniques to involve not only the
                 ordinary user but also the mashup service provider and
                 the data service provider to develop public, private
                 and hybrid data mashup.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Collection Information Systems Security.",
}

@Article{Tran:2018:OMD,
  author =       "Tien Anh Tran",
  title =        "The Optimization of Marine Diesel Engine Rotational
                 Speed Control Process by Fuzzy Logic Control Based on
                 Particle Swarm Optimization Algorithm",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "10",
  pages =        "99",
  day =          "04",
  month =        oct,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10100099",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:02 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/10/99",
  abstract =     "The marine main diesel engine rotational speed
                 automatic control plays a significant role in
                 determining the optimal main diesel engine speed under
                 impacting on navigation environment conditions. In this
                 article, the application of fuzzy logic control theory
                 for main diesel engine speed control has been
                 associated with Particle Swarm Optimization (PSO).
                 Firstly, the controller is designed according to fuzzy
                 logic control theory. Secondly, the fuzzy logic
                 controller will be optimized by Particle Swarm
                 Optimization (PSO) in order to obtain the optimal
                 adjustment of the membership functions only. Finally,
                 the fuzzy logic controller has been completely
                 innovated by Particle Swarm Optimization algorithm. The
                 study results will be represented under digital
                 simulation form, as well as comparison between
                 traditional fuzzy logic controller with fuzzy logic
                 control-particle swarm optimization speed controller
                 being obtained.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue New Perspectives in Intelligent
                 Transportation Systems and Mobile Communications
                 towards a Smart Cities Context.",
}

@Article{Uslander:2018:ASE,
  author =       "Thomas Usl{\"a}nder and Thomas Batz",
  title =        "Agile Service Engineering in the {Industrial Internet
                 of Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "10",
  pages =        "100",
  day =          "09",
  month =        oct,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10100100",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:02 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/10/100",
  abstract =     "The emerging Industrial Internet of Things (IIoT) will
                 not only leverage new and potentially disruptive
                 business models but will also change the way software
                 applications will be analyzed and designed. Agility is
                 a need in a systematic service engineering as well as a
                 co-design of requirements and architectural artefacts.
                 Functional and non-functional requirements of IT users
                 (in smart manufacturing mostly from the disciplines of
                 mechanical engineering and electrical engineering) need
                 to be mapped to the capabilities and interaction
                 patterns of emerging IIoT service platforms, not to
                 forget the corresponding information models. The
                 capabilities of such platforms are usually described,
                 structured, and formalized by software architects and
                 software engineers. However, their technical
                 descriptions are far away from the thinking and the
                 thematic terms of end-users. This complicates the
                 transition from requirements analysis to system design,
                 and hence the re-use of existing and the design of
                 future platform capabilities. Current software
                 engineering methodologies do not systematically cover
                 these interlinked and two-sided aspects. The article
                 describes in a comprehensive manner how to close this
                 gap with the help of a service-oriented analysis and
                 design methodology entitled SERVUS (also mentioned in
                 ISO 19119 Annex D) and a corresponding Web-based
                 Platform Engineering Information System (PEIS).",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Khan:2018:RHD,
  author =       "Sara Khan and Claudio Germak",
  title =        "Reframing {HRI} Design Opportunities for Social
                 Robots: Lessons Learnt from a Service Robotics Case
                 Study Approach Using {UX} for {HRI}",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "10",
  pages =        "101",
  day =          "10",
  month =        oct,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10100101",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:02 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/10/101",
  abstract =     "Over the last few decades, semi-autonomous machine's
                 technology started to promote awareness towards the
                 importance of human--robot interaction (HRI) for
                 improving daily activities. More affordable social
                 robots are being commercially released and in order to
                 implement viable applications of HRI, a combination
                 human-computer interaction and user experience
                 methodologies could play a pivotal role in assessing
                 new scenarios and evaluating new investigations.
                 However, literature shows that it is still challenging
                 to reach an optimal user experience with robotic
                 companions. The aim of the study was to determine the
                 chance to enhance the user experience with a
                 semi-autonomous social robot, using user experience and
                 human--computer interaction methodologies. In this
                 study, a social robotic companion has been developed
                 and prototyped in order to be adopted in a specific
                 public environment such as a company workspace. The
                 challenges emerged from this peculiar environment
                 triggered the need for a more productive and
                 comfortable office for the employees, and, at the same
                 time, the usability, acceptance and likeability of the
                 robotic companion have been evaluated. The results
                 emphasize that, since HRI is highly interdisciplinary,
                 the benefits of combining approaches from other fields
                 could positively benefit from a meaningful social
                 interaction with the users.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Xu:2018:EAS,
  author =       "Yi-Han Xu and Qiu-Ya Sun and Yu-Tong Xiao",
  title =        "An Environmentally Aware Scheme of Wireless Sensor
                 Networks for Forest Fire Monitoring and Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "10",
  pages =        "102",
  day =          "19",
  month =        oct,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10100102",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:02 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/10/102",
  abstract =     "Forest fires are a fatal threat to environmental
                 degradation. Wireless sensor networks (WSNs) are
                 regarded as a promising candidate for forest fire
                 monitoring and detection since they enable real-time
                 monitoring and early detection of fire threats in an
                 efficient way. However, compared to conventional
                 surveillance systems, WSNs operate under a set of
                 unique resource constraints, including limitations with
                 respect to transmission range, energy supply and
                 computational capability. Considering that long
                 transmission distance is inevitable in harsh
                 geographical features such as woodland and shrubland,
                 energy-efficient designs of WSNs are crucial for
                 effective forest fire monitoring and detection systems.
                 In this paper, we propose a novel framework that
                 harnesses the benefits of WSNs for forest fire
                 monitoring and detection. The framework employs random
                 deployment, clustered hierarchy network architecture
                 and environmentally aware protocols. The goal is to
                 accurately detect a fire threat as early as possible
                 while maintaining a reasonable energy consumption
                 level. ns-2-based simulation validates that the
                 proposed framework outperforms the conventional schemes
                 in terms of detection delay and energy consumption.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ibba:2018:ICO,
  author =       "Simona Ibba and Andrea Pinna and Maria Ilaria Lunesu
                 and Michele Marchesi and Roberto Tonelli",
  title =        "Initial Coin Offerings and Agile Practices",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "11",
  pages =        "103",
  day =          "23",
  month =        oct,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10110103",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:03 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/11/103",
  abstract =     "An ICO (Initial Coin Offering) is an innovative way to
                 fund projects based on blockchain. The funding is based
                 on the selling of tokens by means of decentralized
                 applications called smart contracts written in
                 Solidity, a programming language specific for Ethereum
                 blockchain. The ICOs work in a volatile context and it
                 is crucial that the team is capable of handling
                 constant changes. The Agile methods, proven practices
                 enabling to develop software in presence of changing
                 requirements, could be a means for managing
                 uncertainty. The main goals of this work are to
                 understand software engineering activities related to
                 ICOs, recognize the ICOs developed using Agile methods,
                 and make a comparison between ICOs and Agile ICOs. In
                 addition, we perform a deeper analysis of Agile ICOs
                 concerning project planning, software development, and
                 code features. Our work shows that the roles of the
                 people involved in an ICO can be compared to the
                 typical roles of the SCRUM methodology. The majority of
                 Agile ICOs use tool of testing before storing smart
                 contract on blockchain. Finally, the application of
                 volumetric and complexity software metrics shows that
                 the files of Agile ICOs is on average shorter and less
                 complex than in other smart contracts.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2018:RBM,
  author =       "Chuang Wang and Xu'nan Chen and Abdel-Hamid Ali
                 Soliman and Zhixiang Zhu",
  title =        "{RFID} Based Manufacturing Process of Cloud {MES}",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "11",
  pages =        "104",
  day =          "30",
  month =        oct,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10110104",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:03 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/11/104",
  abstract =     "RFID (radio frequency identification) is widely used
                 in the manufacturing processes of enterprises. At the
                 same time, with the advent of the Industry 4.0 era,
                 Manufacturing Execution System (MES) systems began to
                 evolve into cloud MES systems. In this paper, a
                 RFID-based manufacturing process for cloud MES is
                 proposed and a framework manufacturing process for a
                 cloud MES system centered on machine tools is
                 constructed. The process division of the manufacturing
                 process, RFID configuration and cloud processing are
                 analyzed, and other key technologies involved in
                 implementing the framework are briefly discussed.
                 Finally, the effectiveness of a RFID-based
                 manufacturing process of cloud MES is verified by two
                 different types of case analysis namely photovoltaic
                 slice production and garment outsourcing processing.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue New Developments in RFID Technologies
                 and Applications and Their Integration into IoT.",
}

@Article{Li:2018:IPI,
  author =       "YangQun Li",
  title =        "An Integrated Platform for the {Internet of Things}
                 Based on an Open Source Ecosystem",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "11",
  pages =        "105",
  day =          "31",
  month =        oct,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10110105",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:03 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/gnu.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/11/105",
  abstract =     "The Internet of Things (IoT) is increasingly part of
                 daily life. However, the development of IoT
                 applications still faces many problems, such as
                 heterogeneity, complex management, and other
                 difficulties. In this paper, first, the open source
                 technologies of IoT are surveyed. We compare these
                 technologies from the point of view of different levels
                 of technical requirements, such as device management,
                 data management, communication, intelligent data
                 processing, security and privacy protection; we also
                 look at requirements of application development and
                 deployment. Second, an IoT integrated development
                 platform architecture for IoT applications based on
                 open source ecosystem is proposed and evaluated in an
                 industrial setting. We applied P2P technology to
                 distributed resource management and blockchain-based
                 smart contract mechanics for resource billing
                 management. The results show that the IoT gateway based
                 on an open source ecosystem had a stable and reliable
                 system performance with a certain data size and
                 concurrency scale. These conditions satisfy the
                 application requirements of the IoT in most sensing
                 environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Internet of Things.",
}

@Article{Ji:2018:DIR,
  author =       "Wusheng Ji and Li Li and Weiwei Zhou",
  title =        "Design and Implementation of a {RFID} Reader\slash
                 Router in {RFID-WSN} Hybrid System",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "11",
  pages =        "106",
  day =          "03",
  month =        nov,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10110106",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:03 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/11/106",
  abstract =     "In order to put Radio Frequency Identification (RFID)
                 and Wireless Sensor Network (WSN) in a hybrid system,
                 this paper presents the design and implementation of a
                 RFID reader/router that can obtain information of both
                 RFID tags and WSN sensor nodes and transmit the
                 information through the WSN to the PC server. The RFID
                 reader and WSN router are combined with both hardware
                 and software. In hardware structure, CC2530 is used as
                 micro controller and RF module for ZigBee wireless
                 communication, and MF RC522 is used as reader RF chip.
                 The software deals with both identity and sensing
                 information and controls the routing. Experiment
                 results show that the RFID reader/router achieves long
                 distance identification, flexibility, scalability, and
                 low cost. It also provides reliable and secured data
                 transmission and broadens the communication range and
                 application scope of RFID readers.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Nikoloudakis:2018:CSR,
  author =       "Yannis Nikoloudakis and Spyridon Panagiotakis and
                 Thrasivoulos Manios and Evangelos Markakis and
                 Evangelos Pallis",
  title =        "Composting as a Service: a Real-World {IoT}
                 Implementation",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "11",
  pages =        "107",
  day =          "05",
  month =        nov,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10110107",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:03 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/11/107",
  abstract =     "Composting is the delicate procedure of supervised
                 decomposition of organic waste, which gradually
                 transforms waste to nutrient-rich manure. It requires
                 deep knowledge and constant attention by experts to
                 achieve a quality outcome in a timely fashion.
                 Nevertheless, due to the bizarre nature of the
                 materials and the overall procedure, along with the
                 space required and emitted odors, it is required that
                 composting infrastructures and machinery are installed
                 away from residential areas, rendering supervision a
                 very tedious task. Automatic composting machinery is a
                 promising new idea, but still cannot substitute the
                 insightfulness of a human supervisor. In this paper, we
                 introduce COMPosting as a Service (COMPaaS). COMPaaS is
                 a novel cloud service in composition with specialized
                 Internet of Things (IoT)-based composting machinery
                 that allows for unsupervised composting. The focus of
                 this work is on the tiered IT approach that is adopted
                 following the edge-computing paradigm. More
                 specifically, composting machinery, enriched with
                 several sensors and actuators, performs a set of basic
                 routine tasks locally and sends sensor values to a
                 cloud service which performs real-time data analysis
                 and instructs the composting machinery to perform the
                 appropriate actions based on the outcome of the
                 analysis. The overall composting procedure is performed
                 in a completely unsupervised manner, and field
                 evaluation has shown an up to 30\% faster outcome in
                 comparison to traditional supervised composting.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Internet of Things.",
}

@Article{Tsiropoulou:2018:QEC,
  author =       "Eirini Eleni Tsiropoulou and George Kousis and Athina
                 Thanou and Ioanna Lykourentzou and Symeon
                 Papavassiliou",
  title =        "Quality of Experience in Cyber-Physical Social Systems
                 Based on Reinforcement Learning and Game Theory",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "11",
  pages =        "108",
  day =          "07",
  month =        nov,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10110108",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:03 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/11/108",
  abstract =     "This paper addresses the problem of museum visitors'
                 Quality of Experience (QoE) optimization by viewing and
                 treating the museum environment as a cyber-physical
                 social system. To achieve this goal, we harness
                 visitors' internal ability to intelligently sense their
                 environment and make choices that improve their QoE in
                 terms of which the museum touring option is the best
                 for them and how much time to spend on their visit. We
                 model the museum setting as a distributed
                 non-cooperative game where visitors selfishly maximize
                 their own QoE. In this setting, we formulate the
                 problem of Recommendation Selection and Visiting Time
                 Management (RSVTM) and propose a two-stage distributed
                 algorithm based on game theory and reinforcement
                 learning, which learns from visitor behavior to make
                 on-the-fly recommendation selections that maximize
                 visitor QoE. The proposed framework enables autonomic
                 visitor-centric management in a personalized manner and
                 enables visitors themselves to decide on the best
                 visiting strategies. Experimental results evaluating
                 the performance of the proposed RSVTM algorithm under
                 realistic simulation conditions indicate the high
                 operational effectiveness and superior performance when
                 compared to other recommendation approaches. Our
                 results constitute a practical alternative for museums
                 and exhibition spaces meant to enhance visitor QoE in a
                 flexible, efficient, and cost-effective manner.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Giddings:2018:RDB,
  author =       "Roger Giddings and Xiao Duan and Ehab Al-Rawachy and
                 Mingzhi Mao",
  title =        "A Review of {DSP}-Based Enabling Technologies for
                 Cloud Access Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "11",
  pages =        "109",
  day =          "15",
  month =        nov,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10110109",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:03 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/11/109",
  abstract =     "Optical access networks, metro networks and mobile
                 data networks are facing rapidly evolving demands, not
                 only is it essential to satisfy the unyielding need for
                 increased user bandwidths, but future networks must
                 also support the growing wide variation in traffic
                 dynamics and characteristics, due to various emerging
                 technologies, such as cloud-based services, the
                 Internet-of-Things (IoT) and 5G mobile systems, and due
                 to growing trends, such as the proliferation of mobile
                 devices and the rapidly increasing popularity of
                 video-on-demand services. To be cost-effective and
                 commercially sustainable, future optical networks must
                 offer features, such as, dynamic reconfigurability,
                 highly efficient use of network resources, elastic
                 bandwidth provisioning with fine granularity, network
                 sliceabilty and software defined networking (SDN). To
                 meet these requirements Cloud Access Networks (CANs)
                 are proposed which require a number of flexible,
                 adaptive and reconfigurable networking elements. By
                 exploiting digital signal processing (DSP) we have
                 proposed a digital orthogonal filter-based multiplexing
                 technique to implement CANs with multiplexed,
                 independent optical channels at the wavelength,
                 sub-wavelength, and orthogonal sub-band levels. This
                 paper reviews the overall CAN concept, the operating
                 principles of the various CAN network elements and
                 presents an overview of the research work we have
                 undertaken in order to validate the feasibility of the
                 proposed technologies which includes real-time
                 DSP-based demonstrations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Recent Advances in DSP-Based Optical
                 Communications.",
}

@Article{Zhai:2018:IEM,
  author =       "Linbo Zhai and Wenwen Jiang",
  title =        "Intelligent Environment Monitoring System for
                 University Laboratories",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "11",
  pages =        "110",
  day =          "16",
  month =        nov,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10110110",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:03 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/11/110",
  abstract =     "In recent years, the laboratory security of
                 universities has become an important issue for students
                 and devices. To solve this security issue, this paper
                 proposes an intelligent monitoring system to realize
                 environment detection in university laboratories. The
                 main purpose of this system is to monitor the
                 laboratory environment data in time and improve the
                 laboratory inspection efficiency. The system consists
                 of a single chip microcomputer, which is the core of
                 this system, a sensor function module and GPRS wireless
                 communication, realizing data monitoring and short
                 message warning. Therefore, three features, front-end
                 data acquisition, data wireless transmission and a
                 security alarm, are achieved by the proposed system.
                 The real experiments show that front-end data
                 acquisition is effective, data transmission is
                 reliable, and the alarm message is received in time.
                 Furthermore, the system, with the modified function
                 modules, can be used in other scenarios to detect
                 environments, and thus has a significant applied value
                 in other areas.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Internet of Things.",
}

@Article{Song:2018:NSC,
  author =       "Anping Song and Zuoyu Wu and Xuehai Ding and Qian Hu
                 and Xinyi Di",
  title =        "Neurologist Standard Classification of Facial Nerve
                 Paralysis with Deep Neural Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "11",
  pages =        "111",
  day =          "16",
  month =        nov,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10110111",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:03 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/11/111",
  abstract =     "Facial nerve paralysis (FNP) is the most common form
                 of facial nerve damage, which leads to significant
                 physical pain and abnormal function in patients.
                 Traditional FNP detection methods are based on visual
                 diagnosis, which relies solely on the physician's
                 assessment. The use of objective measurements can
                 reduce the frequency of errors which are caused by
                 subjective methods. Hence, a fast, accurate, and
                 objective computer method for FNP classification is
                 proposed that uses a single Convolutional neural
                 network (CNN), trained end-to-end directly from images,
                 with only pixels and disease labels as inputs. We
                 trained the CNN using a dataset of 1049 clinical images
                 and divided the dataset into 7 categories based on
                 classification standards with the help of neurologists.
                 We tested its performance against the neurologists'
                 ground truth, and our results matched the neurologists'
                 level with 97.5\% accuracy.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Innovative Topologies and Algorithms for
                 Neural Networks.",
}

@Article{Xu:2018:QRU,
  author =       "Jialu Xu and Feiyue Ye",
  title =        "Query Recommendation Using Hybrid Query Relevance",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "11",
  pages =        "112",
  day =          "19",
  month =        nov,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10110112",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:03 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/11/112",
  abstract =     "With the explosion of web information, search engines
                 have become main tools in information retrieval.
                 However, most queries submitted in web search are
                 ambiguous and multifaceted. Understanding the queries
                 and mining query intention is critical for search
                 engines. In this paper, we present a novel query
                 recommendation algorithm by combining query information
                 and URL information which can get wide and accurate
                 query relevance. The calculation of query relevance is
                 based on query information by query co-concurrence and
                 query embedding vector. Adding the ranking to query-URL
                 pairs can calculate the strength between query and URL
                 more precisely. Empirical experiments are performed
                 based on AOL log. The results demonstrate the
                 effectiveness of our proposed query recommendation
                 algorithm, which achieves superior performance compared
                 to other algorithms.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Big Data and Augmented Intelligence.",
}

@Article{Li:2018:CTC,
  author =       "Yue Li and Xutao Wang and Pengjian Xu",
  title =        "{Chinese} Text Classification Model Based on Deep
                 Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "11",
  pages =        "113",
  day =          "20",
  month =        nov,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10110113",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:03 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/11/113",
  abstract =     "Text classification is of importance in natural
                 language processing, as the massive text information
                 containing huge amounts of value needs to be classified
                 into different categories for further use. In order to
                 better classify text, our paper tries to build a deep
                 learning model which achieves better classification
                 results in Chinese text than those of other
                 researchers' models. After comparing different methods,
                 long short-term memory (LSTM) and convolutional neural
                 network (CNN) methods were selected as deep learning
                 methods to classify Chinese text. LSTM is a special
                 kind of recurrent neural network (RNN), which is
                 capable of processing serialized information through
                 its recurrent structure. By contrast, CNN has shown its
                 ability to extract features from visual imagery.
                 Therefore, two layers of LSTM and one layer of CNN were
                 integrated to our new model: the BLSTM-C model (BLSTM
                 stands for bi-directional long short-term memory while
                 C stands for CNN.) LSTM was responsible for obtaining a
                 sequence output based on past and future contexts,
                 which was then input to the convolutional layer for
                 extracting features. In our experiments, the proposed
                 BLSTM-C model was evaluated in several ways. In the
                 results, the model exhibited remarkable performance in
                 text classification, especially in Chinese texts.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Innovative Topologies and Algorithms for
                 Neural Networks.",
}

@Article{Ali:2018:PSI,
  author =       "Shaukat Ali and Naveed Islam and Azhar Rauf and Ikram
                 Ud Din and Mohsen Guizani and Joel J. P. C. Rodrigues",
  title =        "Privacy and Security Issues in Online Social
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "12",
  pages =        "114",
  day =          "22",
  month =        nov,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10120114",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:03 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/12/114",
  abstract =     "The advent of online social networks (OSN) has
                 transformed a common passive reader into a content
                 contributor. It has allowed users to share information
                 and exchange opinions, and also express themselves in
                 online virtual communities to interact with other users
                 of similar interests. However, OSN have turned the
                 social sphere of users into the commercial sphere. This
                 should create a privacy and security issue for OSN
                 users. OSN service providers collect the private and
                 sensitive data of their customers that can be misused
                 by data collectors, third parties, or by unauthorized
                 users. In this paper, common security and privacy
                 issues are explained along with recommendations to OSN
                 users to protect themselves from these issues whenever
                 they use social media.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Yang:2018:VBH,
  author =       "Wanli Yang and Yimin Chen and Chen Huang and Mingke
                 Gao",
  title =        "Video-Based Human Action Recognition Using Spatial
                 Pyramid Pooling and {3D} Densely Convolutional
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "12",
  pages =        "115",
  day =          "22",
  month =        nov,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10120115",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:03 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/12/115",
  abstract =     "In recent years, the application of deep neural
                 networks to human behavior recognition has become a hot
                 topic. Although remarkable achievements have been made
                 in the field of image recognition, there are still many
                 problems to be solved in the area of video. It is well
                 known that convolutional neural networks require a
                 fixed size image input, which not only limits the
                 network structure but also affects the recognition
                 accuracy. Although this problem has been solved in the
                 field of images, it has not yet been broken through in
                 the field of video. To address the input problem of
                 fixed size video frames in video recognition, we
                 propose a three-dimensional (3D) densely connected
                 convolutional network based on spatial pyramid pooling
                 (3D-DenseNet-SPP). As the name implies, the network
                 structure is mainly composed of three parts: 3DCNN,
                 DenseNet, and SPPNet. Our models were evaluated on a
                 KTH dataset and UCF101 dataset separately. The
                 experimental results showed that our model has better
                 performance in the field of video-based behavior
                 recognition in comparison to the existing models.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Techno-Social Smart Systems.",
}

@Article{Zhu:2018:BDL,
  author =       "Yonghua Zhu and Xun Gao and Weilin Zhang and Shenkai
                 Liu and Yuanyuan Zhang",
  title =        "A Bi-Directional {LSTM-CNN} Model with Attention for
                 Aspect-Level Text Classification",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "12",
  pages =        "116",
  day =          "24",
  month =        nov,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10120116",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:03 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/12/116",
  abstract =     "The prevalence that people share their opinions on the
                 products and services in their daily lives on the
                 Internet has generated a large quantity of comment
                 data, which contain great business value. As for
                 comment sentences, they often contain several comment
                 aspects and the sentiment on these aspects are
                 different, which makes it meaningless to give an
                 overall sentiment polarity of the sentence. In this
                 paper, we introduce Attention-based Aspect-level
                 Recurrent Convolutional Neural Network (AARCNN) to
                 analyze the remarks at aspect-level. The model
                 integrates attention mechanism and target information
                 analysis, which enables the model to concentrate on the
                 important parts of the sentence and to make full use of
                 the target information. The model uses bidirectional
                 LSTM (Bi-LSTM) to build the memory of the sentence, and
                 then CNN is applied to extracting attention from memory
                 to get the attentive sentence representation. The model
                 uses aspect embedding to analyze the target information
                 of the representation and finally the model outputs the
                 sentiment polarity through a softmax layer. The model
                 was tested on multi-language datasets, and demonstrated
                 that it has better performance than conventional deep
                 learning methods.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Big Data Processing and Analytics in the
                 Era of Extreme Connectivity and Automation.",
}

@Article{Wang:2018:PRA,
  author =       "Bo Wang and Feiyue Ye and Jialu Xu",
  title =        "A Personalized Recommendation Algorithm Based on the
                 User's Implicit Feedback in E-Commerce",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "12",
  pages =        "117",
  day =          "29",
  month =        nov,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10120117",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:03 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/12/117",
  abstract =     "A recommendation system can recommend items of
                 interest to users. However, due to the scarcity of user
                 rating data and the similarity of single ratings, the
                 accuracy of traditional collaborative filtering
                 algorithms (CF) is limited. Compared with user rating
                 data, the user's behavior log is easier to obtain and
                 contains a large amount of implicit feedback
                 information, such as the purchase behavior, comparison
                 behavior, and sequences of items (item-sequences). In
                 this paper, we proposed a personalized recommendation
                 algorithm based on a user's implicit feedback (BUIF).
                 BUIF considers not only the user's purchase behavior
                 but also the user's comparison behavior and
                 item-sequences. We extracted the purchase behavior,
                 comparison behavior, and item-sequences from the user's
                 behavior log; calculated the user's similarity by
                 purchase behavior and comparison behavior; and extended
                 word-embedding to item-embedding to obtain the item's
                 similarity. Based on the above method, we built a
                 secondary reordering model to generate the
                 recommendation results for users. The results of the
                 experiment on the JData dataset show that our algorithm
                 shows better improvement in regard to recommendation
                 accuracy over other CF algorithms.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Data Science for Internet of Things.",
}

@Article{Wei:2018:DBG,
  author =       "Jinlong Wei and Ji Zhou and Elias Giacoumidis and Paul
                 A. Haigh and Jianming Tang",
  title =        "{DSP}-Based {40 GB/s} Lane Rate Next-Generation Access
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "12",
  pages =        "118",
  day =          "30",
  month =        nov,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10120118",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:03 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/12/118",
  abstract =     "To address the continuous growth in high-speed
                 ubiquitous access required by residential users and
                 enterprises, Telecommunication operators must upgrade
                 their networks to higher data rates. For optical fiber
                 access networks that directly connect end users to
                 metro/regional network, capacity upgrade must be done
                 in a cost- and energy-efficient manner. 40 Gb/s is the
                 possible lane rate for the next generation passive
                 optical networks (NG-PONs). Ideally, existing 10 G PON
                 components could be reused to support 40 Gb/s lane-rate
                 NG-PON transceiver, which requires efficient modulation
                 format and digital signal processing (DSP) to alleviate
                 the bandwidth limitation and fiber dispersion. The
                 major contribution of this work is to offer insight
                 performance comparisons of 40 Gb/s lane rate electrical
                 three level Duobinary, optical Duobinary, and
                 four-level pulse amplitude modulation (PAM-4) for
                 incorporating low complex DSPs, including linear and
                 nonlinear Volterra equalization, as well as maximum
                 likelihood sequence estimation. Detailed analysis and
                 comparison of the complexity of various DSP algorithms
                 are performed. Transceiver bandwidth optimization is
                 also undertaken. The results show that the choices of
                 proper modulation format and DSP configuration depend
                 on the transmission distances of interest.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Recent Advances in DSP-Based Optical
                 Communications.",
}

@Article{R:2018:SDM,
  author =       "Jithin R and Priya Chandran",
  title =        "Secure and Dynamic Memory Management Architecture for
                 Virtualization Technologies in {IoT} Devices",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "12",
  pages =        "119",
  day =          "30",
  month =        nov,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10120119",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:03 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/12/119",
  abstract =     "The introduction of the internet in embedded devices
                 led to a new era of technology --- the Internet of
                 Things (IoT) era. The IoT technology-enabled device
                 market is growing faster by the day, due to its
                 complete acceptance in diverse areas such as domicile
                 systems, the automobile industry, and beyond. The
                 introduction of internet connectivity in objects that
                 are frequently used in daily life raises the question
                 of security --- how secure is the information and the
                 infrastructure handled by these devices when they are
                 connected to the internet? Security enhancements
                 through standard cryptographic techniques are not
                 suitable due to the power and performance constraints
                 of IoT devices. The introduction of virtualization
                 technology into IoT devices is a recent development,
                 meant for fulfilling security and performance needs.
                 However, virtualization augments the vulnerability
                 present in IoT devices, due to the addition of one more
                 software layer --- namely, the hypervisor, which
                 enables the sharing of resources among different users.
                 This article proposes the adaptation of ASMI
                 (Architectural Support for Memory Isolation --- a
                 general architecture available in the literature for
                 the improvement of the performance and security of
                 virtualization technology) on the popular MIPS
                 (Microprocessor without Interlocked Pipeline Stages)
                 embedded virtualization platform, which could be
                 adopted in embedded virtualization architectures for
                 IoT devices. The article illustrates the performance
                 enhancement achieved by the proposed architecture with
                 the existing architectures.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue IoT Security and Privacy.",
}

@Article{Collodi:2018:PRC,
  author =       "Stefania Collodi and Sara Panerati and Enrico Imbimbo
                 and Federica Stefanelli and Mirko Duradoni and Andrea
                 Guazzini",
  title =        "Personality and Reputation: a Complex Relationship in
                 Virtual Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "12",
  pages =        "120",
  day =          "01",
  month =        dec,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10120120",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:03 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/12/120",
  abstract =     "Online reputational systems are nowadays widely and
                 effectively adopted by several online platforms to
                 support and improve peoples' interactions and
                 communication. Despite the research approached and
                 modeled social dynamics of reputational systems in
                 different domains, adopting different frameworks, the
                 role played by psycho-social factors, and personality
                 traits, determining the individual susceptibility to
                 online reputation is still elusive. To study such
                 mediation effects, we implemented a modified online
                 version of the Ultimatum Game, in which participants
                 (215 adolescents) played before as proposers, and then
                 as responders, always knowing the reputation of their
                 interactors. Furthermore, after the reception phase,
                 participants could evaluate the received offers, giving
                 positive or negative feedback to their proposers.
                 Despite the participants' belief they were playing with
                 their schoolmates, the interactors' role was always
                 fulfilled by bots characterized by standardized
                 behaviors. Our results show how psychological traits
                 influence the participants' behavior in all the game
                 phases, as well as in the rating dynamics. Reputation
                 seems to have a direct effect only in the allocation
                 behavior, while, in regards the other dynamics of the
                 game (i.e., acceptance and rating), it comes into play
                 in a complex interaction with the psychological
                 dimensions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Vishwakarma:2018:EJM,
  author =       "Gopal Vishwakarma and Wonjun Lee",
  title =        "Exploiting {JTAG} and Its Mitigation in {IOT}: a
                 Survey",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "12",
  pages =        "121",
  day =          "03",
  month =        dec,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10120121",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:03 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/12/121",
  abstract =     "Nowadays, companies are heavily investing in the
                 development of ``Internet of Things(IoT)'' products.
                 These companies usually and obviously hunt for
                 lucrative business models. Currently, each person owns
                 at least 3-4 devices (such as mobiles, personal
                 computers, Google Assistant, Alexa, etc.) that are
                 connected to the Internet 24/7. However, in the future,
                 there might be hundreds of devices that will be
                 constantly online behind each person, keeping track of
                 body health, banking transactions, status of personal
                 devices, etc. to make one's life more efficient and
                 streamlined. Thus, it is very crucial that each device
                 should be highly secure since one's life will become
                 dependent on these devices. However, the current
                 security of IoT devices is mainly focused on resiliency
                 of device. In addition, less complex node devices are
                 easily accessible to the public resulting in higher
                 vulnerability. JTAG is an IEEE standard that has been
                 defined to test proper mounting of components on PCBs
                 (printed circuit boards) and has been extensively used
                 by PCB manufacturers to date. This JTAG interface can
                 be used as a backdoor entry to access and exploit
                 devices, also defined as a physical attack. This attack
                 can be used to make products malfunction, modify data,
                 or, in the worst case, stop working. This paper reviews
                 previous successful JTAG exploitations of well-known
                 devices operating online and also reviews some proposed
                 possible solutions to see how they can affect IoT
                 products in a broader sense.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue IoT Security and Privacy.",
}

@Article{Chen:2018:CPM,
  author =       "Zubin Chen and Baijun Lu and Yanzhou Zhu and Hao Lv",
  title =        "A Compact Printed Monopole Antenna for {WiMAX\slash
                 WLAN} and {UWB} Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "12",
  pages =        "122",
  day =          "13",
  month =        dec,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10120122",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:03 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/12/122",
  abstract =     "In this paper, a printed monopole antenna design for
                 WiMAX/WLAN applications in cable-free self-positioning
                 seismograph nodes is proposed. Great improvements were
                 achieved in miniaturizing the antenna and in widening
                 the narrow bandwidth of the high-frequency band. The
                 antenna was fed by a microstrip gradient line and
                 consisted of a triangle, an inverted-F shape, and an
                 M-shaped structure, which was rotated 90\&deg;
                 counterclockwise to form a surface-radiating patch.
                 This structure effectively widened the operating
                 bandwidth of the antenna. Excitation led to the
                 generation of two impedance bands of 2.39--2.49 and
                 4.26--7.99 GHz for a voltage standing wave ratio of
                 less than 2. The two impedance bandwidths were 100 MHz,
                 i.e., 4.08\% relative to the center frequency of 2.45
                 GHz, and 3730 MHz, i.e., 64.31\% relative to the center
                 frequency of 5.80 GHz, covering the WiMAX
                 high-frequency band (5.25--5.85 GHz) and the WLAN band
                 (2.4/5.2/5.8). This article describes the design
                 details of the antenna and presents the results of both
                 simulations and experiments that show good agreement.
                 The proposed antenna meets the field-work requirements
                 of cable-less seismograph nodes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ali:2018:BRN,
  author =       "Mohammed N. A. Ali and Guanzheng Tan and Aamir
                 Hussain",
  title =        "Bidirectional Recurrent Neural Network Approach for
                 {Arabic} Named Entity Recognition",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "12",
  pages =        "123",
  day =          "13",
  month =        dec,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10120123",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:03 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/12/123",
  abstract =     "Recurrent neural network (RNN) has achieved remarkable
                 success in sequence labeling tasks with memory
                 requirement. RNN can remember previous information of a
                 sequence and can thus be used to solve natural language
                 processing (NLP) tasks. Named entity recognition (NER)
                 is a common task of NLP and can be considered a
                 classification problem. We propose a bidirectional long
                 short-term memory (LSTM) model for this entity
                 recognition task of the Arabic text. The LSTM network
                 can process sequences and relate to each part of it,
                 which makes it useful for the NER task. Moreover, we
                 use pre-trained word embedding to train the inputs that
                 are fed into the LSTM network. The proposed model is
                 evaluated on a popular dataset called ``ANERcorp.''
                 Experimental results show that the model with word
                 embedding achieves a high F-score measure of
                 approximately 88.01\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Innovative Topologies and Algorithms for
                 Neural Networks.",
}

@Article{Deng:2018:MFP,
  author =       "Ziyun Deng and Tingqin He",
  title =        "A Method for Filtering Pages by Similarity Degree
                 based on Dynamic Programming",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "12",
  pages =        "124",
  day =          "13",
  month =        dec,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10120124",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:03 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/12/124",
  abstract =     "To obtain the target webpages from many webpages, we
                 proposed a Method for Filtering Pages by Similarity
                 Degree based on Dynamic Programming (MFPSDDP). The
                 method needs to use one of three same relationships
                 proposed between two nodes, so we give the definition
                 of the three same relationships. The biggest innovation
                 of MFPSDDP is that it does not need to know the
                 structures of webpages in advance. First, we address
                 the design ideas with queue and double threads. Then, a
                 dynamic programming algorithm for calculating the
                 length of the longest common subsequence and a formula
                 for calculating similarity are proposed. Further, for
                 obtaining detailed information webpages from 200,000
                 webpages downloaded from the famous website
                 ``www.jd.com'', we choose the same relationship
                 Completely Same Relationship (CSR) and set the
                 similarity threshold to 0.2. The Recall Ratio (RR) of
                 MFPSDDP is in the middle in the four filtering methods
                 compared. When the number of webpages filtered is
                 nearly 200,000, the PR of MFPSDDP is highest in the
                 four filtering methods compared, which can reach
                 85.1\%. The PR of MFPSDDP is 13.3 percentage points
                 higher than the PR of a Method for Filtering Pages by
                 Containing Strings (MFPCS).",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Big Data Processing and Analytics in the
                 Era of Extreme Connectivity and Automation.",
}

@Article{Pecorella:2018:NSF,
  author =       "Tommaso Pecorella and Laura Pierucci and Francesca
                 Nizzi",
  title =        "''{Network} Sentiment'' Framework to Improve Security
                 and Privacy for Smart Home",
  journal =      j-FUTURE-INTERNET,
  volume =       "10",
  number =       "12",
  pages =        "125",
  day =          "19",
  month =        dec,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi10120125",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:03 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/10/12/125",
  abstract =     "A Smart Home is characterized by the presence of a
                 huge number of small, low power devices, along with
                 more classical devices. According to the Internet of
                 Things (IoT) paradigm, all of them are expected to be
                 always connected to the Internet in order to provide
                 enhanced services. In this scenario, an attacker can
                 undermine both the network security and the user's
                 security/privacy. Traditional security measures are not
                 sufficient, because they are too difficult to setup and
                 are either too weak to effectively protect the user or
                 too limiting for the new services effectiveness. The
                 paper suggests to dynamically adapt the security level
                 of the smart home network according to the user
                 perceived risk level what we have called network
                 sentiment analysis. The security level is not fixed,
                 established by a central system (usually by the
                 Internet Service Provider) but can be changed with the
                 users cooperation. The security of the smart home
                 network is improved by a distributed firewalls and
                 Intrusion Detection Systems both to the smart home side
                 as to the Internet Service Provider side. These two
                 parts must cooperate and integrate their actions for
                 reacting dynamically to new and on going threats.
                 Moreover, the level of network sentiment detected can
                 be propagate to nearby home networks (e.g., the smart
                 home networks of the apartments inside a building) to
                 increase/decrease their level of security, thus
                 creating a true in-line Intrusion Prevention System
                 (IPS). The paper also presents a test bed for Smart
                 Home to detect and counteract to different attacks
                 against the IoT sensors, Wi-Fi and Ethernet
                 connections.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue IoT Security and Privacy.",
}

@Article{Silva:2019:BUM,
  author =       "Cristiano M. Silva and Lucas D. Silva and Leonardo A.
                 L. Santos and Jo{\~a}o F. M. Sarubbi and Andreas
                 Pitsillides",
  title =        "Broadening Understanding on Managing the Communication
                 Infrastructure in Vehicular Networks: Customizing the
                 Coverage Using the Delta Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "1",
  pages =        "1",
  day =          "20",
  month =        dec,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11010001",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/1/1",
  abstract =     "Over the past few decades, the growth of the urban
                 population has been remarkable. Nowadays, 50\% of the
                 population lives in urban areas, and forecasts point
                 that by 2050 this number will reach 70\%. Today, 64\%
                 of all travel made is within urban environments and the
                 total amount of urban kilometers traveled is expected
                 to triple by 2050. Thus, seeking novel solutions for
                 urban mobility becomes paramount for 21st century
                 society. In this work, we discuss the performance of
                 vehicular networks. We consider the metric Delta
                 Network. The Delta Network characterizes the
                 connectivity of the vehicular network through the
                 percentage of travel time in which vehicles are
                 connected to roadside units. This article reviews the
                 concept of the Delta Network and extends its study
                 through the presentation of a general heuristic based
                 on the definition of scores to identify the areas of
                 the road network that should receive coverage. After
                 defining the general heuristic, we show how small
                 changes in the score computation can generate very
                 distinct (and interesting) patterns of coverage, each
                 one suited to a given scenario. In order to exemplify
                 such behavior, we propose three deployment strategies
                 based on simply changing the computation of scores. We
                 compare the proposed strategies to the intuitive
                 strategy of allocating communication units at the most
                 popular zones of the road network. Experiments show
                 that the strategies derived from the general heuristic
                 provide higher coverage than the intuitive strategy
                 when using the same number of communication devices.
                 Moreover, the resulting pattern of coverage is very
                 interesting, with roadside units deployed a circle
                 pattern around the traffic epicenter.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 5G Network Solutions for Automotive
                 Services.",
}

@Article{Giacoumidis:2019:HML,
  author =       "Elias Giacoumidis and Yi Lin and Jinlong Wei and Ivan
                 Aldaya and Athanasios Tsokanos and Liam P. Barry",
  title =        "Harnessing machine learning for fiber-induced
                 nonlinearity mitigation in long-haul coherent optical
                 {OFDM}",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "1",
  pages =        "2",
  day =          "20",
  month =        dec,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11010002",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/1/2",
  abstract =     "Coherent optical orthogonal frequency division
                 multiplexing (CO-OFDM) has attracted a lot of interest
                 in optical fiber communications due to its simplified
                 digital signal processing (DSP) units, high
                 spectral-efficiency, flexibility, and tolerance to
                 linear impairments. However, CO-OFDM's high
                 peak-to-average power ratio imposes high vulnerability
                 to fiber-induced non-linearities. DSP-based machine
                 learning has been considered as a promising approach
                 for fiber non-linearity compensation without
                 sacrificing computational complexity. In this paper, we
                 review the existing machine learning approaches for
                 CO-OFDM in a common framework and review the progress
                 in this area with a focus on practical aspects and
                 comparison with benchmark DSP solutions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Recent Advances in DSP-Based Optical
                 Communications.",
}

@Article{Butun:2019:SRA,
  author =       "Ismail Butun and Nuno Pereira and Mikael Gidlund",
  title =        "Security Risk Analysis of {LoRaWAN} and Future
                 Directions",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "1",
  pages =        "3",
  day =          "21",
  month =        dec,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11010003",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/1/3",
  abstract =     "LoRa (along with its upper layers definition ---
                 LoRaWAN) is one of the most promising Low Power Wide
                 Area Network (LPWAN) technologies for implementing
                 Internet of Things (IoT)-based applications. Although
                 being a popular technology, several works in the
                 literature have revealed vulnerabilities and risks
                 regarding the security of LoRaWAN v1.0 (the official
                 1st specification draft). The LoRa-Alliance has built
                 upon these findings and introduced several improvements
                 in the security and architecture of LoRa. The result of
                 these efforts resulted in LoRaWAN v1.1, released on 11
                 October 2017. This work aims at reviewing and
                 clarifying the security aspects of LoRaWAN v1.1. By
                 following ETSI guidelines, we provide a comprehensive
                 Security Risk Analysis of the protocol and discuss
                 several remedies to the security risks described. A
                 threat catalog is presented, along with discussions and
                 analysis in view of the scale, impact, and likelihood
                 of each threat. To the best of the authors' knowledge,
                 this work is one of the first of its kind, by providing
                 a detailed security risk analysis related to the latest
                 version of LoRaWAN. Our analysis highlights important
                 practical threats, such as end-device physical capture,
                 rogue gateway and self-replay, which require particular
                 attention by developers and organizations implementing
                 LoRa networks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue IoT Security and Privacy.",
}

@Article{Marabissi:2019:RCI,
  author =       "Dania Marabissi and Lorenzo Mucchi and Romano Fantacci
                 and Maria Rita Spada and Fabio Massimiani and Andrea
                 Fratini and Giorgio Cau and Jia Yunpeng and Lucio
                 Fedele",
  title =        "A Real Case of Implementation of the Future {5G}
                 City",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "1",
  pages =        "4",
  day =          "22",
  month =        dec,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11010004",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/1/4",
  abstract =     "The fifth generation (5G) of wireless communication
                 systems is considered the key technology to enable a
                 wide range of application scenarios and the effective
                 spreading of the smart city concept. Vertical business
                 use cases, specifically designed for the future 5G
                 city, will have a strong economical and social impact.
                 For this reason, ongoing 5G field trials have to test
                 newly deployed technologies as well as the capability
                 of 5G to create a new digital economy. This paper
                 describes the 5G field trial environment that was
                 launched in Italy at the end of 2017. The aim is to
                 evaluate the capability of the 5G network of supporting
                 innovative services with reference to suitably designed
                 key performance indicators and to evaluate the
                 opportunities offered by these services. Indeed,
                 vertical business use cases, specifically designed for
                 the future 5G city, with a strong economic and social
                 impact, are under implementation and will be evaluated.
                 In particular, the paper provides a detailed
                 description of the deployment of an actual complete
                 integrated 5G network. It shows how 5G is effective
                 enabling technology for a wide range of vertical
                 business and use cases. Indeed, its flexibility allows
                 to satisfy completely different performance
                 requirements of real services. Some preliminary
                 results, obtained during the first phase, are presented
                 for a smart mobility scenario.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Carta:2019:FCP,
  author =       "Salvatore Carta and Andrea Medda and Alessio Pili and
                 Diego Reforgiato Recupero and Roberto Saia",
  title =        "Forecasting E-Commerce Products Prices by Combining an
                 Autoregressive Integrated Moving Average ({ARIMA})
                 Model and {Google Trends} Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "1",
  pages =        "5",
  day =          "24",
  month =        dec,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11010005",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/1/5",
  abstract =     "E-commerce is becoming more and more the main
                 instrument for selling goods to the mass market. This
                 led to a growing interest in algorithms and techniques
                 able to predict products future prices, since they
                 allow us to define smart systems able to improve the
                 quality of life by suggesting more affordable goods and
                 services. The joint use of time series, reputation and
                 sentiment analysis clearly represents one important
                 approach to this research issue. In this paper we
                 present Price Probe, a suite of software tools
                 developed to perform forecasting on products' prices.
                 Its primary aim is to predict the future price trend of
                 products generating a customized forecast through the
                 exploitation of autoregressive integrated moving
                 average (ARIMA) model. We experimented the
                 effectiveness of the proposed approach on one of the
                 biggest E-commerce infrastructure in the world: Amazon.
                 We used specific APIs and dedicated crawlers to extract
                 and collect information about products and their
                 related prices over time and, moreover, we extracted
                 information from social media and Google Trends that we
                 used as exogenous features for the ARIMA model. We
                 fine-estimated ARIMA's parameters and tried the
                 different combinations of the exogenous features and
                 noticed through experimental analysis that the presence
                 of Google Trends information significantly improved the
                 predictions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Ali:2019:FIE,
  author =       "Syed Mustafa Ali and Ana Filomena Curralo and Maged N.
                 Kamel Boulos and Sara Paiva",
  title =        "A Framework for Improving the Engagement of Medical
                 Practitioners in an E-Training Platform for
                 Tuberculosis Care and Prevention",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "1",
  pages =        "6",
  day =          "28",
  month =        dec,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11010006",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/1/6",
  abstract =     "We propose a new framework to improve the engagement
                 of medical practitioners in a planned e-training
                 platform for the successful identification and
                 effective management of presumptive cases of
                 tuberculosis (TB) in Pakistan. Our work is aligned with
                 the World Health Organization's TB-DOTS (Directly
                 Observed Treatment Short-course) strategy for promoting
                 the effective management of tuberculosis. We start by
                 presenting previous work done at Mercy Corps Pakistan
                 for training medical practitioners, then present the
                 results of a recent survey we administered to a random
                 sample of medical practitioners in Pakistan to learn
                 about their requirements and readiness to embrace a new
                 e-training platform and methodology. Informed by
                 feedback from the survey, we formulated a detailed
                 requirement analysis of the five key learning areas (or
                 phases) that we believe are fundamental to the success
                 of a TB e-training platform. Moreover, survey results
                 revealed that an on-spot, on-demand, and
                 competency-based learning tool can potentially improve
                 the engagement of medical practitioners in the process.
                 Building on the insights gained from the survey, we
                 finally describe our initial UX (user experience)
                 prototypes for phase 1, which corresponds to the
                 identification of presumptive tuberculosis cases.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue New Advances in E-Health.",
}

@Article{Grimaldi:2019:LWC,
  author =       "Matteo Grimaldi and Valerio Tenace and Andrea
                 Calimera",
  title =        "Layer-Wise Compressive Training for Convolutional
                 Neural Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "1",
  pages =        "7",
  day =          "28",
  month =        dec,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11010007",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/1/7",
  abstract =     "Convolutional Neural Networks (CNNs) are
                 brain-inspired computational models designed to
                 recognize patterns. Recent advances demonstrate that
                 CNNs are able to achieve, and often exceed, human
                 capabilities in many application domains. Made of
                 several millions of parameters, even the simplest CNN
                 shows large model size. This characteristic is a
                 serious concern for the deployment on
                 resource-constrained embedded-systems, where
                 compression stages are needed to meet the stringent
                 hardware constraints. In this paper, we introduce a
                 novel accuracy-driven compressive training algorithm.
                 It consists of a two-stage flow: first, layers are
                 sorted by means of heuristic rules according to their
                 significance; second, a modified stochastic gradient
                 descent optimization is applied on less significant
                 layers such that their representation is collapsed into
                 a constrained subspace. Experimental results
                 demonstrate that our approach achieves remarkable
                 compression rates with low accuracy loss (\&lt;1\%).",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Selected papers from INTESA Workshop
                 2018.",
}

@Article{Cocco:2019:ABM,
  author =       "Luisanna Cocco and Roberto Tonelli and Michele
                 Marchesi",
  title =        "An Agent Based Model to Analyze the {Bitcoin} Mining
                 Activity and a Comparison with the Gold Mining
                 Industry",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "1",
  pages =        "8",
  day =          "02",
  month =        jan,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11010008",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/1/8",
  abstract =     "In this paper, we present an analysis of the mining
                 process of two popular assets, Bitcoin and gold. The
                 analysis highlights that Bitcoin, more specifically its
                 underlying technology, is a ``safe haven'' that allows
                 facing the modern environmental challenges better than
                 gold. Our analysis emphasizes that crypto-currencies
                 systems have a social and economic impact much smaller
                 than that of the traditional financial systems. We
                 present an analysis of the several stages needed to
                 produce an ounce of gold and an artificial agent-based
                 market model simulating the Bitcoin mining process and
                 allowing the quantification of Bitcoin mining costs. In
                 this market model, miners validate the Bitcoin
                 transactions using the proof of work as the consensus
                 mechanism, get a reward in Bitcoins, sell a fraction of
                 them to cover their expenses, and stay competitive in
                 the market by buying and divesting hardware units and
                 adjusting their expenses by turning off/on their
                 machines according to the signals provided by a
                 technical analysis indicator, the so-called relative
                 strength index.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhang:2019:ODN,
  author =       "Ying Zhang and Yimin Chen and Chen Huang and Mingke
                 Gao",
  title =        "Object Detection Network Based on Feature Fusion and
                 Attention Mechanism",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "1",
  pages =        "9",
  day =          "02",
  month =        jan,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11010009",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/1/9",
  abstract =     "In recent years, almost all of the current
                 top-performing object detection networks use CNN
                 (convolutional neural networks) features.
                 State-of-the-art object detection networks depend on
                 CNN features. In this work, we add feature fusion in
                 the object detection network to obtain a better CNN
                 feature, which incorporates well deep, but semantic,
                 and shallow, but high-resolution, CNN features, thus
                 improving the performance of a small object. Also, the
                 attention mechanism was applied to our object detection
                 network, AF R-CNN (attention mechanism and convolution
                 feature fusion based object detection), to enhance the
                 impact of significant features and weaken background
                 interference. Our AF R-CNN is a single end to end
                 network. We choose the pre-trained network, VGG-16, to
                 extract CNN features. Our detection network is trained
                 on the dataset, PASCAL VOC 2007 and 2012. Empirical
                 evaluation of the PASCAL VOC 2007 dataset demonstrates
                 the effectiveness and improvement of our approach. Our
                 AF R-CNN achieves an object detection accuracy of
                 75.9\% on PASCAL VOC 2007, six points higher than
                 Faster R-CNN.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Innovative Topologies and Algorithms for
                 Neural Networks.",
}

@Article{Qin:2019:TCB,
  author =       "Jiwei Qin and Liangli Ma and Jinghua Niu",
  title =        "{THBase}: a Coprocessor-Based Scheme for Big
                 Trajectory Data Management",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "1",
  pages =        "10",
  day =          "03",
  month =        jan,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11010010",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/1/10",
  abstract =     "The rapid development of distributed technology has
                 made it possible to store and query massive trajectory
                 data. As a result, a variety of schemes for big
                 trajectory data management have been proposed. However,
                 the factor of data transmission is not considered in
                 most of these, resulting in a certain impact on query
                 efficiency. In view of that, we present THBase, a
                 coprocessor-based scheme for big trajectory data
                 management in HBase. THBase introduces a segment-based
                 data model and a moving-object-based partition model to
                 solve massive trajectory data storage, and exploits a
                 hybrid local secondary index structure based on
                 Observer coprocessor to accelerate spatiotemporal
                 queries. Furthermore, it adopts certain maintenance
                 strategies to ensure the colocation of relevant data.
                 Based on these, THBase designs node-locality-based
                 parallel query algorithms by Endpoint coprocessor to
                 reduce the overhead caused by data transmission, thus
                 ensuring efficient query performance. Experiments on
                 datasets of ship trajectory show that our schemes can
                 significantly outperform other schemes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Big Data Processing and Analytics in the
                 Era of Extreme Connectivity and Automation.",
}

@Article{Fahim:2019:ANI,
  author =       "Mohamed Fahim and Brahim Ouchao and Abdeslam Jakimi
                 and Lahcen {El Bermi}",
  title =        "Application of a Non-Immersive {VR}, {IoT} Based
                 Approach to Help {Moroccan} Students Carry Out
                 Practical Activities in a Personal Learning Style",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "1",
  pages =        "11",
  day =          "04",
  month =        jan,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11010011",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/1/11",
  abstract =     "In the last few years, the evolution of new
                 Information and Communication Technologies (ICT) and
                 networks has enabled the appearance and development of
                 several platforms and tools that serve to operate and
                 distribute the learning content. In some particular
                 domains, especially the scientific one, learners need
                 to work on practical activities, using specific
                 products and equipment to complete, consolidate, or
                 verify their conceptual acquisitions. However, facing
                 the increasing number of learners in Moroccan
                 institutions, it becomes hard and expensive for
                 developing countries, like Morocco, to ensure the
                 appropriate conditions for each learner to perform such
                 activities. The majority of the suggested platforms and
                 tools cannot solve this issue, because of their
                 inefficiency regarding offering students good
                 interactive practical activities. Virtual Reality (VR)
                 and the Internet of Things (IoT), as the two most
                 incredible technologies of the last few decades, can be
                 used as an alternative to create a virtual environment
                 where the learner can carry out practical activities
                 like in the real world. In such an environment,
                 learners interact with both virtual and physical
                 objects. In this research paper, we propose a new
                 approach based on VR and IoT to enhance learning by
                 providing learners with an educational space where they
                 can perform some practical activities. The hybrid
                 proposed approach has been used to create a virtual
                 environment where learners (the final year of high
                 school) can measure ultrasonic velocity in the air. The
                 evaluation results show that the manipulation and
                 coupling of real objects with virtual 3D objects
                 increases in a striking way the learning outcomes of
                 learners, as this allows them to feel linked to the
                 real context.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Internet of Things.",
}

@Article{Song:2019:JUD,
  author =       "Xin Song and Xiuwei Han and Yue Ni and Li Dong and Lei
                 Qin",
  title =        "Joint Uplink and Downlink Resource Allocation for
                 {D2D} Communications System",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "1",
  pages =        "12",
  day =          "06",
  month =        jan,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11010012",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/1/12",
  abstract =     "In cellular networks, device-to-device communications
                 can increase the spectrum efficiency, but some
                 conventional schemes only consider uplink or downlink
                 resource allocation. In this paper, we propose the
                 joint uplink and downlink resource allocation scheme
                 which maximizes the system capacity and guarantees the
                 signal-to-noise-and-interference ratio of both cellular
                 users and device-to-device pairs. The optimization
                 problem is formulated as a mixed integer nonlinear
                 problem that is usually NP hard. To achieve the
                 reasonable resource allocation, the optimization
                 problem is divided into two sub-problems including
                 power allocation and channel assignment. It is proved
                 that the objective function of power control is a
                 convex function, in which the optimal transmission
                 power can be obtained. The Hungarian algorithm is
                 developed to achieve joint uplink and downlink channel
                 assignment. The proposed scheme can improve the system
                 capacity performance and increase the spectrum
                 efficiency. Numerical results reveal that the
                 performance of the proposed scheme of jointly uplink
                 and downlink is better than that of the schemes for
                 independent allocation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Silva:2019:CPM,
  author =       "Marianne Silva and Gabriel Signoretti and Julio
                 Oliveira and Ivanovitch Silva and Daniel G. Costa",
  title =        "A Crowdsensing Platform for Monitoring of Vehicular
                 Emissions: a Smart City Perspective",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "1",
  pages =        "13",
  day =          "08",
  month =        jan,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11010013",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/1/13",
  abstract =     "Historically, cities follow reactive planning models
                 where managers make decisions as problems occur. On the
                 other hand, the exponential growth of Information and
                 Communication Technologies (ICT) has allowed the
                 connection of a diverse array of sensors, devices,
                 systems, and objects. These objects can then generate
                 data that can be transformed into information and used
                 in a more efficient urban planning paradigm, one that
                 allows decisions to be made before the occurrence of
                 problems and emergencies. Therefore, this article aims
                 to propose a platform capable of estimating the amount
                 of carbon dioxide based on sensor readings in vehicles,
                 indirectly contributing to a more proactive city
                 planning based on the monitoring of vehicular
                 pollution. Crowdsensing techniques and an On-Board
                 Diagnostic (OBD-II) reader are used to extract data
                 from vehicles in real time, which are then stored
                 locally on the devices used to perform data collection.
                 With the performed experiments, it was possible to
                 extract information about the operation of the vehicles
                 and their dynamics when moving in a city, providing
                 valuable information that can support auxiliary tools
                 for the management of urban centers.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue New Perspectives in Intelligent
                 Transportation Systems and Mobile Communications
                 towards a Smart Cities Context.",
}

@Article{Office:2019:ARF,
  author =       "Future Internet Editorial Office",
  title =        "Acknowledgement to Reviewers of {{\booktitle{Future
                 Internet}}} in 2018",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "1",
  pages =        "14",
  day =          "10",
  month =        jan,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11010014",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/1/14",
  abstract =     "Aiming at the complex structure of the space
                 information networks (SIN) and the dynamic change of
                 network topology, in order to design an efficient
                 routing strategy, this paper establishes a SIN
                 management architecture based on Software-defined
                 Networking (SDN). A routing algorithm flow of the
                 spatial information network based on a snapshot
                 sequence is designed. For different spatial tasks with
                 different Quality of Service (QoS) requirements, the
                 concept of integrated link weight is proposed. The
                 Warshall--Floyd algorithm is used to design the optimal
                 routing strategy. A Task-oriented Bandwidth Resource
                 Allocation (TBA) algorithm is proposed for multiple
                 spatial tasks in the same link. Simulation results show
                 that the algorithm can effectively guarantee the
                 priority transmission of important tasks and avoid the
                 unnecessary waste of bandwidth resources.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Meng:2019:MTR,
  author =       "Xiangli Meng and Lingda Wu and Shaobo Yu",
  title =        "Multi-Topology Routing Algorithms in {SDN}-Based Space
                 Information Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "1",
  pages =        "15",
  day =          "12",
  month =        jan,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11010015",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/1/15",
  abstract =     "Aiming at the complex structure of the space
                 information networks (SIN) and the dynamic change of
                 network topology, in order to design an efficient
                 routing strategy, this paper establishes a SIN
                 management architecture based on Software-defined
                 Networking (SDN). A routing algorithm flow of the
                 spatial information network based on a snapshot
                 sequence is designed. For different spatial tasks with
                 different Quality of Service (QoS) requirements, the
                 concept of integrated link weight is proposed. The
                 Warshall--Floyd algorithm is used to design the optimal
                 routing strategy. A Task-oriented Bandwidth Resource
                 Allocation (TBA) algorithm is proposed for multiple
                 spatial tasks in the same link. Simulation results show
                 that the algorithm can effectively guarantee the
                 priority transmission of important tasks and avoid the
                 unnecessary waste of bandwidth resources.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Oliveira:2019:MLP,
  author =       "Luiz Oliveira and Joel J. P. C. Rodrigues and Sergei
                 A. Kozlov and Ricardo A. L. Rab{\^e}lo and Victor Hugo
                 C. de Albuquerque",
  title =        "{MAC} Layer Protocols for {Internet of Things}: a
                 Survey",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "1",
  pages =        "16",
  day =          "14",
  month =        jan,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11010016",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/1/16",
  abstract =     "Due to the wide variety of uses and the diversity of
                 features required to meet an application, Internet of
                 Things (IoT) technologies are moving forward at a
                 strong pace to meet this demand while at the same time
                 trying to meet the time-to-market of these
                 applications. The characteristics required by
                 applications, such as coverage area, scalability,
                 transmission data rate, and applicability, refer to the
                 Physical and Medium Access Control (MAC) layer designs
                 of protocols. This paper presents a deep study of
                 medium access control (MAC) layer protocols that are
                 used in IoT with a detailed description of such
                 protocols grouped (by short and long distance
                 coverage). For short range coverage protocols, the
                 following are considered: Radio Frequency
                 Identification (RFID), Near Field Communication (NFC),
                 Bluetooth IEEE 802.15.1, Bluetooth Low Energy, IEEE
                 802.15.4, Wireless Highway Addressable Remote
                 Transducer Protocol (Wireless-HART), Z-Wave,
                 Weightless, and IEEE 802.11 a/b/g/n/ah. For the long
                 range group, Narrow Band IoT (NB-IoT), Long Term
                 Evolution (LTE) CAT-0, LTE CAT-M, LTE CAT-N, Long Range
                 Protocol (LoRa), and SigFox protocols are studied. A
                 comparative study is performed for each group of
                 protocols in order to provide insights and a reference
                 study for IoT applications, considering their
                 characteristics, limitations, and behavior. Open
                 research issues on the topic are also identified.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Xu:2019:FLE,
  author =       "Dong Xu and Ruping Ge and Zhihua Niu",
  title =        "Forward-Looking Element Recognition Based on the
                 {LSTM-CRF} Model with the Integrity Algorithm",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "1",
  pages =        "17",
  day =          "14",
  month =        jan,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11010017",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/1/17",
  abstract =     "A state-of-the-art entity recognition system relies on
                 deep learning under data-driven conditions. In this
                 paper, we combine deep learning with linguistic
                 features and propose the long short-term
                 memory-conditional random field model (LSTM-CRF model)
                 with the integrity algorithm. This approach is
                 primarily based on the use of part-of-speech (POS)
                 syntactic rules to correct the boundaries of LSTM-CRF
                 model annotations and improve its performance by
                 raising the integrity of the elements. The method
                 incorporates the advantages of the data-driven method
                 and dependency syntax, and improves the precision rate
                 of the elements without losing recall rate. Experiments
                 show that the integrity algorithm is not only easy to
                 combine with the other neural network model, but the
                 overall effect is better than several advanced methods.
                 In addition, we conducted cross-domain experiments
                 based on a multi-industry corpus in the financial
                 field. The results indicate that the method can be
                 applied to other industries.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Innovative Topologies and Algorithms for
                 Neural Networks.",
}

@Article{Wang:2019:ADU,
  author =       "Jinpeng Wang and G{\'e}rard Chalhoub and Michel
                 Misson",
  title =        "Adaptive Downward\slash Upward Routing Protocol for
                 Mobile-Sensor Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "1",
  pages =        "18",
  day =          "15",
  month =        jan,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11010018",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/1/18",
  abstract =     "Recently, mobility support has become an important
                 requirement in various Wireless Sensor Networks (WSNs).
                 Low-power and Lossy Networks (LLNs) are a special type
                 of WSNs that tolerate a certain degree of packet loss.
                 However, due to the strict resource constraints in the
                 computation, energy, and memory of LLNs, most routing
                 protocols only support static network topologies. Data
                 collection and data dissemination are two basic traffic
                 modes in LLNs. Unlike data collection, data
                 dissemination is less investigated in LLNs. There are
                 two sorts of data-dissemination methods:
                 point-to-multipoint and point-to-point. In this paper,
                 we focus on the point-to-point method, which requires
                 the source node to build routes to reach the
                 destination node. We propose an adaptive routing
                 protocol that integrates together point-to-point
                 traffic and data-collection traffic, and supports
                 highly mobile scenarios. This protocol quickly reacts
                 to the movement of nodes to make faster decisions for
                 the next-hop selection in data collection and
                 dynamically build routes for point-to-point traffic.
                 Results obtained through simulation show that our work
                 outperforms two generic ad hoc routing protocols AODV
                 and flooding on different performance metrics. Results
                 also show the efficiency of our work in highly mobile
                 scenarios with multiple traffic patterns.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Temoa:2019:RLB,
  author =       "Djorw{\'e} T{\'e}moa and Anna F{\"o}rster and Kolyang
                 and Serge Doka Yamigno",
  title =        "A Reinforcement Learning Based Intercell Interference
                 Coordination in {LTE} Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "1",
  pages =        "19",
  day =          "17",
  month =        jan,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11010019",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/1/19",
  abstract =     "Long Term Evolution networks, which are cellular
                 networks, are subject to many impairments due to the
                 nature of the transmission channel used, i.e. the air.
                 Intercell interference is the main impairment faced by
                 Long Term Evolution networks as it uses frequency reuse
                 one scheme, where the whole bandwidth is used in each
                 cell. In this paper, we propose a full dynamic
                 intercell interference coordination scheme with no
                 bandwidth partitioning for downlink Long Term Evolution
                 networks. We use a reinforcement learning approach. The
                 proposed scheme is a joint resource allocation and
                 power allocation scheme and its purpose is to minimize
                 intercell interference in Long Term Evolution networks.
                 Performances of proposed scheme shows quality of
                 service improvement in terms of SINR, packet loss and
                 delay compared to other algorithms.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fragkos:2019:EES,
  author =       "Georgios Fragkos and Pavlos Athanasios Apostolopoulos
                 and Eirini Eleni Tsiropoulou",
  title =        "{ESCAPE}: Evacuation Strategy through Clustering and
                 Autonomous Operation in Public Safety Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "1",
  pages =        "20",
  day =          "17",
  month =        jan,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11010020",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/1/20",
  abstract =     "Natural disasters and terrorist attacks pose a
                 significant threat to human society, and have stressed
                 an urgent need for the development of comprehensive and
                 efficient evacuation strategies. In this paper, a novel
                 evacuation-planning mechanism is introduced to support
                 the distributed and autonomous evacuation process
                 within the operation of a public safety system, where
                 the evacuees exploit the capabilities of the proposed
                 ESCAPE service, towards making the most beneficial
                 actions for themselves. The ESCAPE service was
                 developed based on the principles of reinforcement
                 learning and game theory, and is executed at two
                 decision-making layers. Initially, evacuees are modeled
                 as stochastic learning automata that select an
                 evacuation route that they want to go based on its
                 physical characteristics and past decisions during the
                 current evacuation. Consequently, a cluster of evacuees
                 is created per evacuation route, and the evacuees
                 decide if they will finally evacuate through the
                 specific evacuation route at the current time slot or
                 not. The evacuees' competitive behavior is modeled as a
                 non-co-operative minority game per each specific
                 evacuation route. A distributed and low-complexity
                 evacuation-planning algorithm (i.e., ESCAPE) is
                 introduced to implement both the aforementioned evacuee
                 decision-making layers. Finally, the proposed framework
                 is evaluated through modeling and simulation under
                 several scenarios, and its superiority and benefits are
                 revealed and demonstrated.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Guazzini:2019:EMA,
  author =       "Andrea Guazzini and Mirko Duradoni and Ambra Capelli
                 and Patrizia Meringolo",
  title =        "An Explorative Model to Assess Individuals' Phubbing
                 Risk",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "1",
  pages =        "21",
  day =          "18",
  month =        jan,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11010021",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/1/21",
  abstract =     "Phubbing could be defined as a new form of addiction;
                 however, checking the phone and ignoring the speaker
                 could also be linked to the increased availability of
                 virtual social environments. We developed a
                 multidimensional model for phubbing considering
                 psychological dimensions and information and
                 communication technology related habits. We collected
                 data through online questionnaires and surveys. The
                 best model obtained from our data was constituted by
                 Information and Communication Technologies' (ICTs)
                 usage behaviours, Trait Anxiety, Virtual Sense of
                 Community and Neuroticism. Finally, our study confirmed
                 a strong connection between phubbing and online
                 addiction behaviours.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Aqlan:2019:IAC,
  author =       "Fares Aqlan and Xiaoping Fan and Abdullah Alqwbani and
                 Akram Al-Mansoub",
  title =        "Improved {Arabic--Chinese} Machine Translation with
                 Linguistic Input Features",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "1",
  pages =        "22",
  day =          "19",
  month =        jan,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11010022",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/1/22",
  abstract =     "This study presents linguistically augmented models of
                 phrase-based statistical machine translation (PBSMT)
                 using different linguistic features (factors) on the
                 top of the source surface form. The architecture
                 addresses two major problems occurring in machine
                 translation, namely the poor performance of direct
                 translation from a highly-inflected and morphologically
                 complex language into morphologically poor languages,
                 and the data sparseness issue, which becomes a
                 significant challenge under low-resource conditions. We
                 use three factors (lemma, part-of-speech tags, and
                 morphological features) to enrich the input side with
                 additional information to improve the quality of direct
                 translation from Arabic to Chinese, considering the
                 importance and global presence of this language pair as
                 well as the limitation of work on machine translation
                 between these two languages. In an effort to deal with
                 the issue of the out of vocabulary (OOV) words and
                 missing words, we propose the best combination of
                 factors and models based on alternative paths. The
                 proposed models were compared with the standard PBSMT
                 model which represents the baseline of this work, and
                 two enhanced approaches tokenized by a state-of-the-art
                 external tool that has been proven to be useful for
                 Arabic as a morphologically rich and complex language.
                 The experiment was performed with a Moses decoder on
                 freely available data extracted from a multilingual
                 corpus from United Nation documents (MultiUN). Results
                 of a preliminary evaluation in terms of BLEU scores
                 show that the use of linguistic features on the Arabic
                 side considerably outperforms baseline and tokenized
                 approaches, the system can consistently reduce the OOV
                 rate as well.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Big Data and Augmented Intelligence.",
}

@Article{Leotta:2019:SHH,
  author =       "Francesco Leotta and Massimo Mecella and Daniele Sora
                 and Tiziana Catarci",
  title =        "Surveying Human Habit Modeling and Mining Techniques
                 in Smart Spaces",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "1",
  pages =        "23",
  day =          "19",
  month =        jan,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11010023",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/1/23",
  abstract =     "A smart space is an environment, mainly equipped with
                 Internet-of-Things (IoT) technologies, able to provide
                 services to humans, helping them to perform daily tasks
                 by monitoring the space and autonomously executing
                 actions, giving suggestions and sending alarms.
                 Approaches suggested in the literature may differ in
                 terms of required facilities, possible applications,
                 amount of human intervention required, ability to
                 support multiple users at the same time adapting to
                 changing needs. In this paper, we propose a Systematic
                 Literature Review (SLR) that classifies most
                 influential approaches in the area of smart spaces
                 according to a set of dimensions identified by
                 answering a set of research questions. These dimensions
                 allow to choose a specific method or approach according
                 to available sensors, amount of labeled data, need for
                 visual analysis, requirements in terms of enactment and
                 decision-making on the environment. Additionally, the
                 paper identifies a set of challenges to be addressed by
                 future research in the field.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Aboagye:2019:SEC,
  author =       "Emelia Opoku Aboagye and Rajesh Kumar",
  title =        "Simple and Efficient Computational Intelligence
                 Strategies for Effective Collaborative Decisions",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "1",
  pages =        "24",
  day =          "21",
  month =        jan,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11010024",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/1/24",
  abstract =     "We approach scalability and cold start problems of
                 collaborative recommendation in this paper. An
                 intelligent hybrid filtering framework that maximizes
                 feature engineering and solves cold start problem for
                 personalized recommendation based on deep learning is
                 proposed in this paper. Present e-commerce sites mainly
                 recommend pertinent items or products to a lot of users
                 through personalized recommendation. Such
                 personalization depends on large extent on scalable
                 systems which strategically responds promptly to the
                 request of the numerous users accessing the site (new
                 users). Tensor Factorization (TF) provides scalable and
                 accurate approach for collaborative filtering in such
                 environments. In this paper, we propose a hybrid-based
                 system to address scalability problems in such
                 environments. We propose to use a multi-task approach
                 which represent multiview data from users, according to
                 their purchasing and rating history. We use a Deep
                 Learning approach to map item and user
                 inter-relationship to a low dimensional feature space
                 where item-user resemblance and their preferred items
                 is maximized. The evaluation results from real world
                 datasets show that, our novel deep learning multitask
                 tensor factorization (NeuralFil) analysis is
                 computationally less expensive, scalable and addresses
                 the cold-start problem through explicit multi-task
                 approach for optimal recommendation decision making.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Dorgham:2019:SSP,
  author =       "Osama Dorgham and Ibrahim Al-Mherat and Jawdat
                 Al-Shaer and Sulieman Bani-Ahmad and Stephen Laycock",
  title =        "Smart System for Prediction of Accurate Surface
                 Electromyography Signals Using an Artificial Neural
                 Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "1",
  pages =        "25",
  day =          "21",
  month =        jan,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11010025",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/1/25",
  abstract =     "Bioelectric signals are used to measure electrical
                 potential, but there are different types of signals.
                 The electromyography (EMG) is a type of bioelectric
                 signal used to monitor and recode the electrical
                 activity of the muscles. The current work aims to model
                 and reproduce surface EMG (SEMG) signals using an
                 artificial neural network. Such research can aid
                 studies into life enhancement for those suffering from
                 damage or disease affecting their nervous system. The
                 SEMG signal is collected from the surface above the
                 bicep muscle through dynamic (concentric and eccentric)
                 contraction with various loads. In this paper, we use
                 time domain features to analyze the relationship
                 between the amplitude of SEMG signals and the load. We
                 extract some features (e.g., mean absolute value, root
                 mean square, variance and standard deviation) from the
                 collected SEMG signals to estimate the bicep' muscle
                 force for the various loads. Further, we use the
                 R-squared value to depict the correlation between the
                 SEMG amplitude and the muscle loads by linear fitting.
                 The best performance the ANN model with 60 hidden
                 neurons for three loads used (3 kg, 5 kg and 7 kg) has
                 given a mean square error of 1.145, 1.3659 and 1.4238,
                 respectively. The R-squared observed are 0.9993,
                 0.99999 and 0.99999 for predicting (reproduction step)
                 of smooth SEMG signals.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Privacy in Information and
                 Communication Systems.",
}

@Article{Li:2019:SPB,
  author =       "Yanli Li and Wendan Ma and Yue Han",
  title =        "A Spatial Prediction-Based Motion-Compensated Frame
                 Rate Up-Conversion",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "2",
  pages =        "26",
  day =          "23",
  month =        jan,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11020026",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/2/26",
  abstract =     "In Multimedia Internet of Things (IoT), in order to
                 reduce the bandwidth consumption of wireless channels,
                 Motion-Compensated Frame Rate Up-Conversion (MC-FRUC)
                 is often used to support the low-bitrate video
                 communication. In this paper, we propose a spatial
                 predictive algorithm which is used to improve the
                 performance of MC-FRUC. The core of the proposed
                 algorithm is a predictive model to split a frame into
                 two kinds of blocks: basic blocks and absent blocks.
                 Then an improved bilateral motion estimation is
                 proposed to compute the Motion Vectors (MVs) of basic
                 blocks. Finally, with the spatial correlation of Motion
                 Vector Field (MVF), the MV of an absent block is
                 predicted based on the MVs of its neighboring basic
                 blocks. Experimental results show that the proposed
                 spatial prediction algorithm can improve both the
                 objective and the subjective quality of the
                 interpolated frame, with a low computational
                 complexity.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Multimedia Internet of Things (IoT) in
                 Smart Environment.",
}

@Article{Arena:2019:OVC,
  author =       "Fabio Arena and Giovanni Pau",
  title =        "An Overview of Vehicular Communications",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "2",
  pages =        "27",
  day =          "24",
  month =        jan,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11020027",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/2/27",
  abstract =     "The transport sector is commonly subordinate to
                 several issues, such as traffic congestion and
                 accidents. Despite this, in recent years, it is also
                 evolving with regard to cooperation between vehicles.
                 The fundamental objective of this trend is to increase
                 road safety, attempting to anticipate the circumstances
                 of potential danger. Vehicle-to-Vehicle (V2V),
                 Vehicle-to-Infrastructure (V2I) and
                 Vehicle-to-Everything (V2X) technologies strive to give
                 communication models that can be employed by vehicles
                 in different application contexts. The resulting
                 infrastructure is an ad-hoc mesh network whose nodes
                 are not only vehicles but also all mobile devices
                 equipped with wireless modules. The interaction between
                 the multiple connected entities consists of information
                 exchange through the adoption of suitable communication
                 protocols. The main aim of the review carried out in
                 this paper is to examine and assess the most relevant
                 systems, applications, and communication protocols that
                 will distinguish the future road infrastructures used
                 by vehicles. The results of the investigation reveal
                 the real benefits that technological cooperation can
                 involve in road safety.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Korla:2019:MLW,
  author =       "Swaroopa Korla and Shanti Chilukuri",
  title =        "{T-Move}: a Light-Weight Protocol for Improved {QoS}
                 in Content-Centric Networks with Producer Mobility",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "2",
  pages =        "28",
  day =          "27",
  month =        jan,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11020028",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/2/28",
  abstract =     "Recent interest in applications where content is of
                 primary interest has triggered the exploration of a
                 variety of protocols and algorithms. For such networks
                 that are information-centric, architectures such as the
                 Content-Centric Networking have been proven to result
                 in good network performance. However, such
                 architectures are still evolving to cater for
                 application-specific requirements. This paper proposes
                 T-Move, a light-weight solution for producer mobility
                 and caching at the edge that is especially suitable for
                 content-centric networks with mobile content producers.
                 T-Move introduces a novel concept called trendiness of
                 data for Content-Centric Networking (CCN)/Named Data
                 Networking (NDN)-based networks. It enhances network
                 performance and quality of service (QoS) using two
                 strategies --- cache replacement and proactive
                 content-pushing for handling producer mobility --- both
                 based on trendiness. It uses simple operations and
                 smaller control message overhead and is suitable for
                 networks where the response needs to be quick.
                 Simulation results using ndnSIM show reduced traffic,
                 content retrieval time, and increased cache hit ratio
                 with T-Move, when compared to MAP-Me and plain NDN for
                 networks of different sizes and mobility rates.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Big Data and Augmented Intelligence.",
}

@Article{Udugama:2019:MST,
  author =       "Asanga Udugama and Jens Dede and Anna F{\"o}rster and
                 Vishnupriya Kuppusamy and Koojana Kuladinithi and
                 Andreas Timm-Giel and Zeynep Vatandas",
  title =        "My {Smartphone} tattles: Considering Popularity of
                 Messages in Opportunistic Data Dissemination",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "2",
  pages =        "29",
  day =          "29",
  month =        jan,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11020029",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/2/29",
  abstract =     "Opportunistic networks have recently seen increasing
                 interest in the networking community. They can serve a
                 range of application scenarios, most of them being
                 destination-less, i.e., without a-priori knowledge of
                 who is the final destination of a message. In this
                 paper, we explore the usage of data popularity for
                 improving the efficiency of data forwarding in
                 opportunistic networks. Whether a message will become
                 popular or not is not known before disseminating it to
                 users. Thus, popularity needs to be estimated in a
                 distributed manner considering a local context. We
                 propose Keetchi, a data forwarding protocol based on
                 Q-Learning to give more preference to popular data
                 rather than less popular data. Our extensive simulation
                 comparison between Keetchi and the well known Epidemic
                 protocol shows that the network overhead of data
                 forwarding can be significantly reduced while keeping
                 the delivery rate the same.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Opportunistic Networks in Urban
                 Environment.",
}

@Article{Boddy:2019:IHD,
  author =       "Aaron Boddy and William Hurst and Michael Mackay and
                 Abdennour {El Rhalibi} and Thar Baker and Casimiro A.
                 Curbelo Monta{\~n}ez",
  title =        "An Investigation into Healthcare-Data Patterns",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "2",
  pages =        "30",
  day =          "30",
  month =        jan,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11020030",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/2/30",
  abstract =     "Visualising complex data facilitates a more
                 comprehensive stage for conveying knowledge. Within the
                 medical data domain, there is an increasing requirement
                 for valuable and accurate information. Patients need to
                 be confident that their data is being stored safely and
                 securely. As such, it is now becoming necessary to
                 visualise data patterns and trends in real-time to
                 identify erratic and anomalous network access
                 behaviours. In this paper, an investigation into
                 modelling data flow within healthcare infrastructures
                 is presented; where a dataset from a Liverpool-based
                 (UK) hospital is employed for the case study.
                 Specifically, a visualisation of transmission control
                 protocol (TCP) socket connections is put forward, as an
                 investigation into the data complexity and user
                 interaction events within healthcare networks. In
                 addition, a filtering algorithm is proposed for noise
                 reduction in the TCP dataset. Positive results from
                 using this algorithm are apparent on visual inspection,
                 where noise is reduced by up to 89.84\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Smart Systems for Healthcare.",
}

@Article{Parchin:2019:DBM,
  author =       "Naser Ojaroudi Parchin and Haleh Jahanbakhsh Basherlou
                 and Raed A. Abd-Alhameed and James M. Noras",
  title =        "Dual-Band Monopole Antenna for {RFID} Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "2",
  pages =        "31",
  day =          "30",
  month =        jan,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11020031",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/2/31",
  abstract =     "Over the past decade, radio-frequency identification
                 (RFID) technology has attracted significant attention
                 and become very popular in different applications, such
                 as identification, management, and monitoring. In this
                 study, a dual-band microstrip-fed monopole antenna has
                 been introduced for RFID applications. The antenna is
                 designed to work at the frequency ranges of 2.2--2.6
                 GHz and 5.3--6.8 GHz, covering 2.4/5.8 GHz RFID
                 operation bands. The antenna structure is like a
                 modified F-shaped radiator. It is printed on an FR-4
                 dielectric with an overall size of 38 \&times; 45
                 \&times; 1.6 mm 3. Fundamental characteristics of the
                 antenna in terms of return loss, Smith Chart, phase,
                 radiation pattern, and antenna gain are investigated
                 and good results are obtained. Simulations have been
                 carried out using computer simulation technology (CST)
                 software. A prototype of the antenna was fabricated and
                 its characteristics were measured. The measured results
                 show good agreement with simulations. The structure of
                 the antenna is planar, simple to design and fabricate,
                 easy to integrate with RF circuit, and suitable for use
                 in RFID systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue New Developments in RFID Technologies
                 and Applications and Their Integration into IoT.",
}

@Article{Ziakis:2019:IFI,
  author =       "Christos Ziakis and Maro Vlachopoulou and Theodosios
                 Kyrkoudis and Makrina Karagkiozidou",
  title =        "Important Factors for Improving {Google} Search Rank",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "2",
  pages =        "32",
  day =          "30",
  month =        jan,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11020032",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/2/32",
  abstract =     "The World Wide Web has become an essential modern tool
                 for people's daily routine. The fact that it is a
                 convenient means for communication and information
                 search has made it extremely popular. This fact led
                 companies to start using online advertising by creating
                 corporate websites. With the rapid increase in the
                 number of websites, search engines had to come up with
                 a solution of algorithms and programs to qualify the
                 results of a search and provide the users with relevant
                 content to their search. On the other side, developers,
                 in pursuit of the highest rankings in the search engine
                 result pages (SERPs), began to study and observe how
                 search engines work and which factors contribute to
                 higher rankings. The knowledge that has been extracted
                 constituted the base for the creation of the profession
                 of Search Engine Optimization (SEO). This paper
                 consists of two parts. The first part aims to perform a
                 literature review of the factors that affect the
                 ranking of websites in the SERPs and to highlight the
                 top factors that contribute to better ranking. To
                 achieve this goal, a collection and analysis of
                 academic papers was conducted. According to our
                 research, 24 website characteristics came up as factors
                 affecting any website's ranking, with the most
                 references mentioning quality and quantity of
                 backlinks, social media support, keyword in title tag,
                 website structure, website size, loading time, domain
                 age, and keyword density. The second part consists of
                 our research which was conducted manually using the
                 phrases ``hotel Athens'', ``email marketing'', and
                 ``casual shoes''. For each one of these keywords, the
                 first 15 Google results were examined considering the
                 factors found in the literature review. For the
                 measurement of the significance of each factor, the
                 Spearman correlation was calculated and every factor
                 was compared with the ranking of the results
                 individually. The findings of the research showed us
                 that the top factors that contribute to higher rankings
                 are the existence of website SSL certificate as well as
                 keyword in URL, the quantity of backlinks pointing to a
                 website, the text length, and the domain age, which is
                 not perfectly aligned with what the literature review
                 showed us.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Search Engine Optimization.",
}

@Article{Touseau:2019:CWT,
  author =       "Lionel Touseau and Nicolas {Le Sommer}",
  title =        "Contribution of the {Web} of Things and of the
                 Opportunistic Computing to the Smart Agriculture: a
                 Practical Experiment",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "2",
  pages =        "33",
  day =          "01",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11020033",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/2/33",
  abstract =     "With the emergence of the Internet of Things,
                 environmental sensing has been gaining interest,
                 promising to improve agricultural practices by
                 facilitating decision-making based on gathered
                 environmental data (i.e., weather forecasting, crop
                 monitoring, and soil moisture sensing). Environmental
                 sensing, and by extension what is referred to as
                 precision or smart agriculture, pose new challenges,
                 especially regarding the collection of environmental
                 data in the presence of connectivity disruptions, their
                 gathering, and their exploitation by end-users or by
                 systems that must perform actions according to the
                 values of those collected data. In this paper, we
                 present a middleware platform for the Internet of
                 Things that implements disruption tolerant
                 opportunistic networking and computing techniques, and
                 that makes it possible to expose and manage physical
                 objects through Web-based protocols, standards and
                 technologies, thus providing interoperability between
                 objects and creating a Web of Things (WoT). This
                 WoT-based opportunistic computing approach is backed up
                 by a practical experiment whose outcomes are presented
                 in this article.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue WSN and IoT in Smart Agriculture.",
}

@Article{Pisani:2019:FVC,
  author =       "Fl{\'a}via Pisani and Vanderson Martins do Rosario and
                 Edson Borin",
  title =        "Fog vs. Cloud Computing: Should {I} Stay or Should {I}
                 Go?",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "2",
  pages =        "34",
  day =          "02",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11020034",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/2/34",
  abstract =     "In this article, we work toward the answer to the
                 question ``is it worth processing a data stream on the
                 device that collected it or should we send it somewhere
                 else?''. As it is often the case in computer science,
                 the response is ``it depends''. To find out the cases
                 where it is more profitable to stay in the device
                 (which is part of the fog) or to go to a different one
                 (for example, a device in the cloud), we propose two
                 models that intend to help the user evaluate the cost
                 of performing a certain computation on the fog or
                 sending all the data to be handled by the cloud. In our
                 generic mathematical model, the user can define a cost
                 type (e.g., number of instructions, execution time,
                 energy consumption) and plug in values to analyze test
                 cases. As filters have a very important role in the
                 future of the Internet of Things and can be implemented
                 as lightweight programs capable of running on
                 resource-constrained devices, this kind of procedure is
                 the main focus of our study. Furthermore, our visual
                 model guides the user in their decision by aiding the
                 visualization of the proposed linear equations and
                 their slope, which allows them to find if either fog or
                 cloud computing is more profitable for their specific
                 scenario. We validated our models by analyzing four
                 benchmark instances (two applications using two
                 different sets of parameters each) being executed on
                 five datasets. We use execution time and energy
                 consumption as the cost types for this investigation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Selected papers from INTESA Workshop
                 2018.",
}

@Article{Bagnoli:2019:PIS,
  author =       "Franco Bagnoli and Emanuele Bellini and Emanuele
                 Massaro and Ra{\'u}l Rechtman",
  title =        "Percolation and {Internet} Science",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "2",
  pages =        "35",
  day =          "02",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11020035",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/2/35",
  abstract =     "Percolation, in its most general interpretation,
                 refers to the ``flow'' of something (a physical agent,
                 data or information) in a network, possibly accompanied
                 by some nonlinear dynamical processes on the network
                 nodes (sometimes denoted reaction--diffusion systems,
                 voter or opinion formation models, etc.). Originated in
                 the domain of theoretical and matter physics, it has
                 many applications in epidemiology, sociology and, of
                 course, computer and Internet sciences. In this review,
                 we illustrate some aspects of percolation theory and
                 its generalization, cellular automata and briefly
                 discuss their relationship with equilibrium systems
                 (Ising and Potts models). We present a model of opinion
                 spreading, the role of the topology of the network to
                 induce coherent oscillations and the influence (and
                 advantages) of risk perception for stopping epidemics.
                 The models and computational tools that are briefly
                 presented here have an application to the filtering of
                 tainted information in automatic trading. Finally, we
                 introduce the open problem of controlling percolation
                 and other processes on distributed systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Lelli:2019:ITI,
  author =       "Francesco Lelli",
  title =        "Interoperability of the Time of {Industry 4.0} and the
                 {Internet of Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "2",
  pages =        "36",
  day =          "03",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11020036",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/2/36",
  abstract =     "Industry 4.0 demands a dynamic optimization of
                 production lines. They are formed by sets of
                 heterogeneous devices that cooperate towards a shared
                 goal. The Internet of Things can serve as a technology
                 enabler for implementing such a vision. Nevertheless,
                 the domain is struggling in finding a shared
                 understanding of the concepts for describing a device.
                 This aspect plays a fundamental role in enabling an
                 ``intelligent interoperability'' among sensor and
                 actuators that will constitute a dynamic Industry 4.0
                 production line. In this paper, we summarize the
                 efforts of academics and practitioners toward
                 describing devices in order to enable dynamic
                 reconfiguration by machines or humans. We also propose
                 a set of concepts for describing devices, and we
                 analyze how present initiatives are covering these
                 aspects.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Stamou:2019:ANM,
  author =       "Adamantia Stamou and Grigorios Kakkavas and
                 Konstantinos Tsitseklis and Vasileios Karyotis and
                 Symeon Papavassiliou",
  title =        "Autonomic Network Management and Cross-Layer
                 Optimization in Software Defined Radio Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "2",
  pages =        "37",
  day =          "03",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11020037",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/2/37",
  abstract =     "The demand for Autonomic Network Management (ANM) and
                 optimization is as intense as ever, even though
                 significant research has been devoted towards this
                 direction. This paper addresses such need in Software
                 Defined (SDR) based Cognitive Radio Networks (CRNs). We
                 propose a new framework for ANM and network
                 reconfiguration combining Software Defined Networks
                 (SDN) with SDR via Network Function Virtualization
                 (NFV) enabled Virtual Utility Functions (VUFs). This is
                 the first approach combining ANM with SDR and SDN via
                 NFV, demonstrating how these state-of-the-art
                 technologies can be effectively combined to achieve
                 reconfiguration flexibility, improved performance and
                 efficient use of available resources. In order to show
                 the feasibility of the proposed framework, we
                 implemented its main functionalities in a cross-layer
                 resource allocation mechanism for CRNs over real SDR
                 testbeds provided by the Orchestration and
                 Reconfiguration Control Architecture (ORCA) EU project.
                 We demonstrate the efficacy of our framework, and based
                 on the obtained results, we identify aspects that can
                 be further investigated for improving the applicability
                 and increasing performance of our broader framework.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Software Defined Networking (SDN) and
                 Network Function Virtualization (NFV).",
}

@Article{Nguyen:2019:RSS,
  author =       "Van Suong Nguyen",
  title =        "Research on a Support System for Automatic Ship
                 Navigation in Fairway",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "2",
  pages =        "38",
  day =          "03",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11020038",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/2/38",
  abstract =     "In previous investigations, controllers for the
                 track-keeping of ships were designed with the
                 assumption of constant ship speed. However, when
                 navigating in a fairway area, the ship's speed is
                 usually decreased to prepare for berthing. The existing
                 track-keeping systems, which are applied when the ship
                 navigates in the open sea with a constant ship speed,
                 cannot be used to navigate the ship in the fairway. In
                 this article, a support system is proposed for ship
                 navigation in the fairway. This system performs three
                 tasks. First, the ship is automatically controlled by
                 regulating the rudder to follow planned tracks. Second,
                 the ship's speed is reduced step by step to approach
                 the berth area at a low speed. Finally, at low speed,
                 when the ship's rudder is not effective enough to
                 control the ship's heading to a desired angle, the
                 ship's heading is adjusted appropriately by the bow
                 thruster before changing the control mode into the
                 automatic berthing system. By the proposed system, the
                 automatic systems can be combined to obtain a fully
                 automatic system for ship control. To validate the
                 effectiveness of this proposed system for automatic
                 ship navigation in the fairway, numerical simulations
                 were conducted with a training ship model.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue New Perspectives in Intelligent
                 Transportation Systems and Mobile Communications
                 towards a Smart Cities Context.",
}

@Article{Konsgen:2019:MME,
  author =       "Andreas K{\"o}nsgen and Md. Shahabuddin and Amanpreet
                 Singh and Anna F{\"o}rster",
  title =        "A Mathematical Model for Efficient and Fair Resource
                 Assignment in Multipath Transport",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "2",
  pages =        "39",
  day =          "10",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11020039",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/2/39",
  abstract =     "Multipath transport protocols are aimed at increasing
                 the throughput of data flows as well as maintaining
                 fairness between users, which are both crucial factors
                 to maximize user satisfaction. In this paper, a mixed
                 (non)linear programming (MINLP) solution is developed
                 which provides an optimum solution to allocate link
                 capacities in a network to a number of given traffic
                 demands considering both the maximization of link
                 utilization as well as fairness between transport layer
                 data flows or subflows. The solutions of the MINLP
                 formulation are evaluated w. r. t. their throughput and
                 fairness using well-known metrics from the literature.
                 It is shown that network flow fairness based capacity
                 allocation achieves better fairness results than the
                 bottleneck-based methods in most cases while yielding
                 the same capacity allocation performance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hortelano:2019:AVG,
  author =       "Lorenzo J. Torres Hortelano",
  title =        "Audio-Visual Genres and Polymediation in Successful
                 {Spanish} {YouTubers}",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "2",
  pages =        "40",
  day =          "11",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11020040",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/2/40",
  abstract =     "This paper is part of broader research entitled
                 ``Analysis of the YouTuber Phenomenon in Spain: An
                 Exploration to Identify the Vectors of Change in the
                 Audio-Visual Market''. My main objective was to
                 determine the predominant audio-visual genres among the
                 10 most influential Spanish YouTubers in 2018. Using a
                 quantitative extrapolation method, I extracted these
                 data from SocialBlade, an independent website, whose
                 main objective is to track YouTube statistics. Other
                 secondary objectives in this research were to analyze:
                 (1) Gender visualization, (2) the originality of these
                 YouTube audio-visual genres with respect to others, and
                 (3) to answer the question as to whether YouTube
                 channels form a new audio-visual genre. I
                 quantitatively analyzed these data to determine how
                 these genres are influenced by the presence of
                 polymediation as an integrated communicative
                 environment working in relational terms with other
                 media. My conclusion is that we can talk about a new
                 audio-visual genre. When connected with polymediation,
                 this may present an opportunity that has not yet been
                 fully exploited by successful Spanish YouTubers.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future Intelligent Systems and Networks
                 2019.",
}

@Article{Lu:2019:SDC,
  author =       "Haoye Lu and Amiya Nayak",
  title =        "A Scheme to Design Community Detection Algorithms in
                 Various Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "2",
  pages =        "41",
  day =          "12",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11020041",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/2/41",
  abstract =     "Network structures, consisting of nodes and edges,
                 have applications in almost all subjects. A set of
                 nodes is called a community if the nodes have strong
                 interrelations. Industries (including cell phone
                 carriers and online social media companies) need
                 community structures to allocate network resources and
                 provide proper and accurate services. However, most
                 detection algorithms are derived independently, which
                 is arduous and even unnecessary. Although recent
                 research shows that a general detection method that
                 serves all purposes does not exist, we believe that
                 there is some general procedure of deriving detection
                 algorithms. In this paper, we represent such a general
                 scheme. We mainly focus on two types of networks:
                 transmission networks and similarity networks. We
                 reduce them to a unified graph model, based on which we
                 propose a method to define and detect community
                 structures. Finally, we also give a demonstration to
                 show how our design scheme works.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Arif:2019:CBF,
  author =       "Sheeraz Arif and Jing Wang and Tehseen {Ul Hassan} and
                 Zesong Fei",
  title =        "{3D-CNN}-Based Fused Feature Maps with {LSTM} Applied
                 to Action Recognition",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "2",
  pages =        "42",
  day =          "13",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11020042",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/2/42",
  abstract =     "Human activity recognition is an active field of
                 research in computer vision with numerous applications.
                 Recently, deep convolutional networks and recurrent
                 neural networks (RNN) have received increasing
                 attention in multimedia studies, and have yielded
                 state-of-the-art results. In this research work, we
                 propose a new framework which intelligently combines
                 3D-CNN and LSTM networks. First, we integrate
                 discriminative information from a video into a map
                 called a \&lsquo;motion map' by using a deep
                 3-dimensional convolutional network (C3D). A motion map
                 and the next video frame can be integrated into a new
                 motion map, and this technique can be trained by
                 increasing the training video length iteratively; then,
                 the final acquired network can be used for generating
                 the motion map of the whole video. Next, a linear
                 weighted fusion scheme is used to fuse the network
                 feature maps into spatio-temporal features. Finally, we
                 use a Long-Short-Term-Memory (LSTM) encoder-decoder for
                 final predictions. This method is simple to implement
                 and retains discriminative and dynamic information. The
                 improved results on benchmark public datasets prove the
                 effectiveness and practicability of the proposed
                 method.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Innovative Topologies and Algorithms for
                 Neural Networks.",
}

@Article{Diogo:2019:CMN,
  author =       "Miguel Diogo and Bruno Cabral and Jorge Bernardino",
  title =        "Consistency Models of {NoSQL} Databases",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "2",
  pages =        "43",
  day =          "14",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11020043",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/2/43",
  abstract =     "Internet has become so widespread that most popular
                 websites are accessed by hundreds of millions of people
                 on a daily basis. Monolithic architectures, which were
                 frequently used in the past, were mostly composed of
                 traditional relational database management systems, but
                 quickly have become incapable of sustaining high data
                 traffic very common these days. Meanwhile, NoSQL
                 databases have emerged to provide some missing
                 properties in relational databases like the schema-less
                 design, horizontal scaling, and eventual consistency.
                 This paper analyzes and compares the consistency model
                 implementation on five popular NoSQL databases: Redis,
                 Cassandra, MongoDB, Neo4j, and OrientDB. All of which
                 offer at least eventual consistency, and some have the
                 option of supporting strong consistency. However,
                 imposing strong consistency will result in less
                 availability when subject to network partition
                 events.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Hall:2019:BIA,
  author =       "Calum C. Hall and Lynsay A. Shepherd and Natalie
                 Coull",
  title =        "{BlackWatch}: Increasing Attack Awareness within {Web}
                 Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "2",
  pages =        "44",
  day =          "15",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11020044",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/2/44",
  abstract =     "Web applications are relied upon by many for the
                 services they provide. It is essential that
                 applications implement appropriate security measures to
                 prevent security incidents. Currently, web applications
                 focus resources towards the preventative side of
                 security. While prevention is an essential part of the
                 security process, developers must also implement a
                 level of attack awareness into their web applications.
                 Being able to detect when an attack is occurring
                 provides applications with the ability to execute
                 responses against malicious users in an attempt to slow
                 down or deter their attacks. This research seeks to
                 improve web application security by identifying
                 malicious behavior from within the context of web
                 applications using our tool BlackWatch. The tool is a
                 Python-based application which analyzes suspicious
                 events occurring within client web applications, with
                 the objective of identifying malicious patterns of
                 behavior. This approach avoids issues typically
                 encountered with traditional web application firewalls.
                 Based on the results from a preliminary study,
                 BlackWatch was effective at detecting attacks from both
                 authenticated and unauthenticated users. Furthermore,
                 user tests with developers indicated BlackWatch was
                 user-friendly, and was easy to integrate into existing
                 applications. Future work seeks to develop the
                 BlackWatch solution further for public release.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sun:2019:TMT,
  author =       "Yue Sun and Songmin Dai and Jide Li and Yin Zhang and
                 Xiaoqiang Li",
  title =        "Tooth-Marked Tongue Recognition Using
                 Gradient-Weighted Class Activation Maps",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "2",
  pages =        "45",
  day =          "15",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11020045",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/2/45",
  abstract =     "The tooth-marked tongue is an important indicator in
                 traditional Chinese medicinal diagnosis. However, the
                 clinical competence of tongue diagnosis is determined
                 by the experience and knowledge of the practitioners.
                 Due to the characteristics of different tongues, having
                 many variations such as different colors and shapes,
                 tooth-marked tongue recognition is challenging. Most
                 existing methods focus on partial concave features and
                 use specific threshold values to classify the
                 tooth-marked tongue. They lose the overall tongue
                 information and lack the ability to be generalized and
                 interpretable. In this paper, we try to solve these
                 problems by proposing a visual explanation method which
                 takes the entire tongue image as an input and uses a
                 convolutional neural network to extract features
                 (instead of setting a fixed threshold artificially)
                 then classifies the tongue and produces a coarse
                 localization map highlighting tooth-marked regions
                 using Gradient-weighted Class Activation Mapping.
                 Experimental results demonstrate the effectiveness of
                 the proposed method.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Innovative Topologies and Algorithms for
                 Neural Networks.",
}

@Article{Xu:2019:ETS,
  author =       "Da Xu and Tao Zhang",
  title =        "Efficient Tensor Sensing for {RF} Tomographic Imaging
                 on {GPUs}",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "2",
  pages =        "46",
  day =          "15",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11020046",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/2/46",
  abstract =     "Radio-frequency (RF) tomographic imaging is a
                 promising technique for inferring multi-dimensional
                 physical space by processing RF signals traversed
                 across a region of interest. Tensor-based approaches
                 for tomographic imaging are superior at detecting the
                 objects within higher dimensional spaces. The
                 recently-proposed tensor sensing approach based on the
                 transform tensor model achieves a lower error rate and
                 faster speed than the previous tensor-based compress
                 sensing approach. However, the running time of the
                 tensor sensing approach increases exponentially with
                 the dimension of tensors, thus not being very practical
                 for big tensors. In this paper, we address this problem
                 by exploiting massively-parallel GPUs. We design,
                 implement, and optimize the tensor sensing approach on
                 an NVIDIA Tesla GPU and evaluate the performance in
                 terms of the running time and recovery error rate.
                 Experimental results show that our GPU tensor sensing
                 is as accurate as the CPU counterpart with an average
                 of 44.79 \&times; and up to 84.70 \&times; speedups for
                 varying-sized synthetic tensor data. For IKEA Model 3D
                 model data of a smaller size, our GPU algorithm
                 achieved 15.374\&times; speedup over the CPU tensor
                 sensing. We further encapsulate the GPU algorithm into
                 an open-source library, called cuTensorSensing (CUDA
                 Tensor Sensing), which can be used for efficient RF
                 tomographic imaging.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Big Data and Augmented Intelligence.",
}

@Article{Song:2019:JOP,
  author =       "Xin Song and Siyang Xu and Zhigang Xie and Xiuwei
                 Han",
  title =        "Joint Optimal Power Allocation and Relay Selection
                 Scheme in Energy Harvesting Two-Way Relaying Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "2",
  pages =        "47",
  day =          "15",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11020047",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/2/47",
  abstract =     "In this paper, we propose a joint power allocation,
                 time switching (TS) factor and relay selection scheme
                 for an energy harvesting two-way relaying communication
                 network (TWRN), where two transceivers exchange
                 information with the help of a wireless-powered relay.
                 By exploiting the TS architecture at the relay node,
                 the relay node needs to use additional time slots for
                 energy transmission, reducing the transmission rate.
                 Thus, we propose a joint resource allocation algorithm
                 to maximize the max-min bidirectional instantaneous
                 information rate. To solve the original non-convex
                 optimization problem, the objective function is
                 decomposed into three sub-problems and solved
                 sequentially. The closed-form solution of the transmit
                 power of two sources and the optimal TS factor can be
                 obtained by the information rate balancing technology
                 and the proposed time allocation scheme, respectively.
                 At last, the optimal relay node can be obtained.
                 Simulation results show that the performance of the
                 proposed algorithm is better than the traditional
                 schemes and power-splitting (PS) scheme.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lee:2019:VPD,
  author =       "Jae-Gil Lee and Kwan Min Lee and Seoung-Ho Ryu",
  title =        "Vehicle Politeness in Driving Situations",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "2",
  pages =        "48",
  day =          "16",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11020048",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/2/48",
  abstract =     "Future vehicles are becoming more like driving
                 partners instead of mere machines. With the application
                 of advanced information and communication technologies
                 (ICTs), vehicles perform driving tasks while drivers
                 monitor the functioning states of vehicles. This change
                 in interaction requires a deliberate consideration of
                 how vehicles should present driving-related
                 information. As a way of encouraging drivers to more
                 readily accept instructions from vehicles, we suggest
                 the use of social rules, such as politeness, in
                 human-vehicle interaction. In a 2 \&times; 2
                 between-subjects experiment, we test the effects of
                 vehicle politeness (plain vs. polite) on drivers'
                 interaction experiences in two operation situations
                 (normal vs. failure). The results indicate that vehicle
                 politeness improves interaction experience in normal
                 working situations but impedes the experience in
                 failure situations. Specifically, in normal situations,
                 vehicles with polite instructions are highly evaluated
                 for social presence, politeness, satisfaction and
                 intention to use. Theoretical and practical
                 implications on politeness research and speech
                 interaction design are discussed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Lombardo:2019:MAA,
  author =       "Gianfranco Lombardo and Paolo Fornacciari and Monica
                 Mordonini and Michele Tomaiuolo and Agostino Poggi",
  title =        "A Multi-Agent Architecture for Data Analysis",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "2",
  pages =        "49",
  day =          "18",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11020049",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/2/49",
  abstract =     "ActoDatA (Actor Data Analysis) is an actor-based
                 software library for the development of distributed
                 data mining applications. It provides a multi-agent
                 architecture with a set of predefined and configurable
                 agents performing the typical tasks of data mining
                 applications. In particular, its architecture can
                 manage different users' applications; it maintains a
                 high level of execution quality by distributing the
                 agents of the applications on a dynamic set of
                 computational nodes. Moreover, it provides reports
                 about the analysis results and the collected data,
                 which can be accessed through either a web browser or a
                 dedicated mobile APP. After an introduction about the
                 actor model and the software framework used for
                 implementing the software library, this article
                 underlines the main features of ActoDatA and presents
                 its experimentation in some well-known data analysis
                 domains.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Nguyen-Duc:2019:MVP,
  author =       "Anh Nguyen-Duc and Khan Khalid and Sohaib Shahid Bajwa
                 and Tor L{\o}nnestad",
  title =        "Minimum Viable Products for {Internet of Things}
                 Applications: Common Pitfalls and Practices",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "2",
  pages =        "50",
  day =          "18",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11020050",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/2/50",
  abstract =     "Internet of Things applications are not only the new
                 opportunity for digital businesses but also a major
                 driving force for the modification and creation of
                 software systems in all industries and businesses.
                 Compared to other types of software-intensive products,
                 the development of Internet of Things applications
                 lacks a systematic approach and guidelines. This paper
                 aims at understanding the common practices and
                 challenges among start-up companies who are developing
                 Internet of Things products. A qualitative research is
                 conducted with data from twelve semi-structured
                 interviews. A thematic analysis reveals common types of
                 Minimum Viable Products, prototyping techniques and
                 production concerns among early stage hardware
                 start-ups. We found that hardware start-ups go through
                 an incremental prototyping process toward production.
                 The progress associates with the transition from
                 speed-focus to quality-focus. Hardware start-ups
                 heavily rely on third-party vendors in term of
                 development speed and final product quality. We
                 identified 24 challenges related to management,
                 requirement, design, implementation and testing.
                 Internet of Things entrepreneurs should be aware of
                 relevant pitfalls and managing both internal and
                 external risks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Internet of Things.",
}

@Article{Yuan:2019:FLD,
  author =       "Quanbo Yuan and Huijuan Wang and Botao Wu and Yaodong
                 Song and Hejia Wang",
  title =        "A Fusion Load Disaggregation Method Based on
                 Clustering Algorithm and Support Vector Regression
                 Optimization for Low Sampling Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "2",
  pages =        "51",
  day =          "19",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11020051",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/2/51",
  abstract =     "In order to achieve more efficient energy consumption,
                 it is crucial that accurate detailed information is
                 given on how power is consumed. Electricity details
                 benefit both market utilities and also power consumers.
                 Non-intrusive load monitoring (NILM), a novel and
                 economic technology, obtains single-appliance power
                 consumption through a single total power meter. This
                 paper, focusing on load disaggregation with low
                 hardware costs, proposed a load disaggregation method
                 for low sampling data from smart meters based on a
                 clustering algorithm and support vector regression
                 optimization. This approach combines the k-median
                 algorithm and dynamic time warping to identify the
                 operating appliance and retrieves single energy
                 consumption from an aggregate smart meter signal via
                 optimized support vector regression (OSVR). Experiments
                 showed that the technique can recognize multiple
                 devices switching on at the same time using
                 low-frequency data and achieve a high load
                 disaggregation performance. The proposed method employs
                 low sampling data acquired by smart meters without
                 installing extra measurement equipment, which lowers
                 hardware cost and is suitable for applications in smart
                 grid environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhao:2019:SAB,
  author =       "Lingling Zhao and Anping Zhao",
  title =        "Sentiment Analysis Based Requirement Evolution
                 Prediction",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "2",
  pages =        "52",
  day =          "21",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11020052",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/2/52",
  abstract =     "To facilitate product developers capturing the varying
                 requirements from users to support their feature
                 evolution process, requirements evolution prediction
                 from massive review texts is in fact of great
                 importance. The proposed framework combines a
                 supervised deep learning neural network with an
                 unsupervised hierarchical topic model to analyze user
                 reviews automatically for product feature requirements
                 evolution prediction. The approach is to discover
                 hierarchical product feature requirements from the
                 hierarchical topic model and to identify their
                 sentiment by the Long Short-term Memory (LSTM) with
                 word embedding, which not only models hierarchical
                 product requirement features from general to specific,
                 but also identifies sentiment orientation to better
                 correspond to the different hierarchies of product
                 features. The evaluation and experimental results show
                 that the proposed approach is effective and feasible.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future Intelligent Systems and Networks
                 2019.",
}

@Article{Zhao:2019:EDL,
  author =       "Hongwei Zhao and Weishan Zhang and Haoyun Sun and Bing
                 Xue",
  title =        "Embedded Deep Learning for Ship Detection and
                 Recognition",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "2",
  pages =        "53",
  day =          "21",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11020053",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:04 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/2/53",
  abstract =     "Ship detection and recognition are important for smart
                 monitoring of ships in order to manage port resources
                 effectively. However, this is challenging due to
                 complex ship profiles, ship background, object
                 occlusion, variations of weather and light conditions,
                 and other issues. It is also expensive to transmit
                 monitoring video in a whole, especially if the port is
                 not in a rural area. In this paper, we propose an
                 on-site processing approach, which is called Embedded
                 Ship Detection and Recognition using Deep Learning
                 (ESDR-DL). In ESDR-DL, the video stream is processed
                 using embedded devices, and we design a two-stage
                 neural network named DCNet, which is composed of a DNet
                 for ship detection and a CNet for ship recognition,
                 running on embedded devices. We have extensively
                 evaluated ESDR-DL, including performance of accuracy
                 and efficiency. The ESDR-DL is deployed at the Dongying
                 port of China, which has been running for over a year
                 and demonstrates that it can work reliably for
                 practical usage.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Innovative Topologies and Algorithms for
                 Neural Networks.",
}

@Article{Sacco:2019:SIS,
  author =       "Giovanni Maria Sacco",
  title =        "{SAES}: An Introduction to Self-Adapting Exploratory
                 Structures",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "3",
  pages =        "54",
  day =          "26",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11030054",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/3/54",
  abstract =     "Self-adapting exploratory structures (SAESs) are the
                 basic components of exploratory search. They are
                 abstract structures which allow searching or querying
                 of an information base and summarizing of results using
                 a uniform representation. A definition and a
                 characterization of SAES is given, as well as a
                 discussion of structures that are SAES or can be
                 modified in order to become SAES. These include dynamic
                 taxonomies (also known as faceted search), tag clouds,
                 continuous sliders, geographic maps, and dynamic
                 clustering methods, such as Scatter-Gather. Finally,
                 the integration of these structures into a single
                 interface is discussed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Svorobej:2019:SFE,
  author =       "Sergej Svorobej and Patricia Takako Endo and Malika
                 Bendechache and Christos Filelis-Papadopoulos and
                 Konstantinos M. Giannoutakis and George A. Gravvanis
                 and Dimitrios Tzovaras and James Byrne and Theo Lynn",
  title =        "Simulating Fog and Edge Computing Scenarios: An
                 Overview and Research Challenges",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "3",
  pages =        "55",
  day =          "26",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11030055",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/3/55",
  abstract =     "The fourth industrial revolution heralds a paradigm
                 shift in how people, processes, things, data and
                 networks communicate and connect with each other.
                 Conventional computing infrastructures are struggling
                 to satisfy dramatic growth in demand from a deluge of
                 connected heterogeneous end points located at the edge
                 of networks while, at the same time, meeting quality of
                 service levels. The complexity of computing at the edge
                 makes it increasingly difficult for infrastructure
                 providers to plan for and provision resources to meet
                 this demand. While simulation frameworks are used
                 extensively in the modelling of cloud computing
                 environments in order to test and validate technical
                 solutions, they are at a nascent stage of development
                 and adoption for fog and edge computing. This paper
                 provides an overview of challenges posed by fog and
                 edge computing in relation to simulation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Cloud Computing and Internet of
                 Things.",
}

@Article{LoIacono:2019:NGR,
  author =       "Luigi {Lo Iacono} and Hoai Viet Nguyen and Peter Leo
                 Gorski",
  title =        "On the Need for a General {REST}-Security Framework",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "3",
  pages =        "56",
  day =          "27",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11030056",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/3/56",
  abstract =     "Contemporary software is inherently distributed. The
                 principles guiding the design of such software have
                 been mainly manifested by the service-oriented
                 architecture (SOA) concept. In a SOA, applications are
                 orchestrated by software services generally operated by
                 distinct entities. Due to the latter fact, service
                 security has been of importance in such systems ever
                 since. A dominant protocol for implementing SOA-based
                 systems is SOAP, which comes with a well-elaborated
                 security framework. As an alternative to SOAP, the
                 architectural style representational state transfer
                 (REST) is gaining traction as a simple, lightweight and
                 flexible guideline for designing distributed service
                 systems that scale at large. This paper starts by
                 introducing the basic constraints representing REST.
                 Based on these foundations, the focus is afterwards
                 drawn on the security needs of REST-based service
                 systems. The limitations of transport-oriented
                 protection means are emphasized and the demand for
                 specific message-oriented safeguards is assessed. The
                 paper then reviews the current activities in respect to
                 REST-security and finds that the available schemes are
                 mostly HTTP-centered and very heterogeneous. More
                 importantly, all of the analyzed schemes contain
                 vulnerabilities. The paper contributes a methodology on
                 how to establish REST-security as a general security
                 framework for protecting REST-based service systems of
                 any kind by consistent and comprehensive protection
                 means. First adoptions of the introduced approach are
                 presented in relation to REST message authentication
                 with instantiations for REST-ful HTTP (web/cloud
                 services) and REST-ful constraint application protocol
                 (CoAP) (internet of things (IoT) services).",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Vangelista:2019:WCI,
  author =       "Lorenzo Vangelista and Marco Centenaro",
  title =        "Worldwide Connectivity for the {Internet of Things}
                 Through {LoRaWAN}",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "3",
  pages =        "57",
  day =          "02",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11030057",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/3/57",
  abstract =     "The low-power wide-area network (LPWAN) paradigm is
                 gradually gaining market acceptance. In particular,
                 three prominent LPWAN technologies are emerging at the
                 moment: LoRaWAN\&trade; and SigFox\&trade;, which
                 operate on unlicensed frequency bands, and NB-IoT,
                 operating on licensed frequency bands. This paper deals
                 with LoRaWAN\&trade;, and has the aim of describing a
                 particularly interesting feature provided by the latest
                 LoRaWAN\&trade; specification --- often neglected in
                 the literature --- i.e., the roaming capability between
                 different operators of LoRaWAN\&trade; networks, across
                 the same country or even different countries. Recalling
                 that LoRaWAN\&trade; devices do not have a subscriber
                 identification module (SIM) like cellular network
                 terminals, at a first glance the implementation of
                 roaming in LoRaWAN\&trade; networks could seem
                 intricate. The contribution of this paper consists in
                 explaining the principles behind the implementation of
                 a global LoRaWAN network, with particular focus on how
                 to cope with the lack of the SIM in the architecture
                 and how to realize roaming.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Gomes:2019:IPI,
  author =       "Luis Gomes and Carlos Ramos and Aria Jozi and Bruno
                 Serra and Lucas Paiva and Zita Vale",
  title =        "{IoH}: a Platform for the Intelligence of Home with a
                 Context Awareness and Ambient Intelligence Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "3",
  pages =        "58",
  day =          "02",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11030058",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/3/58",
  abstract =     "This paper presents IoH (Intelligence of Home), a
                 platform developed to test some basic intelligent
                 behaviors in Home context. Internet of Things, ambient
                 intelligence and context awareness approaches motivated
                 the development of IoH. The platform involves six
                 layers, responsible by connectivity, persistency,
                 unification, Internet of Things integration, subsystems
                 integration and user interface. The integrated
                 subsystems involve intelligent systems for light
                 control, television brightness control, desk light
                 control, persons counting and air conditioner control.
                 The IoH platform is then tested for a real building,
                 and results and conclusions are obtained. Different
                 intelligent methods and technologies are used, form the
                 use of a diversity of sensors, actuators, and
                 controllers and processing units to a set of artificial
                 intelligence approaches varying from machine learning
                 and optimization algorithms to the use of sensor fusion
                 and computer vision. The use of IoH day-by-day
                 demonstrated an intelligent performance for the real
                 building occupants.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Kejriwal:2019:MPI,
  author =       "Mayank Kejriwal and Pedro Szekely",
  title =        "{myDIG}: Personalized Illicit Domain-Specific
                 Knowledge Discovery with No Programming",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "3",
  pages =        "59",
  day =          "04",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11030059",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/3/59",
  abstract =     "With advances in machine learning, knowledge discovery
                 systems have become very complicated to set up,
                 requiring extensive tuning and programming effort.
                 Democratizing such technology so that non-technical
                 domain experts can avail themselves of these advances
                 in an interactive and personalized way is an important
                 problem. We describe myDIG, a highly modular, open
                 source pipeline-construction system that is
                 specifically geared towards investigative users (e.g.,
                 law enforcement) with no programming abilities. The
                 myDIG system allows users both to build a knowledge
                 graph of entities, relationships, and attributes for
                 illicit domains from a raw HTML corpus and also to set
                 up a personalized search interface for analyzing the
                 structured knowledge. We use qualitative and
                 quantitative data from five case studies involving
                 investigative experts from illicit domains such as
                 securities fraud and illegal firearms sales to
                 illustrate the potential of myDIG.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue New Perspectives on Semantic Web
                 Technologies and Applications.",
}

@Article{Wang:2019:HTC,
  author =       "Xuan Wang and Bofeng Zhang and Furong Chang",
  title =        "Hot Topic Community Discovery on Cross Social
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "3",
  pages =        "60",
  day =          "04",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11030060",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/3/60",
  abstract =     "The rapid development of online social networks has
                 allowed users to obtain information, communicate with
                 each other and express different opinions. Generally,
                 in the same social network, users tend to be influenced
                 by each other and have similar views. However, on
                 another social network, users may have opposite views
                 on the same event. Therefore, research undertaken on a
                 single social network is unable to meet the needs of
                 research on hot topic community discovery. ``Cross
                 social network'' refers to multiple social networks.
                 The integration of information from multiple social
                 network platforms forms a new unified dataset. In the
                 dataset, information from different platforms for the
                 same event may contain similar or unique topics. This
                 paper proposes a hot topic discovery method on cross
                 social networks. Firstly, text data from different
                 social networks are fused to build a unified model.
                 Then, we obtain latent topic distributions from the
                 unified model using the Labeled Biterm Latent Dirichlet
                 Allocation (LB-LDA) model. Based on the distributions,
                 similar topics are clustered to form several topic
                 communities. Finally, we choose hot topic communities
                 based on their scores. Experiment result on data from
                 three social networks prove that our model is effective
                 and has certain application value.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Techno-Social Smart Systems.",
}

@Article{Zardari:2019:DAD,
  author =       "Zulfiqar Ali Zardari and Jingsha He and Nafei Zhu and
                 Khalid Hussain Mohammadani and Muhammad Salman Pathan
                 and Muhammad Iftikhar Hussain and Muhammad Qasim
                 Memon",
  title =        "A Dual Attack Detection Technique to Identify Black
                 and {Gray} Hole Attacks Using an Intrusion Detection
                 System and a Connected Dominating Set in {MANETs}",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "3",
  pages =        "61",
  day =          "05",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11030061",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/3/61",
  abstract =     "A mobile ad-hoc network (MANET) is a temporary network
                 of wireless mobile nodes. In a MANET, it is assumed
                 that all of the nodes cooperate with each other to
                 transfer data packets in a multi-hop fashion. However,
                 some malicious nodes don't cooperate with other nodes
                 and disturb the network through false routing
                 information. In this paper, we propose a prominent
                 technique, called dual attack detection for black and
                 gray hole attacks (DDBG), for MANETs. The proposed DDBG
                 technique selects the intrusion detection system (IDS)
                 node using the connected dominating set (CDS) technique
                 with two additional features; the energy and its
                 nonexistence in the blacklist are also checked before
                 putting the nodes into the IDS set. The CDS is an
                 effective, distinguished, and localized approach for
                 detecting nearly-connected dominating sets of nodes in
                 a small range in mobile ad hoc networks. The selected
                 IDS nodes broadcast a kind of status packet within a
                 size of the dominating set for retrieving the complete
                 behavioral information from their nodes. Later, IDS
                 nodes use our DDBG technique to analyze the collected
                 behavioral information to detect the malicious nodes
                 and add them to the blacklist if the behavior of the
                 node is suspicious. Our experimental results show that
                 the quality of the service parameters of the proposed
                 technique outperforms the existing routing schemes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Geyda:2019:MIO,
  author =       "Alexander Geyda and Igor Lysenko",
  title =        "Modeling of Information Operations Effects:
                 Technological Systems Example",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "3",
  pages =        "62",
  day =          "05",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11030062",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/3/62",
  abstract =     "The article outlines conceptual and corresponding
                 formal models of system functioning. Models provide
                 means for estimation of information operation effects
                 and the operational properties of systems and their
                 functioning. Such systems are changed due to
                 information operations. Examples of operational
                 properties are efficiency, the effectiveness of system
                 functioning, system capabilities and system potential.
                 Operational properties are estimated based on
                 functioning effects. Such effects of information
                 operations are manifested through a system functioning
                 under the conditions of a changing environment. An
                 estimation of effects and operational properties is
                 fulfilled analytically. It is made through plotting the
                 dependences of the predicted values of effects and
                 operational properties of information operations and
                 corresponding IT usage against the variables and
                 options of problems solved. To develop this type of
                 model, the use of information operations during system
                 functioning is analyzed through an example of a
                 technological system. General concepts and principles
                 of the modeling of information operations during the
                 operation of such systems are defined. An exemplary
                 modeling of the effects of technological information,
                 and the related technological non-information
                 operations of technological systems operation is
                 provided. Based on concept models of information
                 operations of technological systems, functioning
                 set-theoretical models followed by functional models
                 are introduced. An example of operational properties
                 indicators estimation is considered. It is based on
                 Architecture of Integrated Information Systems (ARIS)
                 diagramming tools' usage. Use cases of such indicators
                 include choosing optimal information operations
                 characteristics.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yeboah-Ofori:2019:CST,
  author =       "Abel Yeboah-Ofori and Shareeful Islam",
  title =        "Cyber Security Threat Modeling for Supply Chain
                 Organizational Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "3",
  pages =        "63",
  day =          "05",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11030063",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/3/63",
  abstract =     "Cyber security in a supply chain (SC) provides an
                 organization the secure network facilities to meet its
                 overall business objectives. The integration of
                 technologies has improved business processes, increased
                 production speed, and reduced distribution costs.
                 However, the increased interdependencies among various
                 supply chain stakeholders have brought many challenges
                 including lack of third party audit mechanisms and
                 cascading cyber threats. This has led to attacks such
                 as the manipulation of the design specifications,
                 alterations, and manipulation during distribution. The
                 aim of this paper is to investigate and understand
                 supply chain threats. In particular, the paper
                 contributes towards modeling and analyzing CSC attacks
                 and cyber threat reporting among supply chain
                 stakeholders. We consider concepts such as goal, actor,
                 attack, TTP, and threat actor relevant to the supply
                 chain, threat model, and requirements domain, and
                 modeled the attack using the widely known STIX threat
                 model. The proposed model was analyzed using a running
                 example of a smart grid case study and an algorithm to
                 model the attack. A discrete probability method for
                 calculating the conditional probabilities was used to
                 determine the attack propagation and cascading effects,
                 and the results showed that our approach effectively
                 analyzed the threats. We have recommended a list of CSC
                 controls to improve the overall security of the studied
                 organization.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Zheng:2019:CPS,
  author =       "Xin Zheng and Gaocai Wang and Qifei Zhao",
  title =        "A Cache Placement Strategy with Energy Consumption
                 Optimization in Information-Centric Networking",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "3",
  pages =        "64",
  day =          "05",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11030064",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/3/64",
  abstract =     "With the rapid development of cloud computing, big
                 data, and Internet of Things, Information-Centric
                 Networking (ICN) has become a novel hotspot in the
                 field of future Internet architecture, and new problems
                 have appeared. In particular, more researchers consider
                 information naming, delivery, mobility, and security in
                 ICN. In this paper, we mainly focus on the cache
                 placement strategy and network performance of ICN, and
                 propose a cache placement strategy with energy
                 consumption optimization. In order to optimize the
                 energy consumption of the ICN, the best cache placement
                 node is selected from the view of users. First of all,
                 the distance sequence of different nodes arriving at
                 each user is obtained in terms of detection results of
                 network distribution channels, and the corresponding
                 energy consumption of information distribution is
                 obtained from the distance sequence. Secondly, the
                 reward function of the cache node is derived using two
                 factors of energy consumption, which includes the
                 additional energy consumed by the change of the cache
                 node and the energy consumption of the content
                 distribution. Finally, we construct the optimal
                 stopping theory problem to solve the maximum expected
                 energy saving. In simulations, we give the comparison
                 results of energy savings, caching benefit, and
                 delivery success rate. The results show that the
                 strategy proposed by this paper has higher delivery
                 success rate and lower energy consumption than other
                 strategies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Information-Centric Networking (ICN).",
}

@Article{Li:2019:GTA,
  author =       "Yang Li and Leyi Shi and Haijie Feng",
  title =        "A Game-Theoretic Analysis for Distributed Honeypots",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "3",
  pages =        "65",
  day =          "05",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11030065",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/3/65",
  abstract =     "A honeypot is a decoy tool for luring an attacker and
                 interacting with it, further consuming its resources.
                 Due to its fake property, a honeypot can be recognized
                 by the adversary and loses its value. Honeypots
                 equipped with dynamic characteristics are capable of
                 deceiving intruders. However, most of their dynamic
                 properties are reflected in the system configuration,
                 rather than the location. Dynamic honeypots are faced
                 with the risk of being identified and avoided. In this
                 paper, we focus on the dynamic locations of honeypots
                 and propose a distributed honeypot scheme. By
                 periodically changing the services, the attacker cannot
                 distinguish the real services from honeypots, and the
                 illegal attack flow can be recognized. We adopt game
                 theory to illustrate the effectiveness of our system.
                 Gambit simulations are conducted to validate our
                 proposed scheme. The game-theoretic reasoning shows
                 that our system comprises an innovative system defense.
                 Further simulation results prove that the proposed
                 scheme improves the server's payoff and that the
                 attacker tends to abandon launching attacks. Therefore,
                 the proposed distributed honeypot scheme is effective
                 for network security.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Jaloudi:2019:CPI,
  author =       "Samer Jaloudi",
  title =        "Communication Protocols of an {Industrial Internet of
                 Things} Environment: a Comparative Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "3",
  pages =        "66",
  day =          "07",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11030066",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/3/66",
  abstract =     "Most industrial and SCADA-like (supervisory control
                 and data acquisition) systems use proprietary
                 communication protocols, and hence interoperability is
                 not fulfilled. However, the MODBUS TCP is an open de
                 facto standard, and is used for some automation and
                 telecontrol systems. It is based on a polling mechanism
                 and follows the synchronous request--response pattern,
                 as opposed to the asynchronous publish--subscribe
                 pattern. In this study, polling-based and event-based
                 protocols are investigated to realize an open and
                 interoperable Industrial Internet of Things (IIoT)
                 environment. Many Internet of Things (IoT) protocols
                 are introduced and compared, and the message queuing
                 telemetry transport (MQTT) is chosen as the
                 event-based, publish--subscribe protocol. The study
                 shows that MODBUS defines an optimized message
                 structure in the application layer, which is dedicated
                 to industrial applications. In addition, it shows that
                 an event-oriented IoT protocol complements the MODBUS
                 TCP but cannot replace it. Therefore, two scenarios are
                 proposed to build the IIoT environment. The first
                 scenario is to consider the MODBUS TCP as an IoT
                 protocol, and build the environment using the MODBUS
                 TCP on a standalone basis. The second scenario is to
                 use MQTT in conjunction with the MODBUS TCP. The first
                 scenario is efficient and complies with most industrial
                 applications where the request--response pattern is
                 needed only. If the publish--subscribe pattern is
                 needed, the MQTT in the second scenario complements the
                 MODBUS TCP and eliminates the need for a gateway;
                 however, MQTT lacks interoperability. To maintain a
                 homogeneous message structure for the entire
                 environment, industrial data are organized using the
                 structure of MODBUS messages, formatted in the UTF-8,
                 and then transferred in the payload of an MQTT publish
                 message. The open and interoperable environment can be
                 used for Internet SCADA, Internet-based monitoring, and
                 industrial control systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Internet of Things.",
}

@Article{Mavroeidi:2019:GVP,
  author =       "Aikaterini-Georgia Mavroeidi and Angeliki Kitsiou and
                 Christos Kalloniatis and Stefanos Gritzalis",
  title =        "Gamification vs. Privacy: Identifying and Analysing
                 the Major Concerns",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "3",
  pages =        "67",
  day =          "07",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11030067",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/3/67",
  abstract =     "Gamification, the use of game design elements in
                 applications that are not games, has been developed to
                 provide attractive environments and maintain user
                 interest in several domains. In domains such as
                 education, marketing and health, where gamification
                 techniques are applied, user engagement in applications
                 has increased. In these applications the protection of
                 users' privacy is an important aspect to consider, due
                 to the applications obtaining a record of the personal
                 information of their users. Thus, the purpose of this
                 paper is to identify if applications where gamification
                 is applied do respect users' privacy. For the
                 accomplishment of this aim, two main steps have been
                 implemented. Since the main principle of gamification
                 is the existence of game elements, the first step was
                 to identify the set of game elements recorded in the
                 literature that are commonly applied in various
                 applications. Afterwards, an examination of the
                 relationship between these elements and privacy
                 requirements was implemented in order to identify which
                 elements conflict with the privacy requirements leading
                 to potential privacy violations and which elements do
                 not. \&Alpha; conceptual model according to the results
                 of this examination was designed, which presents how
                 elements conflict with requirements. Based on the
                 results, there are indeed game elements which can lead
                 to privacy violations. The results of this work provide
                 valuable guidance to software developers, especially
                 during the design stages of gamified applications since
                 it helps them to consider the protection of users'
                 privacy in parallel from the early stages of the
                 application development onwards.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Kato:2019:STE,
  author =       "Shigeru Kato and Naoki Wada and Ryuji Ito and Takaya
                 Shiozaki and Yudai Nishiyama and Tomomichi Kagawa",
  title =        "Snack Texture Estimation System Using a Simple
                 Equipment and Neural Network Model",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "3",
  pages =        "68",
  day =          "08",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11030068",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/3/68",
  abstract =     "Texture evaluation is manually performed in general,
                 and such analytical tasks can get cumbersome. In this
                 regard, a neural network model is employed in this
                 study. This paper describes a system that can estimate
                 the food texture of snacks. The system comprises a
                 simple equipment unit and an artificial neural network
                 model. The equipment simultaneously examines the load
                 and sound when a snack is pressed. The neural network
                 model analyzes the load change and sound signals and
                 then outputs a numerical value within the range (0,1)
                 to express the level of textures such as
                 ``crunchiness'' and ``crispness''. Experimental results
                 validate the model's capacity to output moderate
                 texture values of the snacks. In addition, we applied
                 the convolutional neural network (CNN) model to
                 classify snacks and the capability of the CNN model for
                 texture estimation is discussed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Advanced Techniques for Internet, P2P
                 and Cloud Computing-selected papers from 3PGCIC-2018.",
}

@Article{Leivadeas:2019:VPO,
  author =       "Aris Leivadeas and George Kesidis and Mohamed Ibnkahla
                 and Ioannis Lambadaris",
  title =        "{VNF} Placement Optimization at the Edge and Cloud",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "3",
  pages =        "69",
  day =          "09",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11030069",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/3/69",
  abstract =     "Network Function Virtualization (NFV) has
                 revolutionized the way network services are offered to
                 end users. Individual network functions are decoupled
                 from expensive and dedicated middleboxes and are now
                 provided as software-based virtualized entities called
                 Virtualized Network Functions (VNFs). NFV is often
                 complemented with the Cloud Computing paradigm to
                 provide networking functions to enterprise customers
                 and end-users remote from their premises. NFV along
                 with Cloud Computing has also started to be seen in
                 Internet of Things (IoT) platforms as a means to
                 provide networking functions to the IoT traffic. The
                 intermix of IoT, NFV, and Cloud technologies, however,
                 is still in its infancy creating a rich and open future
                 research area. To this end, in this paper, we propose a
                 novel approach to facilitate the placement and
                 deployment of service chained VNFs in a network cloud
                 infrastructure that can be extended using the Mobile
                 Edge Computing (MEC) infrastructure for accommodating
                 mission critical and delay sensitive traffic. Our aim
                 is to minimize the end-to-end communication delay while
                 keeping the overall deployment cost to minimum. Results
                 reveal that the proposed approach can significantly
                 reduce the delay experienced, while satisfying the
                 Service Providers' goal of low deployment costs.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Software Defined Networking (SDN) and
                 Network Function Virtualization (NFV).",
}

@Article{Mahmood:2019:SDH,
  author =       "Adnan Mahmood and Wei Emma Zhang and Quan Z. Sheng",
  title =        "Software-Defined Heterogeneous Vehicular Networking:
                 The Architectural Design and Open Challenges",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "3",
  pages =        "70",
  day =          "11",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11030070",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/3/70",
  abstract =     "The promising advancements in the telecommunications
                 and automotive sectors over the years have empowered
                 drivers with highly innovative communication and
                 sensing capabilities, in turn paving the way for the
                 next-generation connected and autonomous vehicles.
                 Today, vehicles communicate wirelessly with other
                 vehicles and vulnerable pedestrians in their immediate
                 vicinity to share timely safety-critical information
                 primarily for collision mitigation. Furthermore,
                 vehicles connect with the traffic management entities
                 via their supporting network infrastructure to become
                 more aware of any potential hazards on the roads and
                 for guidance pertinent to their current and anticipated
                 speeds and travelling course to ensure more efficient
                 traffic flows. Therefore, a secure and low-latency
                 communication is highly indispensable in order to meet
                 the stringent performance requirements of such
                 safety-critical vehicular applications. However, the
                 heterogeneity of diverse radio access technologies and
                 inflexibility in their deployment results in network
                 fragmentation and inefficient resource utilization, and
                 these, therefore, act as bottlenecks in realizing the
                 aims for a highly efficient vehicular networking
                 architecture. In order to overcome such sorts of
                 bottlenecks, this article brings forth the current
                 state-of-the-art in the context of intelligent
                 transportation systems (ITS) and subsequently proposes
                 a software-defined heterogeneous vehicular networking
                 (SDHVNet) architecture for ensuring a highly agile
                 networking infrastructure to ensure rapid network
                 innovation on-demand. Finally, a number of potential
                 architectural challenges and their probable solutions
                 are discussed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Eramo:2019:ESR,
  author =       "Vincenzo Eramo and Francesco G. Lavacca and Tiziana
                 Catena and Marco Polverini and Antonio Cianfrani",
  title =        "Effectiveness of Segment Routing Technology in
                 Reducing the Bandwidth and Cloud Resources Provisioning
                 Times in Network Function Virtualization
                 Architectures",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "3",
  pages =        "71",
  day =          "12",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11030071",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/3/71",
  abstract =     "Network Function Virtualization is a new technology
                 allowing for a elastic cloud and bandwidth resource
                 allocation. The technology requires an orchestrator
                 whose role is the service and resource orchestration.
                 It receives service requests, each one characterized by
                 a Service Function Chain, which is a set of service
                 functions to be executed according to a given order. It
                 implements an algorithm for deciding where both to
                 allocate the cloud and bandwidth resources and to route
                 the SFCs. In a traditional orchestration algorithm, the
                 orchestrator has a detailed knowledge of the cloud and
                 network infrastructures and that can lead to high
                 computational complexity of the SFC Routing and Cloud
                 and Bandwidth resource Allocation (SRCBA) algorithm. In
                 this paper, we propose and evaluate the effectiveness
                 of a scalable orchestration architecture inherited by
                 the one proposed within the European Telecommunications
                 Standards Institute (ETSI) and based on the functional
                 separation of an NFV orchestrator in Resource
                 Orchestrator (RO) and Network Service Orchestrator
                 (NSO). Each cloud domain is equipped with an RO whose
                 task is to provide a simple and abstract representation
                 of the cloud infrastructure. These representations are
                 notified of the NSO that can apply a simplified and
                 less complex SRCBA algorithm. In addition, we show how
                 the segment routing technology can help to simplify the
                 SFC routing by means of an effective addressing of the
                 service functions. The scalable orchestration solution
                 has been investigated and compared to the one of a
                 traditional orchestrator in some network scenarios and
                 varying the number of cloud domains. We have verified
                 that the execution time of the SRCBA algorithm can be
                 drastically reduced without degrading the performance
                 in terms of cloud and bandwidth resource costs.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Software Defined Networking (SDN) and
                 Network Function Virtualization (NFV).",
}

@Article{Croft:2019:EHC,
  author =       "Paul J. Croft",
  title =        "Environmental Hazards: a Coverage Response Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "3",
  pages =        "72",
  day =          "14",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11030072",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/3/72",
  abstract =     "The rapid rise and implementation of Smart Systems
                 (i.e., multi-functional observation and platform
                 systems that depict settings and/or identify situations
                 or features of interest, often in real-time) has
                 inversely paralleled and readily exposed the reduced
                 capacity of human and societal systems to effectively
                 respond to environmental hazards. This overarching
                 review and essay explores the complex set of
                 interactions found among Smart, Societal, and
                 Environmental Systems. The resulting rise in the poorly
                 performing response solutions to environmental hazards
                 that has occurred despite best practices, detailed
                 forecast information, and the use and application of
                 real-time in situ observational platforms are
                 considered. The application of Smart Systems, relevant
                 architectures, and ever-increasing numbers of
                 applications and tools development by individuals as
                 they interact with Smart Systems offers a means to
                 ameliorate and resolve confounding found among all of
                 the interdependent Systems. The interactions of human
                 systems with environmental hazards further expose
                 society's complex operational vulnerabilities and gaps
                 in response to such threats. An examination of
                 decision-making, the auto-reactive nature of responses
                 before, during, and after environmental hazards; and
                 the lack of scalability and comparability are presented
                 with regard to the prospects of applying probabilistic
                 methods, cross-scale time and space domains;
                 anticipated impacts, and the need to account for
                 multimodal actions and reactions --- including
                 psycho-social contributions. Assimilation of these
                 concepts and principles in Smart System architectures,
                 applications, and tools is essential to ensure future
                 viability and functionalities with regard to
                 environmental hazards and to produce an effective set
                 of societal engagement responses. Achieving the promise
                 of Smart Systems relative to environmental hazards will
                 require an extensive transdisciplinary approach to tie
                 psycho-social behaviors directly with non-human
                 components and systems in order to close actionable
                 gaps in response. Pathways to achieve a more
                 comprehensive understanding are given for consideration
                 by the wide diversity of disciplines necessary to move
                 forward in Smart Systems as tied with the societal
                 response to environmental hazards.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Aldawood:2019:RCS,
  author =       "Hussain Aldawood and Geoffrey Skinner",
  title =        "Reviewing Cyber Security Social Engineering Training
                 and Awareness Programs-Pitfalls and Ongoing Issues",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "3",
  pages =        "73",
  day =          "18",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11030073",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/3/73",
  abstract =     "The idea and perception of good cyber security
                 protection remains at the forefront of many
                 organizations' information and communication technology
                 strategy and investment. However, delving deeper into
                 the details of its implementation reveals that
                 organizations' human capital cyber security knowledge
                 bases are very low. In particular, the lack of social
                 engineering awareness is a concern in the context of
                 human cyber security risks. This study highlights
                 pitfalls and ongoing issues that organizations
                 encounter in the process of developing the human
                 knowledge to protect from social engineering attacks. A
                 detailed literature review is provided to support these
                 arguments with analysis of contemporary approaches. The
                 findings show that despite state-of-the-art cyber
                 security preparations and trained personnel, hackers
                 are still successful in their malicious acts of
                 stealing sensitive information that is crucial to
                 organizations. The factors influencing users'
                 proficiency in threat detection and mitigation have
                 been identified as business environmental, social,
                 political, constitutional, organizational, economical,
                 and personal. Challenges with respect to both
                 traditional and modern tools have been analyzed to
                 suggest the need for profiling at-risk employees
                 (including new hires) and developing training programs
                 at each level of the hierarchy to ensure that the
                 hackers do not succeed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Privacy in Information and
                 Communication Systems.",
}

@Article{Sofia:2019:OPB,
  author =       "Rute C. Sofia and Paulo M. Mendes",
  title =        "An Overview on Push-Based Communication Models for
                 Information-Centric Networking",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "3",
  pages =        "74",
  day =          "21",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11030074",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/3/74",
  abstract =     "Information-centric networking integrates by design a
                 pull-based model which brings in advantages in terms of
                 control as well as of in-network caching strategies.
                 Currently, ICN main areas of action concern content
                 distribution and IoT, both of which are environments
                 that often require support for periodic and
                 even-triggered data transmission. Such environments can
                 benefit from push-based communication to achieve faster
                 data forwarding. This paper provides an overview on the
                 current push-based mechanisms that can be applied to
                 information-centric paradigms, explaining the trade-off
                 associated with the different approaches. Moreover, the
                 paper provides design guidelines for integrating push
                 communications in information-centric networking,
                 having as example the application of this networking
                 architecture in IoT environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Information-Centric Networking (ICN).",
}

@Article{Sufiev:2019:DSC,
  author =       "Hadar Sufiev and Yoram Haddad and Leonid Barenboim and
                 Jos{\'e} Soler",
  title =        "Dynamic {SDN} Controller Load Balancing",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "3",
  pages =        "75",
  day =          "21",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11030075",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/3/75",
  abstract =     "The software defined networking (SDN) paradigm
                 separates the control plane from the data plane, where
                 an SDN controller receives requests from its connected
                 switches and manages the operation of the switches
                 under its control. Reassignments between switches and
                 their controllers are performed dynamically, in order
                 to balance the load over SDN controllers. In order to
                 perform load balancing, most dynamic assignment
                 solutions use a central element to gather information
                 requests for reassignment of switches. Increasing the
                 number of controllers causes a scalability problem,
                 when one super controller is used for all controllers
                 and gathers information from all switches. In a large
                 network, the distances between the controllers is
                 sometimes a constraint for assigning them switches. In
                 this paper, a new approach is presented to solve the
                 well-known load balancing problem in the SDN control
                 plane. This approach implies less load on the central
                 element and meeting the maximum distance constraint
                 allowed between controllers. An architecture with two
                 levels of load balancing is defined. At the top level,
                 the main component called Super Controller, arranges
                 the controllers in clusters, so that there is a balance
                 between the loads of the clusters. At the bottom level,
                 in each cluster there is a dedicated controller called
                 Master Controller, which performs a reassignment of the
                 switches in order to balance the loads between the
                 controllers. We provide a two-phase algorithm, called
                 Dynamic Controllers Clustering algorithm, for the top
                 level of load balancing operation. The load balancing
                 operation takes place at regular intervals. The length
                 of the cycle in which the operation is performed can be
                 shorter, since the top-level operation can run
                 independently of the bottom level operation. Shortening
                 cycle time allows for more accurate results of load
                 balancing. Theoretical analysis demonstrates that our
                 algorithm provides a near-optimal solution. Simulation
                 results show that our dynamic clustering improves fixed
                 clustering by a multiplicative factor of 5.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Content Centric Future Internet
                 Architectures.",
}

@Article{Hyla:2019:EIM,
  author =       "Tomasz Hyla and Jerzy Peja{\'s}",
  title =        "{eHealth} Integrity Model Based on Permissioned
                 Blockchain",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "3",
  pages =        "76",
  day =          "24",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11030076",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/3/76",
  abstract =     "(1) Background: Large eHealth systems should have a
                 mechanism to detect unauthorized changes in patients'
                 medical documentation, access permissions, and logs.
                 This is due to the fact that modern eHealth systems are
                 connected with many healthcare providers and sites. (2)
                 Methods: Design-science methodology was used to create
                 an integrity-protection service model based on
                 blockchain technology. Based on the problem of
                 transactional transparency, requirements were specified
                 and a model was designed. After that, the model's
                 security and performance were evaluated. (3) Results: a
                 blockchain-based eHealth integrity model for ensuring
                 information integrity in eHealth systems that uses a
                 permissioned blockchain with off-chain information
                 storage was created. In contrast to existing solutions,
                 the proposed model allows information removal, which in
                 many countries' eHealth systems is a legal requirement,
                 and is based on a blockchain using the Practical
                 Byzantine Fault Tolerant algorithm. (4) Conclusion: a
                 blockchain can be used to store medical data or only
                 security-related data. In the proposed model, a
                 blockchain is mainly used to implement a data-integrity
                 service. This service can be implemented using other
                 mechanisms, but a blockchain provides a solution that
                 does not require trusted third parties, works in a
                 distributed eHealth environment, and supports document
                 removal.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Privacy in Information and
                 Communication Systems.",
}

@Article{Corrales-Garay:2019:ODO,
  author =       "Diego Corrales-Garay and Eva-Mar{\'\i}a
                 Mora-Valent{\'\i}n and Marta Ortiz-de-Urbina-Criado",
  title =        "Open Data for Open Innovation: An Analysis of
                 Literature Characteristics",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "3",
  pages =        "77",
  day =          "24",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11030077",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/3/77",
  abstract =     "In this paper, we review some characteristics of the
                 literature that studies the uses and applications of
                 open data for open innovation. Three research questions
                 are proposed about both topics: (1) What journals,
                 conferences and authors have published papers about the
                 use of open data for open innovation? (2) What
                 knowledge areas have been analysed in research on open
                 data for open innovation? and (3) What are the
                 methodological characteristics of the papers on open
                 data for open innovation? To answer the first question,
                 we use a descriptive analysis to identify the relevant
                 journals and authors. To address the second question,
                 we identify the knowledge areas of the studies about
                 open data for open innovation. Finally, we analyse the
                 methodological characteristics of the literature (type
                 of study, analytical techniques, sources of information
                 and geographical area). Our results show that the
                 applications of open data for open innovation are
                 interesting but their multidisciplinary nature makes
                 the context complex and diverse, opening up many future
                 avenues for research. To develop a future research
                 agenda, we propose a theoretical model and some
                 research questions to analyse the open data impact
                 process for open innovation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future Intelligent Systems and Networks
                 2019.",
}

@Article{Galanis:2019:EBS,
  author =       "Ioannis Galanis and Iraklis Anagnostopoulos and Priyaa
                 Gurunathan and Dona Burkard",
  title =        "Environmental-Based Speed Recommendation for Future
                 Smart Cars",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "3",
  pages =        "78",
  day =          "24",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11030078",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/3/78",
  abstract =     "Modern vehicles are enhanced with increased
                 computation, communication and sensing capabilities,
                 providing a variety of new features that pave the way
                 for the deployment of more sophisticated services.
                 Specifically, smart cars employ hundreds of sensors and
                 electronic systems in order to obtain situational and
                 environmental information. This rapid growth of
                 on-vehicle multi-sensor inputs along with off-vehicle
                 data streams introduce the smart car era. Thus,
                 systematic techniques for combining information
                 provided by on- and off-vehicle car connectivity are of
                 remarkable importance for the availability and
                 robustness of the overall system. This paper presents a
                 new method to employ service oriented agents that
                 cohesively align on- and off-vehicle information in
                 order to estimate the current status of the car. In
                 particular, this work combines, integrates, and
                 evaluates multiple information sources targeting future
                 smart cars. Specifically, the proposed methodology
                 leverages weather-based, on-route, and on-vehicle
                 information. As a use case, the presented work informs
                 the driver about the recommended speed that the car
                 should adapt to, based on the current status of the
                 car. It also validates the proposed speed with
                 real-time vehicular measurements.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Luo:2019:TSE,
  author =       "Xiangfeng Luo and Yawen Yi",
  title =        "Topic-Specific Emotion Mining Model for Online
                 Comments",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "3",
  pages =        "79",
  day =          "24",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11030079",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/3/79",
  abstract =     "Nowadays, massive texts are generated on the web,
                 which contain a variety of viewpoints, attitudes, and
                 emotions for products and services. Subjective
                 information mining of online comments is vital for
                 enterprises to improve their products or services and
                 for consumers to make purchase decisions. Various
                 effective methods, the mainstream one of which is the
                 topic model, have been put forward to solve this
                 problem. Although most of topic models can mine the
                 topic-level emotion of the product comments, they do
                 not consider interword relations and the number of
                 topics determined adaptively, which leads to poor
                 comprehensibility, high time requirement, and low
                 accuracy. To solve the above problems, this paper
                 proposes an unsupervised Topic-Specific Emotion Mining
                 Model (TSEM), which adds corresponding relationship
                 between aspect words and opinion words to express
                 comments as a bag of aspect--opinion pairs. On one
                 hand, the rich semantic information obtained by adding
                 interword relationship can enhance the
                 comprehensibility of results. On the other hand, text
                 dimensions reduced by adding relationships can cut the
                 computation time. In addition, the number of topics in
                 our model is adaptively determined by calculating
                 perplexity to improve the emotion accuracy of the topic
                 level. Our experiments using Taobao commodity comments
                 achieve better results than baseline models in terms of
                 accuracy, computation time, and comprehensibility.
                 Therefore, our proposed model can be effectively
                 applied to online comment emotion mining tasks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fondevila-Gascon:2019:ESU,
  author =       "Joan-Francesc Fondevila-Gasc{\'o}n and Gaspar Berbel
                 and M{\`o}nica Mu{\~n}oz-Gonz{\'a}lez",
  title =        "Experimental Study on the Utility and Future of
                 Collaborative Consumption Platforms Offering Tourism
                 Related Services",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "3",
  pages =        "80",
  day =          "25",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11030080",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/3/80",
  abstract =     "The present study analyzes four well-known online
                 platforms used in the tourist industry for travelling,
                 accommodation, eating, and touring (Blablacar, Airbnb,
                 Eatwith, and Trip4real). The objective is to analyze
                 the utility of the portals, intentions for future use
                 and recommendation (prospective), and reputation. The
                 method is an experimental design with a control group
                 and experimental group. Within both groups, three
                 scales were applied. The results indicate clear
                 differences between the control and experimental
                 groups, valuing above all the utility and the intent to
                 use again when the group is exposed to the portals from
                 a needs-based situation (experimental group). The
                 analysis demonstrates a factorial structure that
                 validates the model. At the same time, the results
                 indicate a greater interest in using Trip4Real over
                 BlaBlaCar. Generation Z, the youngest generation, shows
                 greater confidence in the services and greater interest
                 in using tourism related collaborative consumption
                 platforms in the future.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Techno-Social Smart Systems.",
}

@Article{Zhao:2019:NAB,
  author =       "Ning Zhao and Yuhe Liu and Junjie Shen",
  title =        "Nonlinear Analysis of Built-in Sensor in Smart Device
                 under the Condition of Voice Actuating",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "3",
  pages =        "81",
  day =          "26",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11030081",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/3/81",
  abstract =     "A built-in sensor in a smart device, such as the
                 accelerometer and the gyroscope, will produce an
                 obvious nonlinear output when it receives voice signal.
                 In this paper, based on the chaotic theory, the
                 nonlinearity of smartphone built-in accelerometer is
                 revealed by phase space reconstructing after we
                 calculate several nonlinearity characteristics, such as
                 best delay time, embedding dimension, and the attractor
                 of accelerometer system, under the condition of voice
                 commands inputting. The results of theoretical
                 calculation and experiments show that this specific
                 nonlinearity could lay a foundation for further signal
                 extraction and analysis.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Privacy in Information and
                 Communication Systems.",
}

@Article{Dong:2019:ACM,
  author =       "Ying Dong and Zhou Lei",
  title =        "An Access Control Model for Preventing Virtual Machine
                 Hopping Attack",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "3",
  pages =        "82",
  day =          "26",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11030082",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/3/82",
  abstract =     "As a new type of service computing model, cloud
                 computing provides various services through the
                 Internet. Virtual machine (VM) hopping is a security
                 issue often encountered in the virtualization layer.
                 Once it occurs, it directly affects the reliability of
                 the entire computing platform. Therefore, we have
                 thoroughly studied the virtual machine hopping attack.
                 In addition, we designed the access control model PVMH
                 (Prevent VM hopping) to prevent VM hopping attacks
                 based on the BLP model and the Biba model. Finally, we
                 implemented the model on the Xen platform. The
                 experiments demonstrate that our PVMH module succeeds
                 in preventing VM hopping attack with acceptable loss to
                 virtual machine performance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Celesti:2019:SJO,
  author =       "Antonio Celesti and Maria Fazio and Massimo Villari",
  title =        "A Study on Join Operations in {MongoDB} Preserving
                 Collections Data Models for Future {Internet}
                 Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "4",
  pages =        "83",
  day =          "27",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11040083",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/4/83",
  abstract =     "Presently, we are observing an explosion of data that
                 need to be stored and processed over the Internet, and
                 characterized by large volume, velocity and variety.
                 For this reason, software developers have begun to look
                 at NoSQL solutions for data storage. However,
                 operations that are trivial in traditional Relational
                 DataBase Management Systems (DBMSs) can become very
                 complex in NoSQL DBMSs. This is the case of the join
                 operation to establish a connection between two or more
                 DB structures, whose construct is not explicitly
                 available in many NoSQL databases. As a consequence,
                 the data model has to be changed or a set of operations
                 have to be performed to address particular queries on
                 data. Thus, open questions are: how do NoSQL solutions
                 work when they have to perform join operations on data
                 that are not natively supported? What is the quality of
                 NoSQL solutions in such cases? In this paper, we deal
                 with such issues specifically considering one of the
                 major NoSQL document oriented DB available on the
                 market: MongoDB. In particular, we discuss an approach
                 to perform join operations at application layer in
                 MongoDB that allows us to preserve data models. We
                 analyse performance of the proposes approach discussing
                 the introduced overhead in comparison with SQL-like
                 DBs.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Villora:2019:CDA,
  author =       "Beatriz Villora and Santiago Yubero and Ra{\'u}l
                 Navarro",
  title =        "Cyber Dating Abuse and Masculine Gender Norms in a
                 Sample of Male Adults",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "4",
  pages =        "84",
  day =          "28",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11040084",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/4/84",
  abstract =     "Gender role norms have been widely studied in the
                 offline partner violence context. Different studies
                 have indicated that internalizing these norms was
                 associated with dating violence. However, very few
                 research works have analyzed this relation in forms of
                 aggression against partners and former partners using
                 information and communication technologies (ICT). The
                 objective of the present study was to examine the
                 co-occurrence of cyber dating abuse by analyzing the
                 extent to which victimization and perpetration overlap,
                 and by analyzing the differences according to
                 conformity to the masculine gender norms between men
                 who are perpetrators or victims of cyber dating abuse.
                 The participants were 614 male university students, and
                 26.5\% of the sample reported having been a victim and
                 perpetrator of cyber dating abuse. Nonetheless, the
                 regression analyses did not reveal any statistically
                 significant association between conformity to masculine
                 gender norms and practicing either perpetration or
                 victimization by cyber dating abuse.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Techno-Social Smart Systems.",
}

@Article{Yao:2019:RSA,
  author =       "Jiaying Yao and Zhigeng Han and Muhammad Sohail and
                 Liangmin Wang",
  title =        "A Robust Security Architecture for {SDN}-Based {5G}
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "4",
  pages =        "85",
  day =          "28",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11040085",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/4/85",
  abstract =     "5G is the latest generation of cellular mobile
                 communications. Due to its significant advantage in
                 high data rate, reduced latency and massive device
                 connectivity, the 5G network plays a vital role in
                 today's commercial telecommunications networks.
                 However, the 5G network also faces some challenges when
                 used in practice. This is because it consists of
                 various diverse ingredients, termed heterogeneity. The
                 heterogeneity of the 5G network has two consequences:
                 first, it prevents us to use this technology in a
                 uniform way, preventing the wide use of 5G technology;
                 second, it complicates the structure of the 5G network,
                 making it hard to monitor what is going on in a 5G
                 network. To break through this limitation, researchers
                 have worked in this field and design their own
                 protocol, in which software-defined networking (SDN) is
                 one key design concept. By separating control and data
                 plane, SDN can make the 5G network functional and
                 programmable, such that we can handle the heterogeneity
                 in traditional 5G networks. In light of this, we say
                 that SDN-5G network is attractive, but its advantages
                 are not free. The intelligence centralization used in
                 SDN has its own drawbacks when it comes to security. To
                 break through this limitation, we propose a robust
                 security architecture for SDN-based 5G Networks. To
                 find the illegal request from malicious attackers, we
                 add extra cryptographic authentication, termed
                 synchronize secret. The basic idea of our scheme is
                 leveraging preload secrets to differ attacks from
                 regular network communications. The simulation results
                 indicate that our work can completely handle the
                 security problem from SDN with a low disconnect rate of
                 0.01\%, which is much better than that from state of
                 the art.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Software Defined Networking (SDN) and
                 Network Function Virtualization (NFV).",
}

@Article{Lopez:2019:TFD,
  author =       "C{\'e}sar P{\'e}rez L{\'o}pez and Mar{\'\i}a Jes{\'u}s
                 Delgado Rodr{\'\i}guez and Sonia de Lucas Santos",
  title =        "Tax Fraud Detection through Neural Networks: An
                 Application Using a Sample of Personal Income
                 Taxpayers",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "4",
  pages =        "86",
  day =          "30",
  month =        mar,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11040086",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/4/86",
  abstract =     "The goal of the present research is to contribute to
                 the detection of tax fraud concerning personal income
                 tax returns (IRPF, in Spanish) filed in Spain, through
                 the use of Machine Learning advanced predictive tools,
                 by applying Multilayer Perceptron neural network (MLP)
                 models. The possibilities springing from these
                 techniques have been applied to a broad range of
                 personal income return data supplied by the Institute
                 of Fiscal Studies (IEF). The use of the neural networks
                 enabled taxpayer segmentation as well as calculation of
                 the probability concerning an individual taxpayer's
                 propensity to attempt to evade taxes. The results
                 showed that the selected model has an efficiency rate
                 of 84.3\%, implying an improvement in relation to other
                 models utilized in tax fraud detection. The proposal
                 can be generalized to quantify an individual's
                 propensity to commit fraud with regards to other kinds
                 of taxes. These models will support tax offices to help
                 them arrive at the best decisions regarding action
                 plans to combat tax fraud.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future Intelligent Systems and Networks
                 2019.",
}

@Article{Zhao:2019:IQE,
  author =       "Haichuan Zhao",
  title =        "Information Quality or Entities' Interactivity?
                 {Understanding} the Determinants of Social
                 Network-Based Brand Community Participation",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "4",
  pages =        "87",
  day =          "01",
  month =        apr,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11040087",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/4/87",
  abstract =     "The customer's participation is important to the
                 survival of a brand community. By drawing on flow
                 theory, this research identified the most important
                 factors that motivate the customers' participation
                 intention than others in a social network-based brand
                 community. Data were collected from the Sina
                 micro-blog. This study adopted two different but
                 complementary methods to analyse the conceptual model:
                 Structure equation model (SEM) and fuzzy set
                 qualitative analysis (fsQCA). Results support most of
                 the research hypothesis. Specifically, the findings
                 obtained from the fsQCA indicate that information
                 quality and platform-interactivity are necessary
                 conditions that encourage the customers' participation
                 in a brand community.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Techno-Social Smart Systems.",
}

@Article{Lin:2019:OES,
  author =       "Guoying Lin and Yuyao Yang and Feng Pan and Sijian
                 Zhang and Fen Wang and Shuai Fan",
  title =        "An Optimal Energy-Saving Strategy for Home Energy
                 Management Systems with Bounded Customer Rationality",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "4",
  pages =        "88",
  day =          "02",
  month =        apr,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11040088",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/4/88",
  abstract =     "With the development of techniques, such as the
                 Internet of Things (IoT) and edge computing, home
                 energy management systems (HEMS) have been widely
                 implemented to improve the electric energy efficiency
                 of customers. In order to automatically optimize
                 electric appliances' operation schedules, this paper
                 considers how to quantitatively evaluate a customer's
                 comfort satisfaction in energy-saving programs, and how
                 to formulate the optimal energy-saving model based on
                 this satisfaction evaluation. First, the paper
                 categorizes the utility functions of current electric
                 appliances into two types; time-sensitive utilities and
                 temperature-sensitive utilities, which cover nearly all
                 kinds of electric appliances in HEMS. Furthermore,
                 considering the bounded rationality of customers, a
                 novel concept called the energy-saving cost is defined
                 by incorporating prospect theory in behavioral
                 economics into general utility functions. The proposed
                 energy-saving cost depicts the comfort loss risk for
                 customers when their HEMS schedules the operation
                 status of appliances, which is able to be set by
                 residents as a coefficient in the automatic
                 energy-saving program. An optimization model is
                 formulated based on minimizing energy consumption.
                 Because the energy-saving cost has already been
                 evaluated in the context of the satisfaction of
                 customers, the formulation of the optimization program
                 is very simple and has high computational efficiency.
                 The case study included in this paper is first
                 performed on a general simulation system. Then, a case
                 study is set up based on real field tests from a pilot
                 project in Guangdong province, China, in which
                 air-conditioners, lighting, and some other popular
                 electric appliances were included. The total
                 energy-saving rate reached 65.5\% after the proposed
                 energy-saving program was deployed in our project. The
                 benchmark test shows our optimal strategy is able to
                 considerably save electrical energy for residents while
                 ensuring customers' comfort satisfaction is
                 maintained.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Salahdine:2019:SEA,
  author =       "Fatima Salahdine and Naima Kaabouch",
  title =        "Social Engineering Attacks: a Survey",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "4",
  pages =        "89",
  day =          "02",
  month =        apr,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11040089",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/4/89",
  abstract =     "The advancements in digital communication technology
                 have made communication between humans more accessible
                 and instant. However, personal and sensitive
                 information may be available online through social
                 networks and online services that lack the security
                 measures to protect this information. Communication
                 systems are vulnerable and can easily be penetrated by
                 malicious users through social engineering attacks.
                 These attacks aim at tricking individuals or
                 enterprises into accomplishing actions that benefit
                 attackers or providing them with sensitive data such as
                 social security number, health records, and passwords.
                 Social engineering is one of the biggest challenges
                 facing network security because it exploits the natural
                 human tendency to trust. This paper provides an
                 in-depth survey about the social engineering attacks,
                 their classifications, detection strategies, and
                 prevention procedures.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Signal Processing for Next Generation
                 Wireless Networks.",
}

@Article{Li:2019:ACO,
  author =       "Gang Li and Zhijun Wu",
  title =        "Ant Colony Optimization Task Scheduling Algorithm for
                 {SWIM} Based on Load Balancing",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "4",
  pages =        "90",
  day =          "02",
  month =        apr,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11040090",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/4/90",
  abstract =     "This paper focuses on the load imbalance problem in
                 System Wide Information Management (SWIM) task
                 scheduling. In order to meet the quality requirements
                 of users for task completion, we studied large-scale
                 network information system task scheduling methods.
                 Combined with the traditional ant colony optimization
                 (ACO) algorithm, using the hardware performance quality
                 index and load standard deviation function of SWIM
                 resource nodes to update the pheromone, a SWIM ant
                 colony task scheduling algorithm based on load
                 balancing (ACTS-LB) is presented in this paper. The
                 experimental simulation results show that the ACTS-LB
                 algorithm performance is better than the traditional
                 min-min algorithm, ACO algorithm and particle swarm
                 optimization (PSO) algorithm. It not only reduces the
                 task execution time and improves the utilization of
                 system resources, but also can maintain SWIM in a more
                 load balanced state.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Privacy in Information and
                 Communication Systems.",
}

@Article{Zhang:2019:DGR,
  author =       "Xinyu Zhang and Xiaoqiang Li",
  title =        "Dynamic Gesture Recognition Based on {MEMP} Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "4",
  pages =        "91",
  day =          "03",
  month =        apr,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11040091",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/4/91",
  abstract =     "In recent years, gesture recognition has been used in
                 many fields, such as games, robotics and sign language
                 recognition. Human computer interaction (HCI) has been
                 significantly improved by the development of gesture
                 recognition, and now gesture recognition in video is an
                 important research direction. Because each kind of
                 neural network structure has its limitation, we
                 proposed a neural network with alternate fusion of 3D
                 CNN and ConvLSTM, which we called the Multiple
                 extraction and Multiple prediction (MEMP) network. The
                 main feature of the MEMP network is to extract and
                 predict the temporal and spatial feature information of
                 gesture video multiple times, which enables us to
                 obtain a high accuracy rate. In the experimental part,
                 three data sets (LSA64, SKIG and Chalearn 2016) are
                 used to verify the performance of network. Our approach
                 achieved high accuracy on those data sets. In the
                 LSA64, the network achieved an identification rate of
                 99.063\%. In SKIG, this network obtained the
                 recognition rates of 97.01\% and 99.02\% in the RGB
                 part and the rgb-depth part. In Chalearn 2016, the
                 network achieved 74.57\% and 78.85\% recognition rates
                 in RGB part and rgb-depth part respectively.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Innovative Topologies and Algorithms for
                 Neural Networks.",
}

@Article{Hackl:2019:ESU,
  author =       "J{\"u}rgen Hackl and Thibaut Dubernet",
  title =        "Epidemic Spreading in Urban Areas Using Agent-Based
                 Transportation Models",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "4",
  pages =        "92",
  day =          "08",
  month =        apr,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11040092",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/4/92",
  abstract =     "Human mobility is a key element in the understanding
                 of epidemic spreading. Thus, correctly modeling and
                 quantifying human mobility is critical for studying
                 large-scale spatial transmission of infectious diseases
                 and improving epidemic control. In this study, a
                 large-scale agent-based transport simulation (MATSim)
                 is linked with a generic epidemic spread model to
                 simulate the spread of communicable diseases in an
                 urban environment. The use of an agent-based model
                 allows reproduction of the real-world behavior of
                 individuals' daily path in an urban setting and allows
                 the capture of interactions among them, in the form of
                 a spatial-temporal social network. This model is used
                 to study seasonal influenza outbreaks in the
                 metropolitan area of Zurich, Switzerland. The
                 observations of the agent-based models are compared
                 with results from classical SIR models. The model
                 presented is a prototype that can be used to analyze
                 multiple scenarios in the case of a disease spread at
                 an urban scale, considering variations of different
                 model parameters settings. The results of this
                 simulation can help to improve comprehension of the
                 disease spread dynamics and to take better steps
                 towards the prevention and control of an epidemic.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Selected papers from The 7th
                 International Conference on Complex Networks and Their
                 Applications.",
}

@Article{Barro:2019:SCL,
  author =       "Pape Abdoulaye Barro and Marco Zennaro and Jules
                 Degila and Ermanno Pietrosemoli",
  title =        "A Smart Cities {LoRaWAN} Network Based on Autonomous
                 Base Stations ({BS}) for Some Countries with Limited
                 {Internet} Access",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "4",
  pages =        "93",
  day =          "08",
  month =        apr,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11040093",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/4/93",
  abstract =     "An increasing number of implementations of IoT for
                 development use the LoRaWAN protocol as many of them
                 leverage the free network and application servers
                 provided by The Things Networks (TTN) to fulfill their
                 needs. Unfortunately, in some countries in Sub-Saharan
                 Africa and South Asia, Internet access cannot be taken
                 for granted, therefore, TTN might not be available.
                 Moreover, low-cost and low-power consumption options
                 devices are the most sustainable ones. In this paper,
                 we propose a LoRaWAN network with autonomous base
                 stations that can work without Internet connectivity
                 for essential services, while being able to provide
                 additional features whenever Internet access becomes
                 available, even in an intermittent fashion. Security
                 and privacy are preserved, with support for mobile
                 nodes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue IoT for Development (IoT4D).",
}

@Article{Zantalis:2019:RML,
  author =       "Fotios Zantalis and Grigorios Koulouras and Sotiris
                 Karabetsos and Dionisis Kandris",
  title =        "A Review of Machine Learning and {IoT} in Smart
                 Transportation",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "4",
  pages =        "94",
  day =          "10",
  month =        apr,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11040094",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/4/94",
  abstract =     "With the rise of the Internet of Things (IoT),
                 applications have become smarter and connected devices
                 give rise to their exploitation in all aspects of a
                 modern city. As the volume of the collected data
                 increases, Machine Learning (ML) techniques are applied
                 to further enhance the intelligence and the
                 capabilities of an application. The field of smart
                 transportation has attracted many researchers and it
                 has been approached with both ML and IoT techniques. In
                 this review, smart transportation is considered to be
                 an umbrella term that covers route optimization,
                 parking, street lights, accident prevention/detection,
                 road anomalies, and infrastructure applications. The
                 purpose of this paper is to make a self-contained
                 review of ML techniques and IoT applications in
                 Intelligent Transportation Systems (ITS) and obtain a
                 clear view of the trends in the aforementioned fields
                 and spot possible coverage needs. From the reviewed
                 articles it becomes profound that there is a possible
                 lack of ML coverage for the Smart Lighting Systems and
                 Smart Parking applications. Additionally, route
                 optimization, parking, and accident/detection tend to
                 be the most popular ITS applications among
                 researchers.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Wang:2019:IMS,
  author =       "Fei Wang and Zhenfang Zhu and Peiyu Liu and Peipei
                 Wang",
  title =        "Influence Maximization in Social Network Considering
                 Memory Effect and Social Reinforcement Effect",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "4",
  pages =        "95",
  day =          "11",
  month =        apr,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11040095",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/4/95",
  abstract =     "Social networks have attracted a lot of attention as
                 novel information or advertisement diffusion media for
                 viral marketing. Influence maximization describes the
                 problem of finding a small subset of seed nodes in a
                 social network that could maximize the spread of
                 influence. A lot of algorithms have been proposed to
                 solve this problem. Recently, in order to achieve more
                 realistic viral marketing scenarios, some constrained
                 versions of influence maximization, which consider time
                 constraints, budget constraints and so on, have been
                 proposed. However, none of them considers the memory
                 effect and the social reinforcement effect, which are
                 ubiquitous properties of social networks. In this
                 paper, we define a new constrained version of the
                 influence maximization problem that captures the social
                 reinforcement and memory effects. We first propose a
                 novel propagation model to capture the dynamics of the
                 memory and social reinforcement effects. Then, we
                 modify two baseline algorithms and design a new
                 algorithm to solve the problem under the model.
                 Experiments show that our algorithm achieves the best
                 performance with relatively low time complexity. We
                 also demonstrate that the new version captures some
                 important properties of viral marketing in social
                 networks, such as such as social reinforcements, and
                 could explain some phenomena that cannot be explained
                 by existing influence maximization problem
                 definitions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Multi-Agent Systems for Social Media
                 Analysis.",
}

@Article{Li:2019:IAT,
  author =       "Wenkuan Li and Peiyu Liu and Qiuyue Zhang and Wenfeng
                 Liu",
  title =        "An Improved Approach for Text Sentiment Classification
                 Based on a Deep Neural Network via a Sentiment
                 Attention Mechanism",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "4",
  pages =        "96",
  day =          "11",
  month =        apr,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11040096",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/4/96",
  abstract =     "Text sentiment analysis is an important but
                 challenging task. Remarkable success has been achieved
                 along with the wide application of deep learning
                 methods, but deep learning methods dealing with text
                 sentiment classification tasks cannot fully exploit
                 sentiment linguistic knowledge, which hinders the
                 development of text sentiment analysis. In this paper,
                 we propose a sentiment-feature-enhanced deep neural
                 network (SDNN) to address the problem by integrating
                 sentiment linguistic knowledge into a deep neural
                 network via a sentiment attention mechanism.
                 Specifically, first we introduce a novel sentiment
                 attention mechanism to help select the crucial
                 sentiment-word-relevant context words by leveraging the
                 sentiment lexicon in an attention mechanism, which
                 bridges the gap between traditional sentiment
                 linguistic knowledge and current popular deep learning
                 methods. Second, we develop an improved deep neural
                 network to extract sequential correlation information
                 and text local features by combining bidirectional
                 gated recurrent units with a convolutional neural
                 network, which further enhances the ability of
                 comprehensive text representation learning. With this
                 design, the SDNN model can generate a powerful semantic
                 representation of text to improve the performance of
                 text sentiment classification tasks. Extensive
                 experiments were conducted to evaluate the
                 effectiveness of the proposed SDNN model on two
                 real-world datasets with a binary-sentiment-label and a
                 multi-sentiment-label. The experimental results
                 demonstrated that the SDNN achieved substantially
                 better performance than the strong competitors for text
                 sentiment classification tasks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Innovative Topologies and Algorithms for
                 Neural Networks.",
}

@Article{Dong:2019:MBN,
  author =       "Peixin Dong and Dongyuan Li and Jianping Xing and
                 Haohui Duan and Yong Wu",
  title =        "A Method of Bus Network Optimization Based on Complex
                 Network and Beidou Vehicle Location",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "4",
  pages =        "97",
  day =          "15",
  month =        apr,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11040097",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/4/97",
  abstract =     "Aiming at the problems of poor time performance and
                 accuracy in bus stops network optimization, this paper
                 proposes an algorithm based on complex network and
                 graph theory and Beidou Vehicle Location to measure the
                 importance of bus stops. This method narrows the scope
                 of points and edges to be optimized and is applied to
                 the Jinan bus stop network. In this method, the bus
                 driving efficiency, which can objectively reflect
                 actual road conditions, is taken as the weight of the
                 connecting edges in the network, and the network is
                 optimized through the network efficiency. The
                 experimental results show that, compared with the
                 original network, the optimized network time
                 performance is good and the optimized network bus
                 driving efficiency is improved.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yuan:2019:FOS,
  author =       "Peiyan Yuan and Xiaoxiao Pang and Ping Liu and En
                 Zhang",
  title =        "{FollowMe}: One Social Importance-Based Collaborative
                 Scheme in {MONs}",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "4",
  pages =        "98",
  day =          "17",
  month =        apr,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11040098",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/4/98",
  abstract =     "The performance of mobile opportunistic networks
                 mainly relies on collaboration among nodes. Thus far,
                 researchers have ignored the influence of node
                 sociality on the incentive process, leading to poor
                 network performance. Considering the fact that
                 followers always imitate the behavior of superstars,
                 this paper proposes FollowMe, which integrates the
                 social importance of nodes with evolutionary game
                 theory to improve the collaborative behavior of nodes.
                 First, we use the prisoner's dilemma model to establish
                 the matrix of game gains between nodes. Second, we
                 introduce the signal reference as a game rule between
                 nodes. The number of nodes choosing different
                 strategies in a game round is used to calculate the
                 cumulative income of the node in combination with the
                 probability formula. Finally, the Fermi function is
                 used to determine whether the node updates the
                 strategy. The simulation results show that, compared
                 with the random update rule, the proposed strategy is
                 more capable of promoting cooperative behavior between
                 nodes to improve the delivery rate of data packets.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Techno-Social Smart Systems.",
}

@Article{Cilfone:2019:WMN,
  author =       "Antonio Cilfone and Luca Davoli and Laura Belli and
                 Gianluigi Ferrari",
  title =        "Wireless Mesh Networking: An {IoT}-Oriented
                 Perspective Survey on Relevant Technologies",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "4",
  pages =        "99",
  day =          "17",
  month =        apr,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11040099",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/4/99",
  abstract =     "The Internet of Things (IoT), being a ``network of
                 networks'', promises to allow billions of humans and
                 machines to interact with each other. Owing to this
                 rapid growth, the deployment of IoT-oriented networks
                 based on mesh topologies is very attractive, thanks to
                 their scalability and reliability (in the presence of
                 failures). In this paper, we provide a comprehensive
                 survey of the following relevant wireless technologies:
                 IEEE 802.11, Bluetooth, IEEE 802.15.4-oriented, and
                 Sub-GHz-based LoRa. Our goal is to highlight how
                 various communication technologies may be suitable for
                 mesh networking, either providing a native support or
                 being adapted subsequently. Hence, we discuss how these
                 wireless technologies, being either standard or
                 proprietary, can adapt to IoT scenarios (e.g., smart
                 cities and smart agriculture) in which the
                 heterogeneity of the involved devices is a key feature.
                 Finally, we provide reference use cases involving all
                 the analyzed mesh-oriented technologies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Capra:2019:ECS,
  author =       "Maurizio Capra and Riccardo Peloso and Guido Masera
                 and Massimo Ruo Roch and Maurizio Martina",
  title =        "Edge Computing: a Survey On the Hardware Requirements
                 in the {Internet of Things} World",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "4",
  pages =        "100",
  day =          "23",
  month =        apr,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11040100",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/4/100",
  abstract =     "In today's world, ruled by a great amount of data and
                 mobile devices, cloud-based systems are spreading all
                 over. Such phenomenon increases the number of connected
                 devices, broadcast bandwidth, and information exchange.
                 These fine-grained interconnected systems, which enable
                 the Internet connectivity for an extremely large number
                 of facilities (far beyond the current number of
                 devices) go by the name of Internet of Things (IoT). In
                 this scenario, mobile devices have an operating time
                 which is proportional to the battery capacity, the
                 number of operations performed per cycle and the amount
                 of exchanged data. Since the transmission of data to a
                 central cloud represents a very energy-hungry
                 operation, new computational paradigms have been
                 implemented. The computation is not completely
                 performed in the cloud, distributing the power load
                 among the nodes of the system, and data are compressed
                 to reduce the transmitted power requirements. In the
                 edge-computing paradigm, part of the computational
                 power is moved toward data collection sources, and,
                 only after a first elaboration, collected data are sent
                 to the central cloud server. Indeed, the ``edge'' term
                 refers to the extremities of systems represented by IoT
                 devices. This survey paper presents the hardware
                 architectures of typical IoT devices and sums up many
                 of the low power techniques which make them appealing
                 for a large scale of applications. An overview of the
                 newest research topics is discussed, besides a final
                 example of a complete functioning system, embedding all
                 the introduced features.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Ciuffoletti:2019:DOR,
  author =       "Augusto Ciuffoletti",
  title =        "Design of an Open Remote Electrocardiogram ({ECG})
                 Service",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "4",
  pages =        "101",
  day =          "24",
  month =        apr,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11040101",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:05 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/4/101",
  abstract =     "Currently, the deployment of services for real-time
                 delivery of an electrocardiogram to a remote site has a
                 cost that prevents its widespread diffusion, which
                 would contribute to saving lives with prevention,
                 assistance and rescue efficiency. To fill this gap, we
                 introduce the design of a remote electrocardiogram
                 service that privileges open, low-cost options. The
                 architecture is based on the HyperText Transfer
                 Protocol (HTTP) and uses commercial off-the-shelf
                 devices to implement the sensor on the patient's side.
                 The doctor uses a laptop browser to display the
                 tracing, and a cloud computing instance connects the
                 two using WebSockets. A prototype is built to evaluate
                 overall performance, the power consumption of the
                 patient's side device, and the quality of rendering on
                 doctor's browser. The patient's sensor prototype device
                 is portable, and its power consumption is below 1 Watt,
                 thus allowing a daylong autonomy when operated on
                 batteries. Its cost is below 50\$, and the required
                 hardware is commercially available. The whole design is
                 ready for on-field evaluation, and it is available in a
                 public repository.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Techno-Social Smart Systems.",
}

@Article{Vila:2019:RTM,
  author =       "Ga{\"e}l Vila and Christelle Godin and Oumayma Sakri
                 and Etienne Labyt and Audrey Vidal and Sylvie
                 Charbonnier and Simon Ollander and Aur{\'e}lie
                 Campagne",
  title =        "Real-Time Monitoring of Passenger's Psychological
                 Stress",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "5",
  pages =        "102",
  day =          "26",
  month =        apr,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11050102",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/5/102",
  abstract =     "This article addresses the question of passengers'
                 experience through different transport modes. It
                 presents the main results of a pilot study, for which
                 stress levels experienced by a traveller were assessed
                 and predicted over two long journeys. Accelerometer
                 measures and several physiological signals
                 (electrodermal activity, blood volume pulse and skin
                 temperature) were recorded using a smart wristband
                 while travelling from Grenoble to Bilbao. Based on
                 user's feedback, three events of high stress and one
                 period of moderate activity with low stress were
                 identified offline. Over these periods, feature
                 extraction and machine learning were performed from the
                 collected sensor data to build a personalized
                 regressive model, with user's stress levels as output.
                 A smartphone application has been developed on its
                 basis, in order to record and visualize a timely
                 estimated stress level using traveler's physiological
                 signals. This setting was put on test during another
                 travel from Grenoble to Brussels, where the same user's
                 stress levels were predicted in real time by the
                 smartphone application. The number of correctly
                 classified stress-less time windows ranged from 92.6\%
                 to 100\%, depending on participant's level of activity.
                 By design, this study represents a first step for
                 real-life, ambulatory monitoring of passenger's stress
                 while travelling.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Internet of Things for Smart City
                 Applications.",
}

@Article{Burger:2019:CSS,
  author =       "Annetta Burger and Talha Oz and William G. Kennedy and
                 Andrew T. Crooks",
  title =        "Computational Social Science of Disasters:
                 Opportunities and Challenges",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "5",
  pages =        "103",
  day =          "26",
  month =        apr,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11050103",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/5/103",
  abstract =     "Disaster events and their economic impacts are
                 trending, and climate projection studies suggest that
                 the risks of disaster will continue to increase in the
                 near future. Despite the broad and increasing social
                 effects of these events, the empirical basis of
                 disaster research is often weak, partially due to the
                 natural paucity of observed data. At the same time,
                 some of the early research regarding social responses
                 to disasters have become outdated as social, cultural,
                 and political norms have changed. The digital
                 revolution, the open data trend, and the advancements
                 in data science provide new opportunities for social
                 science disaster research. We introduce the term
                 computational social science of disasters (CSSD), which
                 can be formally defined as the systematic study of the
                 social behavioral dynamics of disasters utilizing
                 computational methods. In this paper, we discuss and
                 showcase the opportunities and the challenges in this
                 new approach to disaster research. Following a brief
                 review of the fields that relate to CSSD, namely
                 traditional social sciences of disasters, computational
                 social science, and crisis informatics, we examine how
                 advances in Internet technologies offer a new lens
                 through which to study disasters. By identifying gaps
                 in the literature, we show how this new field could
                 address ways to advance our understanding of the social
                 and behavioral aspects of disasters in a digitally
                 connected world. In doing so, our goal is to bridge the
                 gap between data science and the social sciences of
                 disasters in rapidly changing environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Tejedor:2019:ASU,
  author =       "Santiago Tejedor and Laura Cervi and Gerard Gordon",
  title =        "Analysis of the Structure and Use of Digital Resources
                 on the {Websites} of the Main Football Clubs in
                 {Europe}",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "5",
  pages =        "104",
  day =          "29",
  month =        apr,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11050104",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/5/104",
  abstract =     "Football clubs can be considered global brands, and
                 exactly as any other brand, they need to face the
                 challenge of adapting to digital communications.
                 Nevertheless, communication sciences research in this
                 field is scarce, so the main purpose of this work is to
                 analyze digital communication of the main football
                 clubs in Europe to identify and describe what
                 strategies they follow to make themselves known on the
                 internet and to interact with their users.
                 Specifically, the article studies the characteristics
                 of web pages --- considered as the main showcase of a
                 brand/team in the digital environment --- of the
                 fifteen best teams in the UEFA ranking to establish
                 what type of structure and what online communication
                 resources they use. Through a descriptive and
                 comparative analysis, the study concludes, among other
                 aspects, that the management of communication is
                 effective, but also warns that none of the analyzed
                 team takes full advantage of the possibilities of
                 interaction with the user offered by the digital
                 scenario.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future Intelligent Systems and Networks
                 2019.",
}

@Article{Huang:2019:CFE,
  author =       "Yongrui Huang and Jianhao Yang and Siyu Liu and Jiahui
                 Pan",
  title =        "Combining Facial Expressions and
                 Electroencephalography to Enhance Emotion Recognition",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "5",
  pages =        "105",
  day =          "02",
  month =        may,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11050105",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/5/105",
  abstract =     "Emotion recognition plays an essential role in
                 human--computer interaction. Previous studies have
                 investigated the use of facial expression and
                 electroencephalogram (EEG) signals from single modal
                 for emotion recognition separately, but few have paid
                 attention to a fusion between them. In this paper, we
                 adopted a multimodal emotion recognition framework by
                 combining facial expression and EEG, based on a
                 valence-arousal emotional model. For facial expression
                 detection, we followed a transfer learning approach for
                 multi-task convolutional neural network (CNN)
                 architectures to detect the state of valence and
                 arousal. For EEG detection, two learning targets
                 (valence and arousal) were detected by different
                 support vector machine (SVM) classifiers, separately.
                 Finally, two decision-level fusion methods based on the
                 enumerate weight rule or an adaptive boosting technique
                 were used to combine facial expression and EEG. In the
                 experiment, the subjects were instructed to watch clips
                 designed to elicit an emotional response and then
                 reported their emotional state. We used two emotion
                 datasets --- a Database for Emotion Analysis using
                 Physiological Signals (DEAP) and MAHNOB-human computer
                 interface (MAHNOB-HCI) --- to evaluate our method. In
                 addition, we also performed an online experiment to
                 make our method more robust. We experimentally
                 demonstrated that our method produces state-of-the-art
                 results in terms of binary valence/arousal
                 classification, based on DEAP and MAHNOB-HCI data sets.
                 Besides this, for the online experiment, we achieved
                 69.75\% accuracy for the valence space and 70.00\%
                 accuracy for the arousal space after fusion, each of
                 which has surpassed the highest performing single
                 modality (69.28\% for the valence space and 64.00\% for
                 the arousal space). The results suggest that the
                 combination of facial expressions and EEG information
                 for emotion recognition compensates for their defects
                 as single information sources. The novelty of this work
                 is as follows. To begin with, we combined facial
                 expression and EEG to improve the performance of
                 emotion recognition. Furthermore, we used transfer
                 learning techniques to tackle the problem of lacking
                 data and achieve higher accuracy for facial expression.
                 Finally, in addition to implementing the widely used
                 fusion method based on enumerating different weights
                 between two models, we also explored a novel fusion
                 method, applying boosting technique.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Special Issue on the Future of
                 Intelligent Human-Computer Interface.",
}

@Article{Karagiannis:2019:DLS,
  author =       "Georgios A. Karagiannis and Athanasios D.
                 Panagopoulos",
  title =        "Dynamic Lognormal Shadowing Framework for the
                 Performance Evaluation of Next Generation Cellular
                 Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "5",
  pages =        "106",
  day =          "02",
  month =        may,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11050106",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/5/106",
  abstract =     "Performance evaluation tools for wireless cellular
                 systems are very important for the establishment and
                 testing of future internet applications. As the
                 complexity of wireless networks keeps growing, wireless
                 connectivity becomes the most critical requirement in a
                 variety of applications (considered also complex and
                 unfavorable from propagation point of view environments
                 and paradigms). Nowadays, with the upcoming 5G cellular
                 networks the development of realistic and more accurate
                 channel model frameworks has become more important
                 since new frequency bands are used and new
                 architectures are employed. Large scale fading known
                 also as shadowing, refers to the variations of the
                 received signal mainly caused by obstructions that
                 significantly affect the available signal power at a
                 receiver's position. Although the variability of
                 shadowing is considered mostly spatial for a given
                 propagation environment, moving obstructions may
                 significantly impact the received signal's strength,
                 especially in dense environments, inducing thus a
                 temporal variability even for the fixed users. In this
                 paper, we present the case of lognormal shadowing, a
                 novel engineering model based on stochastic
                 differential equations that models not only the spatial
                 correlation structure of shadowing but also its
                 temporal dynamics. Based on the proposed
                 spatio-temporal shadowing field we present a
                 computationally efficient model for the dynamics of
                 shadowing experienced by stationary or mobile users. We
                 also present new analytical results for the average
                 outage duration and hand-offs based on
                 multi-dimensional level crossings. Numerical results
                 are also presented for the validation of the model and
                 some important conclusions are drawn.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Pelle:2019:EAF,
  author =       "Istv{\'a}n Pelle and Andr{\'a}s Guly{\'a}s",
  title =        "An Extensible Automated Failure Localization Framework
                 Using {NetKAT}, {Felix}, and {SDN} Traceroute",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "5",
  pages =        "107",
  day =          "04",
  month =        may,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11050107",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/5/107",
  abstract =     "Designing, implementing, and maintaining network
                 policies that protect from internal and external
                 threats is a highly non-trivial task. Often,
                 troubleshooting networks consisting of diverse entities
                 realizing complex policies is even harder.
                 Software-defined networking (SDN) enables networks to
                 adapt to changing scenarios, which significantly
                 lessens human effort required for constant manual
                 modifications of device configurations. Troubleshooting
                 benefits SDN's method of accessing forwarding devices
                 as well, since monitoring is made much easier via
                 unified control channels. However, by making policy
                 changes easier, the job of troubleshooting operators is
                 made harder too: For humans, finding, analyzing, and
                 fixing network issues becomes almost intractable. In
                 this paper, we present a failure localization framework
                 and its proof-of-concept prototype that helps in
                 automating the investigation of network issues. Like a
                 controller for troubleshooting tools, our framework
                 integrates the formal specification (expected behavior)
                 and network monitoring (actual behavior) and
                 automatically gives hints about the location and type
                 of network issues by comparing the two types of
                 information. By using NetKAT (Kleene algebra with
                 tests) for formal specification and Felix and SDN
                 traceroute for network monitoring, we show that the
                 integration of these tools in a single framework can
                 significantly ease the network troubleshooting
                 process.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Abro:2019:LEE,
  author =       "Adeel Abro and Zhongliang Deng and Kamran Ali Memon",
  title =        "A Lightweight Elliptic-{Elgamal}-Based Authentication
                 Scheme for Secure Device-to-Device Communication",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "5",
  pages =        "108",
  day =          "07",
  month =        may,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11050108",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/5/108",
  abstract =     "Device-to-Device (D2D) is a major part of 5G that will
                 facilitate deployments with extended coverage where
                 devices can act as users or relays. These relays
                 normally act as decode and forward relays
                 (semi-intelligent devices) with limited computational
                 and storage capabilities. However, introducing such a
                 technology, where users can act as relays, presents a
                 wide range of security threats, in particular, rogue
                 relay devices or man in the middle attacks (M-I-T-M).
                 Second, passing fewer control messages is always
                 advisable when considering authenticity and secrecy. To
                 mitigate M-I-T-M and to reduce communication costs,
                 this paper presents a lightweight
                 elliptic-ElGamal-based authentication scheme using PKI
                 (FHEEP) in D2D communication. Pollard's rho and Baby
                 Step, Giant Step (BSGS) methods are used to evaluate
                 the authenticity and secrecy of our proposed scheme.
                 The communication cost is calculated based on the
                 comparative analysis indicating that our proposed
                 scheme outperforms the baseline protocol. The proposed
                 scheme can be used for any infrastructure architecture
                 that will enhance the security of any D2D settings with
                 better performance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Internet of Things.",
}

@Article{Al-Rahayfeh:2019:NAT,
  author =       "Amer Al-Rahayfeh and Saleh Atiewi and Abdullah
                 Abuhussein and Muder Almiani",
  title =        "Novel Approach to Task Scheduling and Load Balancing
                 Using the Dominant Sequence Clustering and Mean Shift
                 Clustering Algorithms",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "5",
  pages =        "109",
  day =          "08",
  month =        may,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11050109",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/5/109",
  abstract =     "Cloud computing (CC) is fast-growing and frequently
                 adopted in information technology (IT) environments due
                 to the benefits it offers. Task scheduling and load
                 balancing are amongst the hot topics in the realm of
                 CC. To overcome the shortcomings of the existing task
                 scheduling and load balancing approaches, we propose a
                 novel approach that uses dominant sequence clustering
                 (DSC) for task scheduling and a weighted least
                 connection (WLC) algorithm for load balancing. First,
                 users' tasks are clustered using the DSC algorithm,
                 which represents user tasks as graph of one or more
                 clusters. After task clustering, each task is ranked
                 using Modified Heterogeneous Earliest Finish Time
                 (MHEFT) algorithm. where the highest priority task is
                 scheduled first. Afterwards, virtual machines (VM) are
                 clustered using a mean shift clustering (MSC) algorithm
                 using kernel functions. Load balancing is subsequently
                 performed using a WLC algorithm, which distributes the
                 load based on server weight and capacity as well as
                 client connectivity to server. A highly weighted or
                 least connected server is selected for task allocation,
                 which in turn increases the response time. Finally, we
                 evaluate the proposed architecture using metrics such
                 as response time, makespan, resource utilization, and
                 service reliability.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Cloud Computing and Internet of
                 Things.",
}

@Article{Yajima:2019:YPU,
  author =       "Hayato Yajima and Kazumasa Takami",
  title =        "A Yielding Protocol that Uses Inter-Vehicle
                 Communication to Improve the Traffic of Vehicles on a
                 Low-Priority Road at an Unsignalized Intersection",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "5",
  pages =        "110",
  day =          "09",
  month =        may,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11050110",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/5/110",
  abstract =     "Self-driven vehicles are being actively developed.
                 When widespread, they will help reduce the number of
                 traffic accidents and ease traffic congestion. They
                 will coexist with human-driven vehicles for years. If
                 there is a mismatch between human drivers' operations
                 and the judgments of self-driven vehicles, congestion
                 may arise at an unsignalized intersection, in
                 particular, where roads are prioritized. Vehicles on
                 the low-priority road attempting to cross, or turn to,
                 the priority road can significantly reduce the traffic
                 flow. We have proposed a yielding protocol to deal with
                 this problem and evaluated it using a simulation that
                 focused on traffic flow efficiency at an intersection.
                 In the simulation, we have varied the number of
                 vehicles coming into the roads and the percentage of
                 self-driven vehicles and confirmed that the proposed
                 yielding protocol could improve the traffic flow of
                 vehicles on the low-priority road.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Advances in Internet of Vehicles
                 (IoV).",
}

@Article{Sofia:2019:GTI,
  author =       "Rute C. Sofia",
  title =        "Guidelines towards Information-Driven Mobility
                 Management",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "5",
  pages =        "111",
  day =          "10",
  month =        may,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11050111",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/5/111",
  abstract =     "The architectural semantics of Information-Centric
                 Networking bring in interesting features in regards to
                 mobility management: Information-Centric Networking is
                 content-oriented, connection-less, and receiver-driven.
                 Despite such intrinsic advantages, the support for node
                 movement is being based on the principles of IP
                 solutions. IP-based solutions are, however,
                 host-oriented, and Information-Centric Networking
                 paradigms are information-oriented. By following IP
                 mobility management principles, some of the natural
                 mobility support advantages of Information-Centric
                 Networking are not being adequately explored. This
                 paper contributes with an overview on how
                 Information-Centric Networking paradigms handle
                 mobility management as of today, highlighting current
                 challenges and proposing a set of design guidelines to
                 overcome them, thus steering a vision towards a
                 content-centric mobility management approach.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Information-Centric Networking (ICN).",
}

@Article{Rao:2019:SSN,
  author =       "Xuli Rao and Jiaxu Zhao and Zhide Chen and Feng Lin",
  title =        "Substitute Seed Nodes Mining Algorithms for Influence
                 Maximization in Multi-Social Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "5",
  pages =        "112",
  day =          "10",
  month =        may,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11050112",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/5/112",
  abstract =     "Due to the growing interconnections of social
                 networks, the problem of influence maximization has
                 been extended from a single social network to multiple
                 social networks. However, a critical challenge of
                 influence maximization in multi-social networks is that
                 some initial seed nodes may be unable to be active,
                 which obviously leads to a low performance of influence
                 spreading. Therefore, finding substitute nodes for
                 mitigating the influence loss of uncooperative nodes is
                 extremely helpful in influence maximization. In this
                 paper, we propose three substitute mining algorithms
                 for influence maximization in multi-social networks,
                 namely for the Greedy-based substitute mining
                 algorithm, pre-selected-based substitute mining
                 algorithm, and similar-users-based substitute mining
                 algorithm. The simulation results demonstrate that the
                 existence of the uncooperative seed nodes leads to the
                 range reduction of information influence. Furthermore,
                 the viability and performance of the proposed
                 algorithms are presented, which show that three
                 substitute node mining algorithms can find suitable
                 substitute nodes for multi-social networks influence
                 maximization, thus achieves better influence.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Techno-Social Smart Systems.",
}

@Article{Kuppusamy:2019:EFP,
  author =       "Vishnupriya Kuppusamy and Udaya Miriya Thanthrige and
                 Asanga Udugama and Anna F{\"o}rster",
  title =        "Evaluating Forwarding Protocols in Opportunistic
                 Networks: Trends, Advances, Challenges and Best
                 Practices",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "5",
  pages =        "113",
  day =          "11",
  month =        may,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11050113",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/5/113",
  abstract =     "A variety of applications and forwarding protocols
                 have been proposed for opportunistic networks (OppNets)
                 in the literature. However, the methodology of
                 evaluation, testing and comparing these forwarding
                 protocols are not standardized yet, which leads to
                 large levels of ambiguity in performance evaluation
                 studies. Performance results depend largely on the
                 evaluation environment, and on the used parameters and
                 models. More comparability in evaluation scenarios and
                 methodologies would largely improve also the
                 availability of protocols and the repeatability of
                 studies, and thus would accelerate the development of
                 this research topic. In this survey paper, we focus our
                 attention on how various OppNets data forwarding
                 protocols are evaluated rather than what they actually
                 achieve. We explore the models, parameters and the
                 evaluation environments and make observations about
                 their scalability, realism and comparability. Finally,
                 we deduce some best practices on how to achieve the
                 largest impact of future evaluation studies of OppNets
                 data dissemination/forwarding protocols.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Orkphol:2019:WSD,
  author =       "Korawit Orkphol and Wu Yang",
  title =        "Word Sense Disambiguation Using Cosine Similarity
                 Collaborates with {Word2vec} and {WordNet}",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "5",
  pages =        "114",
  day =          "12",
  month =        may,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11050114",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/5/114",
  abstract =     "Words have different meanings (i.e., senses) depending
                 on the context. Disambiguating the correct sense is
                 important and a challenging task for natural language
                 processing. An intuitive way is to select the highest
                 similarity between the context and sense definitions
                 provided by a large lexical database of English,
                 WordNet. In this database, nouns, verbs, adjectives,
                 and adverbs are grouped into sets of cognitive synonyms
                 interlinked through conceptual semantics and lexicon
                 relations. Traditional unsupervised approaches compute
                 similarity by counting overlapping words between the
                 context and sense definitions which must match exactly.
                 Similarity should compute based on how words are
                 related rather than overlapping by representing the
                 context and sense definitions on a vector space model
                 and analyzing distributional semantic relationships
                 among them using latent semantic analysis (LSA). When a
                 corpus of text becomes more massive, LSA consumes much
                 more memory and is not flexible to train a huge corpus
                 of text. A word-embedding approach has an advantage in
                 this issue. Word2vec is a popular word-embedding
                 approach that represents words on a fix-sized vector
                 space model through either the skip-gram or continuous
                 bag-of-words (CBOW) model. Word2vec is also effectively
                 capturing semantic and syntactic word similarities from
                 a huge corpus of text better than LSA. Our method used
                 Word2vec to construct a context sentence vector, and
                 sense definition vectors then give each word sense a
                 score using cosine similarity to compute the similarity
                 between those sentence vectors. The sense definition
                 also expanded with sense relations retrieved from
                 WordNet. If the score is not higher than a specific
                 threshold, the score will be combined with the
                 probability of that sense distribution learned from a
                 large sense-tagged corpus, SEMCOR. The possible answer
                 senses can be obtained from high scores. Our method
                 shows that the result (50.9\% or 48.7\% without the
                 probability of sense distribution) is higher than the
                 baselines (i.e., original, simplified, adapted and LSA
                 Lesk) and outperforms many unsupervised systems
                 participating in the SENSEVAL-3 English lexical sample
                 task.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Big Data Analytics and Artificial
                 Intelligence.",
}

@Article{Liu:2019:CTS,
  author =       "Weihuang Liu and Jinhao Qian and Zengwei Yao and
                 Xintao Jiao and Jiahui Pan",
  title =        "Convolutional Two-Stream Network Using Multi-Facial
                 Feature Fusion for Driver Fatigue Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "5",
  pages =        "115",
  day =          "14",
  month =        may,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11050115",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/5/115",
  abstract =     "Road traffic accidents caused by fatigue driving are
                 common causes of human casualties. In this paper, we
                 present a driver fatigue detection algorithm using
                 two-stream network models with multi-facial features.
                 The algorithm consists of four parts: (1) Positioning
                 mouth and eye with multi-task cascaded convolutional
                 neural networks (MTCNNs). (2) Extracting the static
                 features from a partial facial image. (3) Extracting
                 the dynamic features from a partial facial optical
                 flow. (4) Combining both static and dynamic features
                 using a two-stream neural network to make the
                 classification. The main contribution of this paper is
                 the combination of a two-stream network and
                 multi-facial features for driver fatigue detection.
                 Two-stream networks can combine static and dynamic
                 image information, while partial facial images as
                 network inputs can focus on fatigue-related
                 information, which brings better performance. Moreover,
                 we applied gamma correction to enhance image contrast,
                 which can help our method achieve better results, noted
                 by an increased accuracy of 2\% in night environments.
                 Finally, an accuracy of 97.06\% was achieved on the
                 National Tsing Hua University Driver Drowsiness
                 Detection (NTHU-DDD) dataset.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Special Issue on the Future of
                 Intelligent Human-Computer Interface.",
}

@Article{Vo:2019:ISA,
  author =       "Tri Hoang Vo and Woldemar Fuhrmann and Klaus-Peter
                 Fischer-Hellmann and Steven Furnell",
  title =        "Identity-as-a-Service: An Adaptive Security
                 Infrastructure and Privacy-Preserving User Identity for
                 the Cloud Environment",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "5",
  pages =        "116",
  day =          "15",
  month =        may,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11050116",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/5/116",
  abstract =     "In recent years, enterprise applications have begun to
                 migrate from a local hosting to a cloud provider and
                 may have established a business-to-business
                 relationship with each other manually. Adaptation of
                 existing applications requires substantial
                 implementation changes in individual architectural
                 components. On the other hand, users may store their
                 Personal Identifiable Information (PII) in the cloud
                 environment so that cloud services may access and use
                 it on demand. Even if cloud services specify their
                 privacy policies, we cannot guarantee that they follow
                 their policies and will not (accidentally) transfer PII
                 to another party. In this paper, we present
                 Identity-as-a-Service (IDaaS) as a trusted Identity and
                 Access Management with two requirements: Firstly, IDaaS
                 adapts trust between cloud services on demand. We move
                 the trust relationship and identity propagation out of
                 the application implementation and model them as a
                 security topology. When the business comes up with a
                 new e-commerce scenario, IDaaS uses the security
                 topology to adapt a platform-specific security
                 infrastructure for the given business scenario at
                 runtime. Secondly, we protect the confidentiality of
                 PII in federated security domains. We propose our
                 Purpose-based Encryption to protect the disclosure of
                 PII from intermediary entities in a business
                 transaction and from untrusted hosts. Our solution is
                 compliant with the General Data Protection Regulation
                 and involves the least user interaction to prevent
                 identity theft via the human link. The implementation
                 can be easily adapted to existing Identity Management
                 systems, and the performance is fast.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Privacy in Information and
                 Communication Systems.",
}

@Article{Bellini:2019:EID,
  author =       "Alessandro Bellini and Emanuele Bellini and Monica
                 Gherardelli and Franco Pirri",
  title =        "Enhancing {IoT} Data Dependability through a
                 Blockchain Mirror Model",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "5",
  pages =        "117",
  day =          "21",
  month =        may,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11050117",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/5/117",
  abstract =     "The Internet of Things (IoT) is a remarkable data
                 producer and these data may be used to prevent or
                 detect security vulnerabilities and increase
                 productivity by the adoption of statistical and
                 Artificial Intelligence (AI) techniques. However, these
                 desirable benefits are gained if data from IoT networks
                 are dependable --- this is where blockchain comes into
                 play. In fact, through blockchain, critical IoT data
                 may be trusted, i.e., considered valid for any
                 subsequent processing. A simple formal model named
                 ``the Mirror Model'' is proposed to connect IoT data
                 organized in traditional models to assets of trust in a
                 blockchain. The Mirror Model sets some formal
                 conditions to produce trusted data that remain trusted
                 over time. A possible practical implementation of an
                 application programming interface (API) is proposed,
                 which keeps the data and the trust model in synch.
                 Finally, it is noted that the Mirror Model enforces a
                 top-down approach from reality to implementation
                 instead of going the opposite way as it is now the
                 practice when referring to blockchain and the IoT.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Mitsis:2019:IDD,
  author =       "Giorgos Mitsis and Pavlos Athanasios Apostolopoulos
                 and Eirini Eleni Tsiropoulou and Symeon Papavassiliou",
  title =        "Intelligent Dynamic Data Offloading in a Competitive
                 Mobile Edge Computing Market",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "5",
  pages =        "118",
  day =          "21",
  month =        may,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11050118",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/5/118",
  abstract =     "Software Defined Networks (SDN) and Mobile Edge
                 Computing (MEC), capable of dynamically managing and
                 satisfying the end-users computing demands, have
                 emerged as key enabling technologies of 5G networks. In
                 this paper, the joint problem of MEC server selection
                 by the end-users and their optimal data offloading, as
                 well as the optimal price setting by the MEC servers is
                 studied in a multiple MEC servers and multiple
                 end-users environment. The flexibility and
                 programmability offered by the SDN technology enables
                 the realistic implementation of the proposed framework.
                 Initially, an SDN controller executes a reinforcement
                 learning framework based on the theory of stochastic
                 learning automata towards enabling the end-users to
                 select a MEC server to offload their data. The discount
                 offered by the MEC server, its congestion and its
                 penetration in terms of serving end-users' computing
                 tasks, and its announced pricing for its computing
                 services are considered in the overall MEC selection
                 process. To determine the end-users' data offloading
                 portion to the selected MEC server, a non-cooperative
                 game among the end-users of each server is formulated
                 and the existence and uniqueness of the corresponding
                 Nash Equilibrium is shown. An optimization problem of
                 maximizing the MEC servers' profit is formulated and
                 solved to determine the MEC servers' optimal pricing
                 with respect to their offered computing services and
                 the received offloaded data. To realize the proposed
                 framework, an iterative and low-complexity algorithm is
                 introduced and designed. The performance of the
                 proposed approach was evaluated through modeling and
                 simulation under several scenarios, with both
                 homogeneous and heterogeneous end-users.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Software Defined Networking (SDN) and
                 Network Function Virtualization (NFV).",
}

@Article{Mimidis-Kentis:2019:NGP,
  author =       "Angelos Mimidis-Kentis and Jose Soler and Paul Veitch
                 and Adam Broadbent and Marco Mobilio and Oliviero
                 Riganelli and Steven {Van Rossem} and Wouter Tavernier
                 and Bessem Sayadi",
  title =        "The Next Generation Platform as A Service: Composition
                 and Deployment of Platforms and Services",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "5",
  pages =        "119",
  day =          "21",
  month =        may,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11050119",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/5/119",
  abstract =     "The emergence of widespread cloudification and
                 virtualisation promises increased flexibility,
                 scalability, and programmability for the deployment of
                 services by Vertical Service Providers (VSPs). This
                 cloudification also improves service and network
                 management, reducing the Capital and Operational
                 Expenses (CAPEX, OPEX). A truly cloud-native approach
                 is essential, since 5G will provide a diverse range of
                 services - many requiring stringent performance
                 guarantees while maximising flexibility and agility
                 despite the technological diversity. This paper
                 proposes a workflow based on the principles of
                 build-to-order, Build-Ship-Run, and automation;
                 following the Next Generation Platform as a Service
                 (NGPaaS) vision. Through the concept of Reusable
                 Functional Blocks (RFBs), an enhancement to Virtual
                 Network Functions, this methodology allows a VSP to
                 deploy and manage platforms and services, agnostic to
                 the underlying technologies, protocols, and APIs. To
                 validate the proposed workflow, a use case is also
                 presented herein, which illustrates both the deployment
                 of the underlying platform by the Telco operator and of
                 the services that run on top of it. In this use case,
                 the NGPaaS operator facilitates a VSP to provide
                 Virtual Network Function as a Service (VNFaaS)
                 capabilities for its end customers.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Software Defined Networking (SDN) and
                 Network Function Virtualization (NFV).",
}

@Article{Begotti:2019:CCB,
  author =       "Tatiana Begotti and Daniela Acquadro Maran",
  title =        "Characteristics of Cyberstalking Behavior,
                 Consequences, and Coping Strategies: a Cross-Sectional
                 Study in a Sample of {Italian} University Students",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "5",
  pages =        "120",
  day =          "22",
  month =        may,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11050120",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/5/120",
  abstract =     "Aims: The aim of this study was to compare victims of
                 one type of cyberstalking (OneType) with victims of
                 more than one type of cyberstalking (MoreType)
                 regarding (1) the impact of cyberstalking and (2)
                 attitudes related to telling someone about the
                 experience of cyberstalking and the coping strategies
                 used by victims. Methods: a self-administered
                 questionnaire was distributed to over 250 students at
                 the University of Torino. Results: About half of the
                 participants experienced at least one incident of
                 cyberstalking. Among them, more than half experienced
                 more than one type of cyberstalking. Victims suffered
                 from depression more than those who had never
                 experienced cyberstalking. No statistically significant
                 difference emerged for anxiety. The coping strategies
                 used by MoreType were more varied than those used by
                 OneType victims of cyberstalking. Moreover, MoreType
                 victims told someone about their victimization more
                 than OneType victims. Conclusion: The work presented
                 suggests implications for health care professionals,
                 police officers, and government. For example, our
                 suggestion is to pay attention to cyberstalking victims
                 and provide flyers in schools, universities, and
                 cafeterias that explain the risk of certain online
                 behaviors and their consequences in physical and
                 emotional spheres.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Techno-Social Smart Systems.",
}

@Article{Xu:2019:DTS,
  author =       "Ling Xu and Jianzhong Qiao and Shukuan Lin and Wanting
                 Zhang",
  title =        "Dynamic Task Scheduling Algorithm with Deadline
                 Constraint in Heterogeneous Volunteer Computing
                 Platforms",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "6",
  pages =        "121",
  day =          "28",
  month =        may,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11060121",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/6/121",
  abstract =     "Volunteer computing (VC) is a distributed computing
                 paradigm, which provides unlimited computing resources
                 in the form of donated idle resources for many
                 large-scale scientific computing applications. Task
                 scheduling is one of the most challenging problems in
                 VC. Although, dynamic scheduling problem with deadline
                 constraint has been extensively studied in prior
                 studies in the heterogeneous system, such as cloud
                 computing and clusters, these algorithms can't be fully
                 applied to VC. This is because volunteer nodes can get
                 offline whenever they want without taking any
                 responsibility, which is different from other
                 distributed computing. For this situation, this paper
                 proposes a dynamic task scheduling algorithm for
                 heterogeneous VC with deadline constraint, called
                 deadline preference dispatch scheduling (DPDS). The
                 DPDS algorithm selects tasks with the nearest deadline
                 each time and assigns them to volunteer nodes (VN),
                 which solves the dynamic task scheduling problem with
                 deadline constraint. To make full use of resources and
                 maximize the number of completed tasks before the
                 deadline constraint, on the basis of the DPDS
                 algorithm, improved dispatch constraint scheduling
                 (IDCS) is further proposed. To verify our algorithms,
                 we conducted experiments, and the results show that the
                 proposed algorithms can effectively solve the dynamic
                 task assignment problem with deadline constraint in
                 VC.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bazzi:2019:SPV,
  author =       "Alessandro Bazzi and Giammarco Cecchini and Michele
                 Menarini and Barbara M. Masini and Alberto Zanella",
  title =        "Survey and Perspectives of Vehicular {Wi-Fi} versus
                 Sidelink Cellular-{V2X} in the {5G} Era",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "6",
  pages =        "122",
  day =          "29",
  month =        may,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11060122",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/6/122",
  abstract =     "The revolution of cooperative connected and automated
                 vehicles is about to begin and a key milestone is the
                 introduction of short range wireless communications
                 between cars. Given the tremendous expected market
                 growth, two different technologies have been
                 standardized by international companies and consortia,
                 namely IEEE 802.11p, out for nearly a decade, and short
                 range cellular-vehicle-to-anything (C-V2X), of recent
                 definition. In both cases, evolutions are under
                 discussion. The former is only decentralized and based
                 on a sensing before transmitting access, while the
                 latter is based on orthogonal resources that can be
                 also managed by an infrastructure. Although studies
                 have been conducted to highlight advantages and
                 drawbacks of both, doubts still remain. In this work,
                 with a reference to the literature and the aid of large
                 scale simulations in realistic urban and highway
                 scenarios, we provide an insight in such a comparison,
                 also trying to isolate the contribution of the physical
                 and medium access control layers.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 5G-V2X Communications and Networking for
                 Connected and Autonomous Vehicles.",
}

@Article{Dong:2019:VSE,
  author =       "Huanan Dong and Ming Wen and Zhouwang Yang",
  title =        "Vehicle Speed Estimation Based on {3D ConvNets} and
                 Non-Local Blocks",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "6",
  pages =        "123",
  day =          "30",
  month =        may,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11060123",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/6/123",
  abstract =     "Vehicle speed estimation is an important problem in
                 traffic surveillance. Many existing approaches to this
                 problem are based on camera calibration. Two
                 shortcomings exist for camera calibration-based
                 methods. First, camera calibration methods are
                 sensitive to the environment, which means the accuracy
                 of the results are compromised in some situations where
                 the environmental condition is not satisfied.
                 Furthermore, camera calibration-based methods rely on
                 vehicle trajectories acquired by a two-stage tracking
                 and detection process. In an effort to overcome these
                 shortcomings, we propose an alternate end-to-end method
                 based on 3-dimensional convolutional networks (3D
                 ConvNets). The proposed method bases average vehicle
                 speed estimation on information from video footage. Our
                 methods are characterized by the following three
                 features. First, we use non-local blocks in our model
                 to better capture spatial--temporal long-range
                 dependency. Second, we use optical flow as an input in
                 the model. Optical flow includes the information on the
                 speed and direction of pixel motion in an image. Third,
                 we construct a multi-scale convolutional network. This
                 network extracts information on various characteristics
                 of vehicles in motion. The proposed method showcases
                 promising experimental results on commonly used dataset
                 with mean absolute error (MAE) as 2.71 km/h and mean
                 square error (MSE) as 14.62.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Big Data and Augmented Intelligence.",
}

@Article{Manzoni:2019:IVG,
  author =       "Pietro Manzoni and Carlos T. Calafate and Juan-Carlos
                 Cano and Enrique Hern{\'a}ndez-Orallo",
  title =        "Indoor Vehicles Geolocalization Using {LoRaWAN}",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "6",
  pages =        "124",
  day =          "31",
  month =        may,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11060124",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/6/124",
  abstract =     "One of the main drawbacks of Global Navigation
                 Satellite Sytems (GNSS) is that they do not work
                 indoors. When inside, there is often no direct line
                 from the satellite signals to the device and the ultra
                 high frequency (UHF) used is blocked by thick, solid
                 materials such as brick, metal, stone or wood. In this
                 paper, we describe a solution based on the Long Range
                 Wide Area Network (LoRaWAN) technology to geolocalise
                 vehicles indoors. Through estimation of the behaviour
                 of a LoRaWAN channel and using trilateration, the
                 localisation of a vehicle can be obtained within a
                 20--30 m range. Indoor geolocation for Intelligent
                 Transporation Systems (ITS) can be used to locate
                 vehicles of any type in underground parkings, keep a
                 platoon of trucks in formation or create geo-fences,
                 that is, sending an alert if an object moves outside a
                 defined area, like a bicycle being stolen. Routing of
                 heavy vehicles within an industrial setting is another
                 possibility.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 5G-V2X Communications and Networking for
                 Connected and Autonomous Vehicles.",
}

@Article{Jin:2019:JLD,
  author =       "Mingshuang Jin and Hongbin Luo and Shuai Gao and Bohao
                 Feng",
  title =        "Joint Location-Dependent Pricing and Request Mapping
                 in {ICN}-Based Telco {CDNs} For {5G}",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "6",
  pages =        "125",
  day =          "03",
  month =        jun,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11060125",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/6/125",
  abstract =     "Telco content delivery networks (CDNs) have envisioned
                 building highly distributed and cloudified sites to
                 provide a high-quality CDN service in the 5G era.
                 However, there are still two open problems to be
                 addressed. First, telco CDNs are operated upon the
                 underlay network evolving towards information-centric
                 networking (ICN). Different from CDNs that perform on
                 the application layer, ICN enables information-centric
                 forwarding to the network layer. Thus, it is
                 challenging to take advantage of the benefits of both
                 ICN and CDN to provide a high-quality content delivery
                 service in the context of ICN-based telco CDNs. Second,
                 bandwidth pricing and request mapping issues in
                 ICN-based telco CDNs have not been thoroughly studied.
                 In this paper, we first propose an ICN-based telco CDN
                 framework that integrates the information-centric
                 forwarding enabled by ICN and the powerful edge caching
                 enabled by telco CDNs. Then, we propose a
                 location-dependent pricing (LDP) strategy, taking into
                 consideration the congestion level of different sites.
                 Furthermore, on the basis of LDP, we formulate a
                 price-aware request mapping (PARM) problem, which can
                 be solved by existing linear programming solvers.
                 Finally, we conduct extensive simulations to evaluate
                 the effectiveness of our design.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Information-Centric Networking (ICN).",
}

@Article{C:2019:CCK,
  author =       "Pramod T. C. and Thejas G. S. and S. S. Iyengar and N.
                 R. Sunitha",
  title =        "{CKMI}: Comprehensive Key Management Infrastructure
                 Design for Industrial Automation and Control Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "6",
  pages =        "126",
  day =          "04",
  month =        jun,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11060126",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/6/126",
  abstract =     "Industrial Automation and Control Systems (IACS) are
                 broadly utilized in critical infrastructures for
                 monitoring and controlling the industrial processes
                 remotely. The real-time transmissions in such systems
                 provoke security breaches. Many security breaches have
                 been reported impacting society severely. Hence, it is
                 essential to achieve secure communication between the
                 devices for creating a secure environment. For this to
                 be effective, the keys used for secure communication
                 must be protected against unauthorized disclosure,
                 misuse, alteration or loss, which can be taken care of
                 by a Key Management Infrastructure. In this paper, by
                 considering the generic industrial automation network,
                 a comprehensive key management infrastructure (CKMI) is
                 designed for IACS. To design such an infrastructure,
                 the proposed scheme employs ECDH, matrix method, and
                 polynomial crypto mechanisms. The proposed design
                 handles all the standard key management operations,
                 viz. key generation, device registration, key
                 establishment, key storage, device addition, key
                 revocation, key update, key recovery, key archival, and
                 key de-registration and destruction. The design
                 supports secure communication between the same and
                 different levels of IACS devices. The proposed design
                 can be applied for major industrial automation networks
                 to handle the key management operations. The
                 performance analysis and implementation results
                 highlight the benefits of the proposed design.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Next-Generation Public-Key
                 Infrastructures.",
}

@Article{DeDonno:2019:CSC,
  author =       "Michele {De Donno} and Alberto Giaretta and Nicola
                 Dragoni and Antonio Bucchiarone and Manuel Mazzara",
  title =        "Cyber-Storms Come from Clouds: Security of Cloud
                 Computing in the {IoT} Era",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "6",
  pages =        "127",
  day =          "04",
  month =        jun,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11060127",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/6/127",
  abstract =     "The Internet of Things (IoT) is rapidly changing our
                 society to a world where every ``thing'' is connected
                 to the Internet, making computing pervasive like never
                 before. This tsunami of connectivity and data
                 collection relies more and more on the Cloud, where
                 data analytics and intelligence actually reside. Cloud
                 computing has indeed revolutionized the way
                 computational resources and services can be used and
                 accessed, implementing the concept of utility computing
                 whose advantages are undeniable for every business.
                 However, despite the benefits in terms of flexibility,
                 economic savings, and support of new services, its
                 widespread adoption is hindered by the security issues
                 arising with its usage. From a security perspective,
                 the technological revolution introduced by IoT and
                 Cloud computing can represent a disaster, as each
                 object might become inherently remotely hackable and,
                 as a consequence, controllable by malicious actors.
                 While the literature mostly focuses on the security of
                 IoT and Cloud computing as separate entities, in this
                 article we provide an up-to-date and well-structured
                 survey of the security issues of cloud computing in the
                 IoT era. We give a clear picture of where security
                 issues occur and what their potential impact is. As a
                 result, we claim that it is not enough to secure IoT
                 devices, as cyber-storms come from Clouds.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Cloud Computing and Internet of
                 Things.",
}

@Article{Vladyko:2019:DEC,
  author =       "Andrei Vladyko and Abdukodir Khakimov and Ammar
                 Muthanna and Abdelhamied A. Ateya and Andrey
                 Koucheryavy",
  title =        "Distributed Edge Computing to Assist Ultra-Low-Latency
                 {VANET} Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "6",
  pages =        "128",
  day =          "04",
  month =        jun,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11060128",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/6/128",
  abstract =     "Vehicular ad hoc networks (VANETs) are a recent class
                 of peer-to-peer wireless networks that are used to
                 organize the communication and interaction between cars
                 (V2V), between cars and infrastructure (V2I), and
                 between cars and other types of nodes (V2X). These
                 networks are based on the dedicated short-range
                 communication (DSRC) IEEE 802.11 standards and are
                 mainly intended to organize the exchange of various
                 types of messages, mainly emergency ones, to prevent
                 road accidents, alert when a road accident occurs, or
                 control the priority of the roadway. Initially, it was
                 assumed that cars would only interact with each other,
                 but later, with the advent of the concept of the
                 Internet of things (IoT), interactions with surrounding
                 devices became a demand. However, there are many
                 challenges associated with the interaction of vehicles
                 and the interaction with the road infrastructure. Among
                 the main challenge is the high density and the dramatic
                 increase of the vehicles' traffic. To this end, this
                 work provides a novel system based on mobile edge
                 computing (MEC) to solve the problem of high traffic
                 density and provides and offloading path to vehicle's
                 traffic. The proposed system also reduces the total
                 latency of data communicated between vehicles and
                 stationary roadside units (RSUs). Moreover, a
                 latency-aware offloading algorithm is developed for
                 managing and controlling data offloading from vehicles
                 to edge servers. The system was simulated over a
                 reliable environment for performance evaluation, and a
                 real experiment was conducted to validate the proposed
                 system and the developed offloading method.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Vehicle-to-Everything (V2X)
                 Communication for Intelligent Transportation Systems
                 (ITS).",
}

@Article{Nundloll:2019:DDE,
  author =       "Vatsala Nundloll and Barry Porter and Gordon S. Blair
                 and Bridget Emmett and Jack Cosby and Davey L. Jones
                 and Dave Chadwick and Ben Winterbourn and Philip
                 Beattie and Graham Dean and Rory Shaw and Wayne Shelley
                 and Mike Brown and Izhar Ullah",
  title =        "The Design and Deployment of an End-To-End {IoT}
                 Infrastructure for the Natural Environment",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "6",
  pages =        "129",
  day =          "07",
  month =        jun,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11060129",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/6/129",
  abstract =     "Internet of Things (IoT) systems have seen recent
                 growth in popularity for city and home environments. We
                 report on the design, deployment, and use of the IoT
                 infrastructure for environmental monitoring and
                 management. Working closely with hydrologists, soil
                 scientists, and animal behaviour scientists, we
                 successfully deployed and utilised a system to deliver
                 integrated information across these two fields in the
                 first such example of real-time multidimensional
                 environmental science. We describe the design of this
                 system; its requirements and operational effectiveness
                 for hydrological, soil, and ethological scientists; and
                 our experiences from building, maintaining, and using
                 the deployment at a remote site in difficult
                 conditions. Based on this experience, we discuss key
                 future work for the IoT community when working in these
                 kinds of environmental deployments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Cloud Computing and Internet of
                 Things.",
}

@Article{Garcia:2019:DMA,
  author =       "Juan Jos{\'e} L{\'o}pez Garc{\'\i}a and David Lizcano
                 and Celia M. Q. Ramos and Nelson Matos",
  title =        "Digital Marketing Actions That Achieve a Better
                 Attraction and Loyalty of Users: An Analytical Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "6",
  pages =        "130",
  day =          "08",
  month =        jun,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11060130",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/6/130",
  abstract =     "Currently, the digital economy contributes decisively
                 to an increase in competitiveness, especially as a
                 digital transformation involves migrating to new
                 technological models where digital marketing is a key
                 part of growth and user loyalty strategies. Internet
                 and Digital Marketing have become important factors in
                 campaigns, which attract and retain Internet users.
                 This study aims to identify the main ways in which
                 users can be gained and retained by using Digital
                 Marketing. The Delphi method with in-depth interviews
                 was the methodology used in this study. The results of
                 the research show the most important actions for
                 achieving user recruitment and loyalty with Digital
                 Marketing from the opinions of consulted experts. The
                 limitations of this study are those related to the
                 number of experts included in the study, and the number
                 of research papers consulted in the literature review.
                 The literature review and the results of this research
                 are used to propose new solid research with a
                 consolidated critical methodology. This research deals
                 with a new approach that will optimize web technologies
                 for the evolution of user trends, and therefore, will
                 be of academic and professional use for marketing
                 managers and web solution developers. The conclusions
                 of the investigation show the key factors, discarding
                 others that do not affect the optimization of
                 conversions in B2C businesses such as the duration of
                 the session and the rebound percentage. Likewise, the
                 results of the research identify the specific actions
                 that must be carried out to attract and retain users in
                 B2C companies that use the Digital Marketing ecosystem
                 on the Internet. The requirements for companies that
                 wish to implement a model to optimize conversions using
                 the current digital economy are also shown.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Techno-Social Smart Systems.",
}

@Article{Kapsis:2019:TSI,
  author =       "Theodore T. Kapsis and Nikolaos K. Lyras and Charilaos
                 I. Kourogiorgas and Athanasios D. Panagopoulos",
  title =        "Time Series Irradiance Synthesizer for Optical {GEO}
                 Satellite Downlinks in {5G} Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "6",
  pages =        "131",
  day =          "13",
  month =        jun,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11060131",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/6/131",
  abstract =     "Next generation 5G networks generate a need for
                 broadband, low latency and power efficient backhauling
                 and data-relay services. In this paper, optical
                 satellite communications links, as an integrated
                 component of 5G networks, are studied. More
                 specifically, the Geostationary (GEO)
                 satellite-to-ground optical communication link is
                 investigated. Long-term irradiance statistics based on
                 experimental measurements from the ARTEMIS program are
                 presented and a new time series generator related to
                 the received irradiance/power fluctuations due to
                 atmospheric turbulence is reported. The proposed
                 synthesizer takes into consideration the
                 turbulence-induced scintillation effects that
                 deteriorate the laser beam propagation, on the
                 assumption of the Kolmogorov spectrum. The modeling is
                 based on Rytov theory regarding weak turbulence
                 conditions with the incorporation of first order
                 stochastic differential equations. Summing up, the time
                 series synthesizer is validated in terms of first and
                 second order statistics with experimental results from
                 the European Space Agency\&lsquo;s ARTEMIS experimental
                 optical downlink and simulated received power
                 statistics for various weather conditions are presented
                 using the proposed validated methodology. Some
                 important conclusions are drawn.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Satellite Communications in 5G
                 Networks.",
}

@Article{Autili:2019:CBC,
  author =       "Marco Autili and Amleto {Di Salle} and Francesco Gallo
                 and Claudio Pompilio and Massimo Tivoli",
  title =        "A Choreography-Based and Collaborative Road Mobility
                 System for {L'Aquila City}",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "6",
  pages =        "132",
  day =          "14",
  month =        jun,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11060132",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/6/132",
  abstract =     "Next Generation Internet (NGI) is the European
                 initiative launched to identify the future internet
                 technologies, designed to serve the needs of the
                 digitalized society while ensuring privacy, trust,
                 decentralization, openness, inclusion, and business
                 cooperation. NGI provides efficient support to promote
                 diversity, decentralization and the growth of
                 disruptive innovation envisioned by smart cities. After
                 the earthquake of 6 April 2009, the city of L'Aquila is
                 facing a massive and innovative reconstruction process.
                 As a consequence, nowadays, the L'Aquila city can be
                 considered as a living laboratory model for
                 applications within the context of smart cities. This
                 paper describes and evaluates the realization of a
                 Collaborative Road Mobility System (CRMS) for L'Aquila
                 city by using our CHOReVOLUTION approach for the
                 automated choreography production. The CRMS allows
                 vehicles and transport infrastructure to interconnect,
                 share information and use it to coordinate their
                 actions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Liu:2019:EEM,
  author =       "Ziqi Liu and Gaochao Xu and Peng Liu and Xiaodong Fu
                 and Yang Liu",
  title =        "Energy-Efficient Multi-User Routing in a
                 Software-Defined Multi-Hop Wireless Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "6",
  pages =        "133",
  day =          "17",
  month =        jun,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11060133",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/6/133",
  abstract =     "Software-defined networking (SDN) is an innovative
                 architecture that designs a logical controller to
                 manage and program the network based on the global
                 view, providing more efficient management, better
                 performance, and higher flexibility for the network.
                 Therefore, applying the SDN concept in a multi-hop
                 wireless network (MWN) has been proposed and
                 extensively studied to overcome the challenges of MWN.
                 In this paper, we propose an energy-efficient global
                 routing algorithm for a software-defined multi-hop
                 wireless network (SDMWN), which is able to get
                 transmission paths for several users at the same time
                 to minimize the global energy consumption with the
                 premise of satisfying the QoS required by users. To
                 this end, we firstly propose a Lagrange
                 relaxation-based aggregated cost (LARAC) and K-Dijkstra
                 combined algorithm to get the top K energy-minimum
                 paths that satisfy the QoS in polynomial time. Then, we
                 combine the alternative paths of each user obtained by
                 K-LARAC and propose an improved genetic algorithm to
                 solve the global routing strategy. The simulation
                 results show that the proposed K-LARAC and genetic
                 algorithm combined method has the ability to obtain an
                 approximate optimal solution with lower time cost.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hsu:2019:BUP,
  author =       "Chien-Lung Hsu and Yi-Chuan Liao",
  title =        "Bridging User Perception and Stickiness in Business
                 Microblog Contexts: a Moderated Mediation Model",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "6",
  pages =        "134",
  day =          "19",
  month =        jun,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11060134",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/6/134",
  abstract =     "This study develops a contingent mediation model to
                 investigate whether user perception enhances customer
                 stickiness through emotional connection and further
                 assess such mediating effect varies with different
                 adaptivity. A moderated mediation approach is adopted
                 to test the hypotheses. Findings reveal the mediating
                 role of emotional connection on the link between
                 perceived usefulness and customer stickiness, but not
                 moderated by adaptivity. On the other hand, the results
                 showed that the relationship between perceived ease of
                 use and customer stickiness is not mediated by
                 emotional connection; however, after considering the
                 moderating effect, our results show that moderated
                 mediation exists.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Techno-Social Smart Systems.",
}

@Article{Huertas:2019:IET,
  author =       "Melby Karina Zuniga Huertas and Tarcisio Duarte
                 Coelho",
  title =        "The Interaction Effect of Type of Message {X}
                 {YouTuber's} Media Metrics on Customers' Responses and
                 the Moderation of Conformity Intention",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "6",
  pages =        "135",
  day =          "20",
  month =        jun,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11060135",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/6/135",
  abstract =     "This is a study of the way in which YouTubers' media
                 metrics influence the effect of their one-sided
                 messages (1SMs) and two-sided messages (2SMs),
                 providing theoretical explanations based on the
                 elaboration likelihood model. Its main objective is the
                 proposition and testing of: (i) the interaction effect
                 between type of message and media metrics of the
                 YouTuber on customers' responses, and (ii) the
                 moderation of individuals' conformity intention for the
                 interaction effect between type of message and media
                 metrics on customers' responses. The results of an
                 experiment showed that high YouTubers' media metrics
                 have more effect for 1SMs and less effect for 2SMs.
                 Additionally, conformity intention moderates the effect
                 of the interaction type of message X media metrics. A
                 high level of conformity intention neutralizes the
                 interaction effect between YouTubers' media metrics and
                 message sidedness. This study makes a theoretical
                 contribution to research into online content and
                 information use, providing explanations of how media
                 metrics of a vlog influence the effect of two types of
                 messages.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Deindividuation in Online Human Dynamics
                 Research Advances in the Modern Digital Era.",
}

@Article{Deraman:2019:DIO,
  author =       "Rafikullah Deraman and Chen Wang and Jeffrey Boon Hui
                 Yap and Heng Li and Faizul Azli Mohd-Rahim",
  title =        "Developing {Internet} Online Procurement Frameworks
                 for Construction Firms",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "6",
  pages =        "136",
  day =          "20",
  month =        jun,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11060136",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/6/136",
  abstract =     "Electronic purchasing or e-procurement saves millions
                 of dollars yearly in transaction costs. E-procurement
                 helps to cut down the supplier base, promotes paperless
                 transactions, and increases transparency and
                 accountability in the procurement process. Nonetheless,
                 studies report that around 80\% of e-procurement
                 initiatives have met with failure and failed to achieve
                 the desired results. Although studies to better
                 understand the Critical Success Factors (CSFs) of
                 e-procurement implementation involving various
                 industries have been on the rise, little is known about
                 architecture engineering and construction (AEC)
                 practices, which has led to limited development of
                 pragmatic frameworks to uncover the factors. Thus, this
                 study aims to identify those CSFs (predicting
                 variables) which significantly contribute to
                 e-procurement implementation success in the
                 construction sector and to put forward for better
                 implementation. Results from multiple regression
                 analysis revealed five factors to be statistically
                 significant predictors of success. Three factors were
                 determined to be predictors of user satisfaction.
                 Finally, internet online procurement frameworks were
                 developed for the success of e-procurement
                 implementation in the construction sector.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Techno-Social Smart Systems.",
}

@Article{Kim:2019:NIS,
  author =       "Sanghyun Kim and Hyunsun Park and Moon Jong Choi",
  title =        "Negative Impact of Social Network Services Based on
                 Stressor--Stress-Outcome: The Role of Experience of
                 Privacy Violations",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "6",
  pages =        "137",
  day =          "20",
  month =        jun,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11060137",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  note =         "See comment \cite{Fantinelli:2019:SNS}.",
  URL =          "https://www.mdpi.com/1999-5903/11/6/137",
  abstract =     "Social network service (SNS) information has benefited
                 many individuals. However, as such information has
                 increased exponentially, the number of SNS users has
                 increased dramatically and negative effects of SNSs on
                 users have emerged. Many SNS users experience negative
                 psychological conditions such as fatigue, burnout, and
                 stress. Thus, in this study, we investigated the SNS
                 and user characteristics that affect SNS fatigue,
                 living disorder, and reduced SNS use intention. We
                 developed a research model to examine the impact of two
                 SNS characteristics (irrelevant information overload
                 and open reachability) and two user characteristics
                 (engagement and maintaining self-reputation) on SNS
                 fatigue. We also examined the role of the experience of
                 privacy violations in the relationship between living
                 disorder and reduced SNS use intention. We collected
                 data from 579 SNS users and created a partial least
                 squares structural equation model to test the
                 hypotheses. The results of the analysis showed that
                 three factors, other than open reachability, positively
                 affected SNS fatigue. Furthermore, we found that SNS
                 fatigue significantly affected living disorder and
                 reduced SNS use intention, and that experience of
                 privacy violations significantly affected the
                 relationship between living disorder and reduced SNS
                 use intention. These results expand our understanding
                 of SNS fatigue and users' negative behaviors.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Techno-Social Smart Systems.",
}

@Article{Gunawan:2019:DAH,
  author =       "Dedi Gunawan and Masahiro Mambo",
  title =        "Data Anonymization for Hiding Personal Tendency in
                 Set-Valued Database Publication",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "6",
  pages =        "138",
  day =          "20",
  month =        jun,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11060138",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/6/138",
  abstract =     "Set-valued database publication has been increasing
                 its importance recently due to its benefit for various
                 applications such as marketing analysis and
                 advertising. However, publishing a raw set-valued
                 database may cause individual privacy breach such as
                 the leakage of sensitive information like personal
                 tendencies when data recipients perform data analysis.
                 Even though imposing data anonymization methods such as
                 suppression-based methods and random data swapping
                 methods to such a database can successfully hide
                 personal tendency, it induces item loss from records
                 and causes significant distortion in record structure
                 that degrades database utility. To avoid the problems,
                 we proposed a method based on swapping technique where
                 an individual's items in a record are swapped to items
                 of the other record. Our swapping technique is distinct
                 from existing one called random data swapping which
                 yields much structure distortion. Even though the
                 technique results in inaccuracy at a record level, it
                 can preserve every single item in a database from loss.
                 Thus, data recipients may obtain all the item
                 information in an anonymized database. In addition, by
                 carefully selecting a pair of records for item
                 swapping, we can avoid excessive record structure
                 distortion that leads to alter database content
                 immensely. More importantly, such a strategy allows one
                 to successfully hide personal tendency without
                 sacrificing a lot of database utility.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Privacy in Information and
                 Communication Systems.",
}

@Article{Kuai:2019:LBD,
  author =       "Meng Kuai and Xiaoyan Hong",
  title =        "Location-Based Deferred Broadcast for Ad-Hoc Named
                 Data Networking",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "6",
  pages =        "139",
  day =          "24",
  month =        jun,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11060139",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/6/139",
  abstract =     "The emerging connected and autonomous vehicles (CAVs)
                 challenge ad hoc wireless multi-hop communications by
                 mobility, large-scale, new data acquisition and
                 computing patterns. The Named Data Networking (NDN) is
                 suitable for such vehicle ad hoc networks due to its
                 information centric networking approach. However,
                 flooding interest packets in ad-hoc NDN can lead to
                 broadcast storm issue. Existing solutions will either
                 increase the number of redundant interest packets or
                 need a global knowledge about data producers. In this
                 paper, a Location-Based Deferred Broadcast (LBDB)
                 scheme is introduced to improve the efficiency and
                 performance of interest broadcast in ad-hoc NDN. The
                 scheme takes advantage of location information to set
                 up timers when rebroadcasting an interest. The LBDB is
                 implemented in V-NDN network architecture using ndnSIM
                 simulator. Comparisons with several existing protocols
                 are conducted in simulation. The results show that LBDB
                 improves the overhead, the average number of hops and
                 delay while maintaining an average satisfaction ratio
                 when compared with several other broadcast schemes. The
                 improvement can help offer timely data acquisition for
                 quick responses in emergent CAV application
                 situations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Content Centric Future Internet
                 Architectures.",
}

@Article{De-Pablos-Heredero:2019:FIS,
  author =       "Carmen De-Pablos-Heredero",
  title =        "Future Intelligent Systems and Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "6",
  pages =        "140",
  day =          "25",
  month =        jun,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11060140",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/6/140",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future Intelligent Systems and Networks
                 2019.",
}

@Article{Abro:2019:DAP,
  author =       "Adeel Abro and Zhongliang Deng and Kamran Ali Memon
                 and Asif Ali Laghari and Khalid Hussain Mohammadani and
                 Noor ul Ain",
  title =        "A Dynamic Application-Partitioning Algorithm with
                 Improved Offloading Mechanism for Fog Cloud Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "7",
  pages =        "141",
  day =          "28",
  month =        jun,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11070141",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/7/141",
  abstract =     "This paper aims to propose a new fog cloud
                 architecture that performs a joint energy-efficient
                 task assignment (JEETA). The proposed JEETA
                 architecture utilizes the dynamic
                 application-partitioning algorithm (DAPTS), a novel
                 algorithm that efficiently decides and switches the
                 task to be offloaded or not in heterogeneous
                 environments with minimal energy consumption. The
                 proposed scheme outperforms baseline approaches such as
                 MAUI, Think Air and Clone Cloud in many performance
                 aspects. Results show that for the execution of 1000
                 Tasks on fog, mobile offloaded nodes, JEETA consumes
                 the leas, i.e., 23\% of the total energy whereas other
                 baseline approaches consume in between 50--100\% of the
                 total energy. Results are validated via real test-bed
                 experiments and trice are driven efficient
                 simulations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Cloud Computing and Networking 2019.",
}

@Article{Mastroeni:2019:SLA,
  author =       "Loretta Mastroeni and Alessandro Mazzoccoli and
                 Maurizio Naldi",
  title =        "Service Level Agreement Violations in Cloud Storage:
                 Insurance and Compensation Sustainability",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "7",
  pages =        "142",
  day =          "30",
  month =        jun,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11070142",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/7/142",
  abstract =     "Service Level Agreements are employed to set
                 availability commitments in cloud services. When a
                 violation occurs as in an outage, cloud providers may
                 be called to compensate customers for the losses
                 incurred. Such compensation may be so large as to erode
                 cloud providers' profit margins. Insurance may be used
                 to protect cloud providers against such a danger. In
                 this paper, closed formulas are provided through the
                 expected utility paradigm to set the insurance premium
                 under different outage models and QoS metrics (no. of
                 outages, no. of long outages, and unavailability). When
                 the cloud service is paid through a fixed fee, we also
                 provide the maximum unit compensation that a cloud
                 provider can offer so as to meet constraints on its
                 profit loss. The unit compensation is shown to vary
                 approximately as the inverse square of the service
                 fee.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Network Virtualization and Edge/Fog
                 Computing.",
}

@Article{Tanaka:2019:MSA,
  author =       "Kazuaki Tanaka and Kota Takenouchi and Kohei Ogawa and
                 Yuichiro Yoshikawa and Shuichi Nishio and Hiroshi
                 Ishiguro",
  title =        "Maintaining the Sense of Agency in Semi-Autonomous
                 Robot Conferencing",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "7",
  pages =        "143",
  day =          "03",
  month =        jul,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11070143",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/7/143",
  abstract =     "In semi-autonomous robot conferencing, not only the
                 operator controls the robot, but the robot itself also
                 moves autonomously. Thus, it can modify the operator's
                 movement (e.g., adding social behaviors). However, the
                 sense of agency, that is, the degree of feeling that
                 the movement of the robot is the operator's own
                 movement, would decrease if the operator is conscious
                 of the discrepancy between the teleoperation and
                 autonomous behavior. In this study, we developed an
                 interface to control the robot head by using an eye
                 tracker. When the robot autonomously moves its eye-gaze
                 position, the interface guides the operator's eye
                 movement towards this autonomous movement. The
                 experiment showed that our interface can maintain the
                 sense of agency, because it provided the illusion that
                 the autonomous behavior of a robot is directed by the
                 operator's eye movement. This study reports the
                 conditions of how to provide this illusion in
                 semi-autonomous robot conferencing.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Advanced Telepresence Technologies and
                 Applications.",
}

@Article{Roohitavaf:2019:AAF,
  author =       "Mohammad Roohitavaf and Sandeep Kulkarni",
  title =        "Automatic Addition of Fault-Tolerance in Presence of
                 Unchangeable Environment Actions",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "7",
  pages =        "144",
  day =          "04",
  month =        jul,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11070144",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/java2010.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/7/144",
  abstract =     "We focus on the problem of adding fault-tolerance to
                 an existing concurrent protocol in the presence of
                 unchangeable environment actions. Such unchangeable
                 actions occur in cases where a subset of
                 components/processes cannot be modified since they
                 represent third-party components or are constrained by
                 physical laws. These actions differ from faults in that
                 they are (1) simultaneously collaborative and
                 disruptive, (2) essential for satisfying the
                 specification and (3) possibly non-terminating. Hence,
                 if these actions are modeled as faults while adding
                 fault-tolerance, it causes existing model repair
                 algorithms to declare failure to add fault-tolerance.
                 We present a set of algorithms for adding stabilization
                 and fault-tolerance for programs that run in the
                 presence of environment actions. We prove the
                 soundness, completeness and the complexity of our
                 algorithms. We have implemented all of our algorithms
                 using symbolic techniques in Java. The experimental
                 results of our algorithms for various examples are also
                 provided.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Dependable Cyber Physical Systems.",
}

@Article{Busanelli:2019:SOO,
  author =       "Stefano Busanelli and Simone Cirani and Lorenzo
                 Melegari and Marco Picone and Mirco Rosa and Luca
                 Veltri",
  title =        "A Sidecar Object for the Optimized Communication
                 Between Edge and Cloud in {Internet of Things}
                 Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "7",
  pages =        "145",
  day =          "05",
  month =        jul,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11070145",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/7/145",
  abstract =     "The internet of things (IoT) is one of the most
                 disrupting revolutions that is characterizing the
                 technology ecosystem. In the near future, the IoT will
                 have a significant impact on people's lives and on the
                 design and developments of new paradigms and
                 architectures coping with a completely new set of
                 challenges and service categories. The IoT can be
                 described as an ecosystem where a massive number of
                 constrained devices (denoted as smart objects) will be
                 deployed and connected to cooperate for multiple
                 purposes, such a data collection, actuation, and
                 interaction with people. In order to meet the specific
                 requirements, IoT services may be deployed leveraging a
                 hybrid architecture that will involve services deployed
                 on the edge and the cloud. In this context, one of the
                 challenges is to create an infrastructure of objects
                 and microservices operating between both the edge and
                 in the cloud that can be easily updated and extended
                 with new features and functionalities without the need
                 of updating or re-deploying smart objects. This work
                 introduces a new concept for extending smart objects'
                 support for cloud services, denoted as a sidecar
                 object. A sidecar object serves the purpose of being
                 deployed as additional component of a preexisting
                 object without interfering with the mechanisms and
                 behaviors that have already been implemented. In
                 particular, the sidecar object implementation developed
                 in this work focuses on the communication with existing
                 IoT cloud services (namely, AWS IoT and Google Cloud
                 IoT) to provide a transparent and seamless
                 synchronization of data, states, and commands between
                 the object on the edge and the cloud. The proposed
                 sidecar object implementation has been extensively
                 evaluated through a detailed set of tests, in order to
                 analyze the performances and behaviors in real- world
                 scenarios.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Cloud Computing and Internet of
                 Things.",
}

@Article{Jiang:2019:MII,
  author =       "Shengming Jiang",
  title =        "Marine {Internet} for {Internetworking} in Oceans: a
                 Tutorial",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "7",
  pages =        "146",
  day =          "05",
  month =        jul,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11070146",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/7/146",
  abstract =     "Ever-increasing human activities in oceans require
                 handy, reliable and cost-effective high-speed network
                 access similar to terrestrial Internet services to be
                 available on and under water. However, terrestrial
                 Internet cannot be extended to oceans seamlessly due to
                 huge differences between terrestrial and oceanic
                 environments, while satellite services are still very
                 expensive especially for ordinary users with
                 communication quality susceptible to weather
                 conditions, and cannot cover underwater networks
                 either. Therefore, marine Internet, proposed about six
                 years ago, is the earliest scheme that tries to
                 systematically address the internetworking issue in
                 oceans and still in its infancy stage. This tutorial
                 aims to introduce the principle, architecture and
                 applications of marine Internet, along with discussion
                 on oceanic environments for communication, currently
                 available and under developing communication systems in
                 oceans, as well as challenging issues necessary for
                 further studies to foster the development of marine
                 Internet.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Internet of Things.",
}

@Article{Kohana:2019:WBN,
  author =       "Masaki Kohana and Shinji Sakamoto and Shusuke
                 Okamoto",
  title =        "{Web} Browser Network Based on a {BA} Model for a
                 {Web}-Based Virtual World",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "7",
  pages =        "147",
  day =          "05",
  month =        jul,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11070147",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/7/147",
  abstract =     "Real-time web applications such as a virtual world
                 require considerable computing resources. However, as
                 the number of servers increases, so does the
                 maintenance and financial cost. To share tasks among
                 web browsers, the browsers must share data. Therefore,
                 a network must be constructed among the web browsers.
                 In this paper, we propose the construction of a web
                 browser network based on the Barabasi--Albert model (BA
                 model). We focus on a web-based multiplayer online game
                 that requires higher frequent communication and
                 significant computing resources. We attempt to optimize
                 computing resource utilization for web browsers. We
                 improve upon the method in our previous study, which
                 constructed a network for a web-based virtual world,
                 using only location information. When a new user logged
                 into a world, the web browser connected to two other
                 browsers whose users had a location close to that of
                 the user. The experimental results of that method
                 showed 50\% data coverage, which was insufficient to
                 display the game screen because the web browser
                 displays the characters on the virtual world. In this
                 study, we attempt to use the BA model to construct more
                 efficient networks than those in the previous study to
                 increase data coverage. Our new method uses the number
                 of connections of the web browser and location
                 information to calculate the probability of web browser
                 selection. The experimental results show that the data
                 coverage exceeds 90\%, indicating significant
                 improvement over the previous method.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Advanced Techniques for Internet, P2P
                 and Cloud Computing-selected papers from 3PGCIC-2018.",
}

@Article{Pibernik:2019:EFA,
  author =       "Jesenka Pibernik and Jurica Dolic and Hrvoje Abraham
                 Milicevic and Bojan Kanizaj",
  title =        "The Effects of the Floating Action Button on Quality
                 of Experience",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "7",
  pages =        "148",
  day =          "06",
  month =        jul,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11070148",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/7/148",
  abstract =     "Google's Material Design, created in 2014, led to the
                 extended application of floating action buttons (FAB)
                 in user interfaces of web pages and mobile
                 applications. FAB's roll is to trigger an activity
                 either on the present screen, or it can play out an
                 activity that makes another screen. A few specialists
                 in user experience (UX) and user interface (UI) design
                 are sceptical regarding the usability of FAB in the
                 interfaces of both web pages and mobile applications.
                 They claim that the use of FAB easily distracts users
                 and that it interferes with using other important
                 functions of the applications, and it is unusable in
                 applications designed for iOS systems. The aim of this
                 paper is to investigate by an experiment the quality of
                 experience (QoE) of a static and animated FAB and
                 compare it to the toolbar alternative. The experimental
                 results of different testing methods rejected the
                 hypothesis that the usage and animation of this UI
                 element has a positive influence on the application
                 usability. However, its static and animated utilization
                 enhanced the ratings of hedonic and aesthetic features
                 of the user experience, justifying the usage of this
                 type of button.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Multimedia Quality of Experience (QoE):
                 Current Status and Future Direction.",
}

@Article{Chen:2019:IAS,
  author =       "Yi-Cheng Chen and Yueh-Peng Chou and Yung-Chen Chou",
  title =        "An Image Authentication Scheme Using {Merkle} Tree
                 Mechanisms",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "7",
  pages =        "149",
  day =          "06",
  month =        jul,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11070149",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/7/149",
  abstract =     "Research on digital image processing has become quite
                 popular and rapid in recent years, and scholars have
                 proposed various image verification mechanisms.
                 Similarly, blockchain technology has also become very
                 popular in recent years. This paper proposes a new
                 image verification mechanism based on the Merkle tree
                 technique in the blockchain. The Merkle tree root in
                 the blockchain mechanism provides a reliable
                 environment for storage of image features. In image
                 verification, the verification of each image can be
                 performed by the Merkle tree mechanism to obtain the
                 hash value of the Merkle tree node on the path. In
                 addition, the method combines the Inter-Planetary File
                 System (IPFS) to improve the availability of images.
                 The main purpose of this paper is to achieve the goal
                 of image integrity verification. The proposed method
                 can not only verify the integrity of the image but also
                 restore the tampered area in the case of image
                 tampering. Since the proposed method employs the
                 blockchain mechanism, the image verification mechanism
                 does not need third party resources. The verification
                 method is performed by each node in the blockchain
                 network. The experimental results demonstrate that the
                 proposed method successfully achieved the goal of image
                 authentication and tampered area restoration.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Blockchain Theory and Its
                 Applications.",
}

@Article{Utsu:2019:TWW,
  author =       "Keisuke Utsu and Shun Ueta and Sachi Tajima and
                 Yoshitaka Kajita and Yuji Murakami and Osamu Uchida",
  title =        "Town-Watching Workshop Using Disaster Information
                 Tweeting and Mapping System",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "7",
  pages =        "150",
  day =          "07",
  month =        jul,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11070150",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/7/150",
  abstract =     "Self- and mutual-help by citizens are important as
                 well as social-help from the local governments, for
                 disaster prevention and mitigation. Then, town watching
                 and disaster prevention map-making workshops are held
                 to review the town and promote self- and mutual-help by
                 citizens. On the other hand, the use of social media
                 for information sharing during and after disasters has
                 been gaining attention. To facilitate information
                 sharing in disasters, we developed a web system,
                 Disaster Information Tweeting and Mapping System
                 (DITS/DIMS). From the above background, we organized a
                 town-watching workshop using DITS/DIMS in October 2018
                 in Minami Ward, Sapporo City, Hokkaido, Japan; affected
                 area of the Hokkaido Eastern Iburi Earthquake in
                 September 2018. In this paper, we explain the workshop
                 procedure, outcome, questionnaire survey results, and
                 post-meeting. The questionnaire survey result shows
                 that the workshop educated the participants about
                 posting useful information on social media during a
                 disaster. In addition, at the post-meeting, the
                 participants recognized that they had reviewed the town
                 only from the perspective of ``daily life'' convenience
                 before the earthquake, and they had not evaluated the
                 ``emergency viewpoint.'' Therefore, the workshop was a
                 meaningful opportunity for the participants to review
                 the town in terms of disaster prevention and
                 mitigation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Selected Papers from IEEE ICICT 2019.",
}

@Article{Bader:2019:SRA,
  author =       "Sebastian R. Bader and Maria Maleshkova and Steffen
                 Lohmann",
  title =        "Structuring Reference Architectures for the {Industrial
                 Internet of Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "7",
  pages =        "151",
  day =          "08",
  month =        jul,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11070151",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/7/151",
  abstract =     "The ongoing digital transformation has the potential
                 to revolutionize nearly all industrial manufacturing
                 processes. However, its concrete requirements and
                 implications are still not sufficiently investigated.
                 In order to establish a common understanding, a
                 multitude of initiatives have published guidelines,
                 reference frameworks and specifications, all intending
                 to promote their particular interpretation of the
                 Industrial Internet of Things (IIoT). As a result of
                 the inconsistent use of terminology, heterogeneous
                 structures and proposed processes, an opaque landscape
                 has been created. The consequence is that both new
                 users and experienced experts can hardly manage to get
                 an overview of the amount of information and
                 publications, and make decisions on what is best to use
                 and to adopt. This work contributes to the state of the
                 art by providing a structured analysis of existing
                 reference frameworks, their classifications and the
                 concerns they target. We supply alignments of shared
                 concepts, identify gaps and give a structured mapping
                 of regarded concerns at each part of the respective
                 reference architectures. Furthermore, the linking of
                 relevant industry standards and technologies to the
                 architectures allows a more effective search for
                 specifications and guidelines and supports the direct
                 technology adoption.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Forte:2019:NGC,
  author =       "Andrea G. Forte and Wei Wang and Luca Veltri and
                 Gianluigi Ferrari",
  title =        "A Next-Generation Core Network Architecture for Mobile
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "7",
  pages =        "152",
  day =          "09",
  month =        jul,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11070152",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/7/152",
  abstract =     "Over the years, the cellular mobile network has
                 evolved from a wireless plain telephone system to a
                 very complex system providing telephone service,
                 Internet connectivity and many interworking
                 capabilities with other networks. Its air interface
                 performance has increased drastically over time,
                 leading to high throughput and low latency. Changes to
                 the core network, however, have been slow and
                 incremental, with increased complexity worsened by the
                 necessity of backwards-compatibility with
                 older-generation systems such as the Global System for
                 Mobile communication (GSM). In this paper, a new
                 virtualized Peer-to-Peer (P2P) core network
                 architecture is presented. The key idea of our approach
                 is that each user is assigned a private virtualized
                 copy of the whole core network. This enables a higher
                 degree of security and novel services that are not
                 possible in today's architecture. We describe the new
                 architecture, focusing on its main elements, IP
                 addressing, message flows, mobility management, and
                 scalability. Furthermore, we will show some significant
                 advantages this new architecture introduces. Finally,
                 we investigate the performance of our architecture by
                 analyzing voice-call traffic available in a database of
                 a large U.S. cellular network provider.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Network Virtualization and Edge/Fog
                 Computing.",
}

@Article{Alreshidi:2019:ASI,
  author =       "Abdulrahman Alreshidi and Aakash Ahmad",
  title =        "Architecting Software for the {Internet} of Thing
                 Based Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "7",
  pages =        "153",
  day =          "10",
  month =        jul,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11070153",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/7/153",
  abstract =     "Context --- Internet of Thing (IoT) based systems
                 support any-time/place computations by interconnecting
                 humans, systems, services, devices, and things that
                 enabling autonomous systems to shape-up digitized
                 societies. Software architecture, as the blue-print of
                 software-intensive systems, abstracts the complexities
                 of modeling, design, development, and evolution phases
                 of a software to engineer complex IoT driven systems
                 effectively and efficiently. Objectives and Method ---
                 Research and development efforts are required to
                 exploit architectural principle and practices to design
                 and develop IoT systems to go beyond the
                 state-of-the-art for IoTs. The objectives of this
                 research are to empirically investigate and
                 systematically classify the state-of-the-art on
                 architecting IoT based software. We have used the
                 Evidence Based Software Engineering (EBSE) method to
                 conduct a mapping study of the existing IoT solutions
                 by investigating 88 qualitatively selected studies.
                 Results and Implications --- The results of the mapping
                 study highlight various research themes that exploit
                 software architecture models to develop IoT systems.
                 The identified research themes include, but are not
                 limited to, cloud-based software ecosystems, software
                 defined networking, autonomous, and adaptive software
                 and agent-based systems that IoTs drive. The mapping
                 study suggests that futuristic research on architecting
                 IoT software is focused on architectural languages and
                 patterns that support reusability, automation, and
                 human decision support to develop and dynamically adapt
                 IoT software. The mapping study represents a
                 concentrated knowledge regarding architectural
                 principle and practices to facilitate knowledge
                 transfer --- benefiting researchers and practitioners
                 --- on the role of software architecture for IoT
                 systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Internet of Things.",
}

@Article{Drozdz:2019:SCC,
  author =       "Stanis{\l}aw Drozdz and Ludovico Minati and Pawe{\l}
                 O{\'s}wi{\k{e}}cimka and Marek Stanuszek and Marcin
                 W{\k{a}}torek",
  title =        "Signatures of the Crypto-Currency Market Decoupling
                 from the {Forex}",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "7",
  pages =        "154",
  day =          "10",
  month =        jul,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11070154",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/7/154",
  abstract =     "Based on the high-frequency recordings from Kraken, a
                 cryptocurrency exchange and professional trading
                 platform that aims to bring Bitcoin and other
                 cryptocurrencies into the mainstream, the multiscale
                 cross-correlations involving the Bitcoin (BTC),
                 Ethereum (ETH), Euro (EUR) and US dollar (USD) are
                 studied over the period between 1 July 2016 and 31
                 December 2018. It is shown that the multiscaling
                 characteristics of the exchange rate fluctuations
                 related to the cryptocurrency market approach those of
                 the Forex. This, in particular, applies to the BTC/ETH
                 exchange rate, whose Hurst exponent by the end of 2018
                 started approaching the value of 0.5, which is
                 characteristic of the mature world markets.
                 Furthermore, the BTC/ETH direct exchange rate has
                 already developed multifractality, which manifests
                 itself via broad singularity spectra. A particularly
                 significant result is that the measures applied for
                 detecting cross-correlations between the dynamics of
                 the BTC/ETH and EUR/USD exchange rates do not show any
                 noticeable relationships. This could be taken as an
                 indication that the cryptocurrency market has begun
                 decoupling itself from the Forex.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Blockchain Theory and Its
                 Applications.",
}

@Article{Wang:2019:SBE,
  author =       "Yufeng Wang and Shuangrong Liu and Songqian Li and
                 Jidong Duan and Zhihao Hou and Jia Yu and Kun Ma",
  title =        "Stacking-Based Ensemble Learning of Self-Media Data
                 for Marketing Intention Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "7",
  pages =        "155",
  day =          "10",
  month =        jul,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11070155",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/7/155",
  abstract =     "Social network services for self-media, such as Weibo,
                 Blog, and WeChat Public, constitute a powerful medium
                 that allows users to publish posts every day. Due to
                 insufficient information transparency, malicious
                 marketing of the Internet from self-media posts imposes
                 potential harm on society. Therefore, it is necessary
                 to identify news with marketing intentions for life. We
                 follow the idea of text classification to identify
                 marketing intentions. Although there are some current
                 methods to address intention detection, the challenge
                 is how the feature extraction of text reflects semantic
                 information and how to improve the time complexity and
                 space complexity of the recognition model. To this end,
                 this paper proposes a machine learning method to
                 identify marketing intentions from large-scale We-Media
                 data. First, the proposed Latent Semantic Analysis
                 (LSI)-Word2vec model can reflect the semantic features.
                 Second, the decision tree model is simplified by
                 decision tree pruning to save computing resources and
                 reduce the time complexity. Finally, this paper
                 examines the effects of classifier associations and
                 uses the optimal configuration to help people
                 efficiently identify marketing intention. Finally, the
                 detailed experimental evaluation on several metrics
                 shows that our approaches are effective and efficient.
                 The F1 value can be increased by about 5\%, and the
                 running time is increased by 20\%, which prove that the
                 newly-proposed method can effectively improve the
                 accuracy of marketing news recognition.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Advanced Techniques for Internet, P2P
                 and Cloud Computing-selected papers from 3PGCIC-2018.",
}

@Article{Al-Zahrani:2019:GTI,
  author =       "Ali Y. Al-Zahrani",
  title =        "A Game Theoretic Interference Management Scheme in
                 Full Duplex Cellular Systems under Infeasible {QoS}
                 Requirements",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "7",
  pages =        "156",
  day =          "16",
  month =        jul,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11070156",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/7/156",
  abstract =     "Several emerging mobile applications and services
                 (e.g., autonomous cars) require higher wireless
                 throughput than ever before. This demand stresses the
                 need for investigating novel methods that have the
                 potential to dramatically increase the spectral
                 efficiency (SE) of wireless systems. An evolving
                 approach is the Single-channel full duplex (SCFD)
                 communication where each node may simultaneously
                 receive and transmit over the same frequency channel,
                 and, hence, this could potentially double the current
                 SE figures. In an earlier research work, we derived a
                 model of the signal to interference plus noise ratio
                 (SINR) in an SCFD-based cellular system with imperfect
                 self interference cancellation, and investigated
                 interference management under feasible QoS
                 requirements. In this paper, game theoretic results are
                 exploited to investigate the intercell interference
                 management in SCFD-based cellular networks under
                 infeasible QoS requirements. The investigation starts
                 with a game formulation that captures two different
                 cases. Then, the existence and uniqueness of the Nash
                 equilibrium point are established. After that, a
                 computationally efficient distributed algorithm, which
                 realizes best effort and fair wireless services, is
                 designed. The merit of this scheme is that, when the
                 QoS requirements are feasible, they will be achieved
                 with minimum energy consumption. Results of extensive
                 simulation experiments are presented to show the
                 effectiveness of the proposed schemes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Network Virtualization and Edge/Fog
                 Computing.",
}

@Article{Zhang:2019:MAN,
  author =       "Qiuyue Zhang and Ran Lu",
  title =        "A Multi-Attention Network for Aspect-Level Sentiment
                 Analysis",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "7",
  pages =        "157",
  day =          "16",
  month =        jul,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11070157",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/7/157",
  abstract =     "Aspect-level sentiment analysis (ASA) aims at
                 determining the sentiment polarity of specific aspect
                 term with a given sentence. Recent advances in
                 attention mechanisms suggest that attention models are
                 useful in ASA tasks and can help identify focus words.
                 Or combining attention mechanisms with neural networks
                 are also common methods. However, according to the
                 latest research, they often fail to extract text
                 representations efficiently and to achieve interaction
                 between aspect terms and contexts. In order to solve
                 the complete task of ASA, this paper proposes a
                 Multi-Attention Network (MAN) model which adopts
                 several attention networks. This model not only
                 preprocesses data by Bidirectional Encoder
                 Representations from Transformers (BERT), but a number
                 of measures have been taken. First, the MAN model
                 utilizes the partial Transformer after transformation
                 to obtain hidden sequence information. Second, because
                 words in different location have different effects on
                 aspect terms, we introduce location encoding to analyze
                 the impact on distance from ASA tasks, then we obtain
                 the influence of different words with aspect terms
                 through the bidirectional attention network. From the
                 experimental results of three datasets, we could find
                 that the proposed model could achieve consistently
                 superior results.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Network Virtualization and Edge/Fog
                 Computing.",
}

@Article{Vanneste:2019:DUS,
  author =       "Simon Vanneste and Jens de Hoog and Thomas Huybrechts
                 and Stig Bosmans and Reinout Eyckerman and Muddsair
                 Sharif and Siegfried Mercelis and Peter Hellinckx",
  title =        "Distributed Uniform Streaming Framework: An Elastic
                 Fog Computing Platform for Event Stream Processing and
                 Platform Transparency",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "7",
  pages =        "158",
  day =          "19",
  month =        jul,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11070158",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/7/158",
  abstract =     "The increase of Internet of Things devices and the
                 rise of more computationally intense applications
                 presents challenges for future Internet of Things
                 architectures. We envision a future in which edge, fog,
                 and cloud devices work together to execute future
                 applications. Because the entire application cannot run
                 on smaller edge or fog devices, we will need to split
                 the application into smaller application components.
                 These application components will send event messages
                 to each other to create a single application from
                 multiple application components. The execution location
                 of the application components can be optimized to
                 minimize the resource consumption. In this paper, we
                 describe the Distributed Uniform Stream (DUST)
                 framework that creates an abstraction between the
                 application components and the middleware which is
                 required to make the execution location transparent to
                 the application component. We describe a real-world
                 application that uses the DUST framework for platform
                 transparency. Next to the DUST framework, we also
                 describe the distributed DUST Coordinator, which will
                 optimize the resource consumption by moving the
                 application components to a different execution
                 location. The coordinators will use an adapted version
                 of the Contract Net Protocol to find local minima in
                 resource consumption.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Advanced Techniques for Internet, P2P
                 and Cloud Computing-selected papers from 3PGCIC-2018.",
}

@Article{Menth:2019:IEA,
  author =       "Michael Menth and Habib Mostafaei and Daniel Merling
                 and Marco H{\"a}berle",
  title =        "Implementation and Evaluation of Activity-Based
                 Congestion Management Using {P4 (P4-ABC)}",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "7",
  pages =        "159",
  day =          "19",
  month =        jul,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11070159",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/7/159",
  abstract =     "Activity-Based Congestion management (ABC) is a novel
                 domain-based QoS mechanism providing more fairness
                 among customers on bottleneck links. It avoids per-flow
                 or per-customer states in the core network and is
                 suitable for application in future 5G networks.
                 However, ABC cannot be configured on standard devices.
                 P4 is a novel programmable data plane specification
                 which allows defining new headers and forwarding
                 behavior. In this work, we implement an ABC prototype
                 using P4 and point out challenges experienced during
                 implementation. Experimental validation of ABC using
                 the P4-based prototype reveals the desired fairness
                 results.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Network Virtualization and Edge/Fog
                 Computing.",
}

@Article{Manzoor:2019:CBR,
  author =       "Hamza Manzoor and Kamil Akhuseyinoglu and Jackson
                 Wonderly and Peter Brusilovsky and Clifford A.
                 Shaffer",
  title =        "Crossing the Borders: Re-Use of Smart Learning Objects
                 in Advanced Content Access Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "7",
  pages =        "160",
  day =          "19",
  month =        jul,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11070160",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/7/160",
  abstract =     "Researchers in many disciplines are developing novel
                 interactive smart learning objects like exercises and
                 visualizations. Meanwhile, Learning Management Systems
                 (LMS) and eTextbook systems are also becoming more
                 sophisticated in their ability to use standard
                 protocols to make use of third party smart learning
                 objects. But at this time, educational tool developers
                 do not always make best use of the interoperability
                 standards and need exemplars to guide and motivate
                 their development efforts. In this paper we present a
                 case study where the two large educational ecosystems
                 use the Learning Tools Interoperability (LTI) standard
                 to allow cross-sharing of their educational materials.
                 At the end of our development process, Virginia Tech's
                 OpenDSA eTextbook system became able to import
                 materials from Aalto University's ACOS smart learning
                 content server, such as python programming exercises
                 and Parsons problems. Meanwhile, University of
                 Pittsburgh's Mastery Grids (which already uses the ACOS
                 exercises) was made to support CodeWorkout programming
                 exercises (a system already used within OpenDSA). Thus,
                 four major projects in CS Education became
                 inter-operable.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Trends and Opportunities in Online
                 Education.",
}

@Article{Rejeb:2019:LIT,
  author =       "Abderahman Rejeb and John G. Keogh and Horst
                 Treiblmaier",
  title =        "Leveraging the {Internet of Things} and Blockchain
                 Technology in Supply Chain Management",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "7",
  pages =        "161",
  day =          "20",
  month =        jul,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11070161",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/7/161",
  abstract =     "Modern supply chains have evolved into highly complex
                 value networks and turned into a vital source of
                 competitive advantage. However, it has become
                 increasingly challenging to verify the source of raw
                 materials and maintain visibility of products and
                 merchandise while they are moving through the value
                 chain network. The application of the Internet of
                 Things (IoT) can help companies to observe, track, and
                 monitor products, activities, and processes within
                 their respective value chain networks. Other
                 applications of IoT include product monitoring to
                 optimize operations in warehousing\&sbquo;
                 manufacturing, and transportation. In combination with
                 IoT, Blockchain technology can enable a broad range of
                 different application scenarios to enhance value chain
                 transparency and to increase B2B trust. When combined,
                 IoT and Blockchain technology have the potential to
                 increase the effectiveness and efficiency of modern
                 supply chains. The contribution of this paper is
                 twofold. First, we illustrate how the deployment of
                 Blockchain technology in combination with IoT
                 infrastructure can streamline and benefit modern supply
                 chains and enhance value chain networks. Second, we
                 derive six research propositions outlining how
                 Blockchain technology can impact key features of the
                 IoT (i.e., scalability, security, immutability and
                 auditing, information flows, traceability and
                 interoperability, quality) and thus lay the foundation
                 for future research projects.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Cloud Computing and Internet of
                 Things.",
}

@Article{Serketzis:2019:IFT,
  author =       "Nikolaos Serketzis and Vasilios Katos and Christos
                 Ilioudis and Dimitrios Baltatzis and Georgios
                 Pangalos",
  title =        "Improving Forensic Triage Efficiency through Cyber
                 Threat Intelligence",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "7",
  pages =        "162",
  day =          "23",
  month =        jul,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11070162",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/7/162",
  abstract =     "The complication of information technology and the
                 proliferation of heterogeneous security devices that
                 produce increased volumes of data coupled with the
                 ever-changing threat landscape challenges have an
                 adverse impact on the efficiency of information
                 security controls and digital forensics, as well as
                 incident response approaches. Cyber Threat Intelligence
                 (CTI)and forensic preparedness are the two parts of the
                 so-called managed security services that defendants can
                 employ to repel, mitigate or investigate security
                 incidents. Despite their success, there is no known
                 effort that has combined these two approaches to
                 enhance Digital Forensic Readiness (DFR) and thus
                 decrease the time and cost of incident response and
                 investigation. This paper builds upon and extends a DFR
                 model that utilises actionable CTI to improve the
                 maturity levels of DFR. The effectiveness and
                 applicability of this model are evaluated through a
                 series of experiments that employ malware-related
                 network data simulating real-world attack scenarios. To
                 this extent, the model manages to identify the root
                 causes of information security incidents with high
                 accuracy (90.73\%), precision (96.17\%) and recall
                 (93.61\%), while managing to decrease significantly the
                 volume of data digital forensic investigators need to
                 examine. The contribution of this paper is twofold.
                 First, it indicates that CTI can be employed by digital
                 forensics processes. Second, it demonstrates and
                 evaluates an efficient mechanism that enhances
                 operational DFR.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Privacy in Information and
                 Communication Systems.",
}

@Article{Lettieri:2019:PET,
  author =       "Nicola Lettieri and Alfonso Guarino and Delfina
                 Malandrino and Rocco Zaccagnino",
  title =        "Platform Economy and Techno-Regulation-Experimenting
                 with Reputation and Nudge",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "7",
  pages =        "163",
  day =          "23",
  month =        jul,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11070163",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:06 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/7/163",
  abstract =     "In the cloud-based society, where the vast majority of
                 social, economic and personal interactions is mediated
                 by information communication technology (ICT),
                 technology is no longer simply a subject of regulation
                 but is becoming an integral part of the regulatory
                 process. Techno-regulation, the ``intentional
                 influencing of individuals' behavior by building norms
                 into technological devices,'' is inspiring new ways to
                 support legal safeguards through hardware and software
                 tools, technical solutions allowing the creation of
                 legal relations, hampering breaches of law and even
                 promoting norm compliance. This paper touches on these
                 issues by focusing on Digital Labor Platforms, one of
                 the most relevant phenomena in the gig economy. We
                 present a research project exploring innovative
                 techno-regulatory solutions to protect gig economy
                 workers. The idea is to integrate, in the same
                 strategy, legal principles, regulatory objectives and
                 software solutions. Our attention focuses on two
                 results of our activity --- a techno-regulatory model
                 relying on reputational mechanisms to affect the
                 behavior of digital labor market operators and
                 GigAdvisor, a cross-platform experimental application
                 implementing the model.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Chiti:2019:EEC,
  author =       "Francesco Chiti and Romano Fantacci and Laura
                 Pierucci",
  title =        "Energy Efficient Communications for Reliable {IoT}
                 Multicast {5G}\slash Satellite Services",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "8",
  pages =        "164",
  day =          "25",
  month =        jul,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11080164",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/8/164",
  abstract =     "Satellites can provide strong value-add and
                 complementarity with the new cellular system of the
                 fifth generation (5G) in cost-effective solutions for a
                 massive number of users/devices/things. Due to the
                 inherent broadcast nature of satellite communications,
                 which assures access to remote areas and the support to
                 a very large number of devices, satellite systems will
                 gain a major role in the development of the Internet of
                 Things (IoT) sector. In this vision, reliable multicast
                 services via satellite can be provided to deliver the
                 same content efficiently to multiple devices on the
                 Earth, or for software updating to groups of cars in
                 the Machine-to-Machine (M2M) context or for sending
                 control messages to actuators/IoT embedded devices. The
                 paper focuses on the Network coding (NC) techniques
                 applied to a hybrid satellite/terrestrial network to
                 support reliable multicast services. An energy
                 optimization method is proposed based on joint
                 adaptation of: (i) the repetition factor of data
                 symbols on multiple subcarries of the transmitted
                 orthogonal frequency division multiplexing (OFDM)
                 signal; and (ii) the mean number of needed coded
                 packets according to the requirements of each group and
                 to the physical satellite links conditions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Satellite Communications in 5G
                 Networks.",
}

@Article{Yang:2019:SEO,
  author =       "Jin Sol Yang and Myung-Sook Ko and Kwang Sik Chung",
  title =        "Social Emotional Opinion Decision with Newly Coined
                 Words and Emoticon Polarity of Social Networks
                 Services",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "8",
  pages =        "165",
  day =          "25",
  month =        jul,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11080165",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/8/165",
  abstract =     "Nowadays, based on mobile devices and internet, social
                 network services (SNS) are common trends to everyone.
                 Social opinions as public opinions are very important
                 to the government, company, and a person. Analysis and
                 decision of social polarity of SNS about social
                 happenings, political issues and government policies,
                 or commercial products is very critical to the
                 government, company, and a person. Newly coined words
                 and emoticons on SNS are created every day.
                 Specifically, emoticons are made and sold by a person
                 or companies. Newly coined words are mostly made and
                 used by various kinds of communities. The SNS big data
                 mainly consist of normal text with newly coined words
                 and emoticons so that newly coined words and emoticons
                 analysis is very important to understand the social and
                 public opinions. Social big data is informally made and
                 unstructured, and on social network services, many
                 kinds of newly coined words and various emoticons are
                 made anonymously and unintentionally by people and
                 companies. In the analysis of social data, newly coined
                 words and emoticons limit the guarantee the accuracy of
                 analysis. The newly coined words implicitly contain the
                 social opinions and trends of people. The emotional
                 states of people significantly are expressed by
                 emoticons. Although the newly coined words and
                 emoticons are an important part of the social opinion
                 analysis, they are excluded from the emotional
                 dictionary and social big data analysis. In this
                 research, newly coined words and emoticons are
                 extracted from the raw Twitter's twit messages and
                 analyzed and included in a pre-built dictionary with
                 the polarity and weight of the newly coined words and
                 emoticons. The polarity and weight are calculated for
                 emotional classification. The proposed emotional
                 classification algorithm calculates the weight of
                 polarity (positive or negative) and results in total
                 polarity weight of social opinion. If the total
                 polarity weight of social opinion is more than the
                 pre-fixed threshold value, the twit message is decided
                 as positive. If it is less than the pre-fixed threshold
                 value, the twit message is decided as negative and the
                 other values mean neutral opinion. The accuracy of the
                 social big data analysis result is improved by
                 quantifying and analyzing emoticons and newly coined
                 words.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Selected Papers from IEEE ICICT 2019.",
}

@Article{Elzain:2019:SDW,
  author =       "Hisham Elzain and Yang Wu",
  title =        "Software Defined Wireless Mesh Network Flat
                 Distribution Control Plane",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "8",
  pages =        "166",
  day =          "25",
  month =        jul,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11080166",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/8/166",
  abstract =     "Wireless Mesh Networks (WMNs), have a potential
                 offering relatively stable Internet broadband access.
                 The rapid development and growth of WMNs attract ISPs
                 to support users' coverage anywhere anytime. To achieve
                 this goal network architecture must be addressed
                 carefully. Software Defined Networking (SDN) proposes
                 new network architecture for wired and wireless
                 networks. Software Defined Wireless Networking (SDWN)
                 has a great potential to increase efficiency, ease the
                 complexity of control and management, and accelerate
                 technology innovation rate of wireless networking. An
                 SDN controller is the core component of an SDN network.
                 It needs to have updated reports of the network status
                 change, as in network topology and quality of service
                 (QoS) in order to effectively configure and manage the
                 network it controls. In this paper, we propose Flat
                 Distributed Software Defined Wireless Mesh Network
                 architecture where the controller aggregates entire
                 topology discovery and monitors QoS properties of
                 extended WMN nodes using Link Layer Discovery Protocol
                 (LLDP) protocol, which is not possible in multi-hop
                 ordinary architectures. The proposed architecture has
                 been implemented on top of POX controller and Advanced
                 Message Queuing Protocol (AMQP) protocol. The
                 experiments were conducted in a Mininet-wifi emulator,
                 the results present the architecture control plane
                 consistency and two application cases: topology
                 discovery and QoS monitoring. The current results push
                 us to study QoS-routing for video streaming over WMN.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sengupta:2019:HAT,
  author =       "Saumendra Sengupta and Chen-Fu Chiang and Bruno
                 Andriamanalimanana and Jorge Novillo and Ali Tekeoglu",
  title =        "A Hybrid Adaptive Transaction Injection Protocol and
                 Its Optimization for Verification-Based Decentralized
                 System",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "8",
  pages =        "167",
  day =          "27",
  month =        jul,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11080167",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/8/167",
  abstract =     "Latency is a critical issue that impacts the
                 performance of decentralized systems. Recently we
                 designed various protocols to regulate the injection
                 rate of unverified transactions into the system to
                 improve system performance. Each of the protocols is
                 designed to address issues related to some particular
                 network traffic syndrome. In this work, we first
                 provide the review of our prior protocols. We then
                 provide a hybrid scheme that combines our transaction
                 injection protocols and provides an optimal linear
                 combination of the protocols based on the syndromes in
                 the network. The goal is to speed up the verification
                 process of systems that rely on only one single basic
                 protocol. The underlying basic protocols are Periodic
                 Injection of Transaction via Evaluation Corridor
                 (PITEC), Probabilistic Injection of Transactions (PIT),
                 and Adaptive Semi-synchronous Transaction Injection
                 (ASTI).",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Advanced Techniques for Internet, P2P
                 and Cloud Computing-selected papers from 3PGCIC-2018.",
}

@Article{Yuan:2019:LBD,
  author =       "Jie Yuan and Erxia Li and Chaoqun Kang and Fangyuan
                 Chang and Tingting Yuan and Xiaoyong Li",
  title =        "Latency-Based Dynamic Controller Assignment in Hybrid
                 {SDNs}: Considering the Impact of Legacy Routers",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "8",
  pages =        "168",
  day =          "28",
  month =        jul,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11080168",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/8/168",
  abstract =     "Software-defined networking (SDN) is a modern network
                 architecture, which separates the network control plane
                 from the data plane. Considering the gradual migration
                 from traditional networks to SDNs, the hybrid SDN,
                 which consists of SDN-enabled devices and legacy
                 devices, is an intermediate state. For wide-area hybrid
                 SDNs, to guarantee the control performance, such as low
                 latency, multi SDN controllers are usually needed to be
                 deployed at different places. How to assign them to
                 switches and partition the network into several control
                 domains is a critical problem. For this problem, the
                 control latency and the packet loss rate of control
                 messages are important metrics, which have been
                 considered in a lot of previous works. However, hybrid
                 SDNs have their unique characters, which can affect the
                 assignment scheme and have been ignored by previous
                 studies. For example, control messages pass through
                 Legacy Forwarding Devices (LFDs) in hybrid SDNs and
                 cause more latency and packet loss rate for queuing
                 compared with SDN-enabled Forwarding Devices (SFDs). In
                 this paper, we propose a dynamic controller assignment
                 scheme in hybrid SDNs, which is called the Legacy Based
                 Assignment (LBA). This scheme can dynamically delegate
                 each controller with a subset of SFDs in the hybrid
                 SDNs, whose objective is to minimize average
                 SFD-to-control latency. We performed some experiments
                 compared with other schemes, which show that our scheme
                 has a better performance in terms of the latency and
                 the packet loss rate.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Network, Compute, and Storage Management
                 Using Software Defined Environments (SDEs).",
}

@Article{Tatulea:2019:IFB,
  author =       "Paula Tatulea and Florina Calin and Remus Brad and
                 Lucian Br{\^a}ncovean and Mircea Greavu",
  title =        "An Image Feature-Based Method for Parking Lot
                 Occupancy",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "8",
  pages =        "169",
  day =          "01",
  month =        aug,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11080169",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/8/169",
  abstract =     "The main scope of the presented research was the
                 development of an innovative product for the management
                 of city parking lots. Our application will ensure the
                 implementation of the Smart City concept by using
                 computer vision and communication platforms, which
                 enable the development of new integrated digital
                 services. The use of video cameras could simplify and
                 lower the costs of parking lot controls. In the aim of
                 parking space detection, an aggregated decision was
                 proposed, employing various metrics, computed over a
                 sliding window interval provided by the camera. The
                 history created over 20 images provides an adaptive
                 method for background and accurate detection. The
                 system has shown high robustness in two benchmarks,
                 achieving a recognition rate higher than 93\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Smart System Infrastructure and
                 Applications.",
}

@Article{Sgantzos:2019:AII,
  author =       "Konstantinos Sgantzos and Ian Grigg",
  title =        "Artificial Intelligence Implementations on the
                 Blockchain. {Use} Cases and Future Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "8",
  pages =        "170",
  day =          "02",
  month =        aug,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11080170",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/8/170",
  abstract =     "An exemplary paradigm of how an AI can be a disruptive
                 technological paragon via the utilization of blockchain
                 comes straight from the world of deep learning. Data
                 scientists have long struggled to maintain the quality
                 of a dataset for machine learning by an AI entity.
                 Datasets can be very expensive to purchase, as,
                 depending on both the proper selection of the elements
                 and the homogeneity of the data contained within,
                 constructing and maintaining the integrity of a dataset
                 is difficult. Blockchain as a highly secure storage
                 medium presents a technological quantum leap in
                 maintaining data integrity. Furthermore, blockchain's
                 immutability constructs a fruitful environment for
                 creating high quality, permanent and growing datasets
                 for deep learning. The combination of AI and blockchain
                 could impact fields like Internet of things (IoT),
                 identity, financial markets, civil governance, smart
                 cities, small communities, supply chains, personalized
                 medicine and other fields, and thereby deliver benefits
                 to many people.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Blockchain: Current Challenges and
                 Future Prospects/Applications.",
}

@Article{Duc:2019:MCQ,
  author =       "Tho Nguyen Duc and Chanh Minh Tran and Phan Xuan Tan
                 and Eiji Kamioka",
  title =        "Modeling of Cumulative {QoE} in On-Demand Video
                 Services: Role of Memory Effect and Degree of
                 Interest",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "8",
  pages =        "171",
  day =          "04",
  month =        aug,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11080171",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/8/171",
  abstract =     "The growing demand on video streaming services
                 increasingly motivates the development of a reliable
                 and accurate models for the assessment of Quality of
                 Experience (QoE). In this duty, human-related factors
                 which have significant influence on QoE play a crucial
                 role. However, the complexity caused by multiple
                 effects of those factors on human perception has
                 introduced challenges on contemporary studies. In this
                 paper, we inspect the impact of the human-related
                 factors, namely perceptual factors, memory effect, and
                 the degree of interest. Based on our investigation, a
                 novel QoE model is proposed that effectively
                 incorporates those factors to reflect the user's
                 cumulative perception. Evaluation results indicate that
                 our proposed model performed excellently in predicting
                 cumulative QoE at any moment within a streaming
                 session.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Multimedia Quality of Experience (QoE):
                 Current Status and Future Direction.",
}

@Article{Raviv:2019:SMU,
  author =       "Li-on Raviv and Amir Leshem",
  title =        "Scheduling for Multi-User Multi-Input Multi-Output
                 Wireless Networks with Priorities and Deadlines",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "8",
  pages =        "172",
  day =          "05",
  month =        aug,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11080172",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/8/172",
  abstract =     "The spectral efficiency of wireless networks can be
                 significantly improved by exploiting spatial
                 multiplexing techniques known as multi-user MIMO. These
                 techniques enable the allocation of multiple users to
                 the same time-frequency block, thus reducing the
                 interference between users. There is ample evidence
                 that user groupings can have a significant impact on
                 the performance of spatial multiplexing. The situation
                 is even more complex when the data packets have
                 priority and deadlines for delivery. Hence, combining
                 packet queue management and beamforming would
                 considerably enhance the overall system performance. In
                 this paper, we propose a combination of beamforming and
                 scheduling to improve the overall performance of
                 multi-user MIMO systems in realistic conditions where
                 data packets have both priority and deadlines beyond
                 which they become obsolete. This method dubbed Reward
                 Per Second (RPS), combines advanced matrix
                 factorization at the physical layer with
                 recently-developed queue management techniques. We
                 demonstrate the merits of the this technique compared
                 to other state-of-the-art scheduling methods through
                 simulations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Signal Processing for Next Generation
                 Wireless Networks.",
}

@Article{Bertolazzi:2019:MED,
  author =       "Marco Bertolazzi and Carlo Caini",
  title =        "{Mars} to {Earth} Data Downloading: a Directory
                 Synchronization Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "8",
  pages =        "173",
  day =          "08",
  month =        aug,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11080173",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/8/173",
  abstract =     "This paper aims to present a possible alternative to
                 direct file transfer in ``challenged networks'', by
                 using DTNbox, a recent application for peer-to-peer
                 directory synchronization between DTN nodes. This
                 application uses the Bundle Protocol (BP) to tackle
                 long delays and link intermittency typical of
                 challenged networks. The directory synchronization
                 approach proposed in the paper consists of delegating
                 the transmission of bulk data files to DTNbox, instead
                 of modifying source applications to interface with the
                 API of a specific BP implementation, or making use of
                 custom scripts for file transfers. The validity of the
                 proposed approach is investigated in the paper by
                 considering a Mars to Earth interplanetary environment.
                 Experiments are carried out by means of Virtual
                 Machines running ION, the NASA-JPL implementation of
                 DTN protocols. The results show that the directory
                 synchronization approach is a valid alternative to
                 direct transfer in interplanetary scenarios such as
                 that considered in the paper.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Delay-Tolerant Networking.",
}

@Article{ODonovan:2019:SAR,
  author =       "Peter O'Donovan and Dominic T. J. O'Sullivan",
  title =        "A Systematic Analysis of Real-World Energy Blockchain
                 Initiatives",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "8",
  pages =        "174",
  day =          "10",
  month =        aug,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11080174",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/8/174",
  abstract =     "The application of blockchain technology to the energy
                 sector promises to derive new operating models focused
                 on local generation and sustainable practices, which
                 are driven by peer-to-peer collaboration and community
                 engagement. However, real-world energy blockchains
                 differ from typical blockchain networks insofar as they
                 must interoperate with grid infrastructure, adhere to
                 energy regulations, and embody engineering principles.
                 Naturally, these additional dimensions make real-world
                 energy blockchains highly dependent on the
                 participation of grid operators, engineers, and energy
                 providers. Although much theoretical and
                 proof-of-concept research has been published on energy
                 blockchains, this research aims to establish a lens on
                 real-world projects and implementations that may inform
                 the alignment of academic and industry research
                 agendas. This research classifies 131 real-world energy
                 blockchain initiatives to develop an understanding of
                 how blockchains are being applied to the energy domain,
                 what type of failure rates can be observed from
                 recently reported initiatives, and what level of
                 technical and theoretical details are reported for
                 real-world deployments. The results presented from the
                 systematic analysis highlight that real-world energy
                 blockchains are (a) growing exponentially year-on-year,
                 (b) producing relatively low failure/drop-off rates ($
                 \approx $7\% since 2015), and (c) demonstrating
                 information sharing protocols that produce content with
                 insufficient technical and theoretical depth.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Blockchain: Current Challenges and
                 Future Prospects/Applications.",
}

@Article{Erabadda:2019:QEQ,
  author =       "Buddhiprabha Erabadda and Thanuja Mallikarachchi and
                 Chaminda Hewage and Anil Fernando",
  title =        "Quality of Experience {(QoE)-Aware} Fast Coding Unit
                 Size Selection for {HEVC} Intra-Prediction",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "8",
  pages =        "175",
  day =          "11",
  month =        aug,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11080175",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/8/175",
  abstract =     "The exorbitant increase in the computational
                 complexity of modern video coding standards, such as
                 High Efficiency Video Coding (HEVC), is a compelling
                 challenge for resource-constrained consumer electronic
                 devices. For instance, the brute force evaluation of
                 all possible combinations of available coding modes and
                 quadtree-based coding structure in HEVC to determine
                 the optimum set of coding parameters for a given
                 content demand a substantial amount of computational
                 and energy resources. Thus, the resource requirements
                 for real time operation of HEVC has become a
                 contributing factor towards the Quality of Experience
                 (QoE) of the end users of emerging multimedia and
                 future internet applications. In this context, this
                 paper proposes a content-adaptive Coding Unit (CU) size
                 selection algorithm for HEVC intra-prediction. The
                 proposed algorithm builds content-specific weighted
                 Support Vector Machine (SVM) models in real time during
                 the encoding process, to provide an early estimate of
                 CU size for a given content, avoiding the brute force
                 evaluation of all possible coding mode combinations in
                 HEVC. The experimental results demonstrate an average
                 encoding time reduction of 52.38\%, with an average
                 Bj\&oslash;ntegaard Delta Bit Rate (BDBR) increase of
                 1.19\% compared to the HM16.1 reference encoder.
                 Furthermore, the perceptual visual quality assessments
                 conducted through Video Quality Metric (VQM) show
                 minimal visual quality impact on the reconstructed
                 videos of the proposed algorithm compared to
                 state-of-the-art approaches.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Multimedia Quality of Experience (QoE):
                 Current Status and Future Direction.",
}

@Article{Yang:2019:RFA,
  author =       "Keng Yang",
  title =        "Research on Factors Affecting Solvers' Participation
                 Time in Online Crowdsourcing Contests",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "8",
  pages =        "176",
  day =          "12",
  month =        aug,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11080176",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/8/176",
  abstract =     "A crowdsourcing contest is one of the most popular
                 modes of crowdsourcing and is also an important tool
                 for an enterprise to implement open innovation. The
                 solvers' active participation is one of the major
                 reasons for the success of crowdsourcing contests.
                 Research on solvers' participation behavior is helpful
                 in understanding the sustainability and incentives of
                 solvers' participation in the online crowdsourcing
                 platform. So, how to attract more solvers to
                 participate and put in more effort is the focus of
                 researchers. In this regard, previous studies mainly
                 used the submission quantity to measure solvers'
                 participation behavior and lacked an effective measure
                 on the degree of participation effort expended by a
                 solver. For the first time, we use solvers'
                 participation time as a dependent variable to measure
                 their effort in a crowdsourcing contest. Thus, we
                 incorporate participation time into the solver's
                 participation research. With the data from Taskcn.com,
                 we analyze how participation time is affected four key
                 factors including task design, task description, task
                 process, and environment, respectively. We found that,
                 first, for task design, higher task rewards will
                 attract solvers to invest more time in the
                 participation process and the relationship between
                 participation time and task duration is inverted
                 U-shaped. Second, for task description, the length of
                 the task description has a negative impact on
                 participation time and the task description attachment
                 will positively influence the participation time.
                 Third, for the task process, communication and
                 supplementary explanations in a crowdsourcing process
                 positively affect participation time. Fourth, for
                 environmental factors, the task density of the
                 crowdsourcing platform and the market price of all
                 crowdsourcing contests have respectively negative and
                 positive effects on participation time.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Network Economics and Utility
                 Maximization.",
}

@Article{Fang:2019:ROX,
  author =       "Yong Fang and Cheng Huang and Yijia Xu and Yang Li",
  title =        "{RLXSS}: Optimizing {XSS} Detection Model to Defend
                 Against Adversarial Attacks Based on Reinforcement
                 Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "8",
  pages =        "177",
  day =          "14",
  month =        aug,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11080177",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/8/177",
  abstract =     "With the development of artificial intelligence,
                 machine learning algorithms and deep learning
                 algorithms are widely applied to attack detection
                 models. Adversarial attacks against artificial
                 intelligence models become inevitable problems when
                 there is a lack of research on the cross-site scripting
                 (XSS) attack detection model for defense against
                 attacks. It is extremely important to design a method
                 that can effectively improve the detection model
                 against attack. In this paper, we present a method
                 based on reinforcement learning (called RLXSS), which
                 aims to optimize the XSS detection model to defend
                 against adversarial attacks. First, the adversarial
                 samples of the detection model are mined by the
                 adversarial attack model based on reinforcement
                 learning. Secondly, the detection model and the
                 adversarial model are alternately trained. After each
                 round, the newly-excavated adversarial samples are
                 marked as a malicious sample and are used to retrain
                 the detection model. Experimental results show that the
                 proposed RLXSS model can successfully mine adversarial
                 samples that escape black-box and white-box detection
                 and retain aggressive features. What is more, by
                 alternately training the detection model and the
                 confrontation attack model, the escape rate of the
                 detection model is continuously reduced, which
                 indicates that the model can improve the ability of the
                 detection model to defend against attacks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Cybersecurity.",
}

@Article{Cremer:2019:AII,
  author =       "Stefan Cremer and Claudia Loebbecke",
  title =        "Artificial Intelligence Imagery Analysis Fostering Big
                 Data Analytics",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "8",
  pages =        "178",
  day =          "15",
  month =        aug,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11080178",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/8/178",
  abstract =     "In an era of accelerating digitization and advanced
                 big data analytics, harnessing quality data and
                 insights will enable innovative research methods and
                 management approaches. Among others, Artificial
                 Intelligence Imagery Analysis has recently emerged as a
                 new method for analyzing the content of large amounts
                 of pictorial data. In this paper, we provide background
                 information and outline the application of Artificial
                 Intelligence Imagery Analysis for analyzing the content
                 of large amounts of pictorial data. We suggest that
                 Artificial Intelligence Imagery Analysis constitutes a
                 profound improvement over previous methods that have
                 mostly relied on manual work by humans. In this paper,
                 we discuss the applications of Artificial Intelligence
                 Imagery Analysis for research and practice and provide
                 an example of its use for research. In the case study,
                 we employed Artificial Intelligence Imagery Analysis
                 for decomposing and assessing thumbnail images in the
                 context of marketing and media research and show how
                 properly assessed and designed thumbnail images promote
                 the consumption of online videos. We conclude the paper
                 with a discussion on the potential of Artificial
                 Intelligence Imagery Analysis for research and practice
                 across disciplines.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Big Data Analytics and Artificial
                 Intelligence.",
}

@Article{Kirova:2019:IMV,
  author =       "Veronika Kirova and Kirill Karpov and Eduard Siemens
                 and Irina Zander and Oksana Vasylenko and Dmitry Kachan
                 and Sergii Maksymov",
  title =        "Impact of Modern Virtualization Methods on Timing
                 Precision and Performance of High-Speed Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "8",
  pages =        "179",
  day =          "16",
  month =        aug,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11080179",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/8/179",
  abstract =     "The presented work is a result of extended research
                 and analysis on timing methods precision, their
                 efficiency in different virtual environments and the
                 impact of timing precision on the performance of
                 high-speed networks applications. We investigated how
                 timer hardware is shared among heavily CPU- and
                 I/O-bound tasks on a virtualized OS as well as on bare
                 OS. By replacing the invoked timing methods within a
                 well-known application for estimation of available path
                 bandwidth, we provide the analysis of their impact on
                 estimation accuracy. We show that timer overhead and
                 precision are crucial for high-performance network
                 applications, and low-precision timing methods usage,
                 e.g., the delays and overheads issued by virtualization
                 result in the degradation of the virtual environment.
                 Furthermore, in this paper, we provide confirmation
                 that, by using the methods we intentionally developed
                 for both precise timing operations and AvB estimation,
                 it is possible to overcome the inefficiency of standard
                 time-related operations and overhead that comes with
                 the virtualization. The impacts of negative
                 virtualization factors were investigated in five
                 different environments to define the most optimal
                 virtual environment for high-speed network
                 applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Network Virtualization and Edge/Fog
                 Computing.",
}

@Article{Liao:2019:CSA,
  author =       "Fei Liao and Liangli Ma and Jingjing Pei and Linshan
                 Tan",
  title =        "Combined Self-Attention Mechanism for {Chinese} Named
                 Entity Recognition in Military",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "8",
  pages =        "180",
  day =          "18",
  month =        aug,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11080180",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/8/180",
  abstract =     "Military named entity recognition (MNER) is one of the
                 key technologies in military information extraction.
                 Traditional methods for the MNER task rely on
                 cumbersome feature engineering and specialized domain
                 knowledge. In order to solve this problem, we propose a
                 method employing a bidirectional long short-term memory
                 (BiLSTM) neural network with a self-attention mechanism
                 to identify the military entities automatically. We
                 obtain distributed vector representations of the
                 military corpus by unsupervised learning and the BiLSTM
                 model combined with the self-attention mechanism is
                 adopted to capture contextual information fully carried
                 by the character vector sequence. The experimental
                 results show that the self-attention mechanism can
                 improve effectively the performance of MNER task. The
                 F-score of the military documents and network military
                 texts identification was 90.15\% and 89.34\%,
                 respectively, which was better than other models.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Network Virtualization and Edge/Fog
                 Computing.",
}

@Article{Tang:2019:NTC,
  author =       "Lujie Tang and Bing Tang and Linyao Kang and Li
                 Zhang",
  title =        "A Novel Task Caching and Migration Strategy in
                 Multi-Access Edge Computing Based on the Genetic
                 Algorithm",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "8",
  pages =        "181",
  day =          "20",
  month =        aug,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11080181",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/8/181",
  abstract =     "Multi-access edge computing (MEC) brings
                 high-bandwidth and low-latency access to applications
                 distributed at the edge of the network. Data
                 transmission and exchange become faster, and the
                 overhead of the task migration between mobile devices
                 and edge cloud becomes smaller. In this paper, we adopt
                 the fine-grained task migration model. At the same
                 time, in order to further reduce the delay and energy
                 consumption of task execution, the concept of the task
                 cache is proposed, which involves caching the completed
                 tasks and related data on the edge cloud. Then, we
                 consider the limitations of the edge cloud cache
                 capacity to study the task caching strategy and
                 fine-grained task migration strategy on the edge cloud
                 using the genetic algorithm (GA). Thus, we obtained the
                 optimal mobile device task migration strategy,
                 satisfying minimum energy consumption and the optimal
                 cache on the edge cloud. The simulation results showed
                 that the task caching strategy based on fine-grained
                 migration can greatly reduce the energy consumption of
                 mobile devices in the MEC environment.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Network Virtualization and Edge/Fog
                 Computing.",
}

@Article{Sheridan:2019:OBR,
  author =       "Paul Sheridan and Mikael Onsj{\"o} and Claudia Becerra
                 and Sergio Jimenez and George Due{\~n}as",
  title =        "An Ontology-Based Recommender System with an
                 Application to the {Star Trek} Television Franchise",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "9",
  pages =        "182",
  day =          "22",
  month =        aug,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11090182",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/9/182",
  abstract =     "Collaborative filtering based recommender systems have
                 proven to be extremely successful in settings where
                 user preference data on items is abundant. However,
                 collaborative filtering algorithms are hindered by
                 their weakness against the item cold-start problem and
                 general lack of interpretability. Ontology-based
                 recommender systems exploit hierarchical organizations
                 of users and items to enhance browsing, recommendation,
                 and profile construction. While ontology-based
                 approaches address the shortcomings of their
                 collaborative filtering counterparts, ontological
                 organizations of items can be difficult to obtain for
                 items that mostly belong to the same category (e.g.,
                 television series episodes). In this paper, we present
                 an ontology-based recommender system that integrates
                 the knowledge represented in a large ontology of
                 literary themes to produce fiction content
                 recommendations. The main novelty of this work is an
                 ontology-based method for computing similarities
                 between items and its integration with the classical
                 Item-KNN (K-nearest neighbors) algorithm. As a study
                 case, we evaluated the proposed method against other
                 approaches by performing the classical rating
                 prediction task on a collection of Star Trek television
                 series episodes in an item cold-start scenario. This
                 transverse evaluation provides insights into the
                 utility of different information resources and methods
                 for the initial stages of recommender system
                 development. We found our proposed method to be a
                 convenient alternative to collaborative filtering
                 approaches for collections of mostly similar items,
                 particularly when other content-based approaches are
                 not applicable or otherwise unavailable. Aside from the
                 new methods, this paper contributes a testbed for
                 future research and an online framework to
                 collaboratively extend the ontology of literary themes
                 to cover other narrative content.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue New Perspectives on Semantic Web
                 Technologies and Applications.",
}

@Article{Gunleifsen:2019:PCD,
  author =       "H{\aa}kon Gunleifsen and Thomas Kemmerich and
                 Vasileios Gkioulos",
  title =        "A Proof-of-Concept Demonstration of Isolated and
                 Encrypted Service Function Chains",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "9",
  pages =        "183",
  day =          "24",
  month =        aug,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11090183",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/9/183",
  abstract =     "Contemporary Service Function Chaining (SFC), and the
                 requirements arising from privacy concerns, call for
                 the increasing integration of security features such as
                 encryption and isolation across Network Function
                 Virtualisation (NFV) domains. Therefore, suitable
                 adaptations of automation and encryption concepts for
                 the development of interconnected data centre
                 infrastructures are essential. Nevertheless, packet
                 isolation constraints related to the current NFV
                 infrastructure and SFC protocols, render current NFV
                 standards insecure. Accordingly, the goal of our work
                 was an experimental demonstration of a new SFC packet
                 forwarding standard that enables contemporary data
                 centres to overcome these constraints. This article
                 presents a comprehensive view of the developed
                 architecture, focusing on the elements that constitute
                 a new forwarding standard of encrypted SFC packets.
                 Through a Proof-of-Concept demonstration, we present
                 our closing experimental results of how the
                 architecture fulfills the requirements defined in our
                 use case.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Network Virtualization and Edge/Fog
                 Computing.",
}

@Article{Zhang:2019:MEE,
  author =       "Wenming Zhang and Yiwen Zhang and Qilin Wu and Kai
                 Peng",
  title =        "Mobility-Enabled Edge Server Selection for Multi-User
                 Composite Services",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "9",
  pages =        "184",
  day =          "25",
  month =        aug,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11090184",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/9/184",
  abstract =     "In mobile edge computing, a set of edge servers is
                 geographically deployed near the mobile users such that
                 accessible computing capacities and services can be
                 provided to users with low latency. Due to user's
                 mobility, one fundamental and critical problem in
                 mobile edge computing is how to select edge servers for
                 many mobile users so that the total waiting time is
                 minimized. In this paper, we propose a multi-user
                 waiting time computation model about composite services
                 and show the resource contention of the edge server
                 among mobile users. Then, we introduce a novel and
                 optimal Multi-user Edge server Selection method based
                 on Particle swarm optimization (MESP) in mobile edge
                 computing, which selects edge servers for mobile uses
                 in advance within polynomial time. Extensive
                 simulations on a real-world data-trace show that the
                 MESP algorithm can effectively reduce the total waiting
                 time compared with traditional approaches.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Network Virtualization and Edge/Fog
                 Computing.",
}

@Article{Gao:2019:IMN,
  author =       "Ming Gao and Qifeng Xiao and Shaochun Wu and Kun
                 Deng",
  title =        "An Improved Method for Named Entity Recognition and
                 Its Application to {CEMR}",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "9",
  pages =        "185",
  day =          "26",
  month =        aug,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11090185",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/9/185",
  abstract =     "Named Entity Recognition (NER) on Clinical Electronic
                 Medical Records (CEMR) is a fundamental step in
                 extracting disease knowledge by identifying specific
                 entity terms such as diseases, symptoms, etc. However,
                 the state-of-the-art NER methods based on Long
                 Short-Term Memory (LSTM) fail to exploit GPU
                 parallelism fully under the massive medical records.
                 Although a novel NER method based on Iterated Dilated
                 CNNs (ID-CNNs) can accelerate network computing, it
                 tends to ignore the word-order feature and semantic
                 information of the current word. In order to enhance
                 the performance of ID-CNNs-based models on NER tasks,
                 an attention-based ID-CNNs-CRF model, which combines
                 the word-order feature and local context, is proposed.
                 Firstly, position embedding is utilized to fuse
                 word-order information. Secondly, the ID-CNNs
                 architecture is used to extract global semantic
                 information rapidly. Simultaneously, the attention
                 mechanism is employed to pay attention to the local
                 context. Finally, we apply the CRF to obtain the
                 optimal tag sequence. Experiments conducted on two CEMR
                 datasets show that our model outperforms traditional
                 ones. The F1-scores of 94.55\% and 91.17\% are obtained
                 respectively on these two datasets, and both are better
                 than LSTM-based models.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Big Data and Augmented Intelligence.",
}

@Article{Orogun:2019:SCS,
  author =       "Adebola Orogun and Oluwaseun Fadeyi and Ondrej
                 Krejcar",
  title =        "Sustainable Communication Systems: a Graph-Labeling
                 Approach for Cellular Frequency Allocation in
                 Densely-Populated Areas",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "9",
  pages =        "186",
  day =          "26",
  month =        aug,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11090186",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/9/186",
  abstract =     "The need for smart and sustainable communication
                 systems has led to the development of mobile
                 communication networks. In turn, the vast
                 functionalities of the global system of mobile
                 communication (GSM) have resulted in a growing number
                 of subscribers. As the number of users increases, the
                 need for efficient and effective planning of the
                 ``limited'' frequency spectrum of the GSM is
                 inevitable, particularly in densely-populated areas. As
                 such, there are ongoing discussions about frequency
                 (channel) allocation methods to resolve the challenges
                 of channel allocation, which is a complete NP
                 (Nondeterministic Polynomial time) problem. In this
                 paper, we propose an algorithm for channel allocation
                 which takes into account soft constraints (co-channel
                 interference and adjacent channel interference). By
                 using the Manhattan distance concept, this study shows
                 that the formulation of the algorithm is correct and in
                 line with results in the literature. Hence, the
                 Manhattan distance concept may be useful in other
                 scheduling and optimization problems. Furthermore, this
                 unique concept makes it possible to develop a more
                 sustainable telecommunication system with ease of
                 connectivity among users, even when several subscribers
                 are on a common frequency.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Smart Solutions in Development of Smart
                 Applications and Systems with Aspect of Usefullness and
                 Sustainability.",
}

@Article{Wu:2019:RSS,
  author =       "Zhijun Wu and Shengyan Zhou and Liang Liu and Jin
                 Lei",
  title =        "Research on {SWIM} Services Dynamic Migration Method",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "9",
  pages =        "187",
  day =          "27",
  month =        aug,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11090187",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/9/187",
  abstract =     "Air traffic management (ATM) plays an important role
                 in maintaining and promoting air traffic safety,
                 maintaining air traffic order and ensuring smooth air
                 traffic. As the core of air traffic management, it is
                 essential to ensure the safe and stable operation of
                 system-wide information management (SWIM). Facing the
                 complex and ever-changing network environment, a SWIM
                 services dynamic migration method is proposed in this
                 paper. This method combines SWIM core services to
                 select destination nodes and migrate services. The
                 experiment proves that the method can hide the service
                 node while ensuring service continuity and increase the
                 difficulty of malicious detection. By comparing with
                 others, this method is more suitable for SWIM in terms
                 of invulnerability. The throughput and delay
                 performance of the method can meet the needs of SWIM.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Privacy in Information and
                 Communication Systems.",
}

@Article{Karyotakis:2019:SPS,
  author =       "Minos-Athanasios Karyotakis and Evangelos Lamprou and
                 Matina Kiourexidou and Nikos Antonopoulos",
  title =        "{SEO} Practices: a Study about the Way News {Websites}
                 Allow the Users to Comment on Their News Articles",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "9",
  pages =        "188",
  day =          "30",
  month =        aug,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11090188",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/9/188",
  abstract =     "In the current media world, there is a huge debate
                 about the importance of the visibility of a news
                 website in order to secure its existence. Thus, search
                 engine optimization (SEO) practices have emerged in the
                 news media systems around the world. This study aimed
                 to expand the current literature about the SEO
                 practices by focusing on examining, via the walkthrough
                 method, the ways that news companies allow the users to
                 comment on their online news articles. The comments on
                 the news websites are related to the notions of social
                 influence, information diffusion, and play an essential
                 role as a SEO practice, for instance, by providing
                 content and engagement. The examined sample was
                 collected by the most visited news websites' rankings
                 of alexa.com for a global scale and for the countries
                 Greece and Cyprus. The findings reveal that the news
                 websites throughout the globe use similar features and
                 ways to support the comments of the users. In the
                 meantime, though, a high number of the news websites
                 did not allow the users to use their social media
                 accounts in order to comment the provided news
                 articles, or provided multiple comment platforms. This
                 trend goes against the SEO practices. It is believed
                 that this finding is associated with the difficulty of
                 the news organizations to regulate and protect
                 themselves by the users' comments that promote, in some
                 case harmful rhetoric and polarization.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Search Engine Optimization.",
}

@Article{Parada:2019:RBE,
  author =       "Ra{\'u}l Parada and Alfonso Palaz{\'o}n and Carlos
                 Monzo and Joan Meli{\`a}-Segu{\'\i}",
  title =        "{RFID} Based Embedded System for Sustainable Food
                 Management in an {IoT} Network Paradigm",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "9",
  pages =        "189",
  day =          "01",
  month =        sep,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11090189",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/9/189",
  abstract =     "A third of the food produced in the world ends up in
                 the rubbish, enough to put an end to world hunger. On
                 the other hand, society is increasingly concerned to
                 bring healthy eating habits. A RFID (radio frequency
                 identification) food management system is designed to
                 palliate the previously described issues in an Internet
                 of Things (IoT) network paradigm. It consists of RFID
                 readers placed on a user's kitchen furniture, which
                 automatically reads food information. There is no need
                 for direct sight between reader and tag, as it occurs
                 through the barcode technology. As a complement, a
                 multi-platform web application is developed, allowing
                 its users to check the date of food expiration and
                 other detailed information. The application notifies
                 the user when a product is about to expire. It also
                 offers recipes that might be prepared with available
                 foods, thus preventing them from being wasted. The
                 recipes are accompanied by their nutritional
                 information, so that the user can exhaustively monitor
                 what he/she eats. This embedded system may provide
                 economic benefits to the manufacturer, since it allows
                 supermarkets to pay for displaying their products
                 advertised through the application. After system
                 deployment, design conclusions are shown, and future
                 improvement points are indicated.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue The Internet of Things for Smart
                 Environments.",
}

@Article{Jamal:2019:DLB,
  author =       "Nasir Jamal and Chen Xianqiao and Hamza Aldabbas",
  title =        "Deep Learning-Based Sentimental Analysis for
                 Large-Scale Imbalanced {Twitter} Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "9",
  pages =        "190",
  day =          "02",
  month =        sep,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11090190",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/9/190",
  abstract =     "Emotions detection in social media is very effective
                 to measure the mood of people about a specific topic,
                 news, or product. It has a wide range of applications,
                 including identifying psychological conditions such as
                 anxiety or depression in users. However, it is a
                 challenging task to distinguish useful emotions'
                 features from a large corpus of text because emotions
                 are subjective, with limited fuzzy boundaries that may
                 be expressed in different terminologies and
                 perceptions. To tackle this issue, this paper presents
                 a hybrid approach of deep learning based on TensorFlow
                 with Keras for emotions detection on a large scale of
                 imbalanced tweets' data. First, preprocessing steps are
                 used to get useful features from raw tweets without
                 noisy data. Second, the entropy weighting method is
                 used to compute the importance of each feature. Third,
                 class balancer is applied to balance each class.
                 Fourth, Principal Component Analysis (PCA) is applied
                 to transform high correlated features into normalized
                 forms. Finally, the TensorFlow based deep learning with
                 Keras algorithm is proposed to predict high-quality
                 features for emotions classification. The proposed
                 methodology is analyzed on a dataset of 1,600,000
                 tweets collected from the website \&lsquo;kaggle'.
                 Comparison is made of the proposed approach with other
                 state of the art techniques on different training
                 ratios. It is proved that the proposed approach
                 outperformed among other techniques.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Social Network and Artificial
                 Intelligence.",
}

@Article{Fantinelli:2019:SNS,
  author =       "Stefania Fantinelli and Michela Cortini",
  title =        "Social Network Services Management and Risk of
                 Doocing. {Comment} on {Kim, S.; Park, H.; Choi, M. J.
                 ``Negative Impact of Social Network Services Based on
                 Stressor--Stress-Outcome: The Role of Experience of
                 Privacy Violations. Future Internet 2019, {\bf 11},
                 137''}",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "9",
  pages =        "191",
  day =          "04",
  month =        sep,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11090191",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  note =         "See \cite{Kim:2019:NIS}.",
  URL =          "https://www.mdpi.com/1999-5903/11/9/191",
  abstract =     "In light of the recent work by Kim and colleagues
                 about Social Network Service (SNS), examining the
                 individual and SNS characteristics as predictors of SNS
                 fatigue, we hypothesize to enlarge their model to the
                 job context. SNS is a relevant issue in occupational
                 life as employers use it to have a deeper knowledge of
                 their employees and as a tool of corporate
                 communication. Employees can use SNS as a social
                 platform and as a way to express discontent. In this
                 latter case, the organization can implement a
                 disciplinary procedure toward employees, known as
                 doocing. The perception of privacy violation is
                 strictly related to the fear and awareness of doocing,
                 which in turn can predict SNS fatigue as well. So, it
                 could be worthwhile to extend Kim and colleagues' model
                 to the workplace with particular attention to the
                 doocing phenomenon.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  keywords =     "doocing: a disciplinary procedure toward employees",
  remark =       "Section Techno-Social Smart Systems.",
}

@Article{Kapadais:2019:FDS,
  author =       "Konstantinos Kapadais and Iraklis Varlamis and
                 Christos Sardianos and Konstantinos Tserpes",
  title =        "A Framework for the Detection of Search and Rescue
                 Patterns Using Shapelet Classification",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "9",
  pages =        "192",
  day =          "04",
  month =        sep,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11090192",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/9/192",
  abstract =     "The problem of unmanned supervision of maritime areas
                 has attracted the interest of researchers for the last
                 few years, mainly thanks to the advances in vessel
                 monitoring that the Automatic Identification System
                 (AIS) has brought. Several frameworks and algorithms
                 have been proposed for the management of vessel
                 trajectory data, which focus on data compression, data
                 clustering, classification and visualization, offering
                 a wide variety of solutions from vessel monitoring to
                 automatic detection of complex events. This work builds
                 on our previous work in the topic of automatic
                 detection of Search and Rescue (SAR) missions, by
                 developing and evaluating a methodology for classifying
                 the trajectories of vessels that possibly participate
                 in such missions. The proposed solution takes advantage
                 of a synthetic trajectory generator and a classifier
                 that combines a genetic algorithm (GENDIS) for the
                 extraction of informative shapelets from training data
                 and a transformation to the shapelets' feature space.
                 Using the generator and several SAR patterns that are
                 formally described in naval operations bibliography, it
                 generates a synthetic dataset that is used to train the
                 classifier. Evaluation on both synthetic and real data
                 has very promising results and helped us to identify
                 vessel SAR maneuvers without putting any effort into
                 manual annotation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Emerging Techniques of AI for Mobility
                 Analysis and Mining.",
}

@Article{Volk:2019:SIA,
  author =       "Florian V{\"o}lk and Konstantinos Liolis and Marius
                 Corici and Joe Cahill and Thomas Schlichter {Robert
                 T.Schwarz } and Eric Troudt and Andreas Knopp",
  title =        "Satellite Integration into {5G}: Accent on First
                 Over-The-Air Tests of an Edge Node Concept with
                 Integrated Satellite Backhaul",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "9",
  pages =        "193",
  day =          "05",
  month =        sep,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11090193",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/9/193",
  abstract =     "The 5G vision embraces a broad range of applications
                 including the connectivity in underserved and remote
                 areas. In particular, for these applications,
                 satellites are going to play a role in future 5G
                 networks to provide capacity on trains, vessels,
                 aircraft, and for base stations around the globe. In
                 this paper, a 5G edge node concept, developed and
                 evaluated with over-the-air tests using satellites in
                 the geostationary orbit, is presented. The article
                 covers a testbed demonstration study in Europe with a
                 large-scale testbed including satellites and the latest
                 standardization for the network architecture. The main
                 goal of this testbed is to evaluate how satellite
                 networks can be best integrated within the convergent
                 5G environment. The over-the-air tests for 5G satellite
                 integration in this article are based on a 3GPP Release
                 15 core network architecture.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Satellite Communications in 5G
                 Networks.",
}

@Article{Zeadally:2019:YBT,
  author =       "Sherali Zeadally and Farhan Siddiqui and Zubair Baig",
  title =        "25 Years of {Bluetooth} Technology",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "9",
  pages =        "194",
  day =          "09",
  month =        sep,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11090194",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/9/194",
  abstract =     "Bluetooth technology started off as a wireless,
                 short-range cable replacement technology but it has
                 undergone significant developments over the last two
                 decades. Bluetooth radios are currently embedded in
                 almost all computing devices including personal
                 computers, smart phones, smart watches, and even
                 micro-controllers. For many of us, Bluetooth is an
                 essential technology that we use every day. We provide
                 an insight into the history of Bluetooth and its
                 significant design developments over the last 25 years.
                 We also discuss related issues (including security) and
                 Bluetooth as a driving technology for the Internet of
                 Things (IoT). Finally, we also present recent research
                 results obtained with Bluetooth technology in various
                 application areas.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 10th Anniversary Feature Papers.",
}

@Article{Mackita:2019:ERM,
  author =       "Masky Mackita and Soo-Young Shin and Tae-Young Choe",
  title =        "{ERMOCTAVE}: a Risk Management Framework for {IT}
                 Systems Which Adopt Cloud Computing",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "9",
  pages =        "195",
  day =          "10",
  month =        sep,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11090195",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/9/195",
  abstract =     "Many companies are adapting cloud computing technology
                 because moving to the cloud has an array of benefits.
                 During decision-making, having processed for adopting
                 cloud computing, the importance of risk management is
                 progressively recognized. However, traditional risk
                 management methods cannot be applied directly to cloud
                 computing when data are transmitted and processed by
                 external providers. When they are directly applied,
                 risk management processes can fail by ignoring the
                 distributed nature of cloud computing and leaving
                 numerous risks unidentified. In order to fix this
                 backdrop, this paper introduces a new risk management
                 method, Enterprise Risk Management for Operationally
                 Critical Threat, Asset, and Vulnerability Evaluation
                 (ERMOCTAVE), which combines Enterprise Risk Management
                 and Operationally Critical Threat, Asset, and
                 Vulnerability Evaluation for mitigating risks that can
                 arise with cloud computing. ERMOCTAVE is composed of
                 two risk management methods by combining each component
                 with another processes for comprehensive perception of
                 risks. In order to explain ERMOCTAVE in detail, a case
                 study scenario is presented where an Internet seller
                 migrates some modules to Microsoft Azure cloud. The
                 functionality comparison with ENISA and Microsoft cloud
                 risk assessment shows that ERMOCTAVE has additional
                 features, such as key objectives and strategies,
                 critical assets, and risk measurement criteria.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Network Virtualization and Edge/Fog
                 Computing.",
}

@Article{Cividino:2019:EDU,
  author =       "Sirio Cividino and Gianluca Egidi and Ilaria Zambon
                 and Andrea Colantoni",
  title =        "Evaluating the Degree of Uncertainty of Research
                 Activities in {Industry 4.0}",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "9",
  pages =        "196",
  day =          "11",
  month =        sep,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11090196",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/9/196",
  abstract =     "Research and development (R\&D) are always oriented
                 towards new discoveries, based on original terms or
                 hypotheses, and their concluding outcomes are often
                 uncertain. The present work focused on the degree of
                 uncertainty for R\&D activities. In fact, uncertainty
                 makes it difficult to quantify the time and resources
                 needed to achieve a final outcome, create a work plan
                 and budget, and finalize the resulting ``innovative''
                 products or services that could be transferred or
                 exchanged in a specific market. The present work
                 attempts to indicate the degree of uncertainty of the
                 research activities developed by a set of firms. The
                 method used aimed to quantify the five criteria defined
                 by the Manual of Frascati. Through the creation of an
                 uncertainty cloud, a cone of uncertainty was defined
                 following an approach based on project management. The
                 evaluation grid was characterized by the decomposition
                 of the different variables divided into quartiles,
                 which allowed for the detection of the evolution of the
                 project and each of its component. The ancillary
                 objective aim was to also observe the development
                 degree of these industries towards a framework of
                 Industry 4.0.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yuan:2019:MRC,
  author =       "Baoxi Yuan and Yang Li and Fan Jiang and Xiaojie Xu
                 and Yingxia Guo and Jianhua Zhao and Deyue Zhang and
                 Jianxin Guo and Xiaoli Shen",
  title =        "{MU R-CNN}: a Two-Dimensional Code Instance
                 Segmentation Network Based on Deep Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "9",
  pages =        "197",
  day =          "13",
  month =        sep,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11090197",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/9/197",
  abstract =     "In the context of Industry 4.0, the most popular way
                 to identify and track objects is to add tags, and
                 currently most companies still use cheap quick response
                 (QR) tags, which can be positioned by computer vision
                 (CV) technology. In CV, instance segmentation (IS) can
                 detect the position of tags while also segmenting each
                 instance. Currently, the mask region-based
                 convolutional neural network (Mask R-CNN) method is
                 used to realize IS, but the completeness of the
                 instance mask cannot be guaranteed. Furthermore, due to
                 the rich texture of QR tags, low-quality images can
                 lower intersection-over-union (IoU) significantly,
                 disabling it from accurately measuring the completeness
                 of the instance mask. In order to optimize the IoU of
                 the instance mask, a QR tag IS method named the mask
                 UNet region-based convolutional neural network (MU
                 R-CNN) is proposed. We utilize the UNet branch to
                 reduce the impact of low image quality on IoU through
                 texture segmentation. The UNet branch does not depend
                 on the features of the Mask R-CNN branch so its
                 training process can be carried out independently. The
                 pre-trained optimal UNet model can ensure that the loss
                 of MU R-CNN is accurate from the beginning of the
                 end-to-end training. Experimental results show that the
                 proposed MU R-CNN is applicable to both high- and
                 low-quality images, and thus more suitable for Industry
                 4.0.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Manufacturing Systems and Internet of
                 Thing.",
}

@Article{Xu:2019:DGR,
  author =       "Haiyan Xu and Yanhui Ding and Jing Sun and Kun Zhao
                 and Yuanjian Chen",
  title =        "Dynamic Group Recommendation Based on the Attention
                 Mechanism",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "9",
  pages =        "198",
  day =          "17",
  month =        sep,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11090198",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/9/198",
  abstract =     "Group recommendation has attracted significant
                 research efforts for its importance in benefiting group
                 members. The purpose of group recommendation is to
                 provide recommendations to group users, such as
                 recommending a movie to several friends. Group
                 recommendation requires that the recommendation should
                 be as satisfactory as possible to each member of the
                 group. Due to the lack of weighting of users in
                 different items, group decision-making cannot be made
                 dynamically. Therefore, in this paper, a dynamic
                 recommendation method based on the attention mechanism
                 is proposed. Firstly, an improved density peak
                 clustering (DPC) algorithm is used to discover the
                 potential group; and then the attention mechanism is
                 adopted to learn the influence weight of each user. The
                 normalized discounted cumulative gain (NDCG) and hit
                 ratio (HR) are adopted to evaluate the validity of the
                 recommendation results. Experimental results on the
                 CAMRa2011 dataset show that our method is effective.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Amadeo:2019:EVA,
  author =       "Marica Amadeo and Claudia Campolo and Antonella
                 Molinaro and Jerome Harri and Christian Esteve
                 Rothenberg and Alexey Vinel",
  title =        "Enhancing the {3GPP V2X} Architecture with
                 Information-Centric Networking",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "9",
  pages =        "199",
  day =          "18",
  month =        sep,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11090199",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/9/199",
  abstract =     "Vehicle-to-everything (V2X) communications allow a
                 vehicle to interact with other vehicles and with
                 communication parties in its vicinity (e.g., road-side
                 units, pedestrian users, etc.) with the primary goal of
                 making the driving and traveling experience safer,
                 smarter and more comfortable. A wide set of
                 V2X-tailored specifications have been identified by the
                 Third Generation Partnership Project (3GPP) with focus
                 on the design of architecture enhancements and a
                 flexible air interface to ensure ultra-low latency,
                 highly reliable and high-throughput connectivity as the
                 ultimate aim. This paper discusses the potential of
                 leveraging Information-Centric Networking (ICN)
                 principles in the 3GPP architecture for V2X
                 communications. We consider Named Data Networking (NDN)
                 as reference ICN architecture and elaborate on the
                 specific design aspects, required changes and
                 enhancements in the 3GPP V2X architecture to enable
                 NDN-based data exchange as an alternative/complementary
                 solution to traditional IP networking, which barely
                 matches the dynamics of vehicular environments. Results
                 are provided to showcase the performance improvements
                 of the NDN-based proposal in disseminating content
                 requests over the cellular network against a
                 traditional networking solution.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 5G-V2X Communications and Networking for
                 Connected and Autonomous Vehicles.",
}

@Article{Jia:2019:IBC,
  author =       "Yun-Fei Jia and Shan Li and Renbiao Wu",
  title =        "Incorporating Background Checks with Sentiment
                 Analysis to Identify Violence Risky {Chinese}
                 Microblogs",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "9",
  pages =        "200",
  day =          "19",
  month =        sep,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11090200",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/9/200",
  abstract =     "Based on Web 2.0 technology, more and more people tend
                 to express their attitude or opinions on the Internet.
                 Radical ideas, rumors, terrorism, or violent contents
                 are also propagated on the Internet, causing several
                 incidents of social panic every year in China. In fact,
                 most of this content comprises joking or emotional
                 catharsis. To detect this with conventional techniques
                 usually incurs a large false alarm rate. To address
                 this problem, this paper introduces a technique that
                 combines sentiment analysis with background checks.
                 State-of-the-art sentiment analysis usually depends on
                 training datasets in a specific topic area.
                 Unfortunately, for some domains, such as violence risk
                 speech detection, there is no definitive training data.
                 In particular, topic-independent sentiment analysis of
                 short Chinese text has been rarely reported in the
                 literature. In this paper, the violence risk of the
                 Chinese microblogs is calculated from multiple
                 perspectives. First, a lexicon-based method is used to
                 retrieve violence-related microblogs, and then a
                 similarity-based method is used to extract sentiment
                 words. Semantic rules and emoticons are employed to
                 obtain the sentiment polarity and sentiment strength of
                 short texts. Second, the activity risk is calculated
                 based on the characteristics of part of speech (PoS)
                 sequence and by semantic rules, and then a threshold is
                 set to capture the key users. Finally, the risk is
                 confirmed by historical speeches and the opinions of
                 the friend-circle of the key users. The experimental
                 results show that the proposed approach outperforms the
                 support vector machine (SVM) method on a
                 topic-independent corpus and can effectively reduce the
                 false alarm rate.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Semantic Web Technologies for Sentiment
                 Analysis.",
}

@Article{Sun:2019:RMO,
  author =       "Wei Sun and Shiwei Wei and Huaping Guo and Hongbing
                 Liu",
  title =        "Role-Mining Optimization with Separation-of-Duty
                 Constraints and Security Detections for
                 Authorizations",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "9",
  pages =        "201",
  day =          "19",
  month =        sep,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11090201",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/9/201",
  abstract =     "Role-based access control (RBAC), which has been
                 regarded as one of the most popular access-control
                 mechanisms, is featured by the separation-of-duty
                 constraints, mutually exclusive constraints, and the
                 least-privileges principle. Role mining, a bottom-up
                 role-engineering technology, is an effective method to
                 migrate from a non-RBAC system to an RBAC system.
                 However, conventional role-mining approaches not only
                 do not consider the separation of duty constraints, but
                 also cannot ensure the security of a constructed RBAC
                 system when the corresponding mined results violate the
                 separation of a duty constraint and/or the
                 least-privileges principle. To solve these problems,
                 this paper proposes a novel method called role-mining
                 optimization with separation-of-duty constraints and
                 security detections for authorizations (RMO\_SODSDA),
                 which mainly includes two aspects. First, we present a
                 role-mining-optimization approach for satisfying the
                 separation of duty constraints, and we constructed
                 different variants of mutually exclusive constraints to
                 correctly implement the given separation of duty
                 constraints based on unconstrained role mining. Second,
                 to ensure the security of the constructed system and
                 evaluate authorization performance, we reduced the
                 authorization-query problem to a maximal-satisfiability
                 problem. The experiments validate the effectiveness and
                 efficiency of the proposed method.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Cybersecurity.",
}

@Article{Rovira:2019:RRC,
  author =       "Crist{\`o}fol Rovira and Llu{\'\i}s Codina and
                 Frederic Guerrero-Sol{\'e} and Carlos Lopezosa",
  title =        "Ranking by Relevance and Citation Counts, a
                 Comparative Study: {Google Scholar}, {Microsoft
                 Academic}, {WoS} and {Scopus}",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "9",
  pages =        "202",
  day =          "19",
  month =        sep,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11090202",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/9/202",
  abstract =     "Search engine optimization (SEO) constitutes the set
                 of methods designed to increase the visibility of, and
                 the number of visits to, a web page by means of its
                 ranking on the search engine results pages. Recently,
                 SEO has also been applied to academic databases and
                 search engines, in a trend that is in constant growth.
                 This new approach, known as academic SEO (ASEO), has
                 generated a field of study with considerable future
                 growth potential due to the impact of open science. The
                 study reported here forms part of this new field of
                 analysis. The ranking of results is a key aspect in any
                 information system since it determines the way in which
                 these results are presented to the user. The aim of
                 this study is to analyze and compare the relevance
                 ranking algorithms employed by various academic
                 platforms to identify the importance of citations
                 received in their algorithms. Specifically, we analyze
                 two search engines and two bibliographic databases:
                 Google Scholar and Microsoft Academic, on the one hand,
                 and Web of Science and Scopus, on the other. A reverse
                 engineering methodology is employed based on the
                 statistical analysis of Spearman's correlation
                 coefficients. The results indicate that the ranking
                 algorithms used by Google Scholar and Microsoft are the
                 two that are most heavily influenced by citations
                 received. Indeed, citation counts are clearly the main
                 SEO factor in these academic search engines. An
                 unexpected finding is that, at certain points in time,
                 Web of Science (WoS) used citations received as a key
                 ranking factor, despite the fact that WoS support
                 documents claim this factor does not intervene.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Search Engine Optimization.",
}

@Article{Uchida:2019:VDT,
  author =       "Noriki Uchida and Goshi Sato and Yoshitaka Shibata",
  title =        "Vehicular Delay-Tolerant Networks with Image
                 Recognition-Based Adaptive Array Antenna for Winter
                 Road Surveillance in Local Areas",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "9",
  pages =        "203",
  day =          "19",
  month =        sep,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11090203",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:07 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/9/203",
  abstract =     "The rapid growth of the ITS (intelligent transport
                 system) development requires us to realize new kinds of
                 applications, such as the winter road surveillance
                 system. However, it is still necessary to consider the
                 network difficulty areas for LTE (long-term evolution)
                 or 3G transmissions when one visits sightseeing spots
                 such as ski resorts or spas in mountain areas.
                 Therefore, this paper proposes a winter road
                 surveillance system in the local area based on
                 vehicular delay-tolerant networks. The adaptive array
                 antenna controlled by image recognition with the Kalman
                 filter algorithm is proposed as well to the system in
                 order to realize higher delivery rates. The
                 implementations of the prototype system are presented
                 in this paper as well, and the effectivity of the radio
                 transmission in the prototype system is realized by
                 vehicular image recognition methods and the
                 asynchronous voltage controls for antenna elements for
                 the rapid directional controls of the radio
                 transmission. The experimental results showed that the
                 radio directional controls by the prototype system for
                 the target vehicle can proceed within one second, and
                 that the simulation with the GIS (geographic
                 information system) map pointed out the delivery rates
                 of the proposed method --- which are better than those
                 of the epidemic DTN (delay-tolerant networking) routing
                 by the nondirectional antenna. The experiments of the
                 proposed methods indicate a higher efficiency of the
                 data transmissions --- even in the mountain area.
                 Furthermore, future research subjects are discussed in
                 this paper.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Advanced Techniques for Internet, P2P
                 and Cloud Computing-selected papers from 3PGCIC-2018.",
}

@Article{Dogan:2019:NRD,
  author =       "Safak Dogan and Nasser Haddad and Erhan Ekmekcioglu
                 and Ahmet M. Kondoz",
  title =        "No-Reference Depth Map Quality Evaluation Model Based
                 on Depth Map Edge Confidence Measurement in Immersive
                 Video Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "10",
  pages =        "204",
  day =          "20",
  month =        sep,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11100204",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/10/204",
  abstract =     "When it comes to evaluating perceptual quality of
                 digital media for overall quality of experience
                 assessment in immersive video applications, typically
                 two main approaches stand out: Subjective and objective
                 quality evaluation. On one hand, subjective quality
                 evaluation offers the best representation of perceived
                 video quality assessed by the real viewers. On the
                 other hand, it consumes a significant amount of time
                 and effort, due to the involvement of real users with
                 lengthy and laborious assessment procedures. Thus, it
                 is essential that an objective quality evaluation model
                 is developed. The speed-up advantage offered by an
                 objective quality evaluation model, which can predict
                 the quality of rendered virtual views based on the
                 depth maps used in the rendering process, allows for
                 faster quality assessments for immersive video
                 applications. This is particularly important given the
                 lack of a suitable reference or ground truth for
                 comparing the available depth maps, especially when
                 live content services are offered in those
                 applications. This paper presents a no-reference depth
                 map quality evaluation model based on a proposed depth
                 map edge confidence measurement technique to assist
                 with accurately estimating the quality of rendered
                 (virtual) views in immersive multi-view video content.
                 The model is applied for depth image-based rendering in
                 multi-view video format, providing comparable
                 evaluation results to those existing in the literature,
                 and often exceeding their performance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Multimedia Quality of Experience (QoE):
                 Current Status and Future Direction.",
}

@Article{Song:2019:TPA,
  author =       "Xin Song and Yue Ni and Xiuwei Han and Lei Qin and Li
                 Dong",
  title =        "Time and Power Allocation for Energy Efficiency
                 Maximization in Wireless-Powered Full-Duplex Relay
                 Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "10",
  pages =        "205",
  day =          "20",
  month =        sep,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11100205",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/10/205",
  abstract =     "In this paper, we propose an optimal time and power
                 allocation scheme in a wireless power supply
                 full-duplex (FD) relay system, where we consider the
                 number of relay antennas in the energy harvesting
                 stage. At the same time, the energy efficiency
                 optimization problem of the system is structured, where
                 optimization issues related to time allocation factors
                 and power allocation are established. For the FD
                 dual-antenna and the FD single-antenna energy
                 harvesting system, energy efficiency function is proven
                 to be a concave function over the time-switch factor,
                 and the optimal time-switching factor is theoretically
                 obtained using the Lambert function. Then, according to
                 the given value range of the optimal time switching
                 factor, the optimal power distribution scheme is
                 obtained by analyzing the derivative function of the
                 system energy efficiency and using the properties of
                 the Lambert function. The time-switching factor and
                 transmission power are optimally selected at the
                 wireless power supply FD relay. Results reveal that the
                 performance of energy efficiency of the dual-antenna
                 energy harvesting at the FD relay outperforms that of
                 the single-antenna. Moreover, our results demonstrate
                 that FD relay systems always substantially boost the
                 energy efficiency compared with half-duplex (HD) relay
                 systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Network Virtualization and Edge/Fog
                 Computing.",
}

@Article{Abdo:2019:ACR,
  author =       "Ahmad Abdo and Sadok Aouini and Bilal Riaz and Naim
                 Ben-Hamida and Claude D'Amours",
  title =        "Adaptive Coherent Receiver Settings for Optimum
                 Channel Spacing in Gridless Optical Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "10",
  pages =        "206",
  day =          "25",
  month =        sep,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11100206",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/10/206",
  abstract =     "In this paper, we propose a novel circuit and system
                 to optimize the spacing between optical channels in
                 gridless (also called flexible-grid or elastic)
                 networking. The method will exploit the
                 beginning-of-life link margin by enabling the channel
                 to operate in super-Nyquist dense wavelength division
                 multiplexing mode. We present the work in the context
                 of software-defined networking and high-speed optical
                 flexible-rate transponders. The clock recovery scheme
                 allows the mitigation of jitter by decoupling the
                 contribution of high-jitter noise sources from the
                 clock recovery loop. The method and associated
                 algorithm are experimentally verified where a spectrum
                 gain of up to 2 GHz in spacing between two channels in
                 the Media Channel (MC) is obtained compared to
                 conventional clocking strategies. We showed that the
                 improvement is equivalent to increasing throughput, in
                 a data-center interconnect scenario, by up to 300
                 giga-bits per second per route.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kavallieratos:2019:TAS,
  author =       "Georgios Kavallieratos and Nabin Chowdhury and
                 Sokratis Katsikas and Vasileios Gkioulos and Stephen
                 Wolthusen",
  title =        "Threat Analysis for Smart Homes",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "10",
  pages =        "207",
  day =          "25",
  month =        sep,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11100207",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/10/207",
  abstract =     "The development and deployment of highly dynamic,
                 cyber+connected operational environments, such as smart
                 homes, smart cities, and smart transportation systems,
                 is increasing. The security analysis of such dynamic
                 environments necessitates the use of dynamic risk
                 assessment methodologies and the modeling of
                 dynamically changing states. In this paper, we focus on
                 the smart home environment, where the deployment of IoT
                 devices increase the attack surface. We examine
                 existing dynamic risk assessment methodologies, and by
                 leveraging a smart home reference architecture we
                 identify the security risks of a smart home's physical
                 and communication viewpoints, taking into consideration
                 also dynamic operational aspects. Further, we develop a
                 smart home network topology generator and a graph-based
                 attack model to study dependencies among dynamically
                 changing states and the propagation of a malware
                 infection.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Reliability of
                 IoT---Selected Papers from SecRIoT 2019.",
}

@Article{Yang:2019:JOP,
  author =       "Jie Yang and Ziyu Pan and Hengfei Xu and Han Hu",
  title =        "Joint Optimization of Pico-Base-Station Density and
                 Transmit Power for an Energy-Efficient Heterogeneous
                 Cellular Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "10",
  pages =        "208",
  day =          "27",
  month =        sep,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11100208",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/10/208",
  abstract =     "Heterogeneous cellular networks (HCNs) have emerged as
                 the primary solution for explosive data traffic.
                 However, an increase in the number of base stations
                 (BSs) inevitably leads to an increase in energy
                 consumption. Energy efficiency (EE) has become a focal
                 point in HCNs. In this paper, we apply tools from
                 stochastic geometry to investigate and optimize the
                 energy efficiency (EE) for a two-tier HCN. The average
                 achievable transmission rate and the total power
                 consumption of all the BSs in a two-tier HCN is
                 derived, and then the EE is formulated. In order to
                 maximize EE, a one-dimensional optimization algorithm
                 is used to optimize picocell BS density and transmit
                 power. Based on this, an alternating optimization
                 method aimed at maximizing EE is proposed to jointly
                 optimize transmit power and density of picocell BSs.
                 Simulation results validate the accuracy of the
                 theoretical analysis and demonstrate that the proposed
                 joint optimization method can obviously improve EE.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Energy-Aware Networking and Green
                 Internet.",
}

@Article{deOliveira:2019:PCN,
  author =       "Fab{\'\i}ola Martins Campos de Oliveira and Edson
                 Borin",
  title =        "Partitioning Convolutional Neural Networks to Maximize
                 the Inference Rate on Constrained {IoT} Devices",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "10",
  pages =        "209",
  day =          "29",
  month =        sep,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11100209",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/10/209",
  abstract =     "Billions of devices will compose the IoT system in the
                 next few years, generating a huge amount of data. We
                 can use fog computing to process these data,
                 considering that there is the possibility of
                 overloading the network towards the cloud. In this
                 context, deep learning can treat these data, but the
                 memory requirements of deep neural networks may prevent
                 them from executing on a single resource-constrained
                 device. Furthermore, their computational requirements
                 may yield an unfeasible execution time. In this work,
                 we propose Deep Neural Networks Partitioning for
                 Constrained IoT Devices, a new algorithm to partition
                 neural networks for efficient distributed execution.
                 Our algorithm can optimize the neural network inference
                 rate or the number of communications among devices.
                 Additionally, our algorithm accounts appropriately for
                 the shared parameters and biases of Convolutional
                 Neural Networks. We investigate the inference rate
                 maximization for the LeNet model in constrained setups.
                 We show that the partitionings offered by popular
                 machine learning frameworks such as TensorFlow or by
                 the general-purpose framework METIS may produce invalid
                 partitionings for very constrained setups. The results
                 show that our algorithm can partition LeNet for all the
                 proposed setups, yielding up to 38\% more inferences
                 per second than METIS.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Innovative Topologies and Algorithms for
                 Neural Networks.",
}

@Article{Donati:2019:ALA,
  author =       "Camillo Donati and Andrea Guazzini and Giorgio Gronchi
                 and Andrea Smorti",
  title =        "About {Linda} Again: How Narratives and Group
                 Reasoning Can Influence Conjunction Fallacy",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "10",
  pages =        "210",
  day =          "08",
  month =        oct,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11100210",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/10/210",
  abstract =     "Conjunction fallacy (together with other systematic
                 reasoning errors) is usually explained in terms of the
                 dual process theory of reasoning: Biases should be
                 ascribed to fast and automatic processes, whereas slow
                 and deliberative processes are responsible of producing
                 answers that are correct with respect of normative
                 criterion. The dual process theory is related to
                 Bruner's distinction between narrative and paradigmatic
                 thought: Both modes of thought can be characterized by
                 the two different processes of reasoning. In this
                 paper, we explore the role of Bruner's mode of thought
                 manipulating also the difference between group vs
                 individual reasoning. We observed that the narrative
                 strategy of response induces more wrong answers.
                 However, narrative-based strategies have higher
                 effectiveness in the case of group reasoning. Our
                 results suggest that narrative reasoning and group
                 reasoning may induce violations of the conjunction rule
                 when acceptable by the verisimilitude of the story.
                 Five models are also presented in order to predict
                 answer correctness and strategy of reasoning using a
                 text analysis software.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Latvakoski:2019:TCH,
  author =       "Juhani Latvakoski and Jouni Heikkinen",
  title =        "A Trustworthy Communication Hub for Cyber-Physical
                 Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "10",
  pages =        "211",
  day =          "08",
  month =        oct,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11100211",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/10/211",
  abstract =     "The motivation for this research arises from the
                 challenges in the trustworthy communications related
                 operation of cyber-physical systems (CPS), especially
                 in the energy and mobility domains. The increasing
                 amount of distributed energy resources (DERs) of
                 prosumers and electric vehicles requires new ways for
                 CPS communications to enable information exchanges for
                 smart operation in peak consumption hours and balancing
                 power levels in the energy grids in order to lower the
                 energy cost. The huge number of mobile appliances and
                 the related service providers do not serve properly the
                 privacy of the owners, owing to the vertical silo type
                 of operating model in industries. As the results of
                 this research, we provide a trustworthy communication
                 hub for CPS (CPS hub) for solving the challenges
                 related to trustworthy communications between physical
                 resources owned by different stakeholders. The CPS hub
                 realizes the communication spaces concept, and enables
                 combined trust and communications processes when
                 dynamic resources owned by different stakeholders are
                 exchanging information. The evaluations showed that the
                 provided CPS hub enable information exchanges between
                 distributed energy resources of different stakeholders,
                 so that they can join the aggregation process for more
                 flexible and efficient resource usage in energy
                 markets. The CPS hub enable interaction between
                 heterogeneous physical devices of multiple stakeholders
                 to exchange information so that, for example,
                 authorities can see the situation in the emergency area
                 and, simultaneously, the policies of the owners can be
                 taken into concern. Despite limited evaluation
                 scenarios, it is shown that consideration of the
                 ownership issues in the trustworthy communication for
                 information exchanges between heterogeneous physical
                 resources (devices) is possible and feasible. Several
                 future research items, such as, for example,
                 scalability; real-time and streams based operation; as
                 well as consideration of the security, privacy, trust,
                 and safety challenges, were detected. However, the
                 evaluations showed that the constructed CPS hub
                 contribute a set of very essential technical enablers
                 for future smart CPS systems and create strong a basis
                 for such future research towards a future smart
                 society.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bocharova:2019:LDI,
  author =       "Irina Bocharova and Boris Kudryashov and Nikita Lyamin
                 and Erik Frick and Maben Rabi and Alexey Vinel",
  title =        "Low Delay Inter-Packet Coding in Vehicular Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "10",
  pages =        "212",
  day =          "11",
  month =        oct,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11100212",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/10/212",
  abstract =     "In Cooperative Intelligent Transportation Systems
                 (C-ITSs), vehicles need to wirelessly connect with
                 Roadside units (RSUs) over limited durations when such
                 point-to-point connections are possible. One example of
                 such communications is the downloading of maps to the
                 C-ITS vehicles. Another example occurs in the testing
                 of C-ITS vehicles, where the tested vehicles upload
                 trajectory records to the roadside units. Because of
                 real-time requirements, and limited bandwidths, data
                 are sent as User Datagram Protocol (UDP) packets. We
                 propose an inter-packet error control coding scheme
                 that improves the recovery of data when some of these
                 packets are lost; we argue that the coding scheme has
                 to be one of convolutional coding. We measure
                 performance through the session averaged probability of
                 successfully delivering groups of packets. We analyze
                 two classes of convolution codes and propose a
                 low-complexity decoding procedure suitable for network
                 applications. We conclude that Reed--Solomon
                 convolutional codes perform better than Wyner--Ash
                 codes at the cost of higher complexity. We show this by
                 simulation on the memoryless binary erasure channel
                 (BEC) and channels with memory, and through simulations
                 of the IEEE 802.11p DSRC/ITS-G5 network at the C-ITS
                 test track AstaZero.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 5G-V2X Communications and Networking for
                 Connected and Autonomous Vehicles.",
}

@Article{Voulgaris:2019:BTI,
  author =       "Spyros Voulgaris and Nikos Fotiou and Vasilios A.
                 Siris and George C. Polyzos and Mikael Jaatinen and
                 Yannis Oikonomidis",
  title =        "Blockchain Technology for Intelligent Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "10",
  pages =        "213",
  day =          "11",
  month =        oct,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11100213",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/10/213",
  abstract =     "In the last few years, we have been witnessing the
                 convergence of the physical with the digital world. The
                 Internet of Things (IoT) is progressing at a fast pace,
                 and IoT devices are becoming pervasive in our physical
                 environments, bringing the vision of Intelligent
                 Environments closer to reality. At the same time, the
                 newly-introduced blockchain technology is offering for
                 the first time ever cryptographically proven trust
                 based on a set of mutually untrusted nodes. Blockchain
                 technology thus has the potential to become a key
                 component of many IoT systems, offering them an
                 unprecedented level of accountability, transparency,
                 and reliability. This paper first lays out the
                 principles on which blockchain systems are operating,
                 along with descriptions of the most noteworthy
                 blockchain implementations. It then presents a number
                 of systems through which blockchains may interact with
                 external systems and third-party data sources. Finally,
                 it provides a survey of the state-of-the-art
                 blockchain-based systems targeting IoT applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Collection Featured Reviews of Future Internet
                 Research.",
}

@Article{Li:2019:BTM,
  author =       "Xiaoyu Li and Changyin Sun and Fan Jiang",
  title =        "Beam Training for Millimeter-Wave Communication Based
                 on Tabu Table Enhanced {Rosenbrock} Algorithm",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "10",
  pages =        "214",
  day =          "12",
  month =        oct,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11100214",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/10/214",
  abstract =     "The codebook-based beamforming for millimeter-wave (mm
                 Wave) communication systems is usually used to
                 compensate the severe attenuation of the mm Wave
                 region. The beam training process based on
                 pre-specified beam codebooks is considered a global
                 optimization problem in 2-D planes formed by the
                 potential beam index. The Rosenbrock algorithm (RA) is
                 adopted to implement optimum beam searching whereas the
                 simulated annealing (SA) algorithm is used to solve the
                 problem of falling into the local optimum, due to the
                 unavailable gradient information of the objective
                 function. However, the RA implements rounding to the
                 integer which leads to the problem of repeated search
                 and beam space discontinuity caused by beam index will
                 impair the powerful local search ability. Thus, in this
                 paper, an enhanced RA based on tabu search and combined
                 with SA algorithm is proposed as an alternative
                 solution for beam search success rate. The proposed
                 algorithm reduces the search times by forbidding the
                 repeat search with tabu table and design of neighbor
                 region. Moreover, to prevent the search failure, the
                 search candidate index is defined to keep the local
                 search ability of the original algorithm and wrap
                 around of beam index is applied to maintain continuity
                 of the search direction. Experimental simulations show
                 that the proposed technique can improve the search
                 efficiency in terms of reduced steps and increase
                 search success rate during the beam training procedure
                 compared to existing techniques.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Recent Advancements in Future Networking
                 Technologies.",
}

@Article{Behan:2019:SNF,
  author =       "Miroslav Behan and Ondrej Krejcar and Thabit Sabbah
                 and Ali Selamat",
  title =        "Sensorial Network Framework Embedded in Ubiquitous
                 Mobile Devices",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "10",
  pages =        "215",
  day =          "14",
  month =        oct,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11100215",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/10/215",
  abstract =     "Today's digital society is interconnected and
                 networked, with modern smart devices ubiquitously built
                 into and embedded within smart environments and other
                 environments, where people (their users) typically
                 live. It is very important to mention that sensorial
                 awareness of an environment depends on one's current
                 location and equipment, as well as the equipment's
                 real-time capabilities. Personal sensorial information
                 is considered to be the key factor for progress in the
                 improvement of the productivity of everyday life and
                 creation of a smart surrounding environment. This paper
                 describes the design, implementation, and testing
                 process of a new sensorial framework based on the
                 current possibilities created by ubiquitous smart
                 mobile devices with sensors, which involves computing
                 power and battery power issues. The two parts of the
                 proposed framework have been designed, implemented, and
                 tested. The client part is represented by a front-end
                 mobile application, and the back-end part is
                 represented by a server-side application. The analysis
                 of the data, captured during the testing phase,
                 involves the analysis of the processing time, battery
                 consumption, and transmitted data amount. This analysis
                 reveals that Transmission Control Protocol (TCP) and
                 user datagram protocol (UDP) protocols have a
                 comparable performance, although TCP is preferable for
                 use in local networks. In comparison to other solutions
                 such as MobiSense or Feel the World framework, the
                 final solution of the proposed and developed sensorial
                 framework has two main capabilities, which are the
                 security support and social networking possibilities.
                 The advantage of the MobiSense platform is the
                 existence of several real-world applications, whereas
                 the proposed sensorial framework needs to be verified
                 in the massive context of many users in real time.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Internet of Things for Smart City
                 Applications.",
}

@Article{Erturk:2019:SLA,
  author =       "Mehmet Ali Ert{\"u}rk and Muhammed Ali Aydin and
                 Muhammet Talha B{\"u}y{\"u}kakkaslar and Hayrettin
                 Evirgen",
  title =        "A Survey on {LoRaWAN} Architecture, Protocol and
                 Technologies",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "10",
  pages =        "216",
  day =          "17",
  month =        oct,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11100216",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/10/216",
  abstract =     "Internet of Things (IoT) expansion led the market to
                 find alternative communication technologies since
                 existing protocols are insufficient in terms of
                 coverage, energy consumption to fit IoT needs. Low
                 Power Wide Area Networks (LPWAN) emerged as an
                 alternative cost-effective communication technology for
                 the IoT market. LoRaWAN is an open LPWAN standard
                 developed by LoRa Alliance and has key features i.e.,
                 low energy consumption, long-range communication,
                 builtin security, GPS-free positioning. In this paper,
                 we will introduce LoRaWAN technology, the state of art
                 studies in the literature and provide open
                 opportunities.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Condoluci:2019:VSL,
  author =       "Massimo Condoluci and Laurent Gallo and Laurent Mussot
                 and Apostolos Kousaridas and Panagiotis Spapis and
                 Maliheh Mahlouji and Toktam Mahmoodi",
  title =        "{5G V2X} System-Level Architecture of {5GCAR}
                 Project",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "10",
  pages =        "217",
  day =          "19",
  month =        oct,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11100217",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/10/217",
  abstract =     "One of the goals of the 5G Communication Automotive
                 Research and innovation (5GCAR) project has been to
                 evaluate and propose system architecture enhancements
                 aiming at supporting the strict requirements of
                 vehicle-to-everything (V2X) use cases. In this paper,
                 we provide an overview of 3GPP 5G system architecture,
                 which is used as a baseline architecture in the
                 project, and we present the main architectural
                 enhancements introduced by 5GCAR. The work of the
                 project focused on the following categories: (i)
                 end-to-end security, also including aspects of privacy;
                 (ii) network orchestration and management; (iii)
                 network procedures; (iv) edge computing enhancements;
                 and (v) multi-connectivity cooperation. The
                 enhancements introduced by 5GCAR to above-listed
                 categories are discussed in this paper, while a more
                 detailed analysis of some selected features is
                 presented.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 5G-V2X Communications and Networking for
                 Connected and Autonomous Vehicles.",
}

@Article{Kolsch:2019:SBP,
  author =       "Johannes K{\"o}lsch and Christopher Heinz and Axel
                 Ratzke and Christoph Grimm",
  title =        "Simulation-Based Performance Validation of Homomorphic
                 Encryption Algorithms in the {Internet of Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "10",
  pages =        "218",
  day =          "22",
  month =        oct,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11100218",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/10/218",
  abstract =     "IoT systems consist of Hardware/Software systems
                 (e.g., sensors) that are embedded in a physical world,
                 networked and that interact with complex software
                 platforms. The validation of such systems is a
                 challenge and currently mostly done by prototypes. This
                 paper presents the virtual environment for simulation,
                 emulation and validation of an IoT platform and its
                 semantic model in real life scenarios. It is based on a
                 decentralized, bottom up approach that offers
                 interoperability of IoT devices and the value-added
                 services they want to use across different domains. The
                 framework is demonstrated by a comprehensive case
                 study. The example consists of the complete IoT ``Smart
                 Energy'' use case with focus on data privacy by
                 homomorphic encryption. The performance of the network
                 is compared while using partially homomorphic
                 encryption, fully homomorphic encryption and no
                 encryption at all.As a major result, we found that our
                 framework is capable of simulating big IoT networks and
                 the overhead introduced by homomorphic encryption is
                 feasible for VICINITY.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Reliability of
                 IoT---Selected Papers from SecRIoT 2019.",
}

@Article{Kiptoo:2019:ATE,
  author =       "Mark Kipngetich Kiptoo and Oludamilare Bode Adewuyi
                 and Mohammed Elsayed Lotfy and Theophilus Amara and
                 Keifa Vamba Konneh and Tomonobu Senjyu",
  title =        "Assessing the Techno-Economic Benefits of Flexible
                 Demand Resources Scheduling for Renewable Energy-Based
                 Smart Microgrid Planning",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "10",
  pages =        "219",
  day =          "22",
  month =        oct,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11100219",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/10/219",
  abstract =     "The need for innovative pathways for future
                 zero-emission and sustainable power development has
                 recently accelerated the uptake of variable renewable
                 energy resources (VREs). However, integration of VREs
                 such as photovoltaic and wind generators requires the
                 right approaches to design and operational planning
                 towards coping with the fluctuating outputs. This paper
                 investigates the technical and economic prospects of
                 scheduling flexible demand resources (FDRs) in optimal
                 configuration planning of VRE-based microgrids. The
                 proposed demand-side management (DSM) strategy
                 considers short-term power generation forecast to
                 efficiently schedule the FDRs ahead of time in order to
                 minimize the gap between generation and load demand.
                 The objective is to determine the optimal size of the
                 battery energy storage, photovoltaic and wind systems
                 at minimum total investment costs. Two simulation
                 scenarios, without and with the consideration of DSM,
                 were investigated. The random forest algorithm
                 implemented on scikit-learn python environment is
                 utilized for short-term power prediction, and mixed
                 integer linear programming (MILP) on MATLAB \&reg; is
                 used for optimum configuration optimization. From the
                 simulation results obtained here, the application of
                 FDR scheduling resulted in a significant cost saving of
                 investment costs. Moreover, the proposed approach
                 demonstrated the effectiveness of the FDR in minimizing
                 the mismatch between the generation and load demand.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Global Trends and Advances Towards a
                 Smarter Grid and Smart Cities.",
}

@Article{Morrow:2019:BTI,
  author =       "Monique J. Morrow and Mehran Zarrebini",
  title =        "Blockchain and the Tokenization of the Individual:
                 Societal Implications",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "10",
  pages =        "220",
  day =          "22",
  month =        oct,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11100220",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/10/220",
  abstract =     "We are living in a world where the very systems upon
                 which trust is based are being challenged by new and
                 exciting paradigm shifts. Centralization whether in the
                 form of governments, financial institutions,
                 enterprises and organizations is simply being
                 challenged because of the lack of trust associated with
                 data governance often experienced in the form of data
                 breaches or simply a monetization of our data without
                 our permission and/or incentives to participate in this
                 emerging decentralization of structures. We see this
                 trust deficit challenging the very institutions we have
                 depended on including but not limited to financial
                 institutions, private enterprises or government bodies.
                 A new ``social contract'' is required as we
                 continuously evolve into more decentralized and
                 self-governing (or semi self-governing) entities. We
                 will see more development in digital sovereignty with
                 the caveat that a governance model will need to be
                 defined. This position paper will present evidence that
                 supports the premise that blockchain and individual
                 tokenization could provide a new social contract.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Blockchain: Current Challenges and
                 Future Prospects/Applications.",
}

@Article{Ding:2019:ILL,
  author =       "Zhengyang Ding and Weiwei Miao and Mingxuan Zhang and
                 Wei Li and Rui Liu and Jun Zou and Chen Xu",
  title =        "Integration of {LTE 230} and {LTE 1800} in Power
                 Wireless Private Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "11",
  pages =        "221",
  day =          "23",
  month =        oct,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11110221",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/11/221",
  abstract =     "Power wireless private networks (PWPNs) have been
                 highly developed in China in recent years. They provide
                 a basis for the energy Internet of Things, which
                 enables the exchange of energy information between
                 devices. Although the power wireless private network is
                 an imitation of the public cellular network, a number
                 of special challenges remain in power private networks.
                 Due to the lack of general standards for PWPNs at the
                 beginning of deployment, there are now two independent
                 PWPN systems in China: long-term evolution (LTE) 230
                 and LTE 1800. Each has its own core and access networks
                 with independent hardware. In this paper, we propose a
                 high-level design of multinetwork integration to allow
                 LTE 230 and LTE 1800 to coexist. For core network
                 integration, we propose a protocol controller to select
                 the active protocol according to the user's mode
                 selection, since both LTE 230 and LTE 1800 evolved from
                 the standard LTE system. For access network
                 integration, we propose a multinetwork integration
                 controller to help the device access the optimal cell.
                 The simulation results show that the integrated system
                 can retain the advantages of these two independent
                 systems in terms of both capacity and coverage.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Privacy in Information and
                 Communication Systems.",
}

@Article{Amadeo:2019:FCI,
  author =       "Marica Amadeo and Giuseppe Ruggeri and Claudia Campolo
                 and Antonella Molinaro and Valeria Loscr{\'\i} and
                 Carlos T. Calafate",
  title =        "Fog Computing in {IoT} Smart Environments via Named
                 Data Networking: a Study on Service Orchestration
                 Mechanisms",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "11",
  pages =        "222",
  day =          "24",
  month =        oct,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11110222",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/11/222",
  abstract =     "By offering low-latency and context-aware services,
                 fog computing will have a peculiar role in the
                 deployment of Internet of Things (IoT) applications for
                 smart environments. Unlike the conventional remote
                 cloud, for which consolidated architectures and
                 deployment options exist, many design and
                 implementation aspects remain open when considering the
                 latest fog computing paradigm. In this paper, we focus
                 on the problems of dynamically discovering the
                 processing and storage resources distributed among fog
                 nodes and, accordingly, orchestrating them for the
                 provisioning of IoT services for smart environments. In
                 particular, we show how these functionalities can be
                 effectively supported by the revolutionary Named Data
                 Networking (NDN) paradigm. Originally conceived to
                 support named content delivery, NDN can be extended to
                 request and provide named computation services, with
                 NDN nodes acting as both content routers and in-network
                 service executors. To substantiate our analysis, we
                 present an NDN fog computing framework with focus on a
                 smart campus scenario, where the execution of IoT
                 services is dynamically orchestrated and performed by
                 NDN nodes in a distributed fashion. A simulation
                 campaign in ndnSIM, the reference network simulator of
                 the NDN research community, is also presented to assess
                 the performance of our proposal against
                 state-of-the-art solutions. Results confirm the
                 superiority of the proposal in terms of service
                 provisioning time, paid at the expenses of a slightly
                 higher amount of traffic exchanged among fog nodes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue The Internet of Things for Smart
                 Environments.",
}

@Article{Takano:2019:OSO,
  author =       "Hirotaka Takano and Ryota Goto and Thin Zar Soe and
                 Nguyen Duc Tuyen and Hiroshi Asano",
  title =        "Operation Scheduling Optimization for Microgrids
                 Considering Coordination of Their Components",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "11",
  pages =        "223",
  day =          "24",
  month =        oct,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11110223",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/11/223",
  abstract =     "Operation scheduling is one of the most practical
                 optimization problems to efficiently manage the
                 electric power supply and demand in microgrids.
                 Although various microgrid-related techniques have been
                 developed, there has been no established solution to
                 the problem until now. This is because the formulated
                 problem becomes a complicated mixed-integer programming
                 problem having multiple optimization variables. The
                 authors present a framework for this problem and its
                 effective solution to obtain an operation schedule of
                 the microgrid components considering their
                 coordination. In the framework, trading electricity
                 with traditional main power grids is included in the
                 optimization target, and uncertainty originating from
                 variable renewable energy sources is considered. In the
                 solution, the formulated problem is reformulated to
                 reduce the dimensions of its solution space, and, as a
                 result, a combined algorithm of binary particle swarm
                 optimization and quadratic programming is applicable.
                 Through numerical simulations and discussions of their
                 results, the validity of the authors' proposal is
                 verified.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Global Trends and Advances Towards a
                 Smarter Grid and Smart Cities.",
}

@Article{Hao:2019:IVD,
  author =       "Ruohong Hao and Bingjia Shao and Rong Ma",
  title =        "Impacts of Video Display on Purchase Intention for
                 Digital and Home Appliance Products-Empirical Study
                 from {China}",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "11",
  pages =        "224",
  day =          "24",
  month =        oct,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11110224",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/11/224",
  abstract =     "Rapid online trading expansion and the bloom of
                 internet technologies has raised the importance of
                 effective product video presentations for online
                 retailers. This article developed a model for the
                 impacts of video presentations on purchase intention
                 for digital and home appliance products. Four group
                 experiments were designed, and empirical tests were
                 performed. This research found that presenting videos
                 on how to use digital and home appliance products
                 increased purchase intention by raising the information
                 gained by customers. Meanwhile, video tutorial
                 information had insignificant effects related to the
                 knowledge and experience of customers.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chen:2019:FBB,
  author =       "Yuling Chen and Jinyi Guo and Changlou Li and Wei
                 Ren",
  title =        "{FaDe}: a Blockchain-Based Fair Data Exchange Scheme
                 for Big Data Sharing",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "11",
  pages =        "225",
  day =          "24",
  month =        oct,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11110225",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/11/225",
  abstract =     "In the big data era, data are envisioned as critical
                 resources with various values, e.g., business
                 intelligence, management efficiency, and financial
                 evaluations. Data sharing is always mandatory for value
                 exchanges and profit promotion. Currently, certain big
                 data markets have been created for facilitating data
                 dissemination and coordinating data transaction, but we
                 have to assume that such centralized management of data
                 sharing must be trustworthy for data privacy and
                 sharing fairness, which very likely imposes limitations
                 such as joining admission, sharing efficiency, and
                 extra costly commissions. To avoid these weaknesses, in
                 this paper, we propose a blockchain-based fair data
                 exchange scheme, called FaDe. FaDe can enable
                 de-centralized data sharing in an autonomous manner,
                 especially guaranteeing trade fairness, sharing
                 efficiency, data privacy, and exchanging automation. A
                 fairness protocol based on bit commitment is proposed.
                 An algorithm based on blockchain script architecture
                 for a smart contract, e.g., by a bitcoin virtual
                 machine, is also proposed and implemented. Extensive
                 analysis justifies that the proposed scheme can
                 guarantee data exchanging without a trusted third party
                 fairly, efficiently, and automatically.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Blockchain: Current Challenges and
                 Future Prospects/Applications.",
}

@Article{Spathoulas:2019:CBB,
  author =       "Georgios Spathoulas and Nikolaos Giachoudis and
                 Georgios-Paraskevas Damiris and Georgios Theodoridis",
  title =        "Collaborative Blockchain-Based Detection of
                 Distributed Denial of Service Attacks Based on
                 {Internet of Things} Botnets",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "11",
  pages =        "226",
  day =          "25",
  month =        oct,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11110226",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/11/226",
  abstract =     "Internet of Things is one of the most significant
                 latest developments in computer science. It is common
                 for modern computing infrastructures to partially
                 consist of numerous low power devices that are
                 characterized by high diversity in both hardware and
                 software. Existing security models, approaches and
                 solutions are not able to sufficiently protect such
                 systems. In this paper we propose the use of
                 lightweight agents installed at multiple internet of
                 things (IoT) installations (e.g., smart-homes), in
                 order to collaboratively detect distributed denial of
                 service (DDoS) attacks conducted by the use of IoT
                 devices botnets. Specifically, agents exchange outbound
                 traffic information in order to identify possible
                 victims of DDoS attacks. This information exchange is
                 governed by a blockchain smart contract, that ensures
                 the integrity of both the procedure and the
                 information. A simulation of the operation of the
                 proposed methodology has been conducted in order to
                 evaluate both its detection efficiency and its
                 resilience against malicious agents that aim to falsify
                 results.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Reliability of
                 IoT---Selected Papers from SecRIoT 2019.",
}

@Article{Kamal:2019:IBS,
  author =       "Miraal Kamal and Manal Atif and Hafsa Mujahid and
                 Tamer Shanableh and A. R. Al-Ali and Ahmad {Al
                 Nabulsi}",
  title =        "{IoT} Based Smart City Bus Stops",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "11",
  pages =        "227",
  day =          "26",
  month =        oct,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11110227",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/11/227",
  abstract =     "The advent of smart sensors, single system-on-chip
                 computing devices, Internet of Things (IoT), and cloud
                 computing is facilitating the design and development of
                 smart devices and services. These include smart meters,
                 smart street lightings, smart gas stations, smart
                 parking lots, and smart bus stops. Countries in the
                 Gulf region have hot and humid weather around 6--7
                 months of the year, which might lead to uncomfortable
                 conditions for public commuters. Transportation
                 authorities have made some major enhancements to
                 existing bus stops by installing air-conditioning
                 units, but without any remote monitoring and control
                 features. This paper proposes a smart IoT-based
                 environmentally - friendly enhanced design for existing
                 bus stop services in the United Arab Emirates. The
                 objective of the proposed design was to optimize energy
                 consumption through estimating bus stop occupancy,
                 remotely monitor air conditioning and lights,
                 automatically report utility breakdowns, and measure
                 the air pollution around the area. In order to
                 accomplish this, bus stops will be equipped with a
                 WiFi-Based standalone microcontroller connected to
                 sensors and actuators. The microcontroller transmits
                 the sensor readings to a real-time database hosted in
                 the cloud and incorporates a mobile app that notifies
                 operators or maintenance personnel in the case of
                 abnormal readings or breakdowns. The mobile app
                 encompasses a map interface enabling operators to
                 remotely monitor the conditions of bus stops such as
                 the temperature, humidity, estimated occupancy, and air
                 pollution levels. In addition to presenting the
                 system's architecture and detailed design, a system
                 prototype is built to test and validate the proposed
                 solution.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Global Trends and Advances Towards a
                 Smarter Grid and Smart Cities.",
}

@Article{Pau:2019:SIN,
  author =       "Giovanni Pau and Alessandro Severino and Antonino
                 Canale",
  title =        "Special Issue {``New} Perspectives in Intelligent
                 Transportation Systems and Mobile Communications
                 towards a Smart Cities Context''",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "11",
  pages =        "228",
  day =          "28",
  month =        oct,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11110228",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/11/228",
  abstract =     "Intelligent transportation solutions and smart
                 information and communication technologies will be the
                 core of future smart cities. For this purpose, these
                 topics have captivated noteworthy interest in the
                 investigation and construction of cleverer
                 communication protocols or the application of
                 artificial intelligence in the connection of in-vehicle
                 devices by wireless networks, and in in-vehicle
                 services for autonomous driving using high-precision
                 positioning and sensing systems. This special issue has
                 focused on the collection of high-quality papers aimed
                 at solving open technical problems and challenges
                 typical of mobile communications for Intelligent
                 Transportation Systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue New Perspectives in Intelligent
                 Transportation Systems and Mobile Communications
                 towards a Smart Cities Context.",
}

@Article{Alharbi:2019:PRC,
  author =       "Adel R. Alharbi and Amer Aljaedi",
  title =        "Predicting Rogue Content and {Arabic} Spammers on
                 {Twitter}",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "11",
  pages =        "229",
  day =          "30",
  month =        oct,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11110229",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/11/229",
  abstract =     "Twitter is one of the most popular online social
                 networks for spreading propaganda and words in the Arab
                 region. Spammers are now creating rogue accounts to
                 distribute adult content through Arabic tweets that
                 Arabic norms and cultures prohibit. Arab governments
                 are facing a huge challenge in the detection of these
                 accounts. Researchers have extensively studied English
                 spam on online social networks, while to date, social
                 network spam in other languages has been completely
                 ignored. In our previous study, we estimated that rogue
                 and spam content accounted for approximately three
                 quarters of all content with Arabic trending hashtags
                 in Saudi Arabia. This alarming rate, supported by
                 autonomous concurrent estimates, highlights the urgent
                 need to develop adaptive spam detection methods. In
                 this work, we collected a pure data set from spam
                 accounts producing Arabic tweets. We applied
                 lightweight feature engineering based on rogue content
                 and user profiles. The 47 generated features were
                 analyzed, and the best features were selected. Our
                 performance results show that the random forest
                 classification algorithm with 16 features performs
                 best, with accuracy rates greater than 90\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Cybersecurity.",
}

@Article{Sun:2019:HLS,
  author =       "Xiaolei Sun and Yu Zhang and Jing Chen",
  title =        "High-Level Smart Decision Making of a Robot Based on
                 Ontology in a Search and Rescue Scenario",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "11",
  pages =        "230",
  day =          "31",
  month =        oct,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11110230",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/11/230",
  abstract =     "The search and rescue (SAR) scenario is complex and
                 uncertain where a robot needs to understand the
                 scenario to make smart decisions. Aiming at the
                 knowledge representation (KR) in the field of SAR, this
                 paper builds an ontology model that enables a robot to
                 understand how to make smart decisions. The ontology is
                 divided into three parts, namely entity ontology,
                 environment ontology, and task ontology. Web Ontology
                 Language (OWL) is adopted to represent these three
                 types of ontology. Through ontology and Semantic Web
                 Rule Language (SWRL) rules, the robot infers the tasks
                 to be performed according to the environment state and
                 at the same time obtains the semantic information of
                 the victims. Then, the paper proposes an ontology-based
                 algorithm for task planning to get a sequence of atomic
                 actions so as to complete the high-level inferred task.
                 In addition, an indoor experiment was designed and
                 built for the SAR scenario using a real robot platform
                 --- TurtleBot3. The correctness and usability of the
                 ontology and the proposed methods are verified by
                 experiments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Active Learning and Reasoning in
                 Autonomous Intelligent Agents.",
}

@Article{Mavropoulos:2019:CAC,
  author =       "Thanassis Mavropoulos and Georgios Meditskos and
                 Spyridon Symeonidis and Eleni Kamateri and Maria Rousi
                 and Dimitris Tzimikas and Lefteris Papageorgiou and
                 Christos Eleftheriadis and George Adamopoulos and
                 Stefanos Vrochidis and Ioannis Kompatsiaris",
  title =        "A Context-Aware Conversational Agent in the
                 Rehabilitation Domain",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "11",
  pages =        "231",
  day =          "01",
  month =        nov,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11110231",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/11/231",
  abstract =     "Conversational agents are reshaping our communication
                 environment and have the potential to inform and
                 persuade in new and effective ways. In this paper, we
                 present the underlying technologies and the theoretical
                 background behind a health-care platform dedicated to
                 supporting medical stuff and individuals with movement
                 disabilities and to providing advanced monitoring
                 functionalities in hospital and home surroundings. The
                 framework implements an intelligent combination of two
                 research areas: (1) sensor- and camera-based monitoring
                 to collect, analyse, and interpret people behaviour and
                 (2) natural machine--human interaction through an
                 apprehensive virtual assistant benefiting ailing
                 patients. In addition, the framework serves as an
                 important assistant to caregivers and clinical experts
                 to obtain information about the patients in an
                 intuitive manner. The proposed approach capitalises on
                 latest breakthroughs in computer vision, sensor
                 management, speech recognition, natural language
                 processing, knowledge representation, dialogue
                 management, semantic reasoning, and speech synthesis,
                 combining medical expertise and patient history.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Intelligent Innovations in Multimedia
                 Data.",
}

@Article{Fotiou:2019:NBS,
  author =       "Nikos Fotiou and George C. Polyzos",
  title =        "Name-Based Security for Information-Centric Networking
                 Architectures",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "11",
  pages =        "232",
  day =          "01",
  month =        nov,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11110232",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/11/232",
  abstract =     "Information-Centric Networking (ICN) is an emerging
                 communication paradigm built around content names.
                 Securing ICN using named-based security is, therefore,
                 a natural choice. For this paper, we designed and
                 evaluated name-based security solutions that satisfy
                 security requirements that are particular to ICN
                 architectures. In order to achieve our goal, we
                 leverage identity-based encryption, identity-based
                 proxy re-encryption, and the emerging paradigm of
                 decentralized identifiers. Our solutions support
                 outsourcing content storage, content integrity
                 protection and content authentication, and provenance
                 verification, as well as access control. We show that
                 our solutions have tolerable storage and computation
                 overhead, thus proving their feasibility.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Information-Centric Networking (ICN).",
}

@Article{Zou:2019:RCC,
  author =       "Yongyan Zou and Yanzhi Zhang and Xin Yi",
  title =        "Research on Cooperative Communication Strategy and
                 Intelligent Agent Directional Source Grouping
                 Algorithms for {Internet of Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "11",
  pages =        "233",
  day =          "01",
  month =        nov,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11110233",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/11/233",
  abstract =     "In order to improve the network layer of the Internet
                 of things to improve transmission reliability, save
                 time delay and energy consumption, the Internet of
                 things cooperative communication and intelligent agent
                 technology were studied in this paper. In cooperative
                 communication, a new cooperative communication
                 algorithm KCN (k-cooperative node), and a reliability
                 prediction model are proposed. The k value is
                 determined by the end-to-end reliability. After k
                 cooperative nodes are selected, other nodes enter
                 dormancy. In aggregate traffic allocation, game theory
                 is used to model the traffic equilibrium and end-to-end
                 delay optimization scenarios. In practice, the optimal
                 duty cycle can be calculated, which makes some
                 cooperative nodes enter an idle state to save energy.
                 Under the premise of guaranteeing end-to-end delay, it
                 is shown that the reliability of the proposed KCN
                 algorithm is better than that of the other existing
                 routing protocols. In the aspect of intelligent agent,
                 a Directional source grouping based multi-Agent
                 Itinerary Planning (D-MIP) is proposed. This algorithm
                 studies the routing problem of multi-agent parallel
                 access to multiple source nodes. A directed source
                 packet multi-agent routing planning algorithm is
                 proposed. The iterative algorithm of each source node
                 is limited to a sector, and the optimal intelligent
                 agent route is obtained by selecting an appropriate
                 angle. Compared with other algorithms, it is shown
                 through a lot of simulated results that energy
                 consumption and time delay has been saved by the
                 proposed D-MIP algorithm.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue AI Technology on Dynamic Distributed
                 IoT, Wireless, and Next-Generation Networking.",
}

@Article{Vgena:2019:TAL,
  author =       "Katerina Vgena and Angeliki Kitsiou and Christos
                 Kalloniatis and Dimitris Kavroudakis and Stefanos
                 Gritzalis",
  title =        "Toward Addressing Location Privacy Issues: New
                 Affiliations with Social and Location Attributes",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "11",
  pages =        "234",
  day =          "01",
  month =        nov,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11110234",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2010.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/11/234",
  abstract =     "Nowadays, location-sharing applications (LSA) within
                 social media enable users to share their location
                 information at different levels of precision. Users on
                 their side are willing to disclose this kind of
                 information in order to represent themselves in a
                 socially acceptable online way. However, they express
                 privacy concerns regarding potential malware
                 location-sharing applications, since users' geolocation
                 information can provide affiliations with their social
                 identity attributes that enable the specification of
                 their behavioral normativity, leading to sensitive
                 information disclosure and privacy leaks. This paper,
                 after a systematic review on previous social and
                 privacy location research, explores the overlapping of
                 these fields in identifying users' social attributes
                 through examining location attributes while online, and
                 proposes a targeted set of location privacy attributes
                 related to users' socio-spatial characteristics within
                 social media.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Collection Featured Reviews of Future Internet
                 Research.",
}

@Article{Ashouri:2019:ECS,
  author =       "Majid Ashouri and Fabian Lorig and Paul Davidsson and
                 Romina Spalazzese",
  title =        "Edge Computing Simulators for {IoT} System Design: An
                 Analysis of Qualities and Metrics",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "11",
  pages =        "235",
  day =          "08",
  month =        nov,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11110235",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/11/235",
  abstract =     "The deployment of Internet of Things (IoT)
                 applications is complex since many quality
                 characteristics should be taken into account, for
                 example, performance, reliability, and security. In
                 this study, we investigate to what extent the current
                 edge computing simulators support the analysis of
                 qualities that are relevant to IoT architects who are
                 designing an IoT system. We first identify the quality
                 characteristics and metrics that can be evaluated
                 through simulation. Then, we study the available
                 simulators in order to assess which of the identified
                 qualities they support. The results show that while
                 several simulation tools for edge computing have been
                 proposed, they focus on a few qualities, such as time
                 behavior and resource utilization. Most of the
                 identified qualities are not considered and we suggest
                 future directions for further investigation to provide
                 appropriate support for IoT architects.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Performance Evaluation in the Era of
                 Cloud and Edge Computing.",
}

@Article{Mtonga:2019:MLB,
  author =       "Kambombo Mtonga and Santhi Kumaran and Chomora Mikeka
                 and Kayalvizhi Jayavel and Jimmy Nsenga",
  title =        "Machine Learning-Based Patient Load Prediction and
                 {IoT} Integrated Intelligent Patient Transfer Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "11",
  pages =        "236",
  day =          "12",
  month =        nov,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11110236",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/11/236",
  abstract =     "A mismatch between staffing ratios and service demand
                 leads to overcrowding of patients in waiting rooms of
                 health centers. Overcrowding consequently leads to
                 excessive patient waiting times, incomplete preventive
                 service delivery and disgruntled medical staff. Worse,
                 due to the limited patient load that a health center
                 can handle, patients may leave the clinic before the
                 medical examination is complete. It is true that as one
                 health center may be struggling with an excessive
                 patient load, another facility in the vicinity may have
                 a low patient turn out. A centralized hospital
                 management system, where hospitals are able to timely
                 exchange patient load information would allow excess
                 patient load from an overcrowded health center to be
                 re-assigned in a timely way to the nearest health
                 centers. In this paper, a machine learning-based
                 patient load prediction model for forecasting future
                 patient loads is proposed. Given current and historical
                 patient load data as inputs, the model outputs future
                 predicted patient loads. Furthermore, we propose
                 re-assigning excess patient loads to nearby facilities
                 that have minimal load as a way to control overcrowding
                 and reduce the number of patients that leave health
                 facilities without receiving medical care as a result
                 of overcrowding. The re-assigning of patients will
                 imply a need for transportation for the patient to move
                 from one facility to another. To avoid putting a
                 further strain on the already fragmented ambulatory
                 services, we assume the existence of a scheduled bus
                 system and propose an Internet of Things (IoT)
                 integrated smart bus system. The developed IoT system
                 can be tagged on buses and can be queried by patients
                 through representation state transfer application
                 program interfaces (APIs) to provide them with the
                 position of the buses through web app or SMS relative
                 to their origin and destination stop. The back end of
                 the proposed system is based on message queue telemetry
                 transport, which is lightweight, data efficient and
                 scalable, unlike the traditionally used hypertext
                 transfer protocol.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhang:2019:FFT,
  author =       "Jingren Zhang and Fang'ai Liu and Weizhi Xu and Hui
                 Yu",
  title =        "Feature Fusion Text Classification Model Combining
                 {CNN} and {BiGRU} with Multi-Attention Mechanism",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "11",
  pages =        "237",
  day =          "12",
  month =        nov,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11110237",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/11/237",
  abstract =     "Convolutional neural networks (CNN) and long
                 short-term memory (LSTM) have gained wide recognition
                 in the field of natural language processing. However,
                 due to the pre- and post-dependence of natural language
                 structure, relying solely on CNN to implement text
                 categorization will ignore the contextual meaning of
                 words and bidirectional long short-term memory
                 (BiLSTM). The feature fusion model is divided into a
                 multiple attention (MATT) CNN model and a
                 bi-directional gated recurrent unit (BiGRU) model. The
                 CNN model inputs the word vector (word vector
                 attention, part of speech attention, position
                 attention) that has been labeled by the attention
                 mechanism into our multi-attention mechanism CNN model.
                 Obtaining the influence intensity of the target keyword
                 on the sentiment polarity of the sentence, and forming
                 the first dimension of the sentiment classification,
                 the BiGRU model replaces the original BiLSTM and
                 extracts the global semantic features of the sentence
                 level to form the second dimension of sentiment
                 classification. Then, using PCA to reduce the dimension
                 of the two-dimensional fusion vector, we finally obtain
                 a classification result combining two dimensions of
                 keywords and sentences. The experimental results show
                 that the proposed MATT-CNN+BiGRU fusion model has
                 5.94\% and 11.01\% higher classification accuracy on
                 the MRD and SemEval2016 datasets, respectively, than
                 the mainstream CNN+BiLSTM method.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue New Perspectives on Semantic Web
                 Technologies and Applications.",
}

@Article{Alreshidi:2019:SAM,
  author =       "Abdulrahman Alreshidi and Aakash Ahmad and Ahmed B.
                 Altamimi and Khalid Sultan and Rashid Mehmood",
  title =        "Software Architecture for Mobile Cloud Computing
                 Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "11",
  pages =        "238",
  day =          "13",
  month =        nov,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11110238",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/11/238",
  abstract =     "Mobile cloud computing (MCC) has recently emerged as a
                 state-of-the-art technology for mobile systems. MCC
                 enables portable and context-aware computation via
                 mobile devices by exploiting virtually unlimited
                 hardware and software resources offered by cloud
                 computing servers. Software architecture helps to
                 abstract the complexities of system design,
                 development, and evolution phases to implement MCC
                 systems effectively and efficiently. This paper aims to
                 identify, taxonomically classify, and systematically
                 map the state of the art on architecting MCC-based
                 software. We have used an evidence-based software
                 engineering (EBSE) approach to conduct a systematic
                 mapping study (SMS) based on 121 qualitatively selected
                 research studies published from 2006 to 2019. The
                 results of the SMS highlight that architectural
                 solutions for MCC systems are mainly focused on
                 supporting (i) software as a service for mobile
                 computing, (ii) off-loading mobile device data to
                 cloud-servers, (iii) internet of things, edge, and fog
                 computing along with various aspects like (iv) security
                 and privacy of mobile device data. The emerging
                 research focuses on the existing and futuristic
                 challenges that relate to MCC-based internet of things
                 (IoTs), mobile-cloud edge systems, along with green and
                 energy-efficient computing. The results of the SMS
                 facilitate knowledge transfer that could benefit
                 researchers and practitioners to understand the role of
                 software architecture to develop the next generation of
                 mobile-cloud systems to support internet-driven
                 computing.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hammood:2019:BBC,
  author =       "Dalal Abdulmohsin Hammood and Hasliza A. Rahim and
                 Ahmed Alkhayyat and R. Badlishah Ahmad",
  title =        "Body-to-Body Cooperation in {Internet} of Medical
                 Things: Toward Energy Efficiency Improvement",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "11",
  pages =        "239",
  day =          "14",
  month =        nov,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11110239",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/11/239",
  abstract =     "Internet of Medical Things (IoMT) technologies provide
                 suitability among physicians and patients because they
                 are useful in numerous medical fields. Wireless body
                 sensor networks (WBSNs) are one of the most crucial
                 technologies from within the IoMT evolution of the
                 healthcare system, whereby each patient is monitored by
                 low-powered and lightweight sensors. When the WBSNs are
                 integrated into IoMT networks, they are quite likely to
                 overlap each other; thus, cooperation between WBSN
                 sensors is possible. In this paper, we consider
                 communication between WBSNs and beyond their
                 communication range. Therefore, we propose inter-WBAN
                 cooperation for the IoMT system, which is also known as
                 inter-WBAN cooperation in an IoMT environment
                 (IWC-IoMT). In this paper, first, a proposed
                 architecture for the IoT health-based system is
                 investigated. Then, a mathematical model of the outage
                 probability for the IWC-IoMT is derived. Finally, the
                 energy efficiency of the IWC-IoT is analysed and
                 inspected. The simulation and numerical results show
                 that the IWC-IoMT (cooperative IoMT) system provides
                 superior performance compared to the non-cooperative
                 system.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wu:2019:MIM,
  author =       "Cong Wu and Jianhui Yang",
  title =        "Multimedia Independent Multipath Routing Algorithms
                 for {Internet of Things} Based on a Node Hidden
                 Communication Model",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "11",
  pages =        "240",
  day =          "15",
  month =        nov,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11110240",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/11/240",
  abstract =     "In order to achieve a multi-path routing algorithm
                 with time delay and energy consumption balance to
                 alleviate the energy holes around a sink, a multimedia
                 independent multipath routing algorithm for internet of
                 things (IoT) based on node hidden communication model
                 is proposed in this paper. On the premise of satisfying
                 the application delay, a multi-source multi-path
                 routing algorithm is proposed by using the idea of
                 software definition and fitting multiple curves to form
                 independent multi-path routing. Through a sink node
                 centralized programming control source node routing,
                 according to the priority of the source node, the
                 dynamic angle of the source node can be allocated,
                 which effectively reduces the energy consumption of the
                 network. In addition, considering that the Internet of
                 Things has more perceptive nodes, limited computing and
                 storage capacity, frequent joining and exiting
                 operations and other factors, a hidden communication
                 model of nodes is designed for the IoT. It is helpful
                 to improve the level of privacy protection in the IoT,
                 and to effectively improve the ability of nodes to
                 resist attacks in the IoT. The experimental results
                 show that the proposed algorithm avoids the
                 interference between paths and various network attacks
                 to the greatest extent, and the energy consumption is
                 relatively low under the requirement of quality of
                 service (QoS) delay.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Multimedia Internet of Things (IoT) in
                 Smart Environment.",
}

@Article{Kapetanidou:2019:RBT,
  author =       "Ioanna Angeliki Kapetanidou and Christos-Alexandros
                 Sarros and Vassilis Tsaoussidis",
  title =        "Reputation-Based Trust Approaches in Named Data
                 Networking",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "11",
  pages =        "241",
  day =          "18",
  month =        nov,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11110241",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/11/241",
  abstract =     "Information-Centric Networking (ICN) has arisen as an
                 architectural solution that responds to the needs of
                 today's overloaded Internet, departing from the
                 traditional host-centric access paradigm. In this paper
                 we focus on Named Data Networking (NDN), the most
                 prominent ICN architecture. In the NDN framework,
                 disseminated content is at the core of the design and
                 providing trusted content is essential. In this paper,
                 we provide an overview of reputation-based trust
                 approaches, present their design trade-offs and argue
                 that these approaches can consolidate NDN trust and
                 security by working complementary to the existing
                 credential-based schemes. Finally, we discuss future
                 research directions and challenges.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Information-Centric Networking (ICN).",
}

@Article{Giannakoulopoulos:2019:AEW,
  author =       "Andreas Giannakoulopoulos and Nikos Konstantinou and
                 Dimitris Koutsompolis and Minas Pergantis and Iraklis
                 Varlamis",
  title =        "Academic Excellence, {Website} Quality, {SEO}
                 Performance: Is there a Correlation?",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "11",
  pages =        "242",
  day =          "18",
  month =        nov,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11110242",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/11/242",
  abstract =     "The academic excellence of universities around the
                 globe has always been a matter of extended study and so
                 has the quality of an institution's presence in the
                 World Wide Web. The purpose of this research is to
                 study the extent to which a university's academic
                 excellence is related to the quality of its web
                 presence. In order to achieve this, a method was
                 devised that quantified the website quality and search
                 engine optimization (SEO) performance of the university
                 websites of the top 100 universities in the Academic
                 Ranking of World Universities (ARWU) Shanghai list. A
                 variety of tools was employed to measure and test each
                 website and produced a Web quality ranking, an SEO
                 performance ranking, as well as a combined overall web
                 ranking for each one. Comparing these rankings with the
                 ARWU shows that academic excellence is moderately
                 correlated with website quality, but SEO performance is
                 not. Moreover, the overall web ranking also shows a
                 moderate correlation with ARWU which seems to be
                 positively influenced by website quality and negatively
                 by SEO performance. Conclusively, the results of the
                 research indicate that universities place particular
                 emphasis on issues concerning website quality, while
                 the utilization of SEO does not appear to be of equal
                 importance, indicating possible room for improvement in
                 this area.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Search Engine Optimization.",
}

@Article{Zhang:2019:RMP,
  author =       "Wenjie Zhang and Pin Wu and Yan Peng and Dongke Liu",
  title =        "Roll Motion Prediction of Unmanned Surface Vehicle
                 Based on Coupled {CNN} and {LSTM}",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "11",
  pages =        "243",
  day =          "18",
  month =        nov,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11110243",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/11/243",
  abstract =     "The prediction of roll motion in unmanned surface
                 vehicles (USVs) is vital for marine safety and the
                 efficiency of USV operations. However, the USV roll
                 motion at sea is a complex time-varying nonlinear and
                 non-stationary dynamic system, which varies with
                 time-varying environmental disturbances as well as
                 various sailing conditions. The conventional methods
                 have the disadvantages of low accuracy, poor
                 robustness, and insufficient practical application
                 ability. The rise of deep learning provides new
                 opportunities for USV motion modeling and prediction.
                 In this paper, a data-driven neural network model is
                 constructed by combining a convolution neural network
                 (CNN) with long short-term memory (LSTM) for USV roll
                 motion prediction. The CNN is used to extract spatially
                 relevant and local time series features of the USV
                 sensor data. The LSTM layer is exploited to reflect the
                 long-term movement process of the USV and predict roll
                 motion for the next moment. The fully connected layer
                 is utilized to decode the LSTM output and calculate the
                 final prediction results. The effectiveness of the
                 proposed model was proved using USV roll motion
                 prediction experiments based on two case studies from
                 ``JingHai-VI'' and ``JingHai-III'' USVS of Shanghai
                 University. Experimental results on a real data set
                 indicated that our proposed model obviously
                 outperformed the state-of-the-art methods.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Big Data and Augmented Intelligence.",
}

@Article{Wang:2019:WSS,
  author =       "Huan Wang and Bin Wu and Yuancheng Yao and Mingwei
                 Qin",
  title =        "Wideband Spectrum Sensing Based on Reconfigurable
                 Filter Bank in Cognitive Radio",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "11",
  pages =        "244",
  day =          "18",
  month =        nov,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11110244",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/11/244",
  abstract =     "In order to ease the conflict between the bandwidth
                 demand of high-rate wireless communication and the
                 shortage of spectrum resources, a wideband spectrum
                 sensing method based on reconfigurable filter bank
                 (RFB) with adjustable resolution is presented. The
                 wideband signals are uniformly divided into
                 multi-narrowband signals by RFB, which is designed by
                 polyphase uniform Discrete Fourier Transform (DFT)
                 modulation, and each sub-band is sensed by energy
                 detection. According to the idle proportion of detected
                 sub-bands, the number of RFB sub-bands is reset in next
                 spectrum-sensing time. By simulating with collected
                 wideband dataset, the influence of filter bank
                 sub-bands number and idle state proportion on the
                 sensing results is analyzed, and then on the basis of
                 the trade-off between spectrum-sensing resolution and
                 computational complexity, the optimal sub-bands number
                 of filter bank is selected, so as to improve the
                 detection performance and save resources.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Song:2019:PAR,
  author =       "Xiangpeng Song and Hongbin Yang and Congcong Zhou",
  title =        "Pedestrian Attribute Recognition with Graph
                 Convolutional Network in Surveillance Scenarios",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "11",
  pages =        "245",
  day =          "19",
  month =        nov,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11110245",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:08 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/11/245",
  abstract =     "Pedestrian attribute recognition is to predict a set
                 of attribute labels of the pedestrian from surveillance
                 scenarios, which is a very challenging task for
                 computer vision due to poor image quality, continual
                 appearance variations, as well as diverse spatial
                 distribution of imbalanced attributes. It is desirable
                 to model the label dependencies between different
                 attributes to improve the recognition performance as
                 each pedestrian normally possesses many attributes. In
                 this paper, we treat pedestrian attribute recognition
                 as multi-label classification and propose a novel model
                 based on the graph convolutional network (GCN). The
                 model is mainly divided into two parts, we first use
                 convolutional neural network (CNN) to extract
                 pedestrian feature, which is a normal operation
                 processing image in deep learning, then we transfer
                 attribute labels to word embedding and construct a
                 correlation matrix between labels to help GCN propagate
                 information between nodes. This paper applies the
                 object classifiers learned by GCN to the image
                 representation extracted by CNN to enable the model to
                 have the ability to be end-to-end trainable.
                 Experiments on pedestrian attribute recognition dataset
                 show that the approach obviously outperforms other
                 existing state-of-the-art methods.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Innovative Topologies and Algorithms for
                 Neural Networks.",
}

@Article{Albahli:2019:DEL,
  author =       "Saleh Albahli",
  title =        "A Deep Ensemble Learning Method for Effort-Aware
                 Just-In-Time Defect Prediction",
  journal =      j-FUTURE-INTERNET,
  volume =       "11",
  number =       "12",
  pages =        "246",
  day =          "20",
  month =        nov,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi11120246",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Nov 21 16:51:09 MST 2019",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/11/12/246",
  abstract =     "Since the introduction of just-in-time effort aware
                 defect prediction, many researchers are focusing on
                 evaluating the different learning methods, which can
                 predict the defect inducing changes in a software
                 product. In order to predict these changes, it is
                 important for a learning model to consider the nature
                 of the dataset, its unbalancing properties and the
                 correlation between different attributes. In this
                 paper, we evaluated the importance of these properties
                 for a specific dataset and proposed a novel methodology
                 for learning the effort aware just-in-time prediction
                 of defect inducing changes. Moreover, we devised an
                 ensemble classifier, which fuses the output of three
                 individual classifiers (Random forest, XGBoost,
                 Multi-layer perceptron) to build an efficient
                 state-of-the-art prediction model. The experimental
                 analysis of the proposed methodology showed significant
                 performance with 77\% accuracy on the sample dataset
                 and 81\% accuracy on different datasets. Furthermore,
                 we proposed a highly competent reinforcement learning
                 technique to avoid false alarms in real time
                 predictions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{FIEO:2020:ARF,
  author =       "{Future Internet Editorial Office}",
  title =        "Acknowledgement to Reviewers of {{\booktitle{Future
                 Internet}}} in 2019",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "1",
  pages =        "18",
  day =          "20",
  month =        jan,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12010018",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:41 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/1/18",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wu:2020:SQI,
  author =       "Zhijun Wu and Rong Li and Panpan Yin and Changliang
                 Li",
  title =        "Steganalysis of Quantization Index Modulation
                 Steganography in {G.723.1} Codec",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "1",
  pages =        "17",
  day =          "19",
  month =        jan,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12010017",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:41 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/1/17",
  abstract =     "Steganalysis is used for preventing the illegal use of
                 steganography to ensure the security of network
                 communication through detecting whether or not secret
                 information is hidden in the carrier. This paper
                 presents an approach to detect the quantization index
                 modulation (QIM) of steganography in G.723.1 based on
                 the analysis of the probability of occurrence of index
                 values before and after steganography and studying the
                 influence of adjacent index values in voice over
                 internet protocol (VoIP). According to the change of
                 index value distribution characteristics, this approach
                 extracts the distribution probability matrix and the
                 transition probability matrix as feature vectors, and
                 uses principal component analysis (PCA) to reduce the
                 dimensionality. Through a large amount of sample
                 training, the support vector machine (SVM) is designed
                 as a classifier to detect the QIM steganography. The
                 speech samples with different embedding rates and
                 different durations were tested to verify their impact
                 on the accuracy of the steganalysis. The experimental
                 results show that the proposed approach improves the
                 accuracy and reliability of the steganalysis.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Cyber Security of the Continuous Digital
                 Environment: Challenges, Solutions and Future
                 Directions.",
}

@Article{Matricciani:2020:GSS,
  author =       "Emilio Matricciani",
  title =        "Geocentric Spherical Surfaces Emulating the
                 Geostationary Orbit at Any Latitude with Zenith Links",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "1",
  pages =        "16",
  day =          "18",
  month =        jan,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12010016",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:41 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/1/16",
  abstract =     "According to altitude, the orbits of satellites
                 constellations can be divided into geostationary Earth
                 orbit (GEO), medium Earth orbit (MEO), and low Earth
                 orbit (LEO) constellations. We propose to use a Walker
                 star constellation with polar orbits, at any altitude,
                 to emulate the geostationary orbit with zenith paths at
                 any latitude. Any transmitter/receiver will be linked
                 to a satellite as if the site were at the equator and
                 the satellite at the local zenith. This constellation
                 design can have most of the advantages of the current
                 GEO, MEO, and LEO constellations, without having most
                 of their drawbacks. Doppler phenomena are largely
                 minimized because the connected satellite is always
                 seen almost at the local zenith. The extra free-space
                 loss, due to the fixed pointing of all antennas, is at
                 most 6 dBs when the satellite enters or leaves the
                 service area. The connections among satellites are easy
                 because the positions in the orbital plane and in
                 adjacent planes are constant, although with variable
                 distances. No steering antennas are required. The
                 tropospheric propagation fading and scintillations are
                 minimized. Our aim is to put forth the theoretical
                 ideas about this design, to which we refer to as the
                 geostationary surface (GeoSurf) constellation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Special Issue on Recent Advances in
                 Information and Communication Technologies.",
}

@Article{Wu:2020:MAR,
  author =       "Zhijun Wu and Yun Zhang and Enzhong Xu",
  title =        "Multi-Authority Revocable Access Control Method Based
                 on {CP-ABE} in {NDN}",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "1",
  pages =        "15",
  day =          "16",
  month =        jan,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12010015",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:41 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/1/15",
  abstract =     "For the future of the Internet, because
                 information-centric network (ICN) have natural
                 advantages in terms of content distribution, mobility,
                 and security, it is regarded as a potential solution,
                 or even the key, to solve many current problems. Named
                 Data Network (NDN) is one of the research projects
                 initiated by the United States for network
                 architecture. NDN is a more popular project than ICN.
                 The information cache in the NDN separates content from
                 content publishers, but content security is threatened
                 because of the lack of security controls. Therefore, a
                 multi-authority revocable access control method based
                 on CP-ABE needs to be proposed. This method constructs
                 a proxy-assisted access control scheme, which can
                 implement effective data access control in NDN
                 networks, and the scheme has high security. Because of
                 the partial decryption on the NDN node, the decryption
                 burden of the consumer client in the solution is
                 reduced, and effective user and attribute revocation is
                 achieved, and forward security and backward security
                 are ensured, and collusion attacks are prevented.
                 Finally, through the other security and performance
                 analysis of the scheme of this paper, it proves that
                 the scheme is safe and efficient.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Named Data Networking Architecture.",
}

@Article{Utsu:2020:TBS,
  author =       "Keisuke Utsu and Mariko Abe and Shuji Nishikawa and
                 Osamu Uchida",
  title =        "{Twitter}-Based Safety Confirmation System for
                 Disaster Situations",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "1",
  pages =        "14",
  day =          "16",
  month =        jan,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12010014",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:41 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/1/14",
  abstract =     "In the aftermath of disastrous events in Japan, safety
                 information and rescue requests, as well as emergency
                 alerts and damage situations, have been shared on
                 Twitter. However, even victims who are familiar with
                 smartphones or similar devices and social media cannot
                 easily share detailed information, such as the
                 coordinates or address of their current location, which
                 are essential components of safety information and
                 rescue requests. Moreover, local governments and rescue
                 experts have difficulty in gathering such tweets from
                 Twitter. In this paper, we propose a novel system to
                 enable the victims to share their safety information,
                 make rescue requests, and enable quick information
                 gathering for decision making by local government staff
                 or rescue experts. The proposed system is a
                 Twitter-based safety confirmation system named [email
                 protected] Using the proposed application, the users
                 can easily submit their safety information and send
                 rescue requests on Twitter. The users who want to
                 confirm the safety information can check it quickly on
                 Twitter or via this system. Furthermore, the registered
                 safety information is displayed on an online map to
                 support rescue and assistance activities by local
                 governments and rescue experts.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Web-Based Communities and Social
                 Media.",
}

@Article{Foubert:2020:LRW,
  author =       "Brandon Foubert and Nathalie Mitton",
  title =        "Long-Range Wireless Radio Technologies: a Survey",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "1",
  pages =        "13",
  day =          "14",
  month =        jan,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12010013",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:41 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/1/13",
  abstract =     "Wireless networks are now a part of the everyday life
                 of many people and are used for many applications.
                 Recently, new technologies that enable low-power and
                 long-range communications have emerged. These
                 technologies, in opposition to more traditional
                 communication technologies rather defined as ``short
                 range'', allow kilometer-wide wireless communications.
                 Long-range technologies are used to form Low-Power
                 Wide-Area Networks (LPWAN). Many LPWAN technologies are
                 available, and they offer different performances,
                 business models etc., answering different applications'
                 needs. This makes it hard to find the right tool for a
                 specific use case. In this article, we present a survey
                 about the long-range technologies available presently
                 as well as the technical characteristics they offer.
                 Then we propose a discussion about the energy
                 consumption of each alternative and which one may be
                 most adapted depending on the use case requirements and
                 expectations, as well as guidelines to choose the best
                 suited technology.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Collection Featured Reviews of Future Internet
                 Research.",
}

@Article{Guo:2020:MWA,
  author =       "You Guo and Hector Marco-Gisbert and Paul Keir",
  title =        "Mitigating Webshell Attacks through Machine Learning
                 Techniques",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "1",
  pages =        "12",
  day =          "14",
  month =        jan,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12010012",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:41 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/1/12",
  abstract =     "A webshell is a command execution environment in the
                 form of web pages. It is often used by attackers as a
                 backdoor tool for web server operations. Accurately
                 detecting webshells is of great significance to web
                 server protection. Most security products detect
                 webshells based on feature-matching methods ---
                 matching input scripts against pre-built malicious code
                 collections. The feature-matching method has a low
                 detection rate for obfuscated webshells. However, with
                 the help of machine learning algorithms, webshells can
                 be detected more efficiently and accurately. In this
                 paper, we propose a new PHP webshell detection model,
                 the NB-Opcode (na\&iuml;ve Bayes and opcode sequence)
                 model, which is a combination of na\&iuml;ve Bayes
                 classifiers and opcode sequences. Through experiments
                 and analysis on a large number of samples, the
                 experimental results show that the proposed method
                 could effectively detect a range of webshells. Compared
                 with the traditional webshell detection methods, this
                 method improves the efficiency and accuracy of webshell
                 detection.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Privacy in Social Networks
                 and Solutions.",
}

@Article{Ausaf:2020:WAC,
  author =       "Asfund Ausaf and Mohammad Zubair Khan and Muhammad
                 Awais Javed and Ali Kashif Bashir",
  title =        "{WLAN} Aware Cognitive Medium Access Control Protocol
                 for {IoT} Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "1",
  pages =        "11",
  day =          "11",
  month =        jan,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12010011",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:41 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/1/11",
  abstract =     "Internet of Things (IoT)-based devices consist of
                 wireless sensor nodes that are battery-powered; thus,
                 energy efficiency is a major issue. IEEE
                 802.15.4-compliant IoT devices operate in the
                 unlicensed Industrial, Scientific, and Medical (ISM)
                 band of 2.4 GHz and are subject to interference caused
                 by high-powered IEEE 802.11-compliant Wireless Local
                 Area Network (WLAN) users. This interference causes
                 frequent packet drop and energy loss for IoT users. In
                 this work, we propose a WLAN Aware Cognitive Medium
                 Access Control (WAC-MAC) protocol for IoT users that
                 uses techniques, such as energy detection based
                 sensing, adaptive wake-up scheduling, and adaptive
                 backoff, to reduce interference with the WSN and
                 improve network lifetime of the IoT users. Results show
                 that the proposed WAC-MAC achieves a higher packet
                 reception rate and reduces the energy consumption of
                 IoT nodes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue The Internet of Things for Smart
                 Environments.",
}

@Article{Paez:2020:ABE,
  author =       "Rafael P{\'a}ez and Manuel P{\'e}rez and Gustavo
                 Ram{\'\i}rez and Juan Montes and Lucas Bouvarel",
  title =        "An Architecture for Biometric Electronic
                 Identification Document System Based on Blockchain",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "1",
  pages =        "10",
  day =          "11",
  month =        jan,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12010010",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:41 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/1/10",
  abstract =     "This paper proposes an architecture for biometric
                 electronic identification document (e-ID) system based
                 on Blockchain for citizens identity verification in
                 transactions corresponding to the notary, registration,
                 tax declaration and payment, basic health services and
                 registration of economic activities, among others. To
                 validate the user authentication, a biometric e-ID
                 system is used to avoid spoofing and related attacks.
                 Also, to validate the document a digital certificate is
                 used with the corresponding public and private key for
                 each citizen by using a user's PIN. The proposed
                 transaction validation process was implemented on a
                 Blockchain system in order to record and verify the
                 transactions made by all citizens registered in the
                 electoral census, which guarantees security, integrity,
                 scalability, traceability, and no-ambiguity.
                 Additionally, a Blockchain network architecture is
                 presented in a distributed and decentralized way
                 including all the nodes of the network, database and
                 government entities such as national register and
                 notary offices. The results of the application of a new
                 consensus algorithm to our Blockchain network are also
                 presented showing mining time, memory and CPU usage
                 when the number of transactions scales up.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Smart Cities, Innovation, and
                 Multi-Dimensionality.",
}

@Article{Wang:2020:SBD,
  author =       "Jiajia Wang and Guangming Li",
  title =        "Study on Bridge Displacement Monitoring Algorithms
                 Based on Multi-Targets Tracking",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "1",
  pages =        "9",
  day =          "08",
  month =        jan,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12010009",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:41 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/1/9",
  abstract =     "Bridge displacement measurement is an important area
                 of bridge health monitoring, which can directly reflect
                 whether the deformation of bridge structure exceeds its
                 safety permission. Target tracking technology and
                 Digital Image Correlation (DIC) are two fast-developing
                 and well-known methods for non-contact bridge
                 displacement monitoring in Digital Image Processing
                 (DIP) methods. The former's cost of erecting detection
                 equipment is too large for bridges with a large span
                 that need to locate more multi-targets because of its
                 tracking only one target on a camera while the latter
                 is not suitable for remote detection because it
                 requires very high detection conditions. After
                 investigating the evolution of bridge displacement
                 monitoring, this paper proposes a bridge displacement
                 monitoring algorithm based on multi-target tracking.
                 The algorithm takes full account of practical
                 application and realizes accuracy, robustness,
                 real-time, low-cost, simplicity, and self-adaptability,
                 which sufficiently adapts the bridge displacement
                 monitoring in theory.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2020:NRA,
  author =       "Jingpu Wang and Xin Song and Yatao Ma",
  title =        "A Novel Resource Allocation Scheme in {NOMA}-Based
                 Cellular Network with {D2D} Communications",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "1",
  pages =        "8",
  day =          "06",
  month =        jan,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12010008",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:41 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/1/8",
  abstract =     "Non-orthogonal multiple access (NOMA) has become a
                 promising technology for 5G. With the support of
                 effective resource allocation algorithms, it can
                 improve the spectrum resource utilization and system
                 throughput. In this article, a new resource allocation
                 algorithm in the NOMA-enhanced cellular network with
                 device-to-device (D2D) communications is proposed, in
                 which we use two new searching methods and an optimal
                 link selection scheme to maximize the system throughput
                 and limit the interferences of the NOMA-based cellular
                 network. In the proposed joint user scheduling,
                 tree-based search power allocation and link selection
                 algorithm, we simplify the solving process of previous
                 methods and set up the optimization function, which
                 does not need to be derivable. With successive
                 interference cancellation (SIC) technology, we give
                 conditions for the D2D devices accessing into the
                 network. We also propose a suboptimal scheme to
                 schedule cellular users and D2D devices into multiple
                 subchannels, which reduces the complexity of the
                 exhaustive search method. Through consistent tree-based
                 searching for the power allocation coefficients, we can
                 get the maximum arithmetic average of the system sum
                 rate. Meanwhile, for the existence of the part of
                 interferences from larger power users which can be
                 canceled by the SIC in NOMA systems, the search options
                 are decreased for increasing the search rate of the
                 power allocation algorithm. Moreover, we propose a
                 distance-aware link selection scheme to guarantee the
                 quality of communications. In summary, the proposed
                 algorithm can improve the system throughput, has a low
                 complexity cost and potentially increases spectral
                 utilization. Numerical results demonstrate that the
                 proposed algorithm achieves a higher data transmission
                 rate than some of the traditional methods and we also
                 investigate the convergence and the computational
                 complexity cost of the joint algorithm.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Papavassiliou:2020:SDN,
  author =       "Symeon Papavassiliou",
  title =        "Software Defined Networking ({SDN}) and Network
                 Function Virtualization ({NFV})",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "1",
  pages =        "7",
  day =          "02",
  month =        jan,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12010007",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:41 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/1/7",
  abstract =     "The role of Software Defined Networking (SDN) and
                 Network Function Virtualization (NFV) have been
                 instrumental in realizing the transition and vision
                 ``from black boxes to a white box towards facilitating
                 5G network architectures''. Though significant research
                 results and several deployments have occurred and
                 realized over the last few years focusing on the NFV
                 and SDN technologies, several issues --- both of
                 theoretical and practical importance --- remain still
                 open. Accordingly, the papers of this special issue are
                 significant contributions samples within the general
                 ecosystem highlighted above, ranging from SDN and NFV
                 architectures and implementations, to SDN-NFV
                 integration and orchestration approaches, while
                 considering issues associated with optimization,
                 network management and security aspects. In particular,
                 a total of nine excellent articles (one review and
                 eight original research articles) have been accepted,
                 following a rigorous review process, and addressing
                 many of the aforementioned challenges and beyond.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Software Defined Networking (SDN) and
                 Network Function Virtualization (NFV).",
}

@Article{Veglis:2020:SEO,
  author =       "Andreas Veglis and Dimitrios Giomelakis",
  title =        "Search Engine Optimization",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "1",
  pages =        "6",
  day =          "31",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12010006",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:41 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/1/6",
  abstract =     "The role of Software Defined Networking (SDN) and
                 Network Function Virtualization (NFV) have been
                 instrumental in realizing the transition and vision
                 ``from black boxes to a white box towards facilitating
                 5G network architectures''. Though significant research
                 results and several deployments have occurred and
                 realized over the last few years focusing on the NFV
                 and SDN technologies, several issues --- both of
                 theoretical and practical importance --- remain still
                 open. Accordingly, the papers of this special issue are
                 significant contributions samples within the general
                 ecosystem highlighted above, ranging from SDN and NFV
                 architectures and implementations, to SDN-NFV
                 integration and orchestration approaches, while
                 considering issues associated with optimization,
                 network management and security aspects. In particular,
                 a total of nine excellent articles (one review and
                 eight original research articles) have been accepted,
                 following a rigorous review process, and addressing
                 many of the aforementioned challenges and beyond.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Search Engine Optimization.",
}

@Article{Kousaridas:2020:CBO,
  author =       "Apostolos Kousaridas and Andreas Schimpe and Sebastian
                 Euler and Xavier Vilajosana and Mikael Fallgren and
                 Giada Landi and Francesca Moscatelli and Sokratis
                 Barmpounakis and Francisco V{\'a}zquez-Gallego and
                 Roshan Sedar and Rodrigo Silva and Laurent Dizambourg
                 and Stefan Wendt and Maciej Muehleisen and Kurt Eckert
                 and J{\'e}r{\^o}me H{\"a}rri and Jesus Alonso-Zarate",
  title =        "{5G} Cross-Border Operation for Connected and
                 Automated Mobility: Challenges and Solutions",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "1",
  pages =        "5",
  day =          "24",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12010005",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:41 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/1/5",
  abstract =     "The vision of cooperative, connected and automated
                 mobility (CCAM) across Europe can only be realized when
                 harmonized solutions that support cross-border traffic
                 exist. The possibility of providing CCAM services along
                 different countries when vehicles drive across various
                 national borders has a huge innovative business
                 potential. However, the seamless provision of
                 connectivity and the uninterrupted delivery of services
                 along borders also poses interesting technical
                 challenges. The situation is particularly innovative
                 given the multi-country, multi-operator,
                 multi-telco-vendor, and multi-car-manufacturer scenario
                 of any cross-border layout. This paper introduces the
                 challenges associated to a cross-border deployment of
                 communication technologies through the analysis of
                 three use cases: tele-operated driving, high-definition
                 map generation and distribution for autonomous
                 vehicles, and anticipated cooperative collision
                 avoidance. Furthermore, a set of 5G solutions have been
                 identified to ensure that CCAM services can be
                 supported efficiently in cross-border scenarios. Faster
                 handover of a data connection from one operator to
                 another, generalized inter-mobile edge computing (MEC)
                 coordination, and quality of service (QoS) prediction
                 are some of the solutions that have been introduced to
                 reduce the uncertainties of a real 5G cross-border
                 deployment.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 5G-V2X Communications and Networking for
                 Connected and Autonomous Vehicles.",
}

@Article{Yankson:2020:TET,
  author =       "Samuel Yankson and Mahdi Ghamkhari",
  title =        "Transactive Energy to Thwart Load Altering Attacks on
                 Power Distribution Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "1",
  pages =        "4",
  day =          "24",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12010004",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:41 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/1/4",
  abstract =     "The automatic generation control mechanism in power
                 generators comes into operation whenever an over-supply
                 or under-supply of energy occurs in the power grid. It
                 has been shown that the automatic generation control
                 mechanism is highly vulnerable to load altering
                 attacks. In this type of attack, the power consumption
                 of multiple electric loads in power distribution
                 systems is remotely altered by cyber attackers in such
                 a way that the automatic generation control mechanism
                 is disrupted and is hindered from performing its
                 pivotal role. The existing literature on load altering
                 attacks has studied implementation, detection, and
                 location identification of these attacks. However, no
                 prior work has ever studied design of an
                 attack-thwarting system that can counter load altering
                 attacks, once they are detected in the power grid. This
                 paper addresses the above shortcoming by proposing an
                 attack-thwarting system for countering load altering
                 attacks. The proposed system is based on provoking
                 real-time adjustment in power consumption of the
                 flexible loads in response to the frequency
                 disturbances caused by the load altering attacks. To
                 make the adjustments in-proportion to the frequency
                 disturbances, the proposed attack-thwarting system uses
                 a transactive energy framework to establish a
                 coordination between the flexible loads and the power
                 grid operator.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Global Trends and Advances Towards a
                 Smarter Grid and Smart Cities.",
}

@Article{Lei:2020:DBC,
  author =       "Jianjun Lei and Ying Wang and Hong Yun",
  title =        "Decoupling-Based Channel Access Mechanism for
                 Improving Throughput and Fairness in Dense Multi-Rate
                 {WLANs}",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "1",
  pages =        "3",
  day =          "23",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12010003",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:41 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/1/3",
  abstract =     "Legacy IEEE 802.11 Medium Access Control (MAC) adopts
                 the Distributed Coordination Function (DCF) mechanism,
                 which provides the same access opportunity for all
                 contenders. However, in dense multi-rate Wireless Local
                 Area Networks (WLANs), the pure distributed control
                 mechanism will cause high collision rate and
                 performance anomaly, which results in low network
                 utilization and wasting valuable channel resources. In
                 this paper, we present a decoupling MAC mechanism
                 (DMAC) based on the idea of contention/reservation to
                 reduce collision and realize collision free data
                 transmission. In proposed mechanism, the channel access
                 time is partitioned into channel contention process and
                 data transmission process. The proposed algorithm makes
                 full use of the distributed random channel access
                 mechanism and performs a centralized collision-free
                 data transmission. Wherein, we also design an adaptive
                 algorithm to adjust the length of the contention period
                 to improve the channel utilization. Furthermore, we
                 further propose two airtime fairness algorithms
                 Improve-DMAC1 (I-DMAC1) and Improve-DMAC2 (I-DMAC2) for
                 delay sensitive network and high throughput network
                 scenarios, respectively, to solve the performance
                 anomaly in multi-rate WLANs, based on DMAC. We verify
                 the effectiveness of these decoupling algorithms
                 through extensive simulations. Moreover, the simulation
                 results show that the proposed algorithms achieve
                 better performance than the 802.11 standard and other
                 protocols.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Internet of Things.",
}

@Article{An:2020:ADP,
  author =       "Wen An and Jun Jie Ma and Hong Yang Zhou and Hong Shan
                 Chen and Xu Jun and Xu Jian",
  title =        "An Adaptive Differential Protection and Fast
                 Auto-Closing System for {10 kV} Distribution Networks
                 Based on {4G LTE} Wireless Communication",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "1",
  pages =        "2",
  day =          "20",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12010002",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:41 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/1/2",
  abstract =     "With the development of wireless communication
                 technology and computer technology, more and more smart
                 technologies have been applied in electricity
                 distribution networks. This paper presents an adaptive
                 current differential protection and fast auto-closing
                 system for application in 10 kV distribution networks
                 in China Southern Power Grid. The current differential
                 protection can adaptively change its settings according
                 to the topology change of the primary distribution
                 networks, thus the system effectively reduces the
                 operation and maintenance cost of the power
                 distribution network. In order to restore the power
                 supply for the healthy part of the 10 kV networks
                 quickly after a power system fault is cleared, the
                 protection and control system provides wide area
                 control function for automatic fault isolation and
                 automatic switching. The traditional overcurrent
                 protection and control system have no fault location
                 function, it may take several minutes or even hours to
                 manually locate a fault and then restore the power
                 supply. Compared with the protection and control system
                 of the traditional 10 kV distribution networks, the
                 system developed can locate and isolate faults within
                 900 ms (assuming that the operating time of the load
                 switch is 700 ms), and can quickly restore power supply
                 in less than one second after a power system fault is
                 cleared.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Global Trends and Advances Towards a
                 Smarter Grid and Smart Cities.",
}

@Article{Yang:2020:CEE,
  author =       "Jie Yang and Ziyu Pan and Lihong Guo",
  title =        "Coverage and Energy Efficiency Analysis for Two-Tier
                 Heterogeneous Cellular Networks Based on {Mat{\'e}rn}
                 Hard-Core Process",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "1",
  pages =        "1",
  day =          "19",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12010001",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:41 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/1/1",
  abstract =     "Due to the dense deployment of base stations (BSs) in
                 heterogeneous cellular networks (HCNs), the energy
                 efficiency (EE) of HCN has attracted the attention of
                 academia and industry. Considering its mathematical
                 tractability, the Poisson point process (PPP) has been
                 employed to model HCNs and analyze their performance
                 widely. The PPP falls short in modeling the effect of
                 interference management techniques, which typically
                 introduces some form of spatial mutual exclusion among
                 BSs. In PPP, all the nodes are independent from each
                 other. As such, PPP may not be suitable to model
                 networks with interference management techniques, where
                 there exists repulsion among the nodes. Considering
                 this, we adopt the Mat{\'e}rn hard-core process (MHCP)
                 instead of PPP, in which no two nodes can be closer
                 than a repulsion radius from one another. In this
                 paper, we study the coverage performance and EE of a
                 two-tier HCN modelled by Mat{\'e}rn hard-core process
                 (MHCP); we abbreviate this kind of two-tier HCN as
                 MHCP-MHCP. We first derive the approximate expression
                 of coverage probability of MHCP-MHCP by extending the
                 approximate signal to interference ratio analysis based
                 on the PPP (ASAPPP) method to multi-tier HCN. The
                 concrete SIR gain of the MHCP model relative to the PPP
                 model is derived through simulation and data fitting.
                 On the basis of coverage analysis, we derive and
                 formulate the EE of MHCP-MHCP network. Simulation
                 results verify the correctness of our theoretical
                 analysis and show the performance difference between
                 the MHCP-MHCP and PPP modelled network.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kapsoulis:2020:KYC,
  author =       "Nikolaos Kapsoulis and Alexandros Psychas and Georgios
                 Palaiokrassas and Achilleas Marinakis and Antonios
                 Litke and Theodora Varvarigou",
  title =        "Know Your Customer ({KYC}) Implementation with Smart
                 Contracts on a Privacy-Oriented Decentralized
                 Architecture",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "2",
  pages =        "41",
  day =          "24",
  month =        feb,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12020041",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:42 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/2/41",
  abstract =     "Enterprise blockchain solutions attempt to solve the
                 crucial matter of user privacy, albeit that blockchain
                 was initially directed towards full transparency. In
                 the context of Know Your Customer (KYC)
                 standardization, a decentralized schema that enables
                 user privacy protection on enterprise blockchains is
                 proposed with two types of developed smart contracts.
                 Through the public KYC smart contract, a user registers
                 and uploads their KYC information to the exploited IPFS
                 storage, actions interpreted in blockchain transactions
                 on the permissioned blockchain of Alastria Network.
                 Furthermore, through the public KYC smart contract, an
                 admin user approves or rejects the validity and
                 expiration date of the initial user's KYC documents.
                 Inside the private KYC smart contract, CRUD (Create,
                 read, update and delete) operations for the KYC file
                 repository occur. The presented system introduces
                 effectiveness and time efficiency of operations through
                 its schema simplicity and smart integration of the
                 different technology modules and components. This
                 developed scheme focuses on blockchain technology as
                 the most important and critical part of the
                 architecture and tends to accomplish an optimal schema
                 clarity.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Social Web, New Media, Algorithms and
                 Power.",
}

@Article{Talamo:2020:BBP,
  author =       "Maurizio Talamo and Franco Arcieri and Andrea Dimitri
                 and Christian H. Schunck",
  title =        "A Blockchain based {PKI} Validation System based on
                 Rare Events Management",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "2",
  pages =        "40",
  day =          "14",
  month =        feb,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12020040",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:42 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/2/40",
  abstract =     "Public key infrastructures (PKIs) are the cornerstone
                 for the security of the communication layer of online
                 services relying on certificate-based authentication,
                 such as e-commerce, e-government, online banking, cloud
                 services, and many others. A PKI is an infrastructure
                 based on a hierarchical model, but the use of PKIs in
                 non-hierarchical contexts has exposed them to many
                 types of attacks. Here, we discuss weaknesses exploited
                 in past attacks and we propose a solution based on an
                 original consensus algorithm developed for use on
                 blockchain technology. In this implementation we retain
                 the full functionality around X.509 certificates, i.e.,
                 for the triad (server name, server address, X.509
                 server certificate), and demonstrate a mechanism for
                 obtaining fast consensus. The main properties of the
                 solution are that a consensus may be reached even when
                 not all members of the involved PKI participate in a
                 transaction, and that no advanced trust agreement among
                 PKIs is needed. The proposed solution is able to detect
                 PKI attacks and can distinguish errors from attacks,
                 allowing precise management of anomalies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Blockchain: Current Challenges and
                 Future Prospects/Applications.",
}

@Article{Su:2020:HGR,
  author =       "Zichun Su and Jialin Jiang",
  title =        "Hierarchical Gated Recurrent Unit with Semantic
                 Attention for Event Prediction",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "2",
  pages =        "39",
  day =          "14",
  month =        feb,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12020039",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:42 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/2/39",
  abstract =     "Event prediction plays an important role in financial
                 risk assessment and disaster warning, which can help
                 government decision-making and economic investment.
                 Previous works are mainly based on time series for
                 event prediction such as statistical language model and
                 recurrent neural network, while ignoring the impact of
                 prior knowledge on event prediction. This makes the
                 direction of event prediction often biased or wrong. In
                 this paper, we propose a hierarchical event prediction
                 model based on time series and prior knowledge. To
                 ensure the accuracy of the event prediction, the model
                 obtains the time-based event information and prior
                 knowledge of events by Gated Recurrent Unit and
                 Associated Link Network respectively. The semantic
                 selective attention mechanism is used to fuse the
                 time-based event information and prior knowledge, and
                 finally generate predicted events. Experimental results
                 on Chinese News datasets demonstrate that our model
                 significantly outperforms the state-of-the-art methods,
                 and increases the accuracy by 2.8\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Big Data and Augmented Intelligence.",
}

@Article{Restrepo:2020:CTT,
  author =       "Sandra Restrepo and Dubis Rinc{\'o}n and Edwin
                 Sepulveda",
  title =        "Cognitive Training for the Treatment of Addictions
                 Mediated by Information and Communication Technologies
                 ({ICT})",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "2",
  pages =        "38",
  day =          "14",
  month =        feb,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12020038",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:42 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/2/38",
  abstract =     "This work constitutes a narrative review of the state
                 of knowledge and advances in the intervention and
                 treatment of addictions through the use of information
                 and communication technologies, considering the growing
                 demand for virtuality-mediated strategies that
                 facilitate the approach of problems of public health
                 such as addictions, which increase considerably year
                 after year. To this end, the reader will be provided
                 with a current overview of the drug use trend;
                 subsequently, a conceptualization of the concept of
                 addiction and its understanding from a neurobiological
                 perspective and, finally, the progress in terms of
                 intervention processes and therapeutic approach will be
                 presented; which will imply an approach to the concept
                 of e-health and rehabilitation mediated by information
                 and communication technologies (ICT).",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Internet of Healthcare Things (IoHT):
                 Methods, Advances, and Applications.",
}

@Article{Malik:2020:GTA,
  author =       "Om P. Malik",
  title =        "Global Trends and Advances Towards a Smarter Grid and
                 Smart Cities",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "2",
  pages =        "37",
  day =          "14",
  month =        feb,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12020037",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:42 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/2/37",
  abstract =     "Taking advantage of new developing technologies, power
                 systems are being developed into smarter grids with the
                 vision of becoming the next-generation electric grid
                 for smart cities. Some of the emerging issues and
                 challenges associated with the development of
                 technologies for smarter grids and smart cities are
                 highlighted in this special issue of the Future
                 Internet journal.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Global Trends and Advances Towards a
                 Smarter Grid and Smart Cities.",
}

@Article{Zhou:2020:LSM,
  author =       "Yi Zhou and Fenglei Yang",
  title =        "Latent Structure Matching for Knowledge Transfer in
                 Reinforcement Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "2",
  pages =        "36",
  day =          "13",
  month =        feb,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12020036",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:42 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/2/36",
  abstract =     "Reinforcement learning algorithms usually require a
                 large number of empirical samples and give rise to a
                 slow convergence in practical applications. One
                 solution is to introduce transfer learning: Knowledge
                 from well-learned source tasks can be reused to reduce
                 sample request and accelerate the learning of target
                 tasks. However, if an unmatched source task is
                 selected, it will slow down or even disrupt the
                 learning procedure. Therefore, it is very important for
                 knowledge transfer to select appropriate source tasks
                 that have a high degree of matching with target tasks.
                 In this paper, a novel task matching algorithm is
                 proposed to derive the latent structures of value
                 functions of tasks, and align the structures for
                 similarity estimation. Through the latent structure
                 matching, the highly-matched source tasks are selected
                 effectively, from which knowledge is then transferred
                 to give action advice, and improve exploration
                 strategies of the target tasks. Experiments are
                 conducted on the simulated navigation environment and
                 the mountain car environment. The results illustrate
                 the significant performance gain of the improved
                 exploration strategy, compared with traditional $
                 \epsilon $-greedy exploration strategy. A theoretical
                 proof is also given to verify the improvement of the
                 exploration strategy based on latent structure
                 matching.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fotiou:2020:ICN,
  author =       "Nikos Fotiou",
  title =        "Information-Centric Networking ({ICN})",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "2",
  pages =        "35",
  day =          "13",
  month =        feb,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12020035",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:42 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/2/35",
  abstract =     "Information-Centric Networking (ICN) is novel paradigm
                 considered for the future Internet, as well as for
                 emerging architectures, such as the Internet of Things.
                 Despite the significant research efforts that take
                 place all around the world there are still many
                 challenges and open issues related to the applicability
                 of ICN. The papers of this special issue, six in total,
                 identify such challenges, and propose solutions, design
                 guidelines, and new research directions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Information-Centric Networking (ICN).",
}

@Article{Wang:2020:UME,
  author =       "Xiaofan Wang and Lingyu Xu",
  title =        "Unsteady Multi-Element Time Series Analysis and
                 Prediction Based on Spatial-Temporal Attention and
                 Error Forecast Fusion",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "2",
  pages =        "34",
  day =          "13",
  month =        feb,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12020034",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:42 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/2/34",
  abstract =     "Harmful algal blooms (HABs) often cause great harm to
                 fishery production and the safety of human lives.
                 Therefore, the detection and prediction of HABs has
                 become an important issue. Machine learning has been
                 increasingly used to predict HABs at home and abroad.
                 However, few of them can capture the sudden change of
                 Chl-a in advance and handle the long-term dependencies
                 appropriately. In order to address these challenges,
                 the Long Short-Term Memory (LSTM) based
                 spatial-temporal attentions model for Chlorophyll-a
                 (Chl-a) concentration prediction is proposed, a model
                 which can capture the correlation between various
                 factors and Chl-a adaptively and catch dynamic temporal
                 information from previous time intervals for making
                 predictions. The model can also capture the stage of
                 Chl-a when values soar as red tide breaks out in
                 advance. Due to the instability of the current Chl-a
                 concentration prediction model, the model is also
                 applied to make a prediction about the forecast
                 reliability, to have a basic understanding of the range
                 and fluctuation of model errors and provide a reference
                 to describe the range of marine disasters. The data
                 used in the experiment is retrieved from Fujian Marine
                 Forecasts Station from 2009 to 2011 and is combined
                 into 8-dimension data. Results show that the proposed
                 approach performs better than other Chl-a prediction
                 algorithms (such as Attention LSTM and Seq2seq and back
                 propagation). The result of error prediction also
                 reveals that the error forecast method possesses
                 established advantages for red tides prevention and
                 control.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Shuaieb:2020:RRF,
  author =       "Wafa Shuaieb and George Oguntala and Ali AlAbdullah
                 and Huthaifa Obeidat and Rameez Asif and Raed A.
                 Abd-Alhameed and Mohammed S. Bin-Melha and Chakib
                 Kara-Za{\"\i}tri",
  title =        "{RFID} {RSS} Fingerprinting System for Wearable Human
                 Activity Recognition",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "2",
  pages =        "33",
  day =          "12",
  month =        feb,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12020033",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:42 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/2/33",
  abstract =     "Alternative healthcare solutions have been identified
                 as a viable approach to ameliorate the increasing
                 demand for telehealth and prompt healthcare delivery.
                 Moreover, indoor localization using different
                 technologies and approaches have greatly contributed to
                 alternative healthcare solutions. In this paper, a
                 cost-effective, radio frequency identification
                 (RFID)-based indoor location system that employs
                 received signal strength (RSS) information of passive
                 RFID tags is presented. The proposed system uses RFID
                 tags placed at different positions on the target body.
                 The mapping of the analysed data against a set of
                 reference position datasets is used to accurately track
                 the vertical and horizontal positioning of a patient
                 within a confined space in real-time. The Euclidean
                 distance model achieves an accuracy of 98\% for all
                 sampled activities. However, the accuracy of the
                 activity recognition algorithm performs below the
                 threshold performance for walking and standing, which
                 is due to similarities in the target height, weight and
                 body density for both activities. The obtained results
                 from the proposed system indicate significant
                 potentials to provide reliable health measurement tool
                 for patients at risk.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Jeon:2020:DEC,
  author =       "Soobin Jeon",
  title =        "Data Exchange in Cluster Structure for Longevity of
                 {IoT}",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "2",
  pages =        "32",
  day =          "12",
  month =        feb,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12020032",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:42 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/2/32",
  abstract =     "In the Internet of Things (IoT), the scope of wireless
                 sensor nodes is extended to things deployed in a
                 pervasive world. For various IoT service applications,
                 things can gather and share their information with each
                 other through self-decision-making. Therefore, we
                 cannot apply the existing information aggregation
                 methods of wireless sensor networks to the IoT
                 environment, which aim to transmit the collected data
                 to only a sink node or a central server. Moreover,
                 since the existing methods involve all the sensor nodes
                 in the process of data exchange, they can cause an
                 increase in the network traffic, delay of data
                 transmission, and amount of energy consumed by things.
                 In this paper, we propose a clustering-property-based
                 data exchange method for efficient energy consumption
                 in IoT networks. First, the proposed method assigns
                 properties to each thing according to the
                 characteristics of the obtained data. Second, it
                 constructs a cluster network considering the location
                 of things and their energy consumption. Finally, the
                 things in a cluster communicate with other things in a
                 different cluster based on their properties. In the
                 experiment, the proposed method exhibits a better
                 performance than the existing method. Owing to the
                 energy-saving effect, we demonstrate that the proposed
                 method results in a more reliable network and improves
                 the longevity of IoT networks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Delay-Tolerant Networking.",
}

@Article{Tomaiuolo:2020:STD,
  author =       "Michele Tomaiuolo and Gianfranco Lombardo and Monica
                 Mordonini and Stefano Cagnoni and Agostino Poggi",
  title =        "A Survey on Troll Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "2",
  pages =        "31",
  day =          "10",
  month =        feb,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12020031",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:42 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/2/31",
  abstract =     "A troll is usually defined as somebody who provokes
                 and offends people to make them angry, who wants to
                 dominate any discussion or who tries to manipulate
                 people's opinions. The problems caused by such persons
                 have increased with the diffusion of social media.
                 Therefore, on the one hand, press bodies and magazines
                 have begun to address the issue and to write articles
                 about the phenomenon and its related problems while, on
                 the other hand, universities and research centres have
                 begun to study the features characterizing trolls and
                 to look for solutions for their identification. This
                 survey aims at introducing the main researches
                 dedicated to the description of trolls and to the study
                 and experimentation of methods for their detection.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Collection Featured Reviews of Future Internet
                 Research.",
}

@Article{Zhao:2020:ITC,
  author =       "Yafei Zhao and Paolo Vincenzo Genovese and Zhixing
                 Li",
  title =        "Intelligent Thermal Comfort Controlling System for
                 Buildings Based on {IoT} and {AI}",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "2",
  pages =        "30",
  day =          "10",
  month =        feb,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12020030",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:42 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/python.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/2/30",
  abstract =     "With the improvement of technologies, people's demand
                 for intelligent devices of indoor and outdoor living
                 environments keeps increasing. However, the traditional
                 control system only adjusts living parameters
                 mechanically, which cannot better meet the requirements
                 of human comfort intelligently. This article proposes a
                 building intelligent thermal comfort control system
                 based on the Internet of Things and intelligent
                 artificial intelligence. Through the literature review,
                 various algorithms and prediction methods are analyzed
                 and compared. The system can automatically complete a
                 series of operations through IoT hardware devices which
                 are located at multiple locations in the building with
                 key modules. The code is developed and debugged by
                 Python to establish a model for energy consumption
                 prediction with environmental factors such as
                 temperature, humidity, radiant temperature, and air
                 velocity on thermal comfort indicators. By using the
                 simulation experiments, 1700 data sets are used for
                 training. Then, the output PMV predicted values are
                 compared with the real figure. The results show that
                 the performance of this system is superior to
                 traditional control on energy-saving and comfort.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Internet of Things and Ambient
                 Intelligence.",
}

@Article{Ghaddar:2020:EEA,
  author =       "Alia Ghaddar and Ahmad Merei",
  title =        "{EAOA}: Energy-Aware Grid-Based 3D-Obstacle Avoidance
                 in Coverage Path Planning for {UAVs}",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "2",
  pages =        "29",
  day =          "08",
  month =        feb,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12020029",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:42 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/2/29",
  abstract =     "The presence of obstacles like a tree, buildings, or
                 birds along the path of a drone has the ability to
                 endanger and harm the UAV's flight mission. Avoiding
                 obstacles is one of the critical challenging keys to
                 successfully achieve a UAV's mission. The path planning
                 needs to be adapted to make intelligent and accurate
                 avoidance online and in time. In this paper, we propose
                 an energy-aware grid based solution for obstacle
                 avoidance (EAOA). Our work is based on two phases: in
                 the first one, a trajectory path is generated offline
                 using the area top-view. The second phase depends on
                 the path obtained in the first phase. A camera captures
                 a frontal view of the scene that contains the obstacle,
                 then the algorithm determines the new position where
                 the drone has to move to, in order to bypass the
                 obstacle. In this paper, the obstacles are static. The
                 results show a gain in energy and completion time using
                 3D scene information compared to 2D scene
                 information.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue The Internet of Things for Smart
                 Environments.",
}

@Article{DiMartino:2020:MBC,
  author =       "Beniamino {Di Martino} and Salvatore Venticinque and
                 Antonio Esposito and Salvatore D'Angelo",
  title =        "A Methodology Based on Computational Patterns for
                 Offloading of Big Data Applications on Cloud-Edge
                 Platforms",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "2",
  pages =        "28",
  day =          "07",
  month =        feb,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12020028",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:42 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/2/28",
  abstract =     "Internet of Things (IoT) is becoming a widespread
                 reality, as interconnected smart devices and sensors
                 have overtaken the IT market and invaded every aspect
                 of the human life. This kind of development, while
                 already foreseen by IT experts, implies additional
                 stress to already congested networks, and may require
                 further investments in computational power when
                 considering centralized and Cloud based solutions. That
                 is why a common trend is to rely on local resources,
                 provided by smart devices themselves or by aggregators,
                 to deal with part of the required computations: this is
                 the base concept behind Fog Computing, which is
                 becoming increasingly adopted as a distributed
                 calculation solution. In this paper a methodology,
                 initially developed within the TOREADOR European
                 project for the distribution of Big Data computations
                 over Cloud platforms, will be described and applied to
                 an algorithm for the prediction of energy consumption
                 on the basis of data coming from home sensors, already
                 employed within the CoSSMic European Project. The
                 objective is to demonstrate that, by applying such a
                 methodology, it is possible to improve the calculation
                 performances and reduce communication with centralized
                 resources.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Performance Evaluation in the Era of
                 Cloud and Edge Computing.",
}

@Article{Yu:2020:SSV,
  author =       "Miao Yu and Jianwei Zhuge and Ming Cao and Zhiwei Shi
                 and Lin Jiang",
  title =        "A Survey of Security Vulnerability Analysis,
                 Discovery, Detection, and Mitigation on {IoT} Devices",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "2",
  pages =        "27",
  day =          "06",
  month =        feb,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12020027",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:42 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/2/27",
  abstract =     "With the prosperity of the Internet of Things (IoT)
                 industry environment, the variety and quantity of IoT
                 devices have grown rapidly. IoT devices have been
                 widely used in smart homes, smart wear, smart
                 manufacturing, smart cars, smart medical care, and many
                 other life-related fields. With it, security
                 vulnerabilities of IoT devices are emerging endlessly.
                 The proliferation of security vulnerabilities will
                 bring severe risks to users' privacy and property. This
                 paper first describes the research background,
                 including IoT architecture, device components, and
                 attack surfaces. We review state-of-the-art research on
                 IoT device vulnerability discovery, detection,
                 mitigation, and other related works. Then, we point out
                 the current challenges and opportunities by evaluation.
                 Finally, we forecast and discuss the research
                 directions on vulnerability analysis techniques of IoT
                 devices.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Collection Featured Reviews of Future Internet
                 Research.",
}

@Article{Wang:2020:NLC,
  author =       "Jiong Wang and Hua Zhang and Dongliang Lin and Huibin
                 Feng and Tao Wang and Hongyan Zhang and Xiaoding Wang",
  title =        "A Novel Low-Complexity Fault Diagnosis Algorithm for
                 Energy {Internet} in Smart Cities",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "2",
  pages =        "26",
  day =          "06",
  month =        feb,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12020026",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:42 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/2/26",
  abstract =     "The smart energy system, viewed as an ``Energy
                 Internet'', consists of the intelligent integration of
                 decentralized sustainable energy sources, efficient
                 distribution, and optimized power consumption. That
                 implies the fault diagnosis for a smart energy system
                 should be of low complexity. In this paper, we propose
                 a Strong Tracking Unscented Kalman Filter (STUKF) and
                 modified Bayes' classification-based Modified Three
                 Sigma test (MTS), abbreviated as SFBT, for smart energy
                 networks. The theoretical analysis and simulations
                 indicate that SFBT detects faults with a high accuracy
                 and a low complexity of $ O(n) $.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Energy Internet for Green Cities.",
}

@Article{Marchiori:2020:SSS,
  author =       "Massimo Marchiori and Lino Possamai",
  title =        "Strategies of Success for Social Networks: Mermaids
                 and Temporal Evolution",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "2",
  pages =        "25",
  day =          "04",
  month =        feb,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12020025",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:42 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/2/25",
  abstract =     "The main goal of this article is to investigate
                 techniques that can quickly lead to successful social
                 systems by boosting network connectivity. This is
                 especially useful when starting new online communities
                 where the aim is to increase the system utilization as
                 much as possible. This aspect is very important
                 nowadays, given the existence of many online social
                 networks available on the web, and the relatively high
                 level of competition. In other words, attracting users'
                 attention is becoming a major concern, and time is an
                 essential factor when investing money and resources
                 into online social systems. Our study describes an
                 effective technique that deals with this issue by
                 introducing the notion of mermaids, special attractors
                 that alter the normal evolutive behavior of a social
                 system. We analyze how mermaids can boost social
                 networks, and then provide estimations of fundamental
                 parameters that business strategists can take into
                 account in order to obtain successful systems within a
                 constrained budget.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Techno-Social Smart Systems.",
}

@Article{Duradoni:2020:WBS,
  author =       "Mirko Duradoni and Federico Innocenti and Andrea
                 Guazzini",
  title =        "Well-Being and Social Media: a Systematic Review of
                 {Bergen} Addiction Scales",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "2",
  pages =        "24",
  day =          "29",
  month =        jan,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12020024",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:42 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/2/24",
  abstract =     "Does social media addiction impair the well-being of
                 non-clinical individuals? Despite the Internet being
                 able to be considered as a promoting factor for
                 individual empowerment, previous literature suggests
                 that the current massive availability of Information
                 and Communication Technologies (ICT) may be dangerous
                 for users' well-being. This article discusses the
                 relationship between the most used social media
                 addiction measures (i.e., the Bergen Facebook Addiction
                 Scale --- BFAS, the Bergen Social Media Addiction Scale
                 --- BSMAS) and well-being. A systematic review
                 considering all the publications indexed by PsycInfo,
                 PsycArticles, PubMed, Science Direct, Sociological
                 Abstracts, Academic Search Complete, and Google Scholar
                 databases was performed to collect the data. Ten of 635
                 studies were included in the qualitative synthesis.
                 Overall, most of the included works captured a negative
                 but small relationship between BFAS/BSMAS and
                 well-being, across multiple definitions and
                 measurement.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Collection Featured Reviews of Future Internet
                 Research.",
}

@Article{Kungne:2020:RBL,
  author =       "Willy Kengne Kungne and Georges-Edouard Kouamou and
                 Claude Tangha",
  title =        "A Rule-Based Language and Verification Framework of
                 Dynamic Service Composition",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "2",
  pages =        "23",
  day =          "26",
  month =        jan,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12020023",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:42 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/2/23",
  abstract =     "The emergence of BPML (Business Process Modeling
                 Language) has favored the development of languages for
                 the composition of services. Process-oriented
                 approaches produce imperative languages, which are
                 rigid to change at run-time because they focus on how
                 the processes should be built. Despite the fact that
                 semantics is introduced in languages to increase their
                 flexibility, dynamism is limited to find services that
                 have disappeared or become defective. They do not offer
                 the possibility to adapt the composite service to
                 execution. Although rules-based languages were
                 introduced, they remain very much dependent on the BPML
                 which is the underlying technology. This article
                 proposes the specification of a rule-based declarative
                 language for the composition of services. It consists
                 of the syntactic categories which make up the concepts
                 of the language and a formal description of the
                 operational semantics that highlights the dynamism, the
                 flexibility and the adaptability of the language thus
                 defined. This paper also presents a verification
                 framework made of a formal aspect and a toolset. The
                 verification framework translates service
                 specifications into Promela for model checking. Then, a
                 validation framework is proposed that translates the
                 verified specifications to the operational system.
                 Finally, a case study is presented.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Oliveira:2020:MCI,
  author =       "Thays A. Oliveira and Yuri B. Gabrich and Helena
                 Ramalhinho and Miquel Oliver and Miri W. Cohen and Luiz
                 S. Ochi and Serigne Gueye and F{\'a}bio Protti and
                 Alysson A. Pinto and Di{\'o}genes V. M. Ferreira and
                 Igor M. Coelho and Vitor N. Coelho",
  title =        "Mobility, Citizens, Innovation and Technology in
                 Digital and Smart Cities",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "2",
  pages =        "22",
  day =          "26",
  month =        jan,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12020022",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:42 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/2/22",
  abstract =     "Cities are constantly transforming and, consequently,
                 attracting efforts from researchers and opportunities
                 to the industry. New transportation systems are being
                 built in order to meet sustainability and efficiency
                 criteria, as well as being adapted to the current
                 possibilities. Moreover, citizens are becoming aware
                 about the power and possibilities provided by the
                 current generation of autonomous devices. In this
                 sense, this paper presents and discusses
                 state-of-the-art transportation technologies and
                 systems, highlighting the advances that the concepts of
                 Internet of Things and Value are providing.
                 Decentralized technologies, such as blockchain, are
                 been extensively investigated by the industry, however,
                 its widespread adoption in cities is still desirable.
                 Aligned with operations research opportunities, this
                 paper identifies different points in which cities'
                 services could move to. This also study comments about
                 different combinatorial optimization problems that
                 might be useful and important for an efficient
                 evolution of our cities. By considering different
                 perspectives, didactic examples are presented with a
                 main focus on motivating decision makers to balance
                 citizens, investors and industry goals and wishes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Smart Cities, Innovation, and
                 Multi-Dimensionality.",
}

@Article{Abdo:2020:APP,
  author =       "Ahmad Abdo and Claude D'Amours",
  title =        "Adaptive Pre\slash Post-Compensation of Cascade
                 Filters in Coherent Optical Transponders",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "2",
  pages =        "21",
  day =          "24",
  month =        jan,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12020021",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:42 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/2/21",
  abstract =     "We propose an adaptive joint pre- and
                 post-compensation to correct the filtering effects
                 caused by cascading reconfigurable optical add drop
                 multiplexers (ROADMs). The improvement is achieved
                 without using additional hardware (HW) on the link or
                 within the signal processor in the transponders. Using
                 Monte Carlo simulations, the gradient-descent based
                 method shows an improvement of 0.6 dB and 1.1 dB in the
                 required optical signal-to-noise ratio (R-OSNR) at the
                 threshold pre-decoder bit error rate (BER) of 0.02
                 versus pre-compensation only in the linear and
                 nonlinear operating region of fiber respectively. We
                 experimentally verified the method with lab
                 measurements in the presence of heavy filtering and
                 optical impairments. We observed a gain up to $ \approx
                 0.4 $ dB compared to typically used pre-compensation
                 only. Additionally, other tangible system benefits of
                 our method are listed and discussed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Network Virtualization and Edge/Fog
                 Computing.",
}

@Article{Kakkavas:2020:RAA,
  author =       "Grigorios Kakkavas and Despoina Gkatzioura and
                 Vasileios Karyotis and Symeon Papavassiliou",
  title =        "A Review of Advanced Algebraic Approaches Enabling
                 Network Tomography for Future Network Infrastructures",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "2",
  pages =        "20",
  day =          "22",
  month =        jan,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12020020",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:42 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/2/20",
  abstract =     "Network tomography has emerged as one of the lean
                 approaches for efficient network monitoring, especially
                 aiming at addressing the ever-increasing requirements
                 for scaling and efficiency in modern network
                 architectures and infrastructures. In this paper, we
                 explore network coding and compressed sensing as
                 enabling technologies in the context of network
                 tomography. Both approaches capitalize on algebraic
                 tools for achieving accuracy while allowing scaling of
                 operation as the size of the monitored network
                 increases. Initially, a brief overview of the
                 tomographic problems and the related classification of
                 methods is provided to better comprehend the problems
                 encountered and solutions provided to date.
                 Subsequently, we present representative approaches that
                 employ either one of the aforementioned technologies
                 and we comparatively describe their fundamental
                 operation. Eventually, we provide a qualitative
                 comparison of features and approaches that can be used
                 for further research and technology development for
                 network monitoring in future Internet
                 infrastructures.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Collection Featured Reviews of Future Internet
                 Research.",
}

@Article{Ghaddar:2020:MAC,
  author =       "Alia Ghaddar and Monah Bou Hatoum and Ghassan
                 Fadlallah and Hamid Mcheick",
  title =        "{MCCM}: An Approach for Connectivity and Coverage
                 Maximization",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "2",
  pages =        "19",
  day =          "21",
  month =        jan,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12020019",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:42 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/2/19",
  abstract =     "The internet of Things (IoT) has attracted significant
                 attention in many applications in both academic and
                 industrial areas. In IoT, each object can have the
                 capabilities of sensing, identifying, networking and
                 processing to communicate with ubiquitous objects and
                 services. Often this paradigm (IoT) using Wireless
                 Sensor Networks must cover large area of interest (AoI)
                 with huge number of devices. As these devices might be
                 battery powered and randomly deployed, their long-term
                 availability and connectivity for area coverage is very
                 important, in particular in harsh environments.
                 Moreover, a poor distribution of devices may lead to
                 coverage holes and degradation to the quality of
                 service. In this paper, we propose an approach for
                 self-organization and coverage maximization. We present
                 a distributed algorithm for ``Maintaining Connectivity
                 and Coverage Maximization'' called MCCM. The algorithm
                 operates on different movable devices in homogeneous
                 and heterogeneous distribution. It does not require
                 high computational complexity. The main goal is to keep
                 the movement of devices as minimal as possible to save
                 energy. Another goal is to reduce the overlapping areas
                 covered by different devices to increase the coverage
                 while maintaining connectivity. Simulation results show
                 that the proposed algorithm can achieve higher coverage
                 and lower nodes' movement over existing algorithms in
                 the state of the art.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue The Internet of Things for Smart
                 Environments.",
}

@Article{Ferrag:2020:RRD,
  author =       "Mohamed Amine Ferrag and Leandros Maglaras and Ahmed
                 Ahmim and Makhlouf Derdour and Helge Janicke",
  title =        "{RDTIDS}: Rules and Decision Tree-Based Intrusion
                 Detection System for {Internet-of-Things} Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "3",
  pages =        "44",
  day =          "02",
  month =        mar,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12030044",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:42 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/3/44",
  abstract =     "This paper proposes a novel intrusion detection system
                 (IDS), named RDTIDS, for Internet-of-Things (IoT)
                 networks. The RDTIDS combines different classifier
                 approaches which are based on decision tree and
                 rules-based concepts, namely, REP Tree, JRip algorithm
                 and Forest PA. Specifically, the first and second
                 method take as inputs features of the data set, and
                 classify the network traffic as Attack/Benign. The
                 third classifier uses features of the initial data set
                 in addition to the outputs of the first and the second
                 classifier as inputs. The experimental results obtained
                 by analyzing the proposed IDS using the CICIDS2017
                 dataset and BoT-IoT dataset, attest their superiority
                 in terms of accuracy, detection rate, false alarm rate
                 and time overhead as compared to state of the art
                 existing schemes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Reliability of
                 IoT---Selected Papers from SecRIoT 2019.",
}

@Article{Wu:2020:BLS,
  author =       "Pin Wu and Xuting Chang and Yang Yang and Xiaoqiang
                 Li",
  title =        "{BASN}-Learning Steganography with a Binary Attention
                 Mechanism",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "3",
  pages =        "43",
  day =          "27",
  month =        feb,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12030043",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:42 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/3/43",
  abstract =     "Secret information sharing through image carriers has
                 aroused much research attention in recent years with
                 images' growing domination on the Internet and mobile
                 applications. The technique of embedding secret
                 information in images without being detected is called
                 image steganography. With the booming trend of
                 convolutional neural networks (CNN),
                 neural-network-automated tasks have been embedded more
                 deeply in our daily lives. However, a series of wrong
                 labeling or bad captioning on the embedded images has
                 left a trace of skepticism and finally leads to a
                 self-confession like exposure. To improve the security
                 of image steganography and minimize task result
                 distortion, models must maintain the feature maps
                 generated by task-specific networks being irrelative to
                 any hidden information embedded in the carrier. This
                 paper introduces a binary attention mechanism into
                 image steganography to help alleviate the security
                 issue, and, in the meantime, increase embedding payload
                 capacity. The experimental results show that our method
                 has the advantage of high payload capacity with little
                 feature map distortion and still resist detection by
                 state-of-the-art image steganalysis algorithms.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kan:2020:LCP,
  author =       "MingSung Kan and Atsushi Ito",
  title =        "Language Cognition and Pronunciation Training Using
                 Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "3",
  pages =        "42",
  day =          "25",
  month =        feb,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12030042",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Mar 2 12:22:42 MST 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/3/42",
  abstract =     "In language learning, adults seem to be superior in
                 their ability to memorize knowledge of new languages
                 and have better learning strategies, experiences, and
                 intelligence to be able to integrate new knowledge.
                 However, unless one learns pronunciation in childhood,
                 it is almost impossible to reach a native-level accent.
                 In this research, we take the difficulties of learning
                 tonal pronunciation in Mandarin as an example and
                 analyze the difficulties of tone learning and the
                 deficiencies of general learning methods using the
                 cognitive load theory. With the tasks designed
                 commensurate with the learner's perception ability
                 based on perception experiments and small-step
                 learning, the perception training app is more effective
                 for improving the tone pronunciation ability compared
                 to existing apps with voice analysis function.
                 Furthermore, the learning effect was greatly improved
                 by optimizing the app interface and operation
                 procedures. However, as a result of the combination of
                 pronunciation practice and perception training,
                 pronunciation practice with insufficient feedback could
                 lead to pronunciation errors. Therefore, we also
                 studied pronunciation practice using machine learning
                 and aimed to train the model for the pronunciation task
                 design instead of classification. We used voices
                 designed as training data and trained a model for
                 pronunciation training, and demonstrated that
                 supporting pronunciation practice with machine learning
                 is practicable.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Cognitive Infocommunications-Theory and
                 Applications.",
}

@Article{Giannakoulopoulos:2020:EDE,
  author =       "Andreas Giannakoulopoulos and Minas Pergantis and
                 Nikos Konstantinou and Aristeidis Lamprogeorgos and
                 Laida Limniati and Iraklis Varlamis",
  title =        "Exploring the Dominance of the {English} Language on
                 the {Websites} of {EU} Countries",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "4",
  pages =        "76",
  day =          "22",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12040076",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/4/76",
  abstract =     "The English language is the most dominant language in
                 the Western world and its influence can be noticed in
                 every aspect of human communication. Its increasing
                 diffusion, especially since the turn of the century, is
                 hard to measure with conventional means. The present
                 research studies the use of language in websites of
                 European Union (EU) member states, in order to collect
                 data about the prevalence of the English language in
                 the different countries and regions of the European
                 Union. To achieve a realistic representation of today's
                 landscape of the European Web, this study uses a vast
                 population of websites and a representative sampling
                 size and methodology. By analyzing and processing the
                 findings from over 100,000 websites from every country
                 in the EU, a solid foundation is set that is used to
                 explore the dominance of the English language in the
                 European World Wide Web in general. This is the first
                 study that examines the presence of English content in
                 the websites of all EU member countries and provides
                 statistical evidence regarding the ratio of English
                 content availability for each country. Conclusively,
                 the results of the research demonstrate that the
                 English language is available on more than one quarter
                 of all websites of non-English speaking EU member
                 states. Moreover, it is available in the vast majority
                 of multilingual and bilingual websites, while at the
                 same time being the only language that is available in
                 a number of monolingual websites. In addition, it is
                 shown preference over the national language in a
                 significant number of cases. A moderate negative
                 correlation is found between a member state's
                 population and the availability of English in these
                 countries' websites and the same holds true for a
                 member state's Gross Domestic Product (GDP). Both these
                 correlations indicate that smaller countries tend to
                 provide more content in English in order to establish a
                 stronger presence in the international environment.
                 Taking into account the role of language in the
                 expression of national identity, this study provides
                 data and insights which may contribute to the
                 discussion about the changes underway in the national
                 identity of EU member states.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yang:2020:MBS,
  author =       "Wenzhong Yang and Tingting Yuan and Liejun Wang",
  title =        "Micro-Blog Sentiment Classification Method Based on
                 the Personality and Bagging Algorithm",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "4",
  pages =        "75",
  day =          "20",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12040075",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/4/75",
  abstract =     "Integrated learning can be used to combine weak
                 classifiers in order to improve the effect of emotional
                 classification. Existing methods of emotional
                 classification on micro-blogs seldom consider utilizing
                 integrated learning. Personality can significantly
                 influence user expressions but is seldom accounted for
                 in emotional classification. In this study, a
                 micro-blog emotion classification method is proposed
                 based on a personality and bagging algorithm (PBAL).
                 Introduce text personality analysis and use rule-based
                 personality classification methods to divide five
                 personality types. The micro-blog text is first
                 classified using five personality basic emotion
                 classifiers and a general emotion classifier. A long
                 short-term memory language model is then used to train
                 an emotion classifier for each set, which are then
                 integrated together. Experimental results show that
                 compared with traditional sentiment classifiers, PBAL
                 has higher accuracy and recall. The F value has
                 increased by 9\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rustamov:2020:DDA,
  author =       "Fayozbek Rustamov and Juhwan Kim and JooBeom Yun",
  title =        "{DeepDiver}: Diving into Abysmal Depth of the Binary
                 for Hunting Deeply Hidden Software Vulnerabilities",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "4",
  pages =        "74",
  day =          "18",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12040074",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/4/74",
  abstract =     "Fuzz testing is a simple automated software testing
                 approach that discovers software vulnerabilities at a
                 high level of performance by using randomly generated
                 seeds. However, it is restrained by coverage and thus,
                 there are chances of finding bugs entrenched in the
                 deep execution paths of the program. To eliminate these
                 limitations in mutational fuzzers, patching-based
                 fuzzers and hybrid fuzzers have been proposed as
                 groundbreaking advancements which combine two software
                 testing approaches. Despite those methods having
                 demonstrated high performance across different
                 benchmarks such as DARPA CGC programs, they still
                 present deficiencies in their ability to analyze deeper
                 code branches and in bypassing the roadblocks checks
                 (magic bytes, checksums) in real-world programs. In
                 this research, we design DeepDiver, a novel
                 transformational hybrid fuzzing tool that explores
                 deeply hidden software vulnerabilities. Our approach
                 tackles limitations exhibited by existing hybrid
                 fuzzing frameworks, by negating roadblock checks (RC)
                 in the program. By negating the RCs, the hybrid fuzzer
                 can explore new execution paths to trigger bugs that
                 are hidden in the abysmal depths of the binary. We
                 combine AFL++ and concolic execution engine and
                 leveraged the trace analyzer approach to construct the
                 tree for each input to detect RCs. To demonstrate the
                 efficiency of DeepDiver, we tested it with the LAVA-M
                 dataset and eight large real-world programs. Overall,
                 DeepDiver outperformed existing software testing tools,
                 including the patching-based fuzzer and
                 state-of-the-art hybrid fuzzing techniques. On average,
                 DeepDiver discovered vulnerabilities 32.2\% and 41.6\%
                 faster than QSYM and AFLFast respectively, and it
                 accomplished in-depth code coverage.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Privacy in Social Networks
                 and Solutions.",
}

@Article{Vogel:2020:WOI,
  author =       "Bahtijar Vogel and Yuji Dong and Blerim Emruli and
                 Paul Davidsson and Romina Spalazzese",
  title =        "What Is an Open {IoT} Platform? {Insights} from a
                 Systematic Mapping Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "4",
  pages =        "73",
  day =          "18",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12040073",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/4/73",
  abstract =     "Today, the Internet of Things (IoT) is mainly
                 associated with vertically integrated systems that
                 often are closed and fragmented in their applicability.
                 To build a better IoT ecosystem, the open IoT platform
                 has become a popular term in the recent years. However,
                 this term is usually used in an intuitive way without
                 clarifying the openness aspects of the platforms. The
                 goal of this paper is to characterize the openness
                 types of IoT platforms and investigate what makes them
                 open. We conducted a systematic mapping study by
                 retrieving data from 718 papers. As a result of
                 applying the inclusion and exclusion criteria, 221
                 papers were selected for review. We discovered 46 IoT
                 platforms that have been characterized as open, whereas
                 25 platforms are referred as open by some studies
                 rather than the platforms themselves. We found that the
                 most widely accepted and used open IoT platforms are
                 NodeMCU and ThingSpeak that together hold a share of
                 more than 70\% of the declared open IoT platforms in
                 the selected papers. The openness of an IoT platform is
                 interpreted into different openness types. Our study
                 results show that the most common openness type
                 encountered in open IoT platforms is open-source, but
                 also open standards, open APIs, open data and open
                 layers are used in the literature. Finally, we propose
                 a new perspective on how to define openness in the
                 context of IoT platforms by providing several insights
                 from the different stakeholder viewpoints.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Internet of Things.",
}

@Article{Krol:2020:AIW,
  author =       "Karol Kr{\'o}l and Dariusz Zdonek",
  title =        "Aggregated Indices in {Website} Quality Assessment",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "4",
  pages =        "72",
  day =          "17",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12040072",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/4/72",
  abstract =     "Website users have increasingly high expectations
                 regarding website quality, starting from performance
                 and ending up with the content. This article provides a
                 list and characteristics of selected website quality
                 indices and testing applications that are available
                 free of charge. Aggregated website quality indices were
                 characterised based on a review of various source
                 materials, including the academic literature and
                 Internet materials. Aggregated website quality indices
                 are usually developed with a less specialised user
                 (customer) searching for descriptive information in
                 mind. Their presentation is focused on aesthetic
                 sensations. Most frequently, their values are expressed
                 in points or percent. Many of these indices appear to
                 be of little substantive value, as they present
                 approximate, estimated values. These indices, however,
                 are of great marketing value instead. Specific
                 (``single'') indices are of a specialised nature. They
                 are more difficult to interpret and address the subtle
                 aspects of website and web application functioning.
                 They offer great value to designers and software
                 developers. They indicate critical spots which affect
                 the website quality. Most of them are expressed
                 precisely, often up to two or three decimal places, in
                 specific units. Algorithmic tests for website quality,
                 whose results are presented using indices, enable a
                 reduction in the cost intensiveness of tests as well as
                 an increase in their number and frequency, as the tests
                 are repetitive and their number is not limited. What is
                 more, they allow the results to be compared.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Social Web, New Media, Algorithms and
                 Power.",
}

@Article{Awad:2020:PAS,
  author =       "Nancy Awad and Jean-Fran{\c{c}}ois Couchot and Bechara
                 {Al Bouna} and Laurent Philippe",
  title =        "Publishing Anonymized Set-Valued Data via
                 Disassociation towards Analysis",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "4",
  pages =        "71",
  day =          "17",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12040071",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/4/71",
  abstract =     "Data publishing is a challenging task for privacy
                 preservation constraints. To ensure privacy, many
                 anonymization techniques have been proposed. They
                 differ in terms of the mathematical properties they
                 verify and in terms of the functional objectives
                 expected. Disassociation is one of the techniques that
                 aim at anonymizing of set-valued datasets (e.g.,
                 discrete locations, search and shopping items) while
                 guaranteeing the confidentiality property known as k m
                 -anonymity. Disassociation separates the items of an
                 itemset in vertical chunks to create ambiguity in the
                 original associations. In a previous work, we defined a
                 new ant-based clustering algorithm for the
                 disassociation technique to preserve some items
                 associated together, called utility rules, throughout
                 the anonymization process, for accurate analysis. In
                 this paper, we examine the disassociated dataset in
                 terms of knowledge extraction. To make data analysis
                 easy on top of the anonymized dataset, we define
                 neighbor datasets or in other terms datasets that are
                 the result of a probabilistic re-association process.
                 To assess the neighborhood notion set-valued datasets
                 are formalized into trees and a tree edit distance
                 (TED) is directly applied between these neighbors.
                 Finally, we prove the faithfulness of the neighbors to
                 knowledge extraction for future analysis, in the
                 experiments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Privacy in Social Networks
                 and Solutions.",
}

@Article{Song:2020:DPD,
  author =       "Ha Yoon Song and Hyochang Han",
  title =        "A Design of a Parcel Delivery System for Point to
                 Point Delivery with {IoT} Technology",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "4",
  pages =        "70",
  day =          "17",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12040070",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/4/70",
  abstract =     "Recently, IoT technology, low power networking
                 technology for IoT, and geopositioning systems are very
                 useful tools for future applications. One of the
                 applications is the logistics system, especially for
                 the point to point delivery. The current parcel
                 delivery system is delivered through the logistics hub
                 despite latent economic disadvantages in terms of
                 delivery time and delivery distance. The major
                 disadvantage of current hub and spoke delivery system
                 is that individual parcels must go to the logistics hub
                 first even if the origin and destination are nearby or
                 within a distance that can be delivered through the
                 hub. These sorts of delivery are inefficient and
                 increase total expense of delivery in terms of delivery
                 time and delivery costs. We designed a new delivery
                 system of point to point delivery using IoT technology
                 and end-to-end IoT platform based on ThingPlug and LoRa
                 technology for fast delivery and less cost of delivery.
                 We designed an IoT device that can be part of parcels
                 or attached to parcels, which have various
                 functionalities including the capability to understand
                 current delivery routes with the use of geopositioning
                 systems. In addition, we addressed the difficulties
                 with issues such as linking IoT device into IoT
                 platforms and designing IoT device functionalities. We
                 also showed methods to improve the efficiency of IoT
                 based parcel delivery systems. The proposed system may
                 improve economics of parcel delivery system by reducing
                 travel distance for delivery and dissipation of
                 delivery time.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Internet of Things.",
}

@Article{Zia:2020:IRA,
  author =       "Kashif Zia and Muhammad Shafi and Umar Farooq",
  title =        "Improving Recommendation Accuracy Using Social Network
                 of Owners in Social {Internet of Vehicles}",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "4",
  pages =        "69",
  day =          "16",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12040069",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/4/69",
  abstract =     "The latest manifestation of ``all connected world'' is
                 the Internet of Things (IoT), and Internet of Vehicles
                 (IoV) is one of the key examples of IoT these days. In
                 Social IoV (SIoV), each vehicle is treated as a social
                 object where it establishes and manages its own Social
                 Network (SN). Incidentally, most of the SIoV research
                 in the literature is related to proximity-based
                 connectivity and interactions. In this paper, we bring
                 people in the loop by incorporating their SNs. While
                 emphasizing a recommendation scenario, in which
                 vehicles may require recommendations from SNs of their
                 owners (in addition to their own SIoV), we proposed an
                 agent-based model of information sharing (for
                 context-based recommendations) on a hypothetical
                 population of smart vehicles. Some important hypotheses
                 were tested using a realistic simulation setting. The
                 simulation results reveal that a recommendation using
                 weak ties is more valuable than a recommendation using
                 strong ties in pure SIoV. The simulation results also
                 demonstrate that recommendations using the
                 most-connected person in the social network are not
                 more valuable than recommendation using a random person
                 in the social network. The model presented in this
                 paper can be used to design a multi-scale
                 recommendation system, which uses SIoV and a typical SN
                 in combination.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Advances in Internet of Vehicles
                 (IoV).",
}

@Article{Elagin:2020:BBT,
  author =       "Vasiliy Elagin and Anastasia Spirkina and Andrei
                 Levakov and Ilya Belozertsev",
  title =        "Blockchain Behavioral Traffic Model as a Tool to
                 Influence Service {IT} Security",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "4",
  pages =        "68",
  day =          "15",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12040068",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/4/68",
  abstract =     "The present article describes the behavioral model of
                 blockchain services; their reliability is confirmed on
                 the basis of experimental data. The authors identify
                 the main technical characteristics and features
                 associated with data transmission through the network.
                 The authors determine the network scheme, working with
                 blockchain transactions and the dependence of network
                 characteristics on application parameters. They analyze
                 the application of this model for the detection of the
                 blockchain service and the possibility of the existing
                 security mechanisms of this technology being evaded.
                 Furthermore, the article offers recommendations for
                 hiding the blockchain traffic profile to significantly
                 complicate its identification in the data network.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Cyber Security of the Continuous Digital
                 Environment: Challenges, Solutions and Future
                 Directions.",
}

@Article{Formica:2020:SSE,
  author =       "Anna Formica and Elaheh Pourabbas and Francesco
                 Taglino",
  title =        "Semantic Search Enhanced with Rating Scores",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "4",
  pages =        "67",
  day =          "15",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12040067",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/4/67",
  abstract =     "This paper presents SemSim e, a method based on
                 semantic similarity for searching over a set of digital
                 resources previously annotated by means of concepts
                 from a weighted reference ontology. SemSim e is an
                 enhancement of SemSim and, with respect to the latter,
                 it uses a frequency approach for weighting the
                 ontology, and refines both the user request and the
                 digital resources with the addition of rating scores.
                 Such scores are High, Medium, and Low, and in the user
                 request indicate the preferences assigned by the user
                 to each of the concepts representing the searching
                 criteria, whereas in the annotation of the digital
                 resources they represent the levels of quality
                 associated with each concept in describing the
                 resources. The SemSim e has been evaluated and the
                 results of the experiment show that it performs better
                 than SemSim and an evolution of it, referred to as S e
                 m S i m R V.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue New Perspectives on Semantic Web
                 Technologies and Applications.",
}

@Article{Kumar:2020:PPA,
  author =       "Ajit Kumar and Vinti Agarwal and Shishir Kumar
                 Shandilya and Andrii Shalaginov and Saket Upadhyay and
                 Bhawna Yadav",
  title =        "{PACER}: Platform for {Android} Malware
                 Classification, Performance Evaluation and Threat
                 Reporting",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "4",
  pages =        "66",
  day =          "12",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12040066",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/4/66",
  abstract =     "Android malware has become the topmost threat for the
                 ubiquitous and useful Android ecosystem. Multiple
                 solutions leveraging big data and machine-learning
                 capabilities to detect Android malware are being
                 constantly developed. Too often, these solutions are
                 either limited to research output or remain isolated
                 and incapable of reaching end users or malware
                 researchers. An earlier work named PACE (Platform for
                 Android Malware Classification and Performance
                 Evaluation), was introduced as a unified solution to
                 offer open and easy implementation access to several
                 machine-learning-based Android malware detection
                 techniques, that makes most of the research
                 reproducible in this domain. The benefits of PACE are
                 offered through three interfaces: Representational
                 State Transfer (REST) Application Programming Interface
                 (API), Web Interface, and Android Debug Bridge (ADB)
                 interface. These multiple interfaces enable users with
                 different expertise such as IT administrators, security
                 practitioners, malware researchers, etc. to use their
                 offered services. In this paper, we propose PACER
                 (Platform for Android Malware Classification,
                 Performance Evaluation, and Threat Reporting), which
                 extends PACE by adding threat intelligence and
                 reporting functionality for the end-user device through
                 the ADB interface. A prototype of the proposed platform
                 is introduced, and our vision is that it will help
                 malware analysts and end users to tackle challenges and
                 reduce the amount of manual work.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Advanced Big Data Analytics for Cyber
                 and Cyber-Physical Crime Investigations.",
}

@Article{Kavallieratos:2020:CSC,
  author =       "Georgios Kavallieratos and Sokratis Katsikas and
                 Vasileios Gkioulos",
  title =        "Cybersecurity and Safety Co-Engineering of
                 Cyberphysical Systems --- a Comprehensive Survey",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "4",
  pages =        "65",
  day =          "11",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12040065",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/4/65",
  abstract =     "Safeguarding both safety and cybersecurity is
                 paramount to the smooth and trustworthy operation of
                 contemporary cyber physical systems, many of which
                 support critical functions and services. As safety and
                 security have been known to be interdependent, they
                 need to be jointly considered in such systems. As a
                 result, various approaches have been proposed to
                 address safety and cybersecurity co-engineering in
                 cyber physical systems. This paper provides a
                 comprehensive survey of safety and cybersecurity
                 co-engineering methods, and discusses relevant open
                 issues and research challenges. Despite the extent of
                 the existing literature, several aspects of the subject
                 still remain to be fully addressed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future and Emerging topics in Security
                 for Cyber-Physical Systems.",
}

@Article{Ijaz:2020:RHP,
  author =       "Qaiser Ijaz and El-Bay Bourennane and Ali Kashif
                 Bashir and Hira Asghar",
  title =        "Revisiting the High-Performance Reconfigurable
                 Computing for Future Datacenters",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "4",
  pages =        "64",
  day =          "06",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12040064",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/super.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/4/64",
  abstract =     "Modern datacenters are reinforcing the computational
                 power and energy efficiency by assimilating field
                 programmable gate arrays (FPGAs). The sustainability of
                 this large-scale integration depends on enabling
                 multi-tenant FPGAs. This requisite amplifies the
                 importance of communication architecture and
                 virtualization method with the required features in
                 order to meet the high-end objective. Consequently, in
                 the last decade, academia and industry proposed several
                 virtualization techniques and hardware architectures
                 for addressing resource management, scheduling,
                 adoptability, segregation, scalability,
                 performance-overhead, availability, programmability,
                 time-to-market, security, and mainly, multitenancy.
                 This paper provides an extensive survey covering three
                 important aspects --- discussion on non-standard terms
                 used in existing literature, network-on-chip evaluation
                 choices as a mean to explore the communication
                 architecture, and virtualization methods under latest
                 classification. The purpose is to emphasize the
                 importance of choosing appropriate communication
                 architecture, virtualization technique and standard
                 language to evolve the multi-tenant FPGAs in
                 datacenters. None of the previous surveys encapsulated
                 these aspects in one writing. Open problems are
                 indicated for scientific community as well.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Collection Featured Reviews of Future Internet
                 Research.",
}

@Article{Gupta:2020:ABS,
  author =       "Nishu Gupta and Ravikanti Manaswini and Bongaram
                 Saikrishna and Francisco Silva and Ariel Teles",
  title =        "Authentication-Based Secure Data Dissemination
                 Protocol and Framework for {5G}-Enabled {VANET}",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "4",
  pages =        "63",
  day =          "01",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12040063",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/4/63",
  abstract =     "The amalgamation of Vehicular Ad hoc Network (VANET)
                 with the Internet of Things (IoT) leads to the concept
                 of the Internet of Vehicles (IoV). IoV forms a solid
                 backbone for Intelligent Transportation Systems (ITS),
                 which paves the way for technologies that better
                 explain about traffic efficiency and their management
                 applications. IoV architecture is seen as a big player
                 in different areas such as the automobile industry,
                 research organizations, smart cities and intelligent
                 transportation for various commercial and scientific
                 applications. However, as VANET is vulnerable to
                 various types of security attacks, the IoV structure
                 should ensure security and efficient performance for
                 vehicular communications. To address these issues, in
                 this article, an authentication-based protocol (A-MAC)
                 for smart vehicular communication is proposed along
                 with a novel framework towards an IoV architecture
                 model. The scheme requires hash operations and uses
                 cryptographic concepts to transfer messages between
                 vehicles to maintain the required security. Performance
                 evaluation helps analyzing its strength in withstanding
                 various types of security attacks. Simulation results
                 demonstrate that A-MAC outshines other protocols in
                 terms of communication cost, execution time, storage
                 cost, and overhead.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Advances in Internet of Vehicles
                 (IoV).",
}

@Article{Tagarev:2020:TDC,
  author =       "Todor Tagarev",
  title =        "Towards the Design of a Collaborative Cybersecurity
                 Networked Organisation: Identification and
                 Prioritisation of Governance Needs and Objectives",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "4",
  pages =        "62",
  day =          "28",
  month =        mar,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12040062",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/4/62",
  abstract =     "The effective response to the proliferation and
                 growing diversity and sophistication of cyber threats
                 requires a broad spectrum of competencies, human,
                 technological and financial resources that are in the
                 powers of very few countries. The European Union is
                 addressing this challenge through an initiative to
                 establish one or more cybersecurity competence
                 networks. A number of existing technologies can support
                 collaboration in networked organisations; however,
                 network governance remains a challenge. The study
                 presented in this article aimed to identify and
                 prioritise network governance issues. Towards that
                 purpose, qualitative and quantitative methods were
                 applied in the analysis of norms and regulations,
                 statutory documents of existing networks, academic
                 sources and interviews with representatives of funding
                 organisations and potential major customers. The
                 comprehensiveness and complementarity of these primary
                 sources allowed to identify 33 categories of governance
                 issues and group them in four tiers, indicative of the
                 respective priority level. The results of the study are
                 currently used to inform and orient the development of
                 alternative models for governance of a cybersecurity
                 network and a set of criteria for their evaluation.
                 They will support informed decision-making on the most
                 appropriate governance model of a future networked
                 organisation, evolving from a project consortium.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future and Emerging topics in Security
                 for Cyber-Physical Systems.",
}

@Article{Singh:2020:BFB,
  author =       "Parminder Singh and Anand Nayyar and Avinash Kaur and
                 Uttam Ghosh",
  title =        "Blockchain and Fog Based Architecture for {Internet of
                 Everything} in Smart Cities",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "4",
  pages =        "61",
  day =          "26",
  month =        mar,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12040061",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/4/61",
  abstract =     "Fog computing (FC) is used to reduce the energy
                 consumption and latency for the heterogeneous
                 communication approaches in the smart cities'
                 applications of the Internet of Everything (IoE). Fog
                 computing nodes are connected through wired or wireless
                 medium. The goal of smart city applications is to
                 develop the transaction relationship of real-time
                 response applications. There are various frameworks in
                 real-world to support the IoE in smart-cities but they
                 face the issues like security, platform Independence,
                 multi-application assistance, and resource management.
                 This article is motivated from the Blockchain and Fog
                 computing technologies and presents a secured
                 architecture Blockchain and Fog-based Architecture
                 Network (BFAN) for IoE applications in the smart
                 cities. The proposed architecture secures sensitive
                 data with encryption, authentication, and Blockchain.
                 It assists the System-developers and Architects to
                 deploy the applications in smart city paradigm. The
                 goal of the proposed architecture is to reduce the
                 latency and energy, and ensure improved security
                 features through Blockchain technology. The simulation
                 results demonstrate that the proposed architecture
                 performs better than the existing frameworks for
                 smart-cities.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Special Issue on Cyber Physical Systems:
                 Prospects, Challenges, and Role in Software Defined
                 Networking and Blockchain.",
}

@Article{Henriksen-Bulmer:2020:DCA,
  author =       "Jane Henriksen-Bulmer and Shamal Faily and Sheridan
                 Jeary",
  title =        "{DPIA} in Context: Applying {DPIA} to Assess Privacy
                 Risks of Cyber Physical Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "5",
  pages =        "93",
  day =          "24",
  month =        may,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12050093",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/5/93",
  abstract =     "Cyber Physical Systems (CPS) seamlessly integrate
                 physical objects with technology, thereby blurring the
                 boundaries between the physical and virtual
                 environments. While this brings many opportunities for
                 progress, it also adds a new layer of complexity to the
                 risk assessment process when attempting to ascertain
                 what privacy risks this might impose on an
                 organisation. In addition, privacy regulations, such as
                 the General Data Protection Regulation (GDPR), mandate
                 assessment of privacy risks, including making Data
                 Protection Impact Assessments (DPIAs) compulsory. We
                 present the DPIA Data Wheel, a holistic privacy risk
                 assessment framework based on Contextual Integrity
                 (CI), that practitioners can use to inform decision
                 making around the privacy risks of CPS. This framework
                 facilitates comprehensive contextual inquiry into
                 privacy risk, that accounts for both the elicitation of
                 privacy risks, and the identification of appropriate
                 mitigation strategies. Further, by using this DPIA
                 framework we also provide organisations with a means of
                 assessing privacy from both the perspective of the
                 organisation and the individual, thereby facilitating
                 GDPR compliance. We empirically evaluate this framework
                 in three different real-world settings. In doing so, we
                 demonstrate how CI can be incorporated into the privacy
                 risk decision-making process in a usable, practical
                 manner that will aid decision makers in making informed
                 privacy decisions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future and Emerging topics in Security
                 for Cyber-Physical Systems.",
}

@Article{Fakis:2020:NDN,
  author =       "Alexandros Fakis and Georgios Karopoulos and Georgios
                 Kambourakis",
  title =        "Neither Denied nor Exposed: Fixing {WebRTC} Privacy
                 Leaks",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "5",
  pages =        "92",
  day =          "22",
  month =        may,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12050092",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/5/92",
  abstract =     "To establish peer-to-peer connections and achieve
                 real-time web-based communication, the Web Real-Time
                 Communication (WebRTC) framework requires address
                 information of the communicating peers. This means that
                 users behind, say, Network Address Translation (NAT) or
                 firewalls normally rely on the Interactive Connectivity
                 Establishment (ICE) framework for the sake of
                 negotiating information about the connection and media
                 transferring. This typically involves Session Traversal
                 Utilities for NAT (STUN)/Traversal using Relays around
                 NAT (TURN) servers, which assist the peers with
                 discovering each other's private and public IP:port,
                 and relay traffic if direct connection fails.
                 Nevertheless, these IP:port pieces of data can be
                 easily captured by anyone who controls the
                 corresponding STUN/TURN server, and even more become
                 readily available to the JavaScript application running
                 on the webpage. While this is acceptable for a user
                 that deliberately initiates a WebRTC connection, it
                 becomes a worrisome privacy issue for those being
                 unaware that such a connection is attempted.
                 Furthermore, the application acquires more information
                 about the local network architecture compared to what
                 is exposed in usual HTTP interactions, where only the
                 public IP is visible. Even though this problem is
                 well-known in the related literature, no practical
                 solution has been proposed so far. To this end, and for
                 the sake of detecting and preventing in real time the
                 execution of STUN/TURN clandestine, privacy-invading
                 requests, we introduce two different kinds of
                 solutions: (a) a browser extension, and (b) an HTTP
                 gateway, implemented in C++ as well as in Golang. Both
                 solutions detect any WebRTC API call before it happens
                 and inform accordingly the end-user about the webpage's
                 intentions. We meticulously evaluate the proposed
                 schemes in terms of performance and demonstrate that,
                 even in the worst case, the latency introduced is
                 tolerable.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Cybersecurity.",
}

@Article{Yu:2020:BOT,
  author =       "Jingyuan Yu and Juan Mu{\~n}oz-Justicia",
  title =        "A Bibliometric Overview of {Twitter}-Related Studies
                 Indexed in {Web of Science}",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "5",
  pages =        "91",
  day =          "20",
  month =        may,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12050091",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/5/91",
  abstract =     "Twitter has been one of the most popular social
                 network sites for academic research; the main objective
                 of this study was to update the current knowledge
                 boundary surrounding Twitter-related investigations
                 and, further, identify the major research topics and
                 analyze their evolution across time. A bibliometric
                 analysis has been applied in this article: we retrieved
                 19,205 Twitter-related academic articles from Web of
                 Science after several steps of data cleaning and
                 preparation. The R package ``Bibliometrix'' was mainly
                 used in analyzing this content. Our study has two
                 sections, and performance analysis contains 5
                 categories (Annual Scientific Production, Most Relevant
                 Sources, Most Productive Authors, Most Cited
                 Publications, Most Relevant Keywords.). The science
                 mapping included country collaboration analysis and
                 thematic analysis. We highlight our thematic analysis
                 by splitting the whole bibliographic dataset into three
                 temporal periods, thus a thematic evolution across time
                 has been presented. This study is one of the most
                 comprehensive bibliometric overview in analyzing
                 Twitter-related studies by far. We proceed to explain
                 how the results will benefit the understanding of
                 current academic research interests on the social media
                 giant.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Social Web, New Media, Algorithms and
                 Power.",
}

@Article{Kim:2020:MBS,
  author =       "Mihui Kim and Youngmin Kim",
  title =        "Multi-Blockchain Structure for a Crowdsensing-Based
                 Smart Parking System",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "5",
  pages =        "90",
  day =          "16",
  month =        may,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12050090",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/5/90",
  abstract =     "As a representative example for the construction of a
                 smart city, a smart parking system has been developed
                 in past research and implemented through IoT and cloud
                 technologies. However, the initial installation cost of
                 IoT sensor devices is preventing the spread of this
                 technology, and thus as an alternative, a
                 crowdsensing-based system, operating through data from
                 publicly owned mobile devices, has been proposed. In
                 this paper, we propose a multi-blockchain structure
                 (i.e., constructed with public chain and private chain)
                 in a crowdsensing-based smart parking system. In this
                 structure, many sensing data contributors participate
                 through the opened public blockchain, to transparently
                 provide sensing information and to claim corresponding
                 rewards. The private blockchain provides an environment
                 for sharing the collected information among service
                 providers in real time and for providing parking
                 information to users. The bridge node performs an
                 information relay role between the two blockchains.
                 Performance analysis and security analysis on the
                 implemented proposed system show the feasibility of our
                 proposed system.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Internet of Things (IoT) Applications
                 for Industry 4.0.",
}

@Article{Margariti:2020:MST,
  author =       "Spiridoula V. Margariti and Vassilios V. Dimakopoulos
                 and Georgios Tsoumanis",
  title =        "Modeling and Simulation Tools for Fog Computing --- a
                 Comprehensive Survey from a Cost Perspective",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "5",
  pages =        "89",
  day =          "16",
  month =        may,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12050089",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/5/89",
  abstract =     "Fog computing is an emerging and evolving technology,
                 which bridges the cloud with the network edges,
                 allowing computing to work in a decentralized manner.
                 As such, it introduces a number of complex issues to
                 the research community and the industry alike. Both of
                 them have to deal with many open challenges including
                 architecture standardization, resource management and
                 placement, service management, Quality of Service
                 (QoS), communication, participation, to name a few. In
                 this work, we provide a comprehensive literature review
                 along two axes --- modeling with an emphasis in the
                 proposed fog computing architectures and simulation
                 which investigates the simulation tools which can be
                 used to develop and evaluate novel fog-related ideas.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Network Cost Reduction in Cloud/Fog
                 Computing Environments.",
}

@Article{Hsu:2020:REE,
  author =       "Meng-Hsiang Hsu and Chun-Ming Chang and Shing-Ling
                 Wu",
  title =        "Re-examining the Effect of Online Social Support on
                 Subjective Well-Being: The Moderating Role of
                 Experience",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "5",
  pages =        "88",
  day =          "15",
  month =        may,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12050088",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/5/88",
  abstract =     "Building upon the perspectives of social capital
                 theory, social support, and experience, this study
                 developed a theoretical model to investigate the
                 determinants of subjective well-being on social media.
                 This study also examined the moderating role of
                 experience on the relationship between subjective
                 well-being and social support. Data collected from 267
                 social media users in Taiwan were used to test the
                 proposed model. Structural equation modeling analysis
                 was used to test the measurement model and the
                 structural model. The findings reveal that receiving
                 online support and providing online support are the key
                 predictors of subjective well-being. Furthermore,
                 social capital positively influences the reception and
                 provision of online support. Finally, providing online
                 support has a significant effect on the subjective
                 well-being of users with low levels of use experience,
                 while receiving online support exerts a stronger
                 influence on the subjective well-being of users with
                 high levels of use experience.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Social Web, New Media, Algorithms and
                 Power.",
}

@Article{Abonizio:2020:LIF,
  author =       "Hugo Queiroz Abonizio and Janaina Ignacio de Morais
                 and Gabriel Marques Tavares and Sylvio Barbon Junior",
  title =        "Language-Independent Fake News Detection: {English},
                 {Portuguese}, and {Spanish} Mutual Features",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "5",
  pages =        "87",
  day =          "11",
  month =        may,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12050087",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/5/87",
  abstract =     "Online Social Media (OSM) have been substantially
                 transforming the process of spreading news, improving
                 its speed, and reducing barriers toward reaching out to
                 a broad audience. However, OSM are very limited in
                 providing mechanisms to check the credibility of news
                 propagated through their structure. The majority of
                 studies on automatic fake news detection are restricted
                 to English documents, with few works evaluating other
                 languages, and none comparing language-independent
                 characteristics. Moreover, the spreading of deceptive
                 news tends to be a worldwide problem; therefore, this
                 work evaluates textual features that are not tied to a
                 specific language when describing textual data for
                 detecting news. Corpora of news written in American
                 English, Brazilian Portuguese, and Spanish were
                 explored to study complexity, stylometric, and
                 psychological text features. The extracted features
                 support the detection of fake, legitimate, and
                 satirical news. We compared four machine learning
                 algorithms ($k$-Nearest Neighbors ($k$-NN), Support
                 Vector Machine (SVM), Random Forest (RF), and Extreme
                 Gradient Boosting (XGB)) to induce the detection model.
                 Results show our proposed language-independent features
                 are successful in describing fake, satirical, and
                 legitimate news across three different languages, with
                 an average detection accuracy of 85.3\% with RF.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Social Web, New Media, Algorithms and
                 Power.",
}

@Article{Tsoumanis:2020:ITI,
  author =       "Georgios Tsoumanis and Asterios Papamichail and
                 Vasileios Dragonas and George Koufoudakis and
                 Constantinos T. Angelis and Konstantinos Oikonomou",
  title =        "Implementation of a {Topology Independent MAC (TiMAC)}
                 Policy on a Low-Cost {IoT} System",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "5",
  pages =        "86",
  day =          "11",
  month =        may,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12050086",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/5/86",
  abstract =     "The emerging new paradigm under the fifth generation
                 of wireless communications technologies (5G) and high
                 expectations for massively expanding today's Internet
                 of Things (IoT) under 5G, are expected to support a
                 large plurality of low-cost devices for an
                 all-increasing number of new IoT applications. Many
                 emerging IoT applications are going to take advantage
                 of techniques and technologies that have high demands
                 from low-cost devices in terms of processing large
                 amounts of data and communication. For example, in
                 systems based on fog computing technology, low-cost
                 devices have to assign some of their limited resources
                 for processing purposes. Considering the drawbacks
                 emerging from using low-cost devices and the fact that
                 many applications are in need for time-constrained
                 approaches, TDMA-based Medium Access Control (MAC)
                 policies need to be revisited and implemented in
                 low-cost devices of today. In this sense, a policy
                 independent of the underlying topology, TiMAC policy,
                 is considered here and is implemented in low-cost
                 devices using 433 MHz RF modules. Even though the
                 implementation is limited by synchronization issues and
                 a small number of nodes, the obtained experimental
                 results demonstrate the potential for employing
                 TDMA-based MAC policies on IoT systems consisting of
                 low-cost devices.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Network Cost Reduction in Cloud/Fog
                 Computing Environments.",
}

@Article{Diaz-Noci:2020:AIS,
  author =       "Javier D{\'\i}az-Noci",
  title =        "Artificial Intelligence Systems-Aided News and
                 Copyright: Assessing Legal Implications for Journalism
                 Practices",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "5",
  pages =        "85",
  day =          "08",
  month =        may,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12050085",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/5/85",
  abstract =     "Automated news, or artificial intelligence systems
                 (AIS)-aided production of news items, has been
                 developed from 2010 onwards. It comprises a variety of
                 practices in which the use of data, software and human
                 intervention is involved in diverse degrees. This can
                 affect the application of intellectual property and
                 copyright law in many ways. Using comparative legal
                 methods, we examine the implications of them for some
                 legal categories, such as authorship (and hence
                 required originality) and types of works, namely
                 collaborative, derivative and, most especially,
                 collective works. Sui generis and neighboring rights
                 are also considered for examination as being applicable
                 to AIS-aided news outputs. Our main conclusion is that
                 the economics intellectual property rights are
                 guaranteed in any case through collective works. We
                 propose a shorter term of duration before entering
                 public domain. Still, there is a place for more
                 authorial, personal rights. It shows, however, more
                 difficulty when coming to moral rights, especially in
                 Common Law countries.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Social Web, New Media, Algorithms and
                 Power.",
}

@Article{Lee:2020:TBS,
  author =       "Yu-Tse Lee and Jhan-Jia Lin and Jane Yung-Jen Hsu and
                 Ja-Ling Wu",
  title =        "A Time Bank System Design on the Basis of Hyperledger
                 Fabric Blockchain",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "5",
  pages =        "84",
  day =          "08",
  month =        may,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12050084",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/5/84",
  abstract =     "This paper presents a blockchain-based time bank
                 system on the basis of the Hyperledger Fabric
                 framework, which is one of the permissioned blockchain
                 networks. Most of the services provided by existing
                 Time Bank systems were recorded and conducted manually
                 in the past; furthermore, jobs for matching services
                 with receivers were managed by people. Running a time
                 bank in this way will cost lots of time and human
                 resources and, worse, it lacks security. This work
                 designs and realizes a time bank system enabling all
                 the service-related processes being executed and
                 recorded on a blockchain. The matching between
                 services' supply-and-demand tasks can directly be done
                 through autonomous smart contracts. Building a time
                 bank system on blockchain benefits the transaction of
                 time credit which plays the role of digital currency on
                 the system. In addition, the proposed time bank also
                 retains a grading system, allowing its members to give
                 each other a grade for reflecting their degrees of
                 satisfaction about the results provided by the system.
                 This grading system will incentivize the members to
                 provide a better quality of service and adopt a nicer
                 attitude for receiving a service, which may positively
                 endorse the development of a worldwide time bank
                 system.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Selected Papers from the 3rd Annual
                 Decentralized Conference (DECENTRALIZED 2019).",
}

@Article{Aoyagi:2020:MAP,
  author =       "Saizo Aoyagi and Yiping Le and Tetsuo Shimizu and
                 Kazuki Takahashi",
  title =        "Mobile Application to Provide Traffic Congestion
                 Estimates and Tourism Spots to Promote Additional
                 Stopovers",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "5",
  pages =        "83",
  day =          "29",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12050083",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/5/83",
  abstract =     "In Japan, traffic congestions often occur on the
                 expressways connecting tourism areas with the Tokyo
                 metropolitan area. This congestion can be mitigated if
                 tourists delayed their departure of homeward trips to
                 avoid peak traffic hours. A potential method to promote
                 staggered departure times is providing the estimates of
                 near-future traffic congestion. This study hypothesized
                 and experimentally confirmed that some tourists would
                 delay their departure to avoid traffic based on
                 near-future traffic estimates. The experiment was
                 conducted in the Yatsugatake area using a mobile
                 application that provided this information to tourists.
                 The results suggest that approximately 40\% of
                 self-driving tourists will perform an additional
                 stopover if the returning route is congested and
                 near-future traffic congestion estimate is provided.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Selected Papers from ICITE 2019.",
}

@Article{Mescheryakov:2020:DCE,
  author =       "Serg Mescheryakov and Dmitry Shchemelinin and
                 Konstantin Izrailov and Victor Pokussov",
  title =        "Digital Cloud Environment: Present Challenges and
                 Future Forecast",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "5",
  pages =        "82",
  day =          "29",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12050082",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/5/82",
  abstract =     "This article addresses the challenges of a digital
                 cloud environment when it comes to global scalability
                 with a large number of remote servers and an unsecure
                 public cloud, such as Amazon. The goal of the study was
                 to work out an approach for evaluating the reasonable
                 system capacity under heavy workload. For that purpose,
                 Zabbix monitoring solution is used and business metrics
                 are applied in relation to existing system ones. A
                 prediction data model is proposed to compute the future
                 forecast of the user activity based on the collected
                 historical statistics and to verify whether capacity
                 adjustment is possible or not. The results of capacity
                 planning are implemented at Genesys International
                 Telecommunications Company. System analysis of the
                 production environment indicates the possibility to
                 downscale the capacity of certain virtual servers,
                 which allowed savings to the annual operational costs
                 of \$3500 (50\%) for each affected server.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Cyber Security of the Continuous Digital
                 Environment: Challenges, Solutions and Future
                 Directions.",
}

@Article{Imbimbo:2020:ACI,
  author =       "Enrico Imbimbo and Federica Stefanelli and Andrea
                 Guazzini",
  title =        "Adolescent's Collective Intelligence: Empirical
                 Evidence in Real and Online Classmates Groups",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "5",
  pages =        "81",
  day =          "29",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12050081",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/5/81",
  abstract =     "Humans create teams to be more successful in a large
                 variety of tasks. Groups are characterized by an
                 emergent property called collective intelligence, which
                 leads them to be smarter than single individuals.
                 Previous studies proved that collective intelligence
                 characterizes both real and online environments,
                 focusing on adults' performances. In this work, we
                 explored which factors promote group success in an
                 offline and online logical task with adolescents. Five
                 hundred and fifty high school students participated in
                 the experiment and faced Raven's Advanced Progressive
                 Matrices, first by themselves using the computer, then
                 in a group. Groups interactions could have been
                 computer-mediated or face-to-face, and the participants
                 were randomly assigned to one of the two experimental
                 conditions. Results suggest that groups perform better
                 than singles, regardless of the experimental condition.
                 Among adolescents, online groups performance was
                 negatively affected by participants' average perception
                 of group cohesion, the difficulty of the problem, and
                 the number of communicative exchanges that occur in the
                 interaction. On the contrary, the factors that improve
                 their performances were the average intelligence of the
                 teammates, their levels of neuroticism, and the group
                 heterogeneity in terms of social abilities. This work
                 contributes to the literature with a comprehensive
                 model of collective intelligence among young people.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Markopoulos:2020:ISO,
  author =       "Evangelos Markopoulos and Mika Luimula",
  title =        "Immersive Safe Oceans Technology: Developing Virtual
                 Onboard Training Episodes for Maritime Safety",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "5",
  pages =        "80",
  day =          "28",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12050080",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/5/80",
  abstract =     "This paper introduces four safety training episodes
                 and virtual training technology called Immersive Safe
                 Oceans which can be used in further education of
                 professionals in immersive training scenarios. These
                 episodes were developed for maritime safety and are
                 under testing. Immersive Safe Oceans Technology is a
                 cost-effective, portable technology that can be used on
                 board just in time or in maritime training centers.
                 Four introduced episodes, namely, (1) command bridge,
                 (2) machine room, (3) crane, and (4) fire safety,
                 illustrate how Immersive Safe Oceans technology can be
                 used in various professional training scenarios. These
                 episodes also emphasize the growing need for virtual
                 reality training in the shipping industry. As a result,
                 next generation learning will happen onboard in
                 sophisticated virtual training centers.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Cognitive Infocommunications-Theory and
                 Applications.",
}

@Article{McKenna:2020:HSE,
  author =       "H. Patricia McKenna",
  title =        "Human-Smart Environment Interactions in Smart Cities:
                 Exploring Dimensionalities of Smartness",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "5",
  pages =        "79",
  day =          "27",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12050079",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/5/79",
  abstract =     "In the context of the challenges facing human computer
                 interaction (HCI) on the one hand and the future
                 Internet on the other, the purpose of this study is to
                 explore the multi-dimensionality of smart cities,
                 looking at relationships and interdependencies through
                 correlating selected dimensions of smartness. Key
                 dimensions of smartness are identified for exploration
                 in the context of smart cities in this work through a
                 review of the research literature. Methodologically,
                 this work combines an exploratory case study approach
                 consisting of multiple methods of data collection
                 including survey and in-depth interviews, with an
                 explanatory correlational design. In terms of results,
                 the main findings of this work shed light on the
                 relationships between selected dimensions of the
                 multi-dimensionality construct of smartness in
                 data-rich urban environments. This work is significant
                 in that it provides correlational information for smart
                 city dimensionalities while contributing to the
                 research literature in this domain; uses a hybrid case
                 study and correlational design in relation to the study
                 of multi-dimensionality; and, opens spaces for the
                 study of innovative urban initiatives, while taking the
                 ideas and experiences of people from many sectors into
                 consideration.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Smart Cities, Innovation, and
                 Multi-Dimensionality.",
}

@Article{Effendi:2020:SGD,
  author =       "Sedick Baker Effendi and Brink van der Merwe and
                 Wolf-Tilo Balke",
  title =        "Suitability of Graph Database Technology for the
                 Analysis of Spatio-Temporal Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "5",
  pages =        "78",
  day =          "26",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12050078",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/5/78",
  abstract =     "Every day large quantities of spatio-temporal data are
                 captured, whether by Web-based companies for social
                 data mining or by other industries for a variety of
                 applications ranging from disaster relief to marine
                 data analysis. Making sense of all this data
                 dramatically increases the need for intelligent backend
                 systems to provide realtime query response times while
                 scaling well (in terms of storage and performance) with
                 increasing quantities of structured or semi-structured,
                 multi-dimensional data. Currently, relational database
                 solutions with spatial extensions such as PostGIS, seem
                 to come to their limits. However, the use of graph
                 database technology has been rising in popularity and
                 has been found to handle graph-like spatio-temporal
                 data much more effectively. Motivated by the need to
                 effectively store multi-dimensional, interconnected
                 data, this paper investigates whether or not graph
                 database technology is better suited when compared to
                 the extended relational approach. Three database
                 technologies will be investigated using real world
                 datasets namely: PostgreSQL, JanusGraph, and
                 TigerGraph. The datasets used are the Yelp challenge
                 dataset and an ambulance response simulation dataset,
                 thus combining real world spatial data with realistic
                 simulations offering more control over the dataset. Our
                 extensive evaluation is based on how each database
                 performs under practical data analysis scenarios
                 similar to those found on enterprise level.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Sense Making in the Digital World.",
}

@Article{Psomakelis:2020:SSD,
  author =       "Evangelos Psomakelis and Anastasios Nikolakopoulos and
                 Achilleas Marinakis and Alexandros Psychas and Vrettos
                 Moulos and Theodora Varvarigou and Andreas Christou",
  title =        "A Scalable and Semantic Data as a Service Marketplace
                 for Enhancing Cloud-Based Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "5",
  pages =        "77",
  day =          "25",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12050077",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu May 28 15:16:57 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/5/77",
  abstract =     "Data handling and provisioning play a dominant role in
                 the structure of modern cloud--fog-based architectures.
                 Without a strict, fast, and deterministic method of
                 exchanging data we cannot be sure about the performance
                 and efficiency of transactions and applications. In the
                 present work we propose an architecture for a Data as a
                 Service (DaaS) Marketplace, hosted exclusively in a
                 cloud environment. The architecture includes a storage
                 management engine that ensures the Quality of Service
                 (QoS) requirements, a monitoring component that enables
                 real time decisions about the resources used, and a
                 resolution engine that provides semantic data discovery
                 and ranking based on user queries. We show that the
                 proposed system outperforms the classic ElasticSearch
                 queries in data discovery use cases, providing more
                 accurate results. Furthermore, the semantic enhancement
                 of the process adds extra results which extend the user
                 query with a more abstract definition to each notion.
                 Finally, we show that the real-time scaling, provided
                 by the data storage manager component, limits QoS
                 requirements by decreasing the latency of the read and
                 write data requests.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Network Cost Reduction in Cloud/Fog
                 Computing Environments.",
}

@Article{deMeloeSilva:2020:MES,
  author =       "Alessandra {de Melo e Silva} and Jo{\~a}o Jos{\'e}
                 {Costa Gondim} and Robson {de Oliveira Albuquerque} and
                 Luis Javier {Garc{\'\i}a Villalba}",
  title =        "A Methodology to Evaluate Standards and Platforms
                 within Cyber Threat Intelligence",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "6",
  pages =        "108",
  day =          "23",
  month =        jun,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12060108",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jun 30 14:45:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/6/108",
  abstract =     "The cyber security landscape is fundamentally changing
                 over the past years. While technology is evolving and
                 new sophisticated applications are being developed, a
                 new threat scenario is emerging in alarming
                 proportions. Sophisticated threats with multi-vectored,
                 multi-staged and polymorphic characteristics are
                 performing complex attacks, making the processes of
                 detection and mitigation far more complicated. Thus,
                 organizations were encouraged to change their
                 traditional defense models and to use and to develop
                 new systems with a proactive approach. Such changes are
                 necessary because the old approaches are not effective
                 anymore to detect advanced attacks. Also, the
                 organizations are encouraged to develop the ability to
                 respond to incidents in real-time using complex threat
                 intelligence platforms. However, since the field is
                 growing rapidly, today Cyber Threat Intelligence
                 concept lacks a consistent definition and a
                 heterogeneous market has emerged, including diverse
                 systems and tools, with different capabilities and
                 goals. This work aims to provide a comprehensive
                 evaluation methodology of threat intelligence standards
                 and cyber threat intelligence platforms. The proposed
                 methodology is based on the selection of the most
                 relevant candidates to establish the evaluation
                 criteria. In addition, this work studies the Cyber
                 Threat Intelligence ecosystem and Threat Intelligence
                 standards and platforms existing in state-of-the-art.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Collection Information Systems Security.",
}

@Article{AlSuwaidan:2020:VAH,
  author =       "Lulwah AlSuwaidan and Nuha Almegren",
  title =        "Validating the Adoption of Heterogeneous {Internet of
                 Things} with Blockchain",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "6",
  pages =        "107",
  day =          "21",
  month =        jun,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12060107",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jun 30 14:45:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/6/107",
  abstract =     "Emerging technologies such as Internet of Things (IoT)
                 and blockchain have affected the digital
                 transformation. Blockchain, on the one hand, was
                 initially developed for the purpose of financial
                 trading due to its robustness especially for fault
                 tolerance and cryptographic security in addition to its
                 decentralized architecture. IoT, on the other hand, is
                 an open interconnected network of smart devices able to
                 communicate simultaneously. This arises a challenge in
                 privacy and security, specifically for the data being
                 exchanged. To overcome this, studies have focused on
                 the blockchain to resolve the security and privacy
                 issues of IoT. Indeed, limited studies have proposed to
                 assess blockchain's viability for IoT and the
                 associated challenges. In this paper, a conceptual
                 model has proposed to identify the crucial factors
                 affecting the adoption of blockchain in IoT. The model
                 consists of four dimensions of factors that we assume
                 will affect the adoption of the two technologies. The
                 dimensions are: attitude-related factors, social
                 influence related factors, data-related factors, and
                 security-related factors. This model is validated
                 through a survey that was distributed between
                 professionals in blockchain and IoT. The findings show
                 a significant impact of data-related factors on the
                 adoption of blockchain in IoT and the intention to use
                 them. The model can play an important role in the
                 development of strategies, standards, and performance
                 assessment.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Network Economics and Utility
                 Maximization.",
}

@Article{Olszowski:2020:CIP,
  author =       "Rafa{\l} Olszowski and Marcin Chmielowski",
  title =        "Collective Intelligence in {Polish--Ukrainian}
                 {Internet} Projects. {Debate} Models and Research
                 Methods",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "6",
  pages =        "106",
  day =          "20",
  month =        jun,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12060106",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jun 30 14:45:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/6/106",
  abstract =     "In this study, we focus on models of civic debate
                 suitable for use in Polish-Ukrainian internet projects,
                 as well as methods of researching collective
                 intelligence that can help to monitor particular
                 aspects of such debates and consequently create social
                 bridging capital between these groups. The dynamic
                 socio-political situation of recent years, both in
                 Ukraine and in Poland, has created new conditions.
                 Anti-government protests and social turmoil related to
                 the war in Crimea and Donbas, as well as a high level
                 of migration in the region in a short period led to the
                 creation of a multi-ethnic society. This brings
                 opportunities for the development of a new type of
                 social capital: A new participative model of social
                 life based on internet projects, with a relatively low
                 entry barrier, space for creativity, and the widespread
                 use of ICT technologies, can provide the new ways of
                 debating, civic engagement, and collective action. Our
                 research, based on a multidisciplinary literature
                 review, as well as a series of qualitative in-depth
                 interviews (IDIs), proved that the selected collective
                 intelligence (CI) research methods and debate models
                 can help to develop internet communities that will
                 contribute to building bridging capital between Poles
                 and Ukrainians.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Selected Papers from the INSCI2019:
                 Internet Science 2019.",
}

@Article{Bader:2020:SDD,
  author =       "Sebastian R. Bader and Maria Maleshkova",
  title =        "{SOLIOT} --- Decentralized Data Control and
                 Interactions for {IoT}",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "6",
  pages =        "105",
  day =          "16",
  month =        jun,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12060105",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jun 30 14:45:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/6/105",
  abstract =     "The digital revolution affects every aspect of society
                 and economy. In particular, the manufacturing industry
                 faces a new age of production processes and connected
                 collaboration. The underlying ideas and concepts, often
                 also framed as a new ``Internet of Things'', transfer
                 IT technologies to the shop floor, entailing major
                 challenges regarding the heterogeneity of the domain.
                 On the other hand, web technologies have already proven
                 their value in distributed settings. SOLID (derived
                 from ``social linked data'') is a recent approach to
                 decentralize data control and standardize interactions
                 for social applications in the web. Extending this
                 approach towards industrial applications has the
                 potential to bridge the gap between the World Wide Web
                 and local manufacturing environments. This paper
                 proposes SOLIOT --- a combination of lightweight
                 industrial protocols with the integration and data
                 control provided by SOLID. An in-depth requirement
                 analysis examines the potential but also current
                 limitations of the approach. The conceptual
                 capabilities are outlined, compared and extended for
                 the IoT protocols CoAP and MQTT. The feasibility of the
                 approach is illustrated through an open-source
                 implementation, which is evaluated in a virtual test
                 bed and a detailed analysis of the proposed
                 components.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Internet of Things (IoT) Applications
                 for Industry 4.0.",
}

@Article{Lohr:2020:IXH,
  author =       "Christophe Lohr and J{\'e}r{\^o}me Kerdreux",
  title =        "Improvements of the {xAAL} Home Automation System",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "6",
  pages =        "104",
  day =          "12",
  month =        jun,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12060104",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jun 30 14:45:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/6/104",
  abstract =     "The xAAL home automation system has been designed on
                 the basis of distributed systems principles with
                 messages passing and home network communications over
                 IP. The proposal makes extensive use of standards and
                 provides a clear separation of roles along the
                 distributed system with no predominant actor. This
                 allows openness and interoperability. This objective
                 can be reached once all parts are convinced: consumers,
                 manufacturers, service providers, etc. To get a broad
                 adoption, the proposal comes with fine-tuned
                 communication, architecture, security, and simplicity.
                 Tests and experiments in the long term have led us to
                 optimize the protocol, adjust the architecture, and
                 rearrange device descriptions. This paper provides a
                 full description of the improved system, with all
                 details to make feasible compatible alternative
                 implementations. It also discusses alternatives and all
                 aspects that led us to make structuring choices: CBOR
                 messages on an IP multicast channel, intranet
                 communication, ciphering with Poly1305/Chacha20,
                 structured and extensible abstract device description,
                 and a distributed system architecture.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Atlam:2020:RBA,
  author =       "Hany F. Atlam and Muhammad Ajmal Azad and Madini O.
                 Alassafi and Abdulrahman A. Alshdadi and Ahmed
                 Alenezi",
  title =        "Risk-Based Access Control Model: a Systematic
                 Literature Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "6",
  pages =        "103",
  day =          "11",
  month =        jun,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12060103",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jun 30 14:45:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/6/103",
  abstract =     "Most current access control models are rigid, as they
                 are designed using static policies that always give the
                 same outcome in different circumstances. In addition,
                 they cannot adapt to environmental changes and
                 unpredicted situations. With dynamic systems such as
                 the Internet of Things (IoT) with billions of things
                 that are distributed everywhere, these access control
                 models are obsolete. Hence, dynamic access control
                 models are required. These models utilize not only
                 access policies but also contextual and real-time
                 information to determine the access decision. One of
                 these dynamic models is the risk-based access control
                 model. This model estimates the security risk value
                 related to the access request dynamically to determine
                 the access decision. Recently, the risk-based access
                 control model has attracted the attention of several
                 organizations and researchers to provide more
                 flexibility in accessing system resources. Therefore,
                 this paper provides a systematic review and examination
                 of the state-of-the-art of the risk-based access
                 control model to provide a detailed understanding of
                 the topic. Based on the selected search strategy, 44
                 articles (of 1044 articles) were chosen for a closer
                 examination. Out of these articles, the contributions
                 of the selected articles were summarized. In addition,
                 the risk factors used to build the risk-based access
                 control model were extracted and analyzed. Besides, the
                 risk estimation techniques used to evaluate the risks
                 of access control operations were identified.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Emerging Trends of Fog Computing in
                 Internet of Things Applications.",
}

@Article{Li:2020:CCM,
  author =       "KeDi Li and Ning Gui",
  title =        "{CMS}: A Continuous Machine-Learning and Serving
                 Platform for Industrial Big Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "6",
  pages =        "102",
  day =          "10",
  month =        jun,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12060102",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jun 30 14:45:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/6/102",
  abstract =     "The life-long monitoring and analysis for complex
                 industrial equipment demands a continuously evolvable
                 machine-learning platform. The machine-learning model
                 must be quickly regenerated and updated. This demands
                 the careful orchestration of trainers for model
                 generation and modelets for model serving without the
                 interruption of normal operations. This paper proposes
                 a container-based Continuous Machine-Learning and
                 Serving (CMS) platform. By designing out-of-the-box
                 common architecture for trainers and modelets, it
                 simplifies the model training and deployment process
                 with minimal human interference. An orchestrator is
                 proposed to manage the trainer's execution and enables
                 the model updating without interrupting the online
                 operation of model serving. CMS has been deployed in a
                 1000 MW thermal power plant for about five months. The
                 system running results show that the accuracy of eight
                 models remains at a good level even when they
                 experience major renovations. Moreover, CMS proved to
                 be a resource-efficient, effective resource isolation
                 and seamless model switching with little overhead.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Network Architectures and Protocols for
                 Industrial IoT.",
}

@Article{Olmedo:2020:PAN,
  author =       "Gonzalo Olmedo and Rom{\'a}n Lara-Cueva and Diego
                 Mart{\'\i}nez and Celso de Almeida",
  title =        "Performance Analysis of a Novel {TCP} Protocol
                 Algorithm Adapted to Wireless Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "6",
  pages =        "101",
  day =          "09",
  month =        jun,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12060101",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jun 30 14:45:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/6/101",
  abstract =     "As telecommunication systems evolve towards
                 new-generation architectures, likewise, new protocols
                 are created in order to improve efficiency. One of
                 these protocols is Transmission Control Protocol (TCP),
                 which controls the transmission bit rate in function of
                 network congestion. Nevertheless, in wireless
                 communications, there appear problems such as noise and
                 interference, for which TCP was not designed. Based on
                 these problems, there exist some methods trying to
                 mitigate congestion, such as explicit loss
                 notifications and the use of end-to-end codification.
                 The aim of this work was to propose a wireless TCP
                 protocol improvement, considering a negative
                 acknowledgment (NACK), which allows to differentiate
                 between losses due to congestion and losses due to
                 wireless channel issues. NACK employs a small protocol
                 packet and produces improvement in the quality of
                 service metrics. The experiments were carried out in
                 in-door and out-door environments, over an online video
                 game scenario, and over a long-distance wireless link
                 between two islands. The average results show a
                 25-percent delay improvement and a 5-percent jitter
                 improvement when compared to the original TCP Reno
                 protocol, while for throughput a 90-percent improvement
                 was achieved for distances between 100 and 414 m.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2020:PMV,
  author =       "Jiao Wang and Jay Weitzen and Oguz Bayat and Volkan
                 Sevindik and Mingzhe Li",
  title =        "Performance Model for Video Service in {5G} Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "6",
  pages =        "99",
  day =          "08",
  month =        jun,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12060099",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jun 30 14:45:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/6/99",
  abstract =     "Network slicing allows operators to sell customized
                 slices to various tenants at different prices. To
                 provide better-performing and cost-efficient services,
                 network slicing is looking to intelligent resource
                 management approaches to be aligned to users'
                 activities per slice. In this article, we propose a
                 radio access network (RAN) slicing design methodology
                 for quality of service (QoS) provisioning, for
                 differentiated services in a 5G network. A performance
                 model is constructed for each service using machine
                 learning (ML)-based approaches, optimized using
                 interference coordination approaches, and used to
                 facilitate service level agreement (SLA) mapping to the
                 radio resource. The optimal bandwidth allocation is
                 dynamically adjusted based on instantaneous network
                 load conditions. We investigate the application of
                 machine learning in solving the radio resource slicing
                 problem and demonstrate the advantage of machine
                 learning through extensive simulations. A case study is
                 presented to demonstrate the effectiveness of the
                 proposed radio resource slicing approach.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future Networks: Latest Trends and
                 Developments.",
}

@Article{Hurst:2020:PPV,
  author =       "William Hurst and Aaron Boddy and Madjid Merabti and
                 Nathan Shone",
  title =        "Patient Privacy Violation Detection in Healthcare
                 Critical Infrastructures: an Investigation Using
                 Density-Based Benchmarking",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "6",
  pages =        "100",
  day =          "08",
  month =        jun,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12060100",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jun 30 14:45:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/6/100",
  abstract =     "Hospital critical infrastructures have a distinct
                 threat vector, due to (i) a dependence on legacy
                 software; (ii) the vast levels of interconnected
                 medical devices; (iii) the use of multiple bespoke
                 software and that (iv) electronic devices (e.g.,
                 laptops and PCs) are often shared by multiple users. In
                 the UK, hospitals are currently upgrading towards the
                 use of electronic patient record (EPR) systems. EPR
                 systems and their data are replacing traditional paper
                 records, providing access to patients' test results and
                 details of their overall care more efficiently. Paper
                 records are no-longer stored at patients' bedsides, but
                 instead are accessible via electronic devices for the
                 direct insertion of data. With over 83\% of hospitals
                 in the UK moving towards EPRs, access to this
                 healthcare data needs to be monitored proactively for
                 malicious activity. It is paramount that hospitals
                 maintain patient trust and ensure that the information
                 security principles of integrity, availability and
                 confidentiality are upheld when deploying EPR systems.
                 In this paper, an investigation methodology is
                 presented towards the identification of anomalous
                 behaviours within EPR datasets. Many security solutions
                 focus on a perimeter-based approach; however, this
                 approach alone is not enough to guarantee security, as
                 can be seen from the many examples of breaches. Our
                 proposed system can be complementary to existing
                 security perimeter solutions. The system outlined in
                 this research employs an internal-focused methodology
                 for anomaly detection by using the Local Outlier Factor
                 (LOF) and Density-Based Spatial Clustering of
                 Applications with Noise (DBSCAN) algorithms for
                 benchmarking behaviour, for assisting healthcare data
                 analysts. Out of 90,385 unique IDs, DBSCAN finds 102
                 anomalies, whereas 358 are detected using LOF.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Internet of Healthcare Things (IoHT):
                 Methods, Advances, and Applications.",
}

@Article{Kratzke:2020:VHC,
  author =       "Nane Kratzke",
  title =        "Volunteer Down: How {COVID-19} Created the Largest
                 Idling Supercomputer on {Earth}",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "6",
  pages =        "98",
  day =          "06",
  month =        jun,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12060098",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jun 30 14:45:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/super.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/6/98",
  abstract =     "From close to scratch, the COVID-19 pandemic created
                 the largest volunteer supercomputer on earth. Sadly,
                 processing resources assigned to the corresponding
                 [email protected] project cannot be shared with other
                 volunteer computing projects efficiently. Consequently,
                 the largest supercomputer had significant idle times.
                 This perspective paper investigates how the resource
                 sharing of future volunteer computing projects could be
                 improved. Notably, efficient resource sharing has been
                 optimized throughout the last ten years in cloud
                 computing. Therefore, this perspective paper reviews
                 the current state of volunteer and cloud computing to
                 analyze what both domains could learn from each other.
                 It turns out that the disclosed resource sharing
                 shortcomings of volunteer computing could be addressed
                 by technologies that have been invented, optimized, and
                 adapted for entirely different purposes by cloud-native
                 companies like Uber, Airbnb, Google, or Facebook.
                 Promising technologies might be containers, serverless
                 architectures, image registries, distributed service
                 registries, and all have one thing in common: They
                 already exist and are all tried and tested in large
                 web-scale deployments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Cloud-Native Applications and
                 Services.",
}

@Article{Curreri:2020:ISM,
  author =       "Francesco Curreri and Giacomo Fiumara and Maria
                 Gabriella Xibilia",
  title =        "Input Selection Methods for Soft Sensor Design: a
                 Survey",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "6",
  pages =        "97",
  day =          "04",
  month =        jun,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12060097",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jun 30 14:45:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/6/97",
  abstract =     "Soft Sensors (SSs) are inferential models used in many
                 industrial fields. They allow for real-time estimation
                 of hard-to-measure variables as a function of available
                 data obtained from online sensors. SSs are generally
                 built using industries historical databases through
                 data-driven approaches. A critical issue in SS design
                 concerns the selection of input variables, among those
                 available in a candidate dataset. In the case of
                 industrial processes, candidate inputs can reach great
                 numbers, making the design computationally demanding
                 and leading to poorly performing models. An input
                 selection procedure is then necessary. Most used input
                 selection approaches for SS design are addressed in
                 this work and classified with their benefits and
                 drawbacks to guide the designer through this step.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Collection Featured Reviews of Future Internet
                 Research.",
}

@Article{Pan:2020:MSN,
  author =       "Yirong Pan and Xiao Li and Yating Yang and Rui Dong",
  title =        "Multi-Source Neural Model for Machine Translation of
                 Agglutinative Language",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "6",
  pages =        "96",
  day =          "03",
  month =        jun,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12060096",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jun 30 14:45:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/6/96",
  abstract =     "Benefitting from the rapid development of artificial
                 intelligence (AI) and deep learning, the machine
                 translation task based on neural networks has achieved
                 impressive performance in many high-resource language
                 pairs. However, the neural machine translation (NMT)
                 models still struggle in the translation task on
                 agglutinative languages with complex morphology and
                 limited resources. Inspired by the finding that
                 utilizing the source-side linguistic knowledge can
                 further improve the NMT performance, we propose a
                 multi-source neural model that employs two separate
                 encoders to encode the source word sequence and the
                 linguistic feature sequences. Compared with the
                 standard NMT model, we utilize an additional encoder to
                 incorporate the linguistic features of lemma,
                 part-of-speech (POS) tag, and morphological tag by
                 extending the input embedding layer of the encoder.
                 Moreover, we use a serial combination method to
                 integrate the conditional information from the encoders
                 with the outputs of the decoder, which aims to enhance
                 the neural model to learn a high-quality context
                 representation of the source sentence. Experimental
                 results show that our approach is effective for the
                 agglutinative language translation, which achieves the
                 highest improvements of +2.4 BLEU points on
                 Turkish--English translation task and +0.6 BLEU points
                 on Uyghur--Chinese translation task.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Big Data and Augmented Intelligence.",
}

@Article{Bendechache:2020:SRM,
  author =       "Malika Bendechache and Sergej Svorobej and Patricia
                 Takako Endo and Theo Lynn",
  title =        "Simulating Resource Management across the
                 Cloud-to-Thing Continuum: a Survey and Future
                 Directions",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "6",
  pages =        "95",
  day =          "29",
  month =        may,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12060095",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jun 30 14:45:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/6/95",
  abstract =     "In recent years, there has been significant
                 advancement in resource management mechanisms for cloud
                 computing infrastructure performance in terms of cost,
                 quality of service (QoS) and energy consumption. The
                 emergence of the Internet of Things has led to the
                 development of infrastructure that extends beyond
                 centralised data centers from the cloud to the edge,
                 the so-called cloud-to-thing continuum (C2T). This
                 infrastructure is characterised by extreme
                 heterogeneity, geographic distribution, and complexity,
                 where the key performance indicators (KPIs) for the
                 traditional model of cloud computing may no longer
                 apply in the same way. Existing resource management
                 mechanisms may not be suitable for such complex
                 environments and therefore require thorough testing,
                 validation and evaluation before even being considered
                 for live system implementation. Similarly, previously
                 discounted resource management proposals may be more
                 relevant and worthy of revisiting. Simulation is a
                 widely used technique in the development and evaluation
                 of resource management mechanisms for cloud computing
                 but is a relatively nascent research area for new C2T
                 computing paradigms such as fog and edge computing. We
                 present a methodical literature analysis of C2T
                 resource management research using simulation software
                 tools to assist researchers in identifying suitable
                 methods, algorithms, and simulation approaches for
                 future research. We analyse 35 research articles from a
                 total collection of 317 journal articles published from
                 January 2009 to March 2019. We present our descriptive
                 and synthetic analysis from a variety of perspectives
                 including resource management, C2T layer, and
                 simulation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Network Cost Reduction in Cloud/Fog
                 Computing Environments.",
}

@Article{Ebner:2020:CEL,
  author =       "Martin Ebner and Sandra Sch{\"o}n and Clarissa Braun
                 and Markus Ebner and Ypatios Grigoriadis and Maria Haas
                 and Philipp Leitner and Behnam Taraghi",
  title =        "{COVID-19} Epidemic as E-Learning Boost?
                 {Chronological} Development and Effects at an
                 {Austrian} University against the Background of the
                 Concept of {``E-Learning} Readiness''",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "6",
  pages =        "94",
  day =          "26",
  month =        may,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12060094",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jun 30 14:45:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/6/94",
  abstract =     "The COVID-19 crisis influenced universities worldwide
                 in early 2020. In Austria, all universities were closed
                 in March 2020 as a preventive measure, and meetings
                 with over 100 people were banned and a curfew was
                 imposed. This development also had a massive impact on
                 teaching, which in Austria takes place largely
                 face-to-face. In this paper we would like to describe
                 the situation of an Austrian university regarding
                 e-learning before and during the first three weeks of
                 the changeover of the teaching system, using the
                 example of Graz University of Technology (TU Graz). The
                 authors provide insights into the internal procedures,
                 processes and decisions of their university and present
                 figures on the changed usage behaviour of their
                 students and teachers. As a theoretical reference, the
                 article uses the e-learning readiness assessment
                 according to Alshaher (2013), which provides a
                 framework for describing the status of the situation
                 regarding e-learning before the crisis. The paper
                 concludes with a description of enablers, barriers and
                 bottlenecks from the perspective of the members of the
                 Educational Technology department.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Computational Thinking.",
}

@Article{Hewage:2020:MQE,
  author =       "Chaminda Hewage and Erhan Ekmekcioglu",
  title =        "Multimedia Quality of Experience ({QoE}): Current
                 Status and Future Direction",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "7",
  pages =        "121",
  day =          "20",
  month =        jul,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12070121",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 24 13:38:26 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/7/121",
  abstract =     "Quality of Experience (QoE) is becoming an important
                 factor of User-Centred Design (UCD). The deployment of
                 pure technical measures such as Quality of Service
                 (QoS) parameters to assess the quality of multimedia
                 applications is phasing out due to the failure of those
                 methods to quantify true user satisfaction. Though
                 significant research results and several deployments
                 have occurred and been realized over the last few
                 years, focusing on QoE-based multimedia technologies,
                 several issues both of theoretical and practical
                 importance remain open. Accordingly, the papers of this
                 Special Issue are significant contribution samples
                 within the general ecosystem highlighted above, ranging
                 from QoE in the capture, processing and consumption of
                 next-generation multimedia applications. In particular,
                 a total of five excellent articles have been accepted,
                 following a rigorous review process, which address many
                 of the aforementioned challenges and beyond.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Multimedia Quality of Experience (QoE):
                 Current Status and Future Direction.",
}

@Article{Mallikarachchi:2020:DCR,
  author =       "Thanuja Mallikarachchi and Dumidu Talagala and
                 Hemantha Kodikara Arachchi and Chaminda Hewage and Anil
                 Fernando",
  title =        "A Decoding-Complexity and Rate-Controlled Video-Coding
                 Algorithm for {HEVC}",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "7",
  pages =        "120",
  day =          "16",
  month =        jul,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12070120",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 24 13:38:26 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/7/120",
  abstract =     "Video playback on mobile consumer electronic (CE)
                 devices is plagued by fluctuations in the network
                 bandwidth and by limitations in processing and energy
                 availability at the individual devices. Seen as a
                 potential solution, the state-of-the-art adaptive
                 streaming mechanisms address the first aspect, yet the
                 efficient control of the decoding-complexity and the
                 energy use when decoding the video remain unaddressed.
                 The quality of experience (QoE) of the end-users'
                 experiences, however, depends on the capability to
                 adapt the bit streams to both these constraints (i.e.,
                 network bandwidth and device's energy availability). As
                 a solution, this paper proposes an encoding framework
                 that is capable of generating video bit streams with
                 arbitrary bit rates and decoding-complexity levels
                 using a decoding-complexity--rate--distortion model.
                 The proposed algorithm allocates rate and
                 decoding-complexity levels across frames and coding
                 tree units (CTUs) and adaptively derives the CTU-level
                 coding parameters to achieve their imposed targets with
                 minimal distortion. The experimental results reveal
                 that the proposed algorithm can achieve the target bit
                 rate and the decoding-complexity with 0.4\% and 1.78\%
                 average errors, respectively, for multiple bit rate and
                 decoding-complexity levels. The proposed algorithm also
                 demonstrates a stable frame-wise rate and
                 decoding-complexity control capability when achieving a
                 decoding-complexity reduction of 10.11 (\%/dB). The
                 resultant decoding-complexity reduction translates into
                 an overall energy-consumption reduction of up to 10.52
                 (\%/dB) for a 1 dB peak signal-to-noise ratio (PSNR)
                 quality loss compared to the HM 16.0 encoded bit
                 streams.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Multimedia Quality of Experience (QoE):
                 Current Status and Future Direction.",
}

@Article{Barletta:2020:IDV,
  author =       "Vita Santa Barletta and Danilo Caivano and Antonella
                 Nannavecchia and Michele Scalera",
  title =        "Intrusion Detection for in-Vehicle Communication
                 Networks: An Unsupervised {Kohonen} {SOM} Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "7",
  pages =        "119",
  day =          "14",
  month =        jul,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12070119",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 24 13:38:26 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/7/119",
  abstract =     "The diffusion of embedded and portable communication
                 devices on modern vehicles entails new security risks
                 since in-vehicle communication protocols are still
                 insecure and vulnerable to attacks. Increasing interest
                 is being given to the implementation of automotive
                 cybersecurity systems. In this work we propose an
                 efficient and high-performing intrusion detection
                 system based on an unsupervised Kohonen Self-Organizing
                 Map (SOM) network, to identify attack messages sent on
                 a Controller Area Network (CAN) bus. The SOM network
                 found a wide range of applications in intrusion
                 detection because of its features of high detection
                 rate, short training time, and high versatility. We
                 propose to extend the SOM network to intrusion
                 detection on in-vehicle CAN buses. Many hybrid
                 approaches were proposed to combine the SOM network
                 with other clustering methods, such as the k-means
                 algorithm, in order to improve the accuracy of the
                 model. We introduced a novel distance-based procedure
                 to integrate the SOM network with the K-means algorithm
                 and compared it with the traditional procedure. The
                 models were tested on a car hacking dataset concerning
                 traffic data messages sent on a CAN bus, characterized
                 by a large volume of traffic with a low number of
                 features and highly imbalanced data distribution. The
                 experimentation showed that the proposed method greatly
                 improved detection accuracy over the traditional
                 approach.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Vehicular Networks and Mobility as
                 Service.",
}

@Article{Guazzini:2020:CFC,
  author =       "Andrea Guazzini and Elisa Guidi and Cristina Cecchini
                 and Eiko Yoneki",
  title =        "Collaborative Facilitation and Collaborative
                 Inhibition in Virtual Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "7",
  pages =        "118",
  day =          "13",
  month =        jul,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12070118",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 24 13:38:26 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/7/118",
  abstract =     "Worldwide, organizations and small and medium-sized
                 enterprises have already disruptively changed in many
                 ways their physiological inner mechanisms, because of
                 information and communication technologies (ICT)
                 revolution. Nevertheless, the still ongoing COVID-19
                 worldwide emergency definitely promoted a wide adoption
                 of teleworking modalities for many people around the
                 world, making it more relevant than before to
                 understand the real impact of virtual environments
                 (VEs) on teamwork dynamics. From a psychological point
                 of view, a critical question about teleworking
                 modalities is how the social and cognitive dynamics of
                 collaborative facilitation and collaborative inhibition
                 would affect teamwork within VEs. This study analyzed
                 the impact of a virtual environment (VE) on the recall
                 of individuals and members of nominal and collaborative
                 groups. The research assessed costs and benefits for
                 collaborative retrieval by testing the effect of
                 experimental conditions, stimulus materials, group
                 size, experimental conditions order, anxiety state,
                 personality traits, gender group composition and social
                 interactions. A total of 144 participants were engaged
                 in a virtual Deese-Roediger-McDermott (DRM) classical
                 paradigm, which involved remembering word lists across
                 two successive sessions, in one of four protocols: I
                 -individual/nominal, I I -nominal/individual, I I I
                 -nominal/collaborative, I V -collaborative/nominal.
                 Results suggested, in general, a reduced collaborative
                 inhibition effect in the collaborative condition than
                 the nominal and individual condition. A combined effect
                 between experimental condition and difficulty of the
                 task appears to explain the presence of collaborative
                 inhibition or facilitation. Nominal groups appeared to
                 enhance the collaborative groups' performance when
                 virtual nominal groups come before collaborative
                 groups. Variables such as personality traits, gender
                 and social interactions may have a contribution to
                 collaborative retrieval. In conclusion, this study
                 indicated how VEs could maintain those peculiar social
                 dynamics characterizing the participants' engagement in
                 a task, both working together and individually, and
                 could affect their intrinsic motivation as well as
                 performances. These results could be exploited in order
                 to design brand new and evidenced-based practices, to
                 improve teleworking procedures and workers well-being,
                 as well as teleworking teamwork effectiveness.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Selected Papers from the INSCI2019:
                 Internet Science 2019.",
}

@Article{Graziani:2020:ITA,
  author =       "Salvatore Graziani and Maria Gabriella Xibilia",
  title =        "Innovative Topologies and Algorithms for Neural
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "7",
  pages =        "117",
  day =          "11",
  month =        jul,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12070117",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 24 13:38:26 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/7/117",
  abstract =     "The introduction of new topologies and training
                 procedures to deep neural networks has solicited a
                 renewed interest in the field of neural computation.
                 The use of deep structures has significantly improved
                 the state of the art in many applications, such as
                 computer vision, speech and text processing, medical
                 applications, and IoT (Internet of Things). The
                 probability of a successful outcome from a neural
                 network is linked to selection of an appropriate
                 network architecture and training algorithm.
                 Accordingly, much of the recent research on neural
                 networks is devoted to the study and proposal of novel
                 architectures, including solutions tailored to specific
                 problems. The papers of this Special Issue make
                 significant contributions to the above-mentioned fields
                 by merging theoretical aspects and relevant
                 applications. Twelve papers are collected in the issue,
                 addressing many relevant aspects of the topic.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Innovative Topologies and Algorithms for
                 Neural Networks.",
}

@Article{Molinaro:2020:VCN,
  author =       "Antonella Molinaro and Claudia Campolo and
                 J{\'e}r{\^o}me H{\"a}rri and Christian Esteve
                 Rothenberg and Alexey Vinel",
  title =        "{5G-V2X} Communications and Networking for Connected
                 and Autonomous Vehicles",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "7",
  pages =        "116",
  day =          "08",
  month =        jul,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12070116",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 24 13:38:26 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/7/116",
  abstract =     "The introduction of new topologies and training
                 procedures to deep neural networks has solicited a
                 renewed interest in the field of neural computation.
                 The use of deep structures has significantly improved
                 the state of the art in many applications, such as
                 computer vision, speech and text processing, medical
                 applications, and IoT (Internet of Things). The
                 probability of a successful outcome from a neural
                 network is linked to selection of an appropriate
                 network architecture and training algorithm.
                 Accordingly, much of the recent research on neural
                 networks is devoted to the study and proposal of novel
                 architectures, including solutions tailored to specific
                 problems. The papers of this Special Issue make
                 significant contributions to the above-mentioned fields
                 by merging theoretical aspects and relevant
                 applications. Twelve papers are collected in the issue,
                 addressing many relevant aspects of the topic.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 5G-V2X Communications and Networking for
                 Connected and Autonomous Vehicles.",
}

@Article{Pacini:2020:SCS,
  author =       "Giovanna Pacini and Cinzia Belmonte and Franco
                 Bagnoli",
  title =        "Science Caf{\'e}s, Science Shops and the Lockdown
                 Experience in {Florence} and {Rome}",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "7",
  pages =        "115",
  day =          "08",
  month =        jul,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12070115",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 24 13:38:26 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/7/115",
  abstract =     "The lockdown was crucial to stop the COVID-19 pandemic
                 in Italy, but it affected many aspects of social life,
                 among which traditional live science caf{\'e}s.
                 Moreover, citizens and experts asked for a direct
                 contact, not relying on mass-media communication. In
                 this paper, we describe how the Florence and Rome
                 science caf{\'e}s, contacted by citizens and experts,
                 either directly or through the Florence science shop,
                 responded to these needs by organizing online versions
                 of traditional face-to-face events, experiencing high
                 levels of participation. The science caf{\'e}
                 methodology was also requested by a high school that
                 needed to conclude an engagement experience with
                 students and their families. We also report the results
                 of a survey about the satisfaction of this new
                 methodology with respect to the old one.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Selected Papers from the INSCI2019:
                 Internet Science 2019.",
}

@Article{Goncalves:2020:IBF,
  author =       "Rosiberto Gon{\c{c}}alves and Jesse J. M. Soares and
                 Ricardo M. F. Lima",
  title =        "An {IoT}-Based Framework for Smart Water Supply
                 Systems Management",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "7",
  pages =        "114",
  day =          "07",
  month =        jul,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12070114",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 24 13:38:26 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/7/114",
  abstract =     "The world's population growth and climate changes
                 increase the demand for high-quality water. This fact
                 forces humankind to create new water management
                 strategies. Smart cities have successfully applied the
                 Internet of Things (IoT) technology in many sectors.
                 Moreover, Complex Event Processing (CEP) can analyze
                 and process large data sets produced by IoT sensors in
                 real-time. Traditional business processes are too rigid
                 in expressing the dynamic behavior of water supply
                 systems. Every execution path must be explicitly
                 specified. On the other hand, declarative business
                 processes allow execution paths that are not prohibited
                 by the rules, providing more flexibility for water
                 supply managers. This paper joins together IoT, CEP,
                 and declarative processes to create a powerful,
                 efficient, and flexible architecture (REFlex Water) to
                 manage water supply systems. To the knowledge of the
                 authors, REFlex Water is the first solution to combine
                 these technologies in the context of water supply
                 systems. The paper describes the REFlex Water
                 architecture and demonstrates its application to a real
                 water system from a Brazilian municipality. Results are
                 promising, and the managers from the Brazilian water
                 company are expanding the use of REFlex Water to other
                 sectors of their water supply system.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Internet of Things for Smart City
                 Applications.",
}

@Article{Capra:2020:USE,
  author =       "Maurizio Capra and Beatrice Bussolino and Alberto
                 Marchisio and Muhammad Shafique and Guido Masera and
                 Maurizio Martina",
  title =        "An Updated Survey of Efficient Hardware Architectures
                 for Accelerating Deep Convolutional Neural Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "7",
  pages =        "113",
  day =          "07",
  month =        jul,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12070113",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 24 13:38:26 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/7/113",
  abstract =     "Deep Neural Networks (DNNs) are nowadays a common
                 practice in most of the Artificial Intelligence (AI)
                 applications. Their ability to go beyond human
                 precision has made these networks a milestone in the
                 history of AI. However, while on the one hand they
                 present cutting edge performance, on the other hand
                 they require enormous computing power. For this reason,
                 numerous optimization techniques at the hardware and
                 software level, and specialized architectures, have
                 been developed to process these models with high
                 performance and power/energy efficiency without
                 affecting their accuracy. In the past, multiple surveys
                 have been reported to provide an overview of different
                 architectures and optimization techniques for efficient
                 execution of Deep Learning (DL) algorithms. This work
                 aims at providing an up-to-date survey, especially
                 covering the prominent works from the last 3 years of
                 the hardware architectures research for DNNs. In this
                 paper, the reader will first understand what a hardware
                 accelerator is, and what are its main components,
                 followed by the latest techniques in the field of
                 dataflow, reconfigurability, variable bit-width, and
                 sparsity.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Collection Featured Reviews of Future Internet
                 Research.",
}

@Article{Shen:2020:SDR,
  author =       "Bingqing Shen and Weiming Tan and Jingzhi Guo and
                 Hongming Cai and Bin Wang and Shuaihe Zhuo",
  title =        "A Study on Design Requirement Development and
                 Satisfaction for Future Virtual World Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "7",
  pages =        "112",
  day =          "06",
  month =        jul,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12070112",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 24 13:38:26 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/7/112",
  abstract =     "Virtual worlds have become global platforms connecting
                 millions of people and containing various technologies.
                 For example, No Man's Sky (nomanssky.com), a
                 cross-platform virtual world, can dynamically and
                 automatically generate content with the progress of
                 user adventure. AltspaceVR (altvr.com) is a social
                 virtual reality platform supporting motion capture
                 through Microsoft's Kinect, eye tracking, and mixed
                 reality extension. The changes in industrial
                 investment, market revenue, user population, and
                 consumption drive the evolution of
                 virtual-world-related technologies (e.g., computing
                 infrastructure and interaction devices), which turns
                 into new design requirements and thus results in the
                 requirement satisfaction problem in virtual world
                 system architecture design. In this paper, we first
                 study the new or evolving features of virtual worlds
                 and emerging requirements of system development through
                 market/industry trend analysis, including
                 infrastructure mobility, content diversity, function
                 interconnectivity, immersive environment, and
                 intelligent agents. Based on the trend analysis, we
                 propose a new design requirement space. We, then,
                 discuss the requirement satisfaction of existing system
                 architectures and highlight their limitations through a
                 literature review. The feature-based requirement
                 satisfaction comparison of existing system
                 architectures sheds some light on the future virtual
                 world system development to match the changing trends
                 of the user market. At the end of this study, a new
                 architecture from an ongoing research, called Virtual
                 Net, is discussed, which can provide higher resource
                 sufficiency, computing reliability, content
                 persistency, and service credibility.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue VR, AR, and 3-D User Interfaces for
                 Measurement and Control.",
}

@Article{Kashevnik:2020:HPA,
  author =       "Alexey Kashevnik and Mikhail Kruglov and Igor Lashkov
                 and Nikolay Teslya and Polina Mikhailova and Evgeny
                 Ripachev and Vladislav Malutin and Nikita Saveliev and
                 Igor Ryabchikov",
  title =        "Human Psychophysiological Activity Estimation Based on
                 Smartphone Camera and Wearable Electronics",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "7",
  pages =        "111",
  day =          "01",
  month =        jul,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12070111",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 24 13:38:26 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/7/111",
  abstract =     "This paper presents a study related to human
                 psychophysiological activity estimation based on a
                 smartphone camera and sensors. In recent years,
                 awareness of the human body, as well as human mental
                 states, has become more and more popular. Yoga and
                 meditation practices have moved from the east to
                 Europe, the USA, Russia, and other countries, and there
                 are a lot of people who are interested in them.
                 However, recently, people have tried the practice but
                 would prefer an objective assessment. We propose to
                 apply the modern methods of computer vision, pattern
                 recognition, competence management, and dynamic
                 motivation to estimate the quality of the meditation
                 process and provide the users with objective
                 information about their practice. We propose an
                 approach that covers the possibility of recognizing
                 pictures of humans from a smartphone and utilizes
                 wearable electronics to measure the user's heart rate
                 and motions. We propose a model that allows building
                 meditation estimation scores based on these parameters.
                 Moreover, we propose a meditation expert network
                 through which users can find the coach that is most
                 appropriate for him/her. Finally, we propose the
                 dynamic motivation model, which encourages people to
                 perform the practice every day.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Recent Advances of Machine Learning
                 Techniques on Smartphones.",
}

@Article{Sindermann:2020:IRB,
  author =       "Cornelia Sindermann and Ren{\'e} Riedl and Christian
                 Montag",
  title =        "Investigating the Relationship between Personality and
                 Technology Acceptance with a Focus on the Smartphone
                 from a Gender Perspective: Results of an Exploratory
                 Survey Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "7",
  pages =        "110",
  day =          "30",
  month =        jun,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12070110",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 24 13:38:26 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/7/110",
  abstract =     "Prior research found that user personality
                 significantly affects technology acceptance perceptions
                 and decisions. Yet, evidence on the moderating
                 influence of user gender on the relationship between
                 personality and technology acceptance is barely
                 existent despite theoretical consideration. Considering
                 this research gap, the present study reports the
                 results of a survey in which we examined the
                 relationships between personality and technology
                 acceptance from a gender perspective. This study draws
                 upon a sample of N = 686 participants ( n = 209 men, n
                 = 477 women) and applied the HEXACO Personality
                 Inventory---Revised along with established technology
                 acceptance measures. The major result of this study is
                 that we do not find significant influence of user
                 gender on the relationship between personality and
                 technology acceptance, except for one aspect of
                 personality, namely altruism. We found a negative
                 association between altruism and intention to use the
                 smartphone in men, but a positive association in women.
                 Consistent with this finding, we also found the same
                 association pattern for altruism and predicted usage: a
                 negative one in men and a positive one in women.
                 Implications for research and practice are discussed,
                 along with limitations of the present study and
                 possible avenues for future research.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Selected Papers from the INSCI2019:
                 Internet Science 2019.",
}

@Article{Maniou:2020:ECN,
  author =       "Theodora A. Maniou and Andreas Veglis",
  title =        "Employing a Chatbot for News Dissemination during
                 Crisis: Design, Implementation and Evaluation",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "7",
  pages =        "109",
  day =          "30",
  month =        jun,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12070109",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 24 13:38:26 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/7/109",
  abstract =     "The use of chatbots in news media platforms, although
                 relatively recent, offers many advantages to
                 journalists and media professionals and, at the same
                 time, facilitates users' interaction with useful and
                 timely information. This study shows the usability of a
                 news chatbot during a crisis situation, employing the
                 2020 COVID-19 pandemic as a case study. The basic
                 targets of the research are to design and implement a
                 chatbot in a news media platform with a two-fold aim in
                 regard to evaluation: first, the technical effort of
                 creating a functional and robust news chatbot in a
                 crisis situation both from the AI perspective and
                 interoperability with other platforms, which
                 constitutes the novelty of the approach; and second,
                 users' perception regarding the appropriation of this
                 news chatbot as an alternative means of accessing
                 existing information during a crisis situation. The
                 chatbot designed was evaluated in terms of effectively
                 fulfilling the social responsibility function of crisis
                 reporting, to deliver timely and accurate information
                 on the COVID-19 pandemic to a wide audience. In this
                 light, this study shows the advantages of implementing
                 chatbots in news platforms during a crisis situation,
                 when the audience's needs for timely and accurate
                 information rapidly increase.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Data Science and Knowledge Discovery.",
}

@Article{Giusfredi:2020:CAC,
  author =       "Michele Giusfredi and Franco Bagnoli",
  title =        "From Color-Avoiding to Color-Favored Percolation in
                 Diluted Lattices",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "8",
  pages =        "139",
  day =          "18",
  month =        aug,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12080139",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 28 12:33:08 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/8/139",
  abstract =     "We study the problem of color-avoiding and
                 color-favored percolation in a network, i.e., the
                 problem of finding a path that avoids a certain number
                 of colors, associated with vulnerabilities of nodes or
                 links, or is attracted by them. We investigate here
                 regular (mainly directed) lattices with a fractions of
                 links removed (hence the term ``diluted''). We show
                 that this problem can be formulated as a self-organized
                 critical problem, in which the asymptotic phase space
                 can be obtained in one simulation. The method is
                 particularly effective for certain ``convex''
                 formulations, but can be extended to arbitrary problems
                 using multi-bit coding. We obtain the phase diagram for
                 some problem related to color-avoiding percolation on
                 directed models. We also show that the interference
                 among colors induces a paradoxical effect in which
                 color-favored percolation is permitted where standard
                 percolation for a single color is impossible.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Selected Papers from the INSCI2019:
                 Internet Science 2019.",
}

@Article{Poulter:2020:ESU,
  author =       "Andrew John Poulter and Steven J. Ossont and Simon J.
                 Cox",
  title =        "Enabling the Secure Use of Dynamic Identity for the
                 {Internet of Things} --- Using the {Secure Remote
                 Update Protocol (SRUP)}",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "8",
  pages =        "138",
  day =          "18",
  month =        aug,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12080138",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 28 12:33:08 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/8/138",
  abstract =     "This paper examines dynamic identity, as it pertains
                 to the Internet of Things (IoT), and explores the
                 practical implementation of a mitigation technique for
                 some of the key weaknesses of a conventional dynamic
                 identity model. This paper explores human-centric and
                 machine-based observer approaches for confirming device
                 identity, permitting automated identity confirmation
                 for deployed systems. It also assesses the advantages
                 of dynamic identity in the context of identity
                 revocation permitting secure change of ownership for
                 IoT devices. The paper explores use-cases for human and
                 machine-based observation for authentication of device
                 identity when devices join a Command and Control(C2)
                 network, and considers the relative merits for these
                 two approaches for different types of system.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Feature Papers for Future
                 Internet-Internet of Things Section.",
}

@Article{Jiang:2020:PTI,
  author =       "Bo Jiang and Yanbai He and Rui Chen and Chuanyan Hao
                 and Sijiang Liu and Gangyao Zhang",
  title =        "Progressive Teaching Improvement For Small Scale
                 Learning: A Case Study in {China}",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "8",
  pages =        "137",
  day =          "17",
  month =        aug,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12080137",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 28 12:33:08 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/8/137",
  abstract =     "Learning data feedback and analysis have been widely
                 investigated in all aspects of education, especially
                 for large scale remote learning scenario like Massive
                 Open Online Courses (MOOCs) data analysis. On-site
                 teaching and learning still remains the mainstream form
                 for most teachers and students, and learning data
                 analysis for such small scale scenario is rarely
                 studied. In this work, we first develop a novel user
                 interface to progressively collect students' feedback
                 after each class of a course with WeChat mini program
                 inspired by the evaluation mechanism of most popular
                 shopping website. Collected data are then visualized to
                 teachers and pre-processed. We also propose a novel
                 artificial neural network model to conduct a
                 progressive study performance prediction. These
                 prediction results are reported to teachers for
                 next-class and further teaching improvement.
                 Experimental results show that the proposed neural
                 network model outperforms other state-of-the-art
                 machine learning methods and reaches a precision value
                 of 74.05\% on a 3-class classifying task at the end of
                 the term.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Computational Thinking.",
}

@Article{Begotti:2020:CSA,
  author =       "Tatiana Begotti and Martina Bollo and Daniela Acquadro
                 Maran",
  title =        "Coping Strategies and Anxiety and Depressive Symptoms
                 in Young Adult Victims of Cyberstalking: A
                 Questionnaire Survey in an {Italian} Sample",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "8",
  pages =        "136",
  day =          "12",
  month =        aug,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12080136",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 28 12:33:08 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/8/136",
  abstract =     "Aims: In the last decade, the use of smartphones,
                 computers and devices has progressively increased, and
                 prolonged use of technology and the internet has
                 generated new arenas (and tools) for victimization. The
                 first aim of this study was to analyze the use of
                 coping strategies in young adult self-declared victims
                 of cyberstalking. The coping strategies were
                 categorized as proactive behavior, avoidance tactics
                 and passivity. To better understand these strategies,
                 they were analyzed in light of the experience of
                 victimization in terms of incurred misconduct. The
                 second aim was to analyze the coping strategies and the
                 consequences (in terms of depression and anxiety) that
                 occurred in victims; a comparison was made between
                 males and females. Methods: A self-administered
                 questionnaire was distributed to over 433 young adults
                 living in Italy. The questionnaires were filled out by
                 398 (92\%) subjects, 41\% males and 59\% females. Their
                 ages ranged from 18 to 30 years (M = 23.5, SD = 2.76).
                 Respondents took part on a voluntary basis and did not
                 receive any compensation (or extra credit) for their
                 participation. Results: Findings from this
                 investigation confirmed that among victims, females
                 were more prone than males to experience cyberstalking
                 (respectively, 65\% and 35\%), with females
                 experiencing a higher percentage of more than one form
                 of cyberstalking behavior than males. Young adult male
                 victims used the internet principally for online
                 gaming, and for this activity, they experienced more
                 cyberstalking behavior than females. In most cases, the
                 perpetrator was a male, and the victim--cyberstalker
                 relationship was a friendship or an acquaintance. For
                 the coping strategies adopted, the findings indicated
                 that the victims were more prone to use avoidance
                 tactics than proactivity behavior and passivity
                 strategies. Young adults involved in this investigation
                 mainly used avoidance tactics to cope with the
                 stressful situation, which implies that they preferred
                 to decrease the use of the internet or stop online
                 contact than collect evidence and try to contact and
                 reason with the cyberstalker or increase the misuse of
                 alcohol of psychotropic substances. Moreover, females
                 were less prone to use proactive behavior than
                 expected. Our findings suggested that males were more
                 prone than females to adopt passivity strategies, while
                 females were more prone to adopt avoidance tactics.
                 Moreover, the data showed that proactivity behavior was
                 adopted more in the case of online contacts and online
                 identity fraud, while passivity strategies were adopted
                 in the case of online threats. Conclusion: Findings
                 from this investigation show the importance of
                 improving the knowledge about the coping strategies
                 that could be suggested to victims and the impact on
                 their psychological health.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Artificial Intelligence and Machine
                 Learning in Cybercrime Detection.",
}

@Article{Lynn:2020:UDF,
  author =       "Theo Lynn and Grace Fox and Anna Gourinovitch and
                 Pierangelo Rosati",
  title =        "Understanding the Determinants and Future Challenges
                 of Cloud Computing Adoption for High Performance
                 Computing",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "8",
  pages =        "135",
  day =          "11",
  month =        aug,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12080135",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 28 12:33:08 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/8/135",
  abstract =     "High performance computing (HPC) is widely recognized
                 as a key enabling technology for advancing scientific
                 progress, industrial competitiveness, national and
                 regional security, and the quality of human life.
                 Notwithstanding this contribution, the large upfront
                 investment and technical expertise required has limited
                 the adoption of HPC to large organizations, government
                 bodies, and third level institutions. Recent advances
                 in cloud computing and telecommunications have the
                 potential to overcome the historical issues associated
                 with HPC through increased flexibility and efficiency,
                 and reduced capital and operational expenditure. This
                 study seeks to advance the literature on technology
                 adoption and assimilation in the under-examined HPC
                 context through a mixed methods approach. Firstly, the
                 determinants of cloud computing adoption for HPC are
                 examined through a survey of 121 HPC decision makers
                 worldwide. Secondly, a modified Delphi method was
                 conducted with 13 experts to identify and prioritize
                 critical issues in the adoption of cloud computing for
                 HPC. Results from the quantitative phase suggest that
                 only organizational and human factors significantly
                 influence cloud computing adoption decisions for HPC.
                 While security was not identified as a significant
                 influencer in adoption decisions, qualitative research
                 findings suggest that data privacy and security issues
                 are an immediate and long-term concern.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Cloud-Native Applications and
                 Services.",
}

@Article{Kapsoulis:2020:CBS,
  author =       "Nikolaos Kapsoulis and Alexandros Psychas and Georgios
                 Palaiokrassas and Achilleas Marinakis and Antonios
                 Litke and Theodora Varvarigou and Charalampos Bouchlis
                 and Amaryllis Raouzaiou and Gon{\c{c}}al Calvo and
                 Jordi Escudero Subirana",
  title =        "Consortium Blockchain Smart Contracts for Musical
                 Rights Governance in a Collective Management
                 Organizations ({CMOs}) Use Case",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "8",
  pages =        "134",
  day =          "11",
  month =        aug,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12080134",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 28 12:33:08 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/8/134",
  abstract =     "Private and permissioned blockchains are
                 conceptualized and mostly assembled for fulfilling
                 corporations' demands and needs in the context of their
                 own premises. This paper presents a complete and
                 sophisticated end-to-end permissioned blockchain
                 application for governance and management of musical
                 rights endorsed by smart contract development. In a
                 music industry use case, this disclosed solution
                 monitors and regulates conflicting musical rights of
                 diverse entities under a popular permissioned
                 distributed ledger technology network. The proposed
                 implementation couples various and distinct business
                 domains across the music industry organizations and
                 non-profit blockchain associations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Intelligent Innovations in Multimedia
                 Data.",
}

@Article{Florea:2020:MDL,
  author =       "George Albert Florea and Radu-Casian Mihailescu",
  title =        "Multimodal Deep Learning for Group Activity
                 Recognition in Smart Office Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "8",
  pages =        "133",
  day =          "09",
  month =        aug,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12080133",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 28 12:33:08 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/8/133",
  abstract =     "Deep learning (DL) models have emerged in recent years
                 as the state-of-the-art technique across numerous
                 machine learning application domains. In particular,
                 image processing-related tasks have seen a significant
                 improvement in terms of performance due to increased
                 availability of large datasets and extensive growth of
                 computing power. In this paper we investigate the
                 problem of group activity recognition in office
                 environments using a multimodal deep learning approach,
                 by fusing audio and visual data from video. Group
                 activity recognition is a complex classification task,
                 given that it extends beyond identifying the activities
                 of individuals, by focusing on the combinations of
                 activities and the interactions between them. The
                 proposed fusion network was trained based on the
                 audio--visual stream from the AMI Corpus dataset. The
                 procedure consists of two steps. First, we extract a
                 joint audio--visual feature representation for activity
                 recognition, and second, we account for the temporal
                 dependencies in the video in order to complete the
                 classification task. We provide a comprehensive set of
                 experimental results showing that our proposed
                 multimodal deep network architecture outperforms
                 previous approaches, which have been designed for
                 unimodal analysis, on the aforementioned AMI dataset.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Internet of Things.",
}

@Article{Collodi:2020:HRS,
  author =       "Stefania Collodi and Maria Fiorenza and Andrea
                 Guazzini and Mirko Duradoni",
  title =        "How Reputation Systems Change the Psychological
                 Antecedents of Fairness in Virtual Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "8",
  pages =        "132",
  day =          "09",
  month =        aug,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12080132",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 28 12:33:08 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/8/132",
  abstract =     "Reputational systems promote pro-social behaviors,
                 also in virtual environments, therefore their study
                 contributes to the knowledge of social interactions.
                 Literature findings emphasize the power of reputation
                 in fostering fairness in many circumstances, even when
                 its influence is not directly oriented towards specific
                 individuals. The present study contributes to the
                 investigation of the psychological antecedents of
                 fairness, introducing (or not) reputation in the social
                 dilemma framework. Although reputational systems
                 usually influence fairness dynamics, there are also
                 socio-psychological characteristics that can play a
                 role, affecting the adhesion to the norm online. To
                 investigate their effects, we employed a virtual
                 bargaining game that could include a reputational
                 system depending on the experimental condition. Results
                 show that the participant's fairness could be
                 significantly influenced by socio-psychological and
                 demographic characteristics, as well as personality
                 traits. Reputation seems to decrease fairness in those
                 individuals who report high levels of Neuroticism and
                 Openness. At the same time, high values of
                 Self-Efficacy appear to be more likely associated with
                 unfair behaviors when reputation is off the bargaining.
                 Finally, Age and Sense of Community emerge as fairness
                 promoters regardless of the experimental condition.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Selected Papers from the INSCI2019:
                 Internet Science 2019.",
}

@Article{Lo:2020:IEL,
  author =       "Chih-Fong Lo and Chin-Huang Lin",
  title =        "The Impact of {English} Learning Motivation and
                 Attitude on Well-Being: Cram School Students in
                 {Taiwan}",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "8",
  pages =        "131",
  day =          "06",
  month =        aug,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12080131",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 28 12:33:08 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/8/131",
  abstract =     "As English is a global language, it is important for
                 students to learn it effectively and efficiently.
                 Learning English from English cram schools is very
                 popular in Taiwan. Most students have studied in
                 English cram schools for some period of time of their
                 English learning experience. The present study concerns
                 about how English cram school learners' English
                 learning attitudes related to their learning motivation
                 and learning well-being in Taiwan. By using the
                 quantitative research methodology, an empirical
                 research model has been proposed and 277 valid
                 questionnaires were collected. The research results
                 show that learning motivation has a significant impact
                 on learning attitude and learning well-being. Then, the
                 English learning attitude provides mediated effects
                 between learning motivation and well-being. Learning
                 attitude is the key to English learning well-being.
                 Furthermore, a participant's gender has a significant
                 moderating effect between learning intrinsic motivation
                 and attitude. According to research findings, some
                 suggestions such as using e-learning tools were
                 provided for teachers and educators of the cram schools
                 in Taiwan.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Network Virtualization and Edge/Fog
                 Computing.",
}

@Article{Ko:2020:PBN,
  author =       "Kyi Thar Ko and Htet Htet Hlaing and Masahiro Mambo",
  title =        "A {PEKS}-Based {NDN} Strategy for Name Privacy",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "8",
  pages =        "130",
  day =          "31",
  month =        jul,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12080130",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 28 12:33:08 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/8/130",
  abstract =     "Named Data Networking (NDN), where addressable content
                 name is used, is considered as a candidate of
                 next-generation Internet architectures. NDN routers use
                 In-Network cache to replicate and store passing packets
                 to make faster content delivery. Because NDN uses a
                 human-readable name, it is easy for an adversary to
                 guess what kind of content is requested. To solve this
                 issue, we develop a PEKS-based strategy for forwarding
                 packets, where PEKS stands for public key encryption
                 with keyword search. We implement the PEKS-based
                 strategy based on the best route strategy and multicast
                 strategy of NDN and show the performance of the
                 PEKS-based NDN strategy. We also discuss the issues of
                 the PEKS-based NDN strategy.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Information and Future Internet
                 Security, Trust and Privacy.",
}

@Article{Coelho:2020:CPI,
  author =       "Igor M. Coelho and Vitor N. Coelho and Rodolfo P.
                 Araujo and Wang Yong Qiang and Brett D. Rhodes",
  title =        "Challenges of {PBFT}-Inspired Consensus for Blockchain
                 and Enhancements over Neo {dBFT}",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "8",
  pages =        "129",
  day =          "30",
  month =        jul,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12080129",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 28 12:33:08 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/8/129",
  abstract =     "Consensus mechanisms are a core feature for handling
                 negotiation and agreements. Blockchain technology has
                 seen the introduction of different sorts of consensus
                 mechanism, ranging from tasks of heavy computation to
                 the subtle mathematical proofs of Byzantine agreements.
                 This paper presents the pioneer Delegated Byzantine
                 Fault Tolerance (dBFT) protocol of Neo Blockchain,
                 which was inspired by the Practical Byzantine Fault
                 Tolerance (PBFT). Besides introducing its history, this
                 study describes proofs and didactic examples, as well
                 as novel design and extensions for Neo dBFT with
                 multiple block proposals. Finally, we discuss
                 challenges when dealing with strong Byzantine
                 adversaries, and propose solutions inspired on PBFT for
                 current weak-synchrony problems and increasing system
                 robustness against attacks. Key Contribution: Presents
                 an overview of the history of PBFT-inspired consensus
                 for blockchain, highlighting its current importance on
                 the literature, challenges and assumptions. Contributes
                 to the field of Distributed Consensus, proposing novel
                 extensions for the Neo dBFT (dBFT 2.0+, dBFT 3.0 and
                 dBFT 3.0+), with new insights on innovative consensus
                 mechanisms.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Special Issue on Cyber Physical Systems:
                 Prospects, Challenges, and Role in Software Defined
                 Networking and Blockchain.",
}

@Article{Sandner:2020:RCI,
  author =       "Philipp Sandner and Anna Lange and Philipp Schulden",
  title =        "The Role of the {CFO} of an Industrial Company: An
                 Analysis of the Impact of Blockchain Technology",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "8",
  pages =        "128",
  day =          "30",
  month =        jul,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12080128",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 28 12:33:08 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/8/128",
  abstract =     "This qualitative multiple case study explores the
                 influence of blockchain technology on the chief
                 financial officer (CFO) of an industrial company. Due
                 to the advancing digitalization of business sectors and
                 increasing competitive pressures, industrial companies
                 are forced to promote their own digital transformation
                 to sustain on the market. Here, the literature regards
                 the CFO as a key corporate function to induce
                 digitization initiatives within organizations. The
                 blockchain technology, due to its features of
                 transparency, immutability and cryptography combined
                 with its ability to coordinate data flows of e.g., the
                 Internet of Things (IoT) or Artificial Intelligence
                 (AI), constitutes a suitable instrument for the CFO to
                 meet the requirements of Industry 4.0. This paper
                 provides a contribution to address existing research
                 gaps regarding the application side of blockchain
                 technology. Thus, the objective of this work is to
                 provide corporate financial functions, such as the CFO
                 of an industrial company, with an understanding of the
                 extent to which blockchain technology can be used for
                 the role-specific responsibilities. Therefore, the
                 underlying qualitative study explores the influence of
                 blockchain technology on the CFO-function of an
                 industrial company. Thus, intending to address a
                 research gap on the application side, it asks (1) What
                 is the impact of blockchain technology on the financial
                 as well strategic role of the CFO? (2) What is the
                 impact of blockchain technology in convergence with the
                 Machine Economy on the key performance indicators
                 (KPIs) of the CFO? (3) What is the impact of
                 blockchain-enabled integrated business ecosystems on
                 the role of the CFO? Based on a review of literature,
                 semi-structured expert interviews were conducted with
                 23 participants. Analysis of the responses demonstrated
                 a considerable impact of blockchain technology on the
                 CFO-function. The results indicate improvements of
                 business processes in regard to efficiency and
                 automation, a relocation of the CFO's strategic role,
                 improvements of CFO-relevant KPIs through integrating
                 machines into payment networks as well as the emergence
                 of integrated business ecosystems facilitating new
                 forms of inter-organizational collaboration. Necessary
                 prerequisites for adoption include digital competences
                 of the CFO, appropriate organizational structures,
                 digital currencies and identities on the blockchain, a
                 change of the competitive mindset as well as
                 standardized platforms with a neutral governance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Selected Papers from the 3rd Annual
                 Decentralized Conference (DECENTRALIZED 2019).",
}

@Article{Hassan:2020:AAA,
  author =       "Walaa Hassan and Tamer Farag",
  title =        "Adaptive Allocation Algorithm for Multi-Radio
                 Multi-Channel Wireless Mesh Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "8",
  pages =        "127",
  day =          "29",
  month =        jul,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12080127",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 28 12:33:08 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/8/127",
  abstract =     "The wireless mesh network (WMN) has proven to be a
                 great choice for network communication technology. WMNs
                 are composed of access points (APs) that are installed
                 and communicate with each other through multi-hop
                 wireless networks. One or more of these APs acts as a
                 gateway (GW) to the internet. Hosts of WMNs are
                 stationary or mobile. According to the structure of
                 WMNs, some network features may be affected, such as
                 the overall performance, channel interference, and AP
                 connectivity. In this paper, we propose a new adaptive
                 channel allocation algorithm for a multi-radio
                 multi-channel wireless mesh network. The algorithm is
                 aimed to minimize the number of channel reassignments
                 while maximizing the performance under practical
                 constraints. The algorithm defines a decision function
                 for the channel reassignments. The decision function
                 aims to minimize the traffic around the GW. Whenever
                 the traffic changes in the wireless mesh network, the
                 decision function decides which channel radio
                 reassignment should be done. We demonstrated the
                 effectiveness of our algorithm through extensive
                 simulations using Network Simulator 2 (NS-2).",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Smart System Infrastructure and
                 Applications.",
}

@Article{Derakhshannia:2020:DLG,
  author =       "Marzieh Derakhshannia and Carmen Gervet and Hicham
                 Hajj-Hassan and Anne Laurent and Arnaud Martin",
  title =        "Data Lake Governance: Towards a Systemic and Natural
                 Ecosystem Analogy",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "8",
  pages =        "126",
  day =          "27",
  month =        jul,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12080126",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 28 12:33:08 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/8/126",
  abstract =     "The realm of big data has brought new venues for
                 knowledge acquisition, but also major challenges
                 including data interoperability and effective
                 management. The great volume of miscellaneous data
                 renders the generation of new knowledge a complex data
                 analysis process. Presently, big data technologies
                 provide multiple solutions and tools towards the
                 semantic analysis of heterogeneous data, including
                 their accessibility and reusability. However, in
                 addition to learning from data, we are faced with the
                 issue of data storage and management in a
                 cost-effective and reliable manner. This is the core
                 topic of this paper. A data lake, inspired by the
                 natural lake, is a centralized data repository that
                 stores all kinds of data in any format and structure.
                 This allows any type of data to be ingested into the
                 data lake without any restriction or normalization.
                 This could lead to a critical problem known as data
                 swamp, which can contain invalid or incoherent data
                 that adds no values for further knowledge acquisition.
                 To deal with the potential avalanche of data, some
                 legislation is required to turn such heterogeneous
                 datasets into manageable data. In this article, we
                 address this problem and propose some solutions
                 concerning innovative methods, derived from a
                 multidisciplinary science perspective to manage data
                 lake. The proposed methods imitate the supply chain
                 management and natural lake principles with an emphasis
                 on the importance of the data life cycle, to implement
                 responsible data governance for the data lake.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Selected Papers from the INSCI2019:
                 Internet Science 2019.",
}

@Article{Hazari:2020:ITS,
  author =       "Shihab Shahriar Hazari and Qusay H. Mahmoud",
  title =        "Improving Transaction Speed and Scalability of
                 Blockchain Systems via Parallel Proof of Work",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "8",
  pages =        "125",
  day =          "27",
  month =        jul,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12080125",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 28 12:33:08 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/8/125",
  abstract =     "A blockchain is a distributed ledger forming a
                 distributed consensus on a history of transactions, and
                 is the underlying technology for the Bitcoin
                 cryptocurrency. Its applications are far beyond the
                 financial sector. The transaction verification process
                 for cryptocurrencies is much slower than traditional
                 digital transaction systems. One approach to
                 scalability or the speed at which transactions are
                 processed is to design a solution that offers faster
                 Proof of Work. In this paper, we propose a method for
                 accelerating the process of Proof of Work based on
                 parallel mining rather than solo mining. The goal is to
                 ensure that no more than two or more miners put the
                 same effort into solving a specific block. The proposed
                 method includes a process for selection of a manager,
                 distribution of work and a reward system. This method
                 has been implemented in a test environment that
                 contains all the characteristics needed to perform
                 Proof of Work for Bitcoin and has been tested, using a
                 variety of case scenarios, by varying the difficulty
                 level and number of validators. Experimental
                 evaluations were performed locally and in a cloud
                 environment, and experimental results demonstrate the
                 feasibility the proposed method.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Special Issue on Cyber Physical Systems:
                 Prospects, Challenges, and Role in Software Defined
                 Networking and Blockchain.",
}

@Article{Moreno-Guerrero:2020:SDE,
  author =       "Antonio-Jos{\'e} Moreno-Guerrero and Jes{\'u}s
                 L{\'o}pez-Belmonte and Jos{\'e}-Antonio
                 Mar{\'\i}n-Mar{\'\i}n and Rebeca Soler-Costa",
  title =        "Scientific Development of Educational Artificial
                 Intelligence in {Web of Science}",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "8",
  pages =        "124",
  day =          "24",
  month =        jul,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12080124",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 28 12:33:08 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/8/124",
  abstract =     "The social and technological changes that society is
                 undergoing in this century are having a global
                 influence on important aspects such as the economy,
                 health and education. An example of this is the
                 inclusion of artificial intelligence in the
                 teaching--learning processes. The objective of this
                 study was to analyze the importance and the projection
                 that artificial intelligence has acquired in the
                 scientific literature in the Web of Science categories
                 related to the field of education. For this, scientific
                 mapping of the reported documents was carried out.
                 Different bibliometric indicators were analyzed and a
                 word analysis was carried out. We worked with an
                 analysis unit of 379 publications. The results show
                 that scientific production is irregular from its
                 beginnings in 1956 to the present. The language of
                 greatest development is English. The most significant
                 publication area is Education Educational Research,
                 with conference papers as document types. The
                 underlying organization is the Open University UK. It
                 can be concluded that there is an evolution in
                 artificial intelligence (AI) research in the
                 educational field, focusing in the last years on the
                 performance and influence of AI in the educational
                 processes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Distributed Systems and Artificial
                 Intelligence.",
}

@Article{Romero-Rodriguez:2020:CII,
  author =       "Jos{\'e}-Mar{\'\i}a Romero-Rodr{\'\i}guez and Santiago
                 Alonso-Garc{\'\i}a and Jos{\'e}-Antonio
                 Mar{\'\i}n-Mar{\'\i}n and Gerardo
                 G{\'o}mez-Garc{\'\i}a",
  title =        "Considerations on the Implications of the {Internet of
                 Things} in {Spanish} Universities: The Usefulness
                 Perceived by Professors",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "8",
  pages =        "123",
  day =          "24",
  month =        jul,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12080123",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 28 12:33:08 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/8/123",
  abstract =     "Internet of Things (IoT) is an emerging technology in
                 the field of education, which has not yet been
                 consolidated. Acceptance and adoption studies of IoT in
                 higher education are scarce. Accordingly, the purpose
                 of this study was to explore the acceptance of the IoT
                 by university professors for future adoption in higher
                 education. An online survey was implemented based on
                 the unified theory of acceptance and use of technology
                 (UTAUT), in a sample of 587 Spanish university
                 teachers, aged between 21 and 58. The results showed
                 that performance expectancy, facilitating conditions,
                 and attitude toward using technology were influential
                 in behavioral intention to use IoT. While the intention
                 for use was similar between men and women and with
                 respect to age. However, in the different constructs of
                 the UTAUT model, the highest average scores were
                 obtained in men and in teachers over 36 years of age.
                 Finally, the findings and implications of the paper are
                 discussed, showing empirical evidence on the adoption
                 and acceptance of IoT in higher education in the
                 context of Spain, highlighting the need for further
                 research on emerging technologies in a context that is
                 marked by COVID-19.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Internet of Things.",
}

@Article{Wang:2020:HCA,
  author =       "Baocheng Wang and Zetao Li and Haibin Li",
  title =        "Hybrid Consensus Algorithm Based on Modified
                 Proof-of-Probability and {DPoS}",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "8",
  pages =        "122",
  day =          "24",
  month =        jul,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12080122",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 28 12:33:08 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/8/122",
  abstract =     "As the core of blockchain technology, the consensus
                 algorithm plays an important role in determining the
                 security, data consistency, and efficiency of
                 blockchain systems. The existing mainstream consensus
                 algorithm is experiencing difficulties satisfying the
                 needs of efficiency, security, and decentralization in
                 real-world scenarios. This paper proposes a hybrid
                 consensus algorithm based on modified
                 Proof-of-Probability and Delegated Proof-of-Stake. In
                 this method, the work of block generation and
                 validation is, respectively, completed by the nodes
                 using the modified Proof-of-Probability consensus
                 algorithm and Delegated Proof-of-Stake consensus
                 algorithm. When a transaction occurs, the system sends
                 several target hash values to the whole network. Each
                 modified Proof-of-Probability node has a different
                 sorting algorithm, so they have different mining
                 priorities. Every time a hash is decrypted by a
                 modified Proof-of-Probability node, the modulo
                 operation is done to the value of nonce, which is then
                 compared with the expected value given by the supernode
                 selected by the Delegated Proof-of-Stake nodes. If they
                 are not the same, the Proof-of-Probability node enters
                 the waiting time and the other Proof-of-Probability
                 nodes continue to mine. By adopting two consensus
                 algorithms, the malicious nodes must control more than
                 51\% of the nodes that adopt the two consensus
                 algorithms, at the same time, to effectively attack the
                 system, that is, they must have more than 51\% of the
                 computing power and more than 51\% of the tokens. This
                 not only increases the cost of malicious attacks, but
                 also reduces waste of computing power. In addition, the
                 efficiency of the DPoS algorithm makes up for the
                 deficiency of the PoP algorithm in system efficiency,
                 and the mining behavior based on probability in the PoP
                 algorithm also significantly weakens the ability of
                 supernodes in the DPoS algorithm to conduct monopoly
                 behavior or other malicious behaviors. In a word, the
                 combination of the two algorithms makes the system
                 perform better in terms of security, system efficiency,
                 and decentralization.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Special Issue on Cyber Physical Systems:
                 Prospects, Challenges, and Role in Software Defined
                 Networking and Blockchain.",
}

@Article{Pombo:2020:ELC,
  author =       "I{\~n}igo Pombo and Leire Godino and Jose Antonio
                 S{\'a}nchez and Rafael Lizarralde",
  title =        "Expectations and limitations of Cyber-Physical Systems
                 ({CPS}) for Advanced Manufacturing: A View from the
                 Grinding Industry",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "9",
  pages =        "159",
  day =          "22",
  month =        sep,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12090159",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 28 10:44:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/9/159",
  abstract =     "Grinding is a critical technology in the manufacturing
                 of high added-value precision parts, accounting for
                 approximately 20--25\% of all machining costs in the
                 industrialized world. It is a commonly used process in
                 the finishing of parts in numerous key industrial
                 sectors such as transport (including the aeronautical,
                 automotive and railway industries), and energy or
                 biomedical industries. As in the case of many other
                 manufacturing technologies, grinding relies heavily on
                 the experience and knowledge of the operatives. For
                 this reason, considerable efforts have been devoted to
                 generating a systematic and sustainable approach that
                 reduces and eventually eliminates costly
                 trial-and-error strategies. The main contribution of
                 this work is that, for the first time, a complete
                 digital twin (DT) for the grinding industry is
                 presented. The required flow of information between
                 numerical simulations, advanced mechanical testing and
                 industrial practice has been defined, thus producing a
                 virtual mirror of the real process. The structure of
                 the DT comprises four layers, which integrate: (1)
                 scientific knowledge of the process (advanced process
                 modeling and numerical simulation); (2)
                 characterization of materials through specialized
                 mechanical testing; (3) advanced sensing techniques, to
                 provide feedback for process models; and (4) knowledge
                 integration in a configurable open-source industrial
                 tool. To this end, intensive collaboration between all
                 the involved agents (from university to industry) is
                 essential. One of the most remarkable results is the
                 development of new and more realistic models for
                 predicting wheel wear, which currently can only be
                 known in industry through costly trial-and-error
                 strategies. Also, current work is focused on the
                 development of an intelligent grinding wheel, which
                 will provide on-line information about process
                 variables such as temperature and forces. This is a
                 critical issue in the advance towards a zero-defect
                 grinding process.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Collaborative Networks, Decision
                 Systems, Web Applications and Services for Supporting
                 Engineering and Production Management.",
}

@Article{Ventruto:2020:FED,
  author =       "Federica Ventruto and Marco Pulimeno and Massimo
                 Cafaro and Italo Epicoco",
  title =        "On Frequency Estimation and Detection of Heavy Hitters
                 in Data Streams",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "9",
  pages =        "158",
  day =          "18",
  month =        sep,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12090158",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 28 10:44:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/9/158",
  abstract =     "A stream can be thought of as a very large set of
                 data, sometimes even infinite, which arrives
                 sequentially and must be processed without the
                 possibility of being stored. In fact, the memory
                 available to the algorithm is limited and it is not
                 possible to store the whole stream of data which is
                 instead scanned upon arrival and summarized through a
                 succinct data structure in order to maintain only the
                 information of interest. Two of the main tasks related
                 to data stream processing are frequency estimation and
                 heavy hitter detection. The frequency estimation
                 problem requires estimating the frequency of each item,
                 that is the number of times or the weight with which
                 each appears in the stream, while heavy hitter
                 detection means the detection of all those items with a
                 frequency higher than a fixed threshold. In this work
                 we design and analyze ACMSS, an algorithm for frequency
                 estimation and heavy hitter detection, and compare it
                 against the state of the art AS ketch algorithm. We
                 show that, given the same budgeted amount of memory,
                 for the task of frequency estimation our algorithm
                 outperforms AS ketch with regard to accuracy.
                 Furthermore, we show that, under the assumptions stated
                 by its authors, AS ketch may not be able to report all
                 of the heavy hitters whilst ACMSS will provide with
                 high probability the full list of heavy hitters.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Big Data and Augmented Intelligence.",
}

@Article{Lee:2020:ITI,
  author =       "In Lee",
  title =        "{Internet of Things (IoT)} Cybersecurity: Literature
                 Review and {IoT} Cyber Risk Management",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "9",
  pages =        "157",
  day =          "18",
  month =        sep,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12090157",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 28 10:44:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/9/157",
  abstract =     "Along with the growing threat of cyberattacks,
                 cybersecurity has become one of the most important
                 areas of the Internet of Things (IoT). The purpose of
                 IoT cybersecurity is to reduce cybersecurity risk for
                 organizations and users through the protection of IoT
                 assets and privacy. New cybersecurity technologies and
                 tools provide potential for better IoT security
                 management. However, there is a lack of effective IoT
                 cyber risk management frameworks for managers. This
                 paper reviews IoT cybersecurity technologies and cyber
                 risk management frameworks. Then, this paper presents a
                 four-layer IoT cyber risk management framework. This
                 paper also applies a linear programming method for the
                 allocation of financial resources to multiple IoT
                 cybersecurity projects. An illustration is provided as
                 a proof of concept.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Frontiers in Cyber Security.",
}

@Article{Ghourabi:2020:HCL,
  author =       "Abdallah Ghourabi and Mahmood A. Mahmood and Qusay M.
                 Alzubi",
  title =        "A Hybrid {CNN-LSTM} Model for {SMS} Spam Detection in
                 {Arabic} and {English} Messages",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "9",
  pages =        "156",
  day =          "18",
  month =        sep,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12090156",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 28 10:44:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/9/156",
  abstract =     "Despite the rapid evolution of Internet protocol-based
                 messaging services, SMS still remains an indisputable
                 communication service in our lives until today. For
                 example, several businesses consider that text messages
                 are more effective than e-mails. This is because 82\%
                 of SMSs are read within 5 min., but consumers only open
                 one in four e-mails they receive. The importance of SMS
                 for mobile phone users has attracted the attention of
                 spammers. In fact, the volume of SMS spam has increased
                 considerably in recent years with the emergence of new
                 security threats, such as SMiShing. In this paper, we
                 propose a hybrid deep learning model for detecting SMS
                 spam messages. This detection model is based on the
                 combination of two deep learning methods CNN and LSTM.
                 It is intended to deal with mixed text messages that
                 are written in Arabic or English. For the comparative
                 evaluation, we also tested other well-known machine
                 learning algorithms. The experimental results that we
                 present in this paper show that our CNN-LSTM model
                 outperforms the other algorithms. It achieved a very
                 good accuracy of 98.37\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Cybersecurity.",
}

@Article{Pires:2020:IHA,
  author =       "Ivan Miguel Pires and Faisal Hussain and Nuno M.
                 Garcia and Eftim Zdravevski",
  title =        "Improving Human Activity Monitoring by Imputation of
                 Missing Sensory Data: Experimental Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "9",
  pages =        "155",
  day =          "17",
  month =        sep,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12090155",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 28 10:44:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/9/155",
  abstract =     "The automatic recognition of human activities with
                 sensors available in off-the-shelf mobile devices has
                 been the subject of different research studies in
                 recent years. It may be useful for the monitoring of
                 elderly people to present warning situations,
                 monitoring the activity of sports people, and other
                 possibilities. However, the acquisition of the data
                 from different sensors may fail for different reasons,
                 and the human activities are recognized with better
                 accuracy if the different datasets are fulfilled. This
                 paper focused on two stages of a system for the
                 recognition of human activities: data imputation and
                 data classification. Regarding the data imputation, a
                 methodology for extrapolating the missing samples of a
                 dataset to better recognize the human activities was
                 proposed. The K-Nearest Neighbors (KNN) imputation
                 technique was used to extrapolate the missing samples
                 in dataset captures. Regarding the data classification,
                 the accuracy of the previously implemented method,
                 i.e., Deep Neural Networks (DNN) with normalized and
                 non-normalized data, was improved in relation to the
                 previous results without data imputation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Deep Neural Networks on Reconfigurable
                 Embedded Systems.",
}

@Article{Roy:2020:ERF,
  author =       "Animesh Chandra Roy and Mohammad Shamsul Arefin and A.
                 S. M. Kayes and Mohammad Hammoudeh and Khandakar
                 Ahmed",
  title =        "An Empirical Recommendation Framework to Support
                 Location-Based Services",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "9",
  pages =        "154",
  day =          "17",
  month =        sep,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12090154",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 28 10:44:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/9/154",
  abstract =     "The rapid growth of Global Positioning System (GPS)
                 and availability of real-time Geo-located data allow
                 the mobile devices to provide information which leads
                 towards the Location Based Services (LBS). The need for
                 providing suggestions to personals about the activities
                 of their interests, the LBS contributing more
                 effectively to this purpose. Recommendation system (RS)
                 is one of the most effective and efficient features
                 that has been initiated by the LBS. Our proposed system
                 is intended to design a recommendation system that will
                 provide suggestions to the user and also find a
                 suitable place for a group of users and it is according
                 to their preferred type of places. In our work, we
                 propose the Density-Based Spatial Clustering of
                 Applications with Noise (DBSCAN) algorithm for
                 clustering the check-in spots of the user's and
                 user-based Collaborative Filtering (CF) to find similar
                 users as we are considering constructing an interest
                 profile for each user. We also introduced a grid-based
                 structure to present the Point of Interest (POI) into a
                 map. Finally, similarity calculation is done to make
                 the recommendations. We evaluated our system on real
                 world users and acquired the F-measure score on average
                 0.962 and 0.964 for a single user and for a group of
                 user respectively. We also observed that our system
                 provides effective recommendations for a single user as
                 well as for a group of users.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Sustainable Smart City.",
}

@Article{Ramakrishnan:2020:STC,
  author =       "Abinaya Megan Ramakrishnan and Aparna Nicole
                 Ramakrishnan and Sarah Lagan and John Torous",
  title =        "From Symptom Tracking to Contact Tracing: A Framework
                 to Explore and Assess {COVID-19} Apps",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "9",
  pages =        "153",
  day =          "08",
  month =        sep,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12090153",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 28 10:44:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/9/153",
  abstract =     "Smartphone applications related to coronavirus disease
                 2019 (COVID-19) continue to emerge and evolve, but
                 despite a wide variety of different app functions,
                 there has yet to be a comprehensive study of what the
                 most prevalent publicly available apps provide, and
                 there exists no standardized evaluation system for end
                 users to determine the safety and efficacy of an app
                 before they download it. Furthermore, limited oversight
                 means that the rapidly growing space creates challenges
                 for end users trying to find a relevant app. We adapted
                 the M-Health Index and Navigation Database (MIND) from
                 apps.digitalpsych.org that previously has been used to
                 evaluate mental health applications to guide the
                 assessment of COVID apps. Using this framework, we
                 conducted a thorough analysis of the top-100 returned
                 coronavirus apps on two separate dates a month apart to
                 understand the clinical utility and features of
                 COVID-19 apps and how these change in a short period of
                 time. We ultimately identified a significant turnover
                 rate, as well as privacy concerns around lack of
                 privacy policies and disclosure of personal
                 information. Our research offers insight into the
                 current status of COVID-19 apps and provides a
                 comprehensive and adaptable framework to help
                 individuals assess the growing number of such digital
                 tools in the wake of the pandemic.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Recent Advances of Machine Learning
                 Techniques on Smartphones.",
}

@Article{Milicic:2020:GTA,
  author =       "Gregor Milicic and Sina Wetzel and Matthias Ludwig",
  title =        "Generic Tasks for Algorithms",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "9",
  pages =        "152",
  day =          "03",
  month =        sep,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12090152",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 28 10:44:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/9/152",
  abstract =     "Due to its links to computer science (CS), teaching
                 computational thinking (CT) often involves the handling
                 of algorithms in activities, such as their
                 implementation or analysis. Although there already
                 exists a wide variety of different tasks for various
                 learning environments in the area of computer science,
                 there is less material available for CT. In this
                 article, we propose so-called Generic Tasks for
                 algorithms inspired by common programming tasks from CS
                 education. Generic Tasks can be seen as a family of
                 tasks with a common underlying structure, format, and
                 aim, and can serve as best-practice examples. They thus
                 bring many advantages, such as facilitating the process
                 of creating new content and supporting asynchronous
                 teaching formats. The Generic Tasks that we propose
                 were evaluated by 14 experts in the field of Science,
                 Technology, Engineering, and Mathematics (STEM)
                 education. Apart from a general estimation in regard to
                 the meaningfulness of the proposed tasks, the experts
                 also rated which and how strongly six core CT skills
                 are addressed by the tasks. We conclude that, even
                 though the experts consider the tasks to be meaningful,
                 not all CT-related skills can be specifically
                 addressed. It is thus important to define additional
                 tasks for CT that are detached from algorithms and
                 programming.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Computational Thinking.",
}

@Article{Baldi:2020:IGR,
  author =       "Alberto Baldi and Franco Bagnoli",
  title =        "Intransitiveness: From Games to Random Walks",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "9",
  pages =        "151",
  day =          "03",
  month =        sep,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12090151",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 28 10:44:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/9/151",
  abstract =     "Many games in which chance plays a role can be
                 simulated as a random walk over a graph of possible
                 configurations of board pieces, cards, dice or coins.
                 The end of the game generally consists of the
                 appearance of a predefined winning pattern; for random
                 walks, this corresponds to an absorbing trap. The
                 strategy of a player consist of betting on a given
                 sequence, i.e., in placing a trap on the graph. In
                 two-players games, the competition between strategies
                 corresponds to the capabilities of the corresponding
                 traps in capturing the random walks originated by the
                 aleatory components of the game. The concept of
                 dominance transitivity of strategies implies an
                 advantage for the first player, who can choose the
                 strategy that, at least statistically, wins. However,
                 in some games, the second player is statistically
                 advantaged, so these games are denoted
                 ``intransitive''. In an intransitive game, the second
                 player can choose a location for his/her trap which
                 captures more random walks than that of the first one.
                 The transitivity concept can, therefore, be extended to
                 generic random walks and in general to Markov chains.
                 We analyze random walks on several kinds of networks
                 (rings, scale-free, hierarchical and city-inspired)
                 with many variations: traps can be partially absorbing,
                 the walkers can be biased and the initial distribution
                 can be arbitrary. We found that the transitivity
                 concept can be quite useful for characterizing the
                 combined properties of a graph and that of the
                 walkers.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Selected Papers from the INSCI2019:
                 Internet Science 2019.",
}

@Article{AlMojamed:2020:IIM,
  author =       "Mohammad {Al Mojamed}",
  title =        "Integrating {IP} Mobility Management Protocols and
                 {MANET}: A Survey",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "9",
  pages =        "150",
  day =          "03",
  month =        sep,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12090150",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 28 10:44:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/9/150",
  abstract =     "The Mobile ad hoc Network (MANET) is a collection of
                 mobile devices that forms a self-created,
                 self-administered, and self-organized network. It is an
                 infrastructureless network that does not require an
                 existing infrastructure to operate. MANET suits
                 scenarios where a temporary network is needed, such as
                 emergency rescue, the military field, and disaster
                 areas. MANET is an isolated network, and communication
                 is restricted to the participating nodes' transmission
                 coverage. In order to increase its connectivity and its
                 application scope, however, MANET requires integration
                 with other networks, forming a hybrid MANET. The
                 integration of MANET and IP networks raises many
                 challenges and issues. Mobility management is one of
                 the main challenges. Traditional mobility management
                 protocols provide seamless mobility in a single hop
                 infrastructure network. Consequently, mobile nodes can
                 maintain their global connectivity without interrupting
                 the ongoing sessions. Mobility management becomes more
                 challenging in a network that relies on multi-hop
                 communication, such as MANET. This paper presents a
                 survey of the use of mobility management systems when
                 integrating MANET with the internet, with the objective
                 of serving as a handy reference in this field of
                 research. It presents, analyzes, and discusses existing
                 mobility management solutions for integrated MANET
                 networks. It also investigates their shortcomings and
                 provides a comparative study of the surveyed
                 proposals.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Smart System Infrastructure and
                 Applications.",
}

@Article{Lorenzo-Lledo:2020:DVQ,
  author =       "Alejandro Lorenzo-Lled{\'o}",
  title =        "Design and Validation of a Questionnaire to Measure
                 Future {Spanish} Teachers' Perceptions of Cinema in
                 Pre-School and Primary Education: Towards Active and
                 Technological Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "9",
  pages =        "149",
  day =          "03",
  month =        sep,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12090149",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 28 10:44:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/9/149",
  abstract =     "State of the art: Cinema, because of the eclectic
                 nature of art, technology and mass media, can be
                 manifested as an educational tool in the classroom. In
                 this sense, the educational possibilities detected in
                 the cinema are numerous. The pre-service teacher
                 education in the figure of the teacher determines their
                 educational resources. Purpose: The general objective
                 of this study is to design and validate an instrument
                 to measure the perceptions of students of Pre-School
                 Teacher Degree and Primary Teacher Degree in Spanish
                 universities about cinema as a teaching resource in
                 Pre-School and Primary Education. Design/methodology:
                 For this purpose, a systematic and planned process was
                 developed for the design and validation of the
                 Percepciones sobre las potencialidades del cine como
                 recurso did{\'a}ctico en las aulas de Infantil y
                 Primaria ((PECID) (perceptions about the potentialities
                 of cinema as a didactic resource in pre-school and
                 primary classrooms)) questionnaire. Main findings: The
                 results obtained showed a good content validity of 25
                 items after an expert judgement. On the other hand, a
                 reliability of the internal consistency of the
                 instrument of 0.978 was obtained. Furthermore, a
                 three-factor structure was confirmed through factor
                 analysis. Conclusions: It is concluded that the PECID
                 questionnaire is a valid and reliable instrument to
                 measure the perceptions of future teachers in Spain
                 about using cinema as a resource for future teaching.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Techno-Social Smart Systems.",
}

@Article{Ismailov:2020:VOS,
  author =       "Max Ismailov and Michail Tsikerdekis and Sherali
                 Zeadally",
  title =        "Vulnerabilities to Online Social Network Identity
                 Deception Detection Research and Recommendations for
                 Mitigation",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "9",
  pages =        "148",
  day =          "31",
  month =        aug,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12090148",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 28 10:44:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/9/148",
  abstract =     "Identity deception in online social networks is a
                 pervasive problem. Ongoing research is developing
                 methods for identity deception detection. However, the
                 real-world efficacy of these methods is currently
                 unknown because they have been evaluated largely
                 through laboratory experiments. We present a review of
                 representative state-of-the-art results on identity
                 deception detection. Based on this analysis, we
                 identify common methodological weaknesses for these
                 approaches, and we propose recommendations that can
                 increase their effectiveness for when they are applied
                 in real-world environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Privacy in Social Networks
                 and Solutions.",
}

@Article{Isyaku:2020:SDN,
  author =       "Babangida Isyaku and Mohd Soperi Mohd Zahid and Maznah
                 Bte Kamat and Kamalrulnizam Abu Bakar and Fuad A.
                 Ghaleb",
  title =        "Software Defined Networking Flow Table Management of
                 {OpenFlow} Switches Performance and Security
                 Challenges: A Survey",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "9",
  pages =        "147",
  day =          "31",
  month =        aug,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12090147",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 28 10:44:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/9/147",
  abstract =     "Software defined networking (SDN) is an emerging
                 network paradigm that decouples the control plane from
                 the data plane. The data plane is composed of
                 forwarding elements called switches and the control
                 plane is composed of controllers. SDN is gaining
                 popularity from industry and academics due to its
                 advantages such as centralized, flexible, and
                 programmable network management. The increasing number
                 of traffics due to the proliferation of the Internet of
                 Thing (IoT) devices may result in two problems: (1)
                 increased processing load of the controller, and (2)
                 insufficient space in the switches' flow table to
                 accommodate the flow entries. These problems may cause
                 undesired network behavior and unstable network
                 performance, especially in large-scale networks. Many
                 solutions have been proposed to improve the management
                 of the flow table, reducing controller processing load,
                 and mitigating security threats and vulnerabilities on
                 the controllers and switches. This paper provides
                 comprehensive surveys of existing schemes to ensure SDN
                 meets the quality of service (QoS) demands of various
                 applications and cloud services. Finally, potential
                 future research directions are identified and discussed
                 such as management of flow table using machine
                 learning.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future Networks: Latest Trends and
                 Developments.",
}

@Article{Studen:2020:SMQ,
  author =       "Laura Studen and Victor Tiberius",
  title =        "Social Media, Quo Vadis? {Prospective} Development and
                 Implications",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "9",
  pages =        "146",
  day =          "28",
  month =        aug,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12090146",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 28 10:44:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/9/146",
  abstract =     "Over the past two decades, social media have become a
                 crucial and omnipresent cultural and economic
                 phenomenon, which has seen platforms come and go and
                 advance technologically. In this study, we explore the
                 further development of social media regarding
                 interactive technologies, platform development,
                 relationships to news media, the activities of
                 institutional and organizational users, and effects of
                 social media on the individual and the society over the
                 next five to ten years by conducting an international,
                 two-stage Delphi study. Our results show that enhanced
                 interaction on platforms, including virtual and
                 augmented reality, somatosensory sense, and touch- and
                 movement-based navigation are expected. AIs will
                 interact with other social media users. Inactive user
                 profiles will outnumber active ones. Platform providers
                 will diversify into the WWW, e-commerce, edu-tech,
                 fintechs, the automobile industry, and HR. They will
                 change to a freemium business model and put more effort
                 into combating cybercrime. Social media will become the
                 predominant news distributor, but fake news will still
                 be problematic. Firms will spend greater amounts of
                 their budgets on social media advertising, and schools,
                 politicians, and the medical sector will increase their
                 social media engagement. Social media use will
                 increasingly lead to individuals' psychic issues.
                 Society will benefit from economic growth and new jobs,
                 increased political interest, democratic progress, and
                 education due to social media. However, censorship and
                 the energy consumption of platform operators might
                 rise.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Wireless Internet, Multimedia, and
                 Artificial Intelligence: New Applications and
                 Infrastructures.",
}

@Article{Tchakounte:2020:CRF,
  author =       "Franklin Tchakount{\'e} and Athanase Esdras Yera Pagor
                 and Jean Claude Kamgang and Marcellin Atemkeng",
  title =        "{CIAA-RepDroid}: A Fine-Grained and Probabilistic
                 Reputation Scheme for {Android} Apps Based on Sentiment
                 Analysis of Reviews",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "9",
  pages =        "145",
  day =          "27",
  month =        aug,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12090145",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 28 10:44:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/9/145",
  abstract =     "To keep its business reliable, Google is concerned to
                 ensure the quality of apps on the store. One crucial
                 aspect concerning quality is security. Security is
                 achieved through Google Play protect and anti-malware
                 solutions. However, they are not totally efficient
                 since they rely on application features and application
                 execution threads. Google provides additional elements
                 to enable consumers to collectively evaluate
                 applications providing their experiences via reviews or
                 showing their satisfaction through rating. The latter
                 is more informal and hides details of rating whereas
                 the former is textually expressive but requires further
                 processing to understand opinions behind it. Literature
                 lacks approaches which mine reviews through sentiment
                 analysis to extract useful information to improve the
                 security aspects of provided applications. This work
                 goes in this direction and in a fine-grained way,
                 investigates in terms of confidentiality, integrity,
                 availability, and authentication (CIAA). While assuming
                 that reviews are reliable and not fake, the proposed
                 approach determines review polarities based on
                 CIAA-related keywords. We rely on the popular
                 classifier Naive Bayes to classify reviews into
                 positive, negative, and neutral sentiment. We then
                 provide an aggregation model to fusion different
                 polarities to obtain application global and CIAA
                 reputations. Quantitative experiments have been
                 conducted on 13 applications including e-banking, live
                 messaging and anti-malware apps with a total of 1050
                 security-related reviews and 7,835,322
                 functionality-related reviews. Results show that 23\%
                 of applications (03 apps) have a reputation greater
                 than 0.5 with an accent on integrity, authentication,
                 and availability, while the remaining 77\% has a
                 polarity under 0.5. Developers should make a lot of
                 effort in security while developing codes and that more
                 efforts should be made to improve confidentiality
                 reputation. Results also show that applications with
                 good functionality-related reputation generally offer a
                 bad security-related reputation. This situation means
                 that even if the number of security reviews is low, it
                 does not mean that the security aspect is not a
                 consumer preoccupation. Unlike, developers put much
                 more time to test whether applications work without
                 errors even if they include possible security
                 vulnerabilities. A quantitative comparison against
                 well-known rating systems reveals the effectiveness and
                 robustness of CIAA-RepDroid to repute apps in terms of
                 security. CIAA-RepDroid can be associated with existing
                 rating solutions to recommend developers exact CIAA
                 aspects to improve within source codes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Cybersecurity.",
}

@Article{Bodrunova:2020:TDB,
  author =       "Svetlana S. Bodrunova and Andrey V. Orekhov and Ivan
                 S. Blekanov and Nikolay S. Lyudkevich and Nikita A.
                 Tarasov",
  title =        "Topic Detection Based on Sentence Embeddings and
                 Agglomerative Clustering with {Markov} Moment",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "9",
  pages =        "144",
  day =          "26",
  month =        aug,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12090144",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 28 10:44:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/9/144",
  abstract =     "The paper is dedicated to solving the problem of
                 optimal text classification in the area of automated
                 detection of typology of texts. In conventional
                 approaches to topicality-based text classification
                 (including topic modeling), the number of clusters is
                 to be set up by the scholar, and the optimal number of
                 clusters, as well as the quality of the model that
                 designates proximity of texts to each other, remain
                 unresolved questions. We propose a novel approach to
                 the automated definition of the optimal number of
                 clusters that also incorporates an assessment of word
                 proximity of texts, combined with text encoding model
                 that is based on the system of sentence embeddings. Our
                 approach combines Universal Sentence Encoder (USE) data
                 pre-processing, agglomerative hierarchical clustering
                 by Ward's method, and the Markov stopping moment for
                 optimal clustering. The preferred number of clusters is
                 determined based on the ``e-2'' hypothesis. We set up
                 an experiment on two datasets of real-world labeled
                 data: News20 and BBC. The proposed model is tested
                 against more traditional text representation methods,
                 like bag-of-words and word2vec, to show that it
                 provides a much better-resulting quality than the
                 baseline DBSCAN and OPTICS models with different
                 encoding methods. We use three quality metrics to
                 demonstrate that clustering quality does not drop when
                 the number of clusters grows. Thus, we get close to the
                 convergence of text clustering and text
                 classification.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Selected Papers from the INSCI2019:
                 Internet Science 2019.",
}

@Article{Bylieva:2020:OGS,
  author =       "Daria Bylieva and Zafer Bekirogullari and Dmitry
                 Kuznetsov and Nadezhda Almazova and Victoria Lobatyuk
                 and Anna Rubtsova",
  title =        "Online Group Student Peer-Communication as an Element
                 of Open Education",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "9",
  pages =        "143",
  day =          "26",
  month =        aug,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12090143",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 28 10:44:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/9/143",
  abstract =     "Information and communication technologies transform
                 modern education into a more available learning matrix.
                 One of the unexplored aspects of open education is the
                 constant communicative interaction within the student
                 group by using social media. The aim of the study was
                 to determine principal functions of student-led
                 communication in the educational process, the method
                 for assessing its strong points and the disadvantages
                 disrupting traditional learning. For the primary study
                 of the phenomenon, we used methods that made it
                 possible to propose approaches to further analysis.
                 Netnography is the main research method defining the
                 essence and characteristics of the student-led
                 peer-communication. In our research, we applied data
                 visualization, analytical and quantitative methods and
                 developed a set of quantitative indicators that can be
                 used to assess various aspects of student communication
                 in chats. The elaborated visual model can serve as a
                 simple tool for diagnosing group communication
                 processes. We revealed that online group chats perform
                 a support function in learning. They provide constant
                 informational resource on educational and
                 organizational issues and create emotional comfort.
                 Identified features serve to define shortcomings (e.g.,
                 lack of students' readiness to freely exchange answers
                 to assignments) and significant factors (e.g.,
                 underutilized opportunities for self-organization) that
                 exist in the modern system of higher education.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue E-learning and Technology Enhanced
                 Learning.",
}

@Article{Wu:2020:HSD,
  author =       "Zhijun Wu and Bohua Cui",
  title =        "A Hybrid {SWIM} Data Naming Scheme Based on {TLC}
                 Structure",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "9",
  pages =        "142",
  day =          "25",
  month =        aug,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12090142",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 28 10:44:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/9/142",
  abstract =     "Aiming at the problem of low interconnection
                 efficiency caused by the wide variety of data in SWIM
                 (System-Wide Information Management) and the
                 inconsistent data naming methods, this paper proposes a
                 new TLC (Type-Length-Content) structure hybrid data
                 naming scheme combined with Bloom filters. This
                 solution can meet the uniqueness and durability
                 requirements of SWIM data names, solve the ``suffix
                 loopholes'' encountered in prefix-based route
                 aggregation in hierarchical naming, and realize
                 scalable and effective route state aggregation.
                 Simulation verification results show that the hybrid
                 naming scheme is better than prefix-based aggregation
                 in the probability of route identification errors. In
                 terms of search time, this scheme has increased by
                 17.8\% and 18.2\%, respectively, compared with the
                 commonly used hierarchical and flat naming methods.
                 Compared with the other two naming methods, scalability
                 has increased by 19.1\% and 18.4\%, respectively.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Big Data and Augmented Intelligence.",
}

@Article{Ziouzios:2020:DAS,
  author =       "Dimitris Ziouzios and Dimitris Tsiktsiris and Nikolaos
                 Baras and Minas Dasygenis",
  title =        "A Distributed Architecture for Smart Recycling Using
                 Machine Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "9",
  pages =        "141",
  day =          "24",
  month =        aug,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12090141",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 28 10:44:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/9/141",
  abstract =     "Recycling is vital for a sustainable and clean
                 environment. Developed and developing countries are
                 both facing the problem of solid management waste and
                 recycling issues. Waste classification is a good
                 solution to separate the waste from the recycle
                 materials. In this work, we propose a cloud based
                 classification algorithm for automated machines in
                 recycling factories using machine learning. We trained
                 an efficient MobileNet model, able to classify five
                 different types of waste. The inference can be
                 performed in real-time on a cloud server. Various
                 techniques are described and used in order to improve
                 the classification accuracy, such as data augmentation
                 and hyper-parameter tuning. Multiple industrial
                 stations are supported and interconnected via custom
                 data transmission protocols, along with security
                 features. Experimental results indicated that our
                 solution can achieve excellent performance with 96.57\%
                 accuracy utilizing a cloud server.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Smart System Infrastructure and
                 Applications.",
}

@Article{Masinde:2020:SEL,
  author =       "Newton Masinde and Liat Khitman and Iakov Dlikman and
                 Kalman Graffi",
  title =        "Systematic Evaluation of {LibreSocial} --- a
                 Peer-to-Peer Framework for Online Social Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "9",
  pages =        "140",
  day =          "20",
  month =        aug,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12090140",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 28 10:44:27 MDT 2020",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/9/140",
  abstract =     "Peer-to-peer (P2P) networks have been under
                 investigation for several years now, with many novel
                 mechanisms proposed as is shown by available articles.
                 Much of the research focused on showing how the
                 proposed mechanism improves system performance. In
                 addition, several applications were proposed to harness
                 the benefits of the P2P networks. Of these
                 applications, online social networks (OSNs) raised much
                 interest particularly because of the scalability and
                 privacy concerns with centralized OSNs, hence several
                 proposals are in existence. However, accompanying
                 studies on the overall performance of the P2P network
                 under the weight of the OSN applications outside
                 simulations are very few, if any. In this paper, the
                 aim is to undertake a systematic evaluation of the
                 performance of a P2P framework for online social
                 networks called LibreSocial. Benchmark tests are
                 designed, taking into account the random behavior of
                 users, effects of churn on system stability and effect
                 of replication factor. We manage to run benchmark tests
                 for up to 2000 nodes and show the performance against
                 costs of the system in general. From the results it is
                 evident that LibreSocial's performance is capable of
                 meeting the needs of users.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Privacy in Social Networks
                 and Solutions.",
}

@Article{Carta:2020:LFE,
  author =       "Salvatore Carta and Alessandro Sebastian Podda and
                 Diego Reforgiato Recupero and Roberto Saia",
  title =        "A Local Feature Engineering Strategy to Improve
                 Network Anomaly Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "10",
  pages =        "177",
  day =          "21",
  month =        oct,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12100177",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/10/177",
  abstract =     "The dramatic increase in devices and services that has
                 characterized modern societies in recent decades,
                 boosted by the exponential growth of ever faster
                 network connections and the predominant use of wireless
                 connection technologies, has materialized a very
                 crucial challenge in terms of security. The
                 anomaly-based intrusion detection systems, which for a
                 long time have represented some of the most efficient
                 solutions to detect intrusion attempts on a network,
                 have to face this new and more complicated scenario.
                 Well-known problems, such as the difficulty of
                 distinguishing legitimate activities from illegitimate
                 ones due to their similar characteristics and their
                 high degree of heterogeneity, today have become even
                 more complex, considering the increase in the network
                 activity. After providing an extensive overview of the
                 scenario under consideration, this work proposes a
                 Local Feature Engineering (LFE) strategy aimed to face
                 such problems through the adoption of a data
                 preprocessing strategy that reduces the number of
                 possible network event patterns, increasing at the same
                 time their characterization. Unlike the canonical
                 feature engineering approaches, which take into account
                 the entire dataset, it operates locally in the feature
                 space of each single event. The experiments conducted
                 on real-world data showed that this strategy, which is
                 based on the introduction of new features and the
                 discretization of their values, improves the
                 performance of the canonical state-of-the-art
                 solutions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Wireless Internet, Multimedia, and
                 Artificial Intelligence: New Applications and
                 Infrastructures.",
}

@Article{Scheel:2020:VIA,
  author =       "Christian Scheel and Francesca Fallucchi and Ernesto
                 William {De Luca}",
  title =        "Visualization, Interaction and Analysis of
                 Heterogeneous Textbook Resources",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "10",
  pages =        "176",
  day =          "21",
  month =        oct,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12100176",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/10/176",
  abstract =     "Historically grown research projects, run by
                 researchers with limited understanding of data
                 sustainability, data reusability and standards, often
                 lead to data silos. While the data are very valuable it
                 can not be used by any service except the tool it was
                 prepared for. Over the years, the number of such data
                 graveyards will increase because new projects will
                 always be designed from scratch. In this work we
                 propose a Component Metadata Infrastructure
                 (CMDI)-based approach for data rescue and data reuse,
                 where data are retroactively joined into one repository
                 minimizing the implementation effort of future research
                 projects.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Data Science and Knowledge Discovery.",
}

@Article{Song:2020:SCU,
  author =       "Xin Song and Lin Xia and Siyang Xu and Yue Wang",
  title =        "Secure Communication for Uplink Cellular Networks
                 Assisted with Full-Duplex Device-to-Device User",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "10",
  pages =        "175",
  day =          "18",
  month =        oct,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12100175",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/10/175",
  abstract =     "In this paper, the secure communication based on the
                 full-duplex (FD) device-to-device (D2D) in cellular
                 networks is proposed. For the proposed scheme, the
                 novel model is established, in which a D2D user is
                 played as a relay operating in FD mode to assist in the
                 secure transmission of uplink information. Considering
                 that the D2D user as a relay is untrusted, D2D link
                 rate maximization is formulated with the constraint of
                 secrecy rate, which ensures the security of uplink
                 cellular networks. To cope with the optimization
                 problem, the optimal power allocation factors of the
                 cellular user (CU) and the D2D user are jointly
                 optimized. Firstly, by using the monotonicity of the
                 objective function, the optimal solution of the power
                 allocation factor at the D2D user can be obtained.
                 Subsequently, the closed-form expression of the optimal
                 power allocation factor at the CU is derived and
                 verified that the solution is the global minimum point.
                 Simulation results verify that the proposed scheme has
                 better output performance than the conventional
                 scheme.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Cybersecurity.",
}

@Article{Rahayu:2020:RTU,
  author =       "Flourensia Sapty Rahayu and Lukito Edi Nugroho and
                 Ridi Ferdiana and Djoko Budiyanto Setyohadi",
  title =        "Research Trend on the Use of {IT} in Digital
                 Addiction: an Investigation Using a Systematic
                 Literature Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "10",
  pages =        "174",
  day =          "18",
  month =        oct,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12100174",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/10/174",
  abstract =     "Despite the negative role of IT in digital addiction
                 development, IT may have a positive role in dealing
                 with digital addiction. The present study undertakes a
                 systematic literature review to explore the state of
                 play and the trend regarding the use of IT in digital
                 addiction research. Using predefined keywords, the
                 Scopus database was searched for relevant literature
                 published from 2017 to 2020. The initial search found
                 1655 papers. Six stages of study selection were
                 completed using a set of inclusion and exclusion
                 criteria. The study selection and quality assessment
                 process were applied, then 15 papers were selected for
                 further review. The results show that addiction
                 detection using IT is the most researched topic in
                 digital addiction research. The most commonly used IT
                 in the selected studies are AI methods and biosignal
                 recording systems. Various approaches in detection,
                 prevention, and intervention are suggested in the
                 selected studies. The advantages and limitations of
                 each approach are discussed. Based on these results,
                 some future research directions are suggested.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue The Future Internet of Medical Things.",
}

@Article{Vilella:2020:IDT,
  author =       "Salvatore Vilella and Mirko Lai and Daniela Paolotti
                 and Giancarlo Ruffo",
  title =        "Immigration as a Divisive Topic: Clusters and Content
                 Diffusion in the {Italian} {Twitter} Debate",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "10",
  pages =        "173",
  day =          "15",
  month =        oct,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12100173",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/10/173",
  abstract =     "In this work, we apply network science to analyse
                 almost 6 M tweets about the debate around immigration
                 in Italy, collected between 2018 and 2019, when many
                 related events captured media outlets' attention. Our
                 aim was to better understand the dynamics underlying
                 the interactions on social media on such a delicate and
                 divisive topic, which are the actors that are leading
                 the discussion, and whose messages have the highest
                 chance to reach out the majority of the accounts that
                 are following the debate. The debate on Twitter is
                 represented with networks; we provide a
                 characterisation of the main clusters by looking at the
                 highest in-degree nodes in each one and by analysing
                 the text of the tweets of all the users. We find a
                 strongly segregated network which shows an explicit
                 interplay with the Italian political and social
                 landscape, that however seems to be disconnected from
                 the actual geographical distribution and relocation of
                 migrants. In addition, quite surprisingly, the
                 influencers and political leaders that apparently lead
                 the debate, do not necessarily belong to the clusters
                 that include the majority of nodes: we find evidence of
                 the existence of a `silent majority' that is more
                 connected to accounts who expose a more positive stance
                 toward migrants, while leaders whose stance is negative
                 attract apparently more attention. Finally, we see that
                 the community structure clearly affects the diffusion
                 of content (URLs) by identifying the presence of both
                 local and global trends of diffusion, and that
                 communities tend to display segregation regardless of
                 their political and cultural background. In particular,
                 we observe that messages that spread widely in the two
                 largest clusters, whose most popular members are also
                 notoriously at the opposite sides of the political
                 spectrum, have a very low chance to get visibility into
                 other clusters.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Network analysis and computational
                 social science: theory, methods, applications, future
                 perspectives.",
}

@Article{Shi:2020:ERS,
  author =       "Yanjun Shi and Yijia Guo and Lingling Lv and Keshuai
                 Zhang",
  title =        "An Efficient Resource Scheduling Strategy for {V2X}
                 Microservice Deployment in Edge Servers",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "10",
  pages =        "172",
  day =          "15",
  month =        oct,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12100172",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/10/172",
  abstract =     "The fast development of connected vehicles with
                 support for various V2X (vehicle-to-everything)
                 applications carries high demand for quality of edge
                 services, which concerns microservice deployment and
                 edge computing. We herein propose an efficient resource
                 scheduling strategy to containerize microservice
                 deployment for better performance. Firstly, we quantify
                 three crucial factors (resource utilization, resource
                 utilization balancing, and microservice dependencies)
                 in resource scheduling. Then, we propose a
                 multi-objective model to achieve equilibrium in these
                 factors and a multiple fitness genetic algorithm (MFGA)
                 for the balance between resource utilization, resource
                 utilization balancing, and calling distance, where a
                 container dynamic migration strategy in the crossover
                 and mutation process of the algorithm is provided. The
                 simulated results from Container-CloudSim showed the
                 effectiveness of our MFGA.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Selected Papers from the International
                 Conference on Communications, Signal Processing and
                 Their Applications (ICCSPA '20).",
}

@Article{Tipantuna:2020:NEE,
  author =       "Christian Tipantu{\~n}a and Xavier Hesselbach",
  title =        "{NFV}-Enabled Efficient Renewable and Non-Renewable
                 Energy Management: Requirements and Algorithms",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "10",
  pages =        "171",
  day =          "14",
  month =        oct,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12100171",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/10/171",
  abstract =     "The increasing worldwide energy demand, the CO$_2$
                 emissions generated due to the production and use of
                 energy, climate change, and the depletion of natural
                 resources are important concerns that require new
                 solutions for energy generation and management. In
                 order to ensure energy sustainability, measures,
                 including the use of renewable energy sources, the
                 deployment of adaptive energy consumption schemes, and
                 consumer participation, are currently envisioned as
                 feasible alternatives. Accordingly, this paper presents
                 the requirements and algorithmic solutions for
                 efficient management of energy consumption, which aims
                 to optimize the use of available energy, whether or not
                 it is 100\% renewable, by minimizing the waste of
                 energy. The proposal works within a Demand-Response
                 environment, uses Network Functions Virtualization as
                 an enabling technology, and leverages the massive
                 connectivity of the Internet of Things provided by
                 modern communications technologies. The energy
                 consumption optimization problem is formulated as an
                 Integer Linear Program. It is optimally solved while
                 using a brute-force search strategy, defined as O pt T
                 s, to detect all concerns that are related to the
                 problem. Given the NP-hard nature of the problem and
                 the non-polynomial complexity of O pt T s, some
                 heuristic solutions are analyzed. Subsequently, a
                 heuristic strategy, described as Fast Ts based on a
                 pre-partitioning method, is implemented. The simulation
                 results validate our proposed energy management
                 solution. Exact and heuristic strategies, when deployed
                 in the Network Functions Virtualization domain,
                 demonstrate improvements in the way that energy is
                 consumed, thereby offering an increase in service
                 processing. The evaluation results also show that Fast
                 Ts produces high-quality solutions that are close to
                 those of O pt Ts while executing 230 $ \times $--5000
                 $ \times $ faster.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Feature Papers for Future
                 Internet-Internet of Things Section.",
}

@Article{Huang:2020:ANS,
  author =       "Hailong Huang and Andrey V. Savkin",
  title =        "Autonomous Navigation of a Solar-Powered {UAV} for
                 Secure Communication in Urban Environments with
                 Eavesdropping Avoidance",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "10",
  pages =        "170",
  day =          "10",
  month =        oct,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12100170",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/10/170",
  abstract =     "This paper considers the navigation of a solar-powered
                 unmanned aerial vehicle (UAV) for securing the
                 communication with an intended ground node in the
                 presence of eavesdroppers in urban environments. To
                 complete this task, the UAV needs to not only fly
                 safely in the complex urban environment, but also take
                 into account the communication performance with the
                 intended node and eavesdroppers. To this end, we
                 formulate a multi-objective optimization problem to
                 plan the UAV path. This problem jointly considers the
                 maximization of the residual energy of the
                 solar-powered UAV at the end of the mission, the
                 maximization of the time period in which the UAV can
                 securely communicate with the intended node and the
                 minimization of the time to reach the destination. We
                 pay attention to the impact of the buildings in the
                 urban environments, which may block the transmitted
                 signals and also create some shadow region where the
                 UAV cannot harvest energy. A Rapidly-exploring Random
                 Tree (RRT) based path planning scheme is presented.
                 This scheme captures the nonlinear UAV motion model,
                 and is computationally efficient considering the
                 randomness nature. From the generated tree, a set of
                 possible paths can be found. We evaluate the security
                 of the wireless communication, compute the overall
                 energy consumption as well as the harvested amount for
                 each path and calculate the time to complete the
                 flight. Compared to a general RRT scheme, the proposed
                 method enables a large time window for the UAV to
                 securely transmit data.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Wireless Internet, Multimedia, and
                 Artificial Intelligence: New Applications and
                 Infrastructures.",
}

@Article{Petrov:2020:ACC,
  author =       "Mikhail Petrov",
  title =        "An Approach to Changing Competence Assessment for
                 Human Resources in Expert Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "10",
  pages =        "169",
  day =          "03",
  month =        oct,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12100169",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/10/169",
  abstract =     "An expert network is a community of professionals in a
                 specific field, united by an information system, in
                 which different tasks are solved. One of the main tasks
                 in expert networks is the selection of specialists with
                 specified competencies for joint problem solving. The
                 main characteristic of an expert network member is a
                 set of competencies, which includes both functional
                 aspects and personal qualities. For this reason, the
                 procedure for selecting specialists and ranking them is
                 critical. Such a procedure uses specialists' competence
                 assessments from the expert network. If these
                 assessments are out of date, the project results can be
                 unsuccessful. This article proposes an approach aimed
                 at automating the assessment of the specialists'
                 competencies based on the projects results. This
                 approach consists of a reference model and an algorithm
                 of competence assessment change for human resources.
                 The paper also includes an algorithm evaluation on
                 generated data.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Techno-Social Smart Systems.",
}

@Article{Alabdan:2020:PAS,
  author =       "Rana Alabdan",
  title =        "Phishing Attacks Survey: Types, Vectors, and Technical
                 Approaches",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "10",
  pages =        "168",
  day =          "30",
  month =        sep,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12100168",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/10/168",
  abstract =     "Phishing attacks, which have existed for several
                 decades and continue to be a major problem today,
                 constitute a severe threat in the cyber world.
                 Attackers are adopting multiple new and creative
                 methods through which to conduct phishing attacks,
                 which are growing rapidly. Therefore, there is a need
                 to conduct a comprehensive review of past and current
                 phishing approaches. In this paper, a review of the
                 approaches used during phishing attacks is presented.
                 This paper comprises a literature review, followed by a
                 comprehensive examination of the characteristics of the
                 existing classic, modern, and cutting-edge phishing
                 attack techniques. The aims of this paper are to build
                 awareness of phishing techniques, educate individuals
                 about these attacks, and encourage the use of phishing
                 prevention techniques, in addition to encouraging
                 discourse among the professional community about this
                 topic.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Privacy in Social Networks
                 and Solutions.",
}

@Article{Thapa:2020:CML,
  author =       "Niraj Thapa and Zhipeng Liu and Dukka B. KC and
                 Balakrishna Gokaraju and Kaushik Roy",
  title =        "Comparison of Machine Learning and Deep Learning
                 Models for Network Intrusion Detection Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "10",
  pages =        "167",
  day =          "30",
  month =        sep,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12100167",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/10/167",
  abstract =     "The development of robust anomaly-based network
                 detection systems, which are preferred over static
                 signal-based network intrusion, is vital for
                 cybersecurity. The development of a flexible and
                 dynamic security system is required to tackle the new
                 attacks. Current intrusion detection systems (IDSs)
                 suffer to attain both the high detection rate and low
                 false alarm rate. To address this issue, in this paper,
                 we propose an IDS using different machine learning (ML)
                 and deep learning (DL) models. This paper presents a
                 comparative analysis of different ML models and DL
                 models on Coburg intrusion detection datasets (CIDDSs).
                 First, we compare different ML- and DL-based models on
                 the CIDDS dataset. Second, we propose an ensemble model
                 that combines the best ML and DL models to achieve
                 high-performance metrics. Finally, we benchmarked our
                 best models with the CIC-IDS2017 dataset and compared
                 them with state-of-the-art models. While the popular
                 IDS datasets like KDD99 and NSL-KDD fail to represent
                 the recent attacks and suffer from network biases,
                 CIDDS, used in this research, encompasses labeled
                 flow-based data in a simulated office environment with
                 both updated attacks and normal usage. Furthermore,
                 both accuracy and interpretability must be considered
                 while implementing AI models. Both ML and DL models
                 achieved an accuracy of 99\% on the CIDDS dataset with
                 a high detection rate, low false alarm rate, and
                 relatively low training costs. Feature importance was
                 also studied using the Classification and regression
                 tree (CART) model. Our models performed well in 10-fold
                 cross-validation and independent testing. CART and
                 convolutional neural network (CNN) with embedding
                 achieved slightly better performance on the CIC-IDS2017
                 dataset compared to previous models. Together, these
                 results suggest that both ML and DL methods are robust
                 and complementary techniques as an effective network
                 intrusion detection system.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Computer Vision, Deep Learning and
                 Machine Learning with Applications.",
}

@Article{Papa:2020:SDM,
  author =       "Louis Edward Papa and Thaier Hayajneh",
  title =        "A Survey of Defensive Measures for Digital Persecution
                 in the Global South",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "10",
  pages =        "166",
  day =          "29",
  month =        sep,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12100166",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/10/166",
  abstract =     "This paper examines the phenomenon of digital
                 persecution in the Global South and evaluates tools
                 that defend against it. First, the paper explains the
                 nature of persecution and its digital incarnation. It
                 then provides a contextual overview of real-world
                 instances of digital persecution in seven Global South
                 countries. The possible defensive technologies against
                 censorship and surveillance are discussed. The article
                 goes on to discuss barriers to technology adoption in
                 the Global South, explains the security implication of
                 these difficulties, and examines the role that human
                 computer interaction (HCI) metrics could play in
                 overcoming these challenges. Finally, the paper surveys
                 the viability of sixteen security tools in a Global
                 South context. The survey results were mixed, with
                 37.5\% of the reviewed tools being deemed to be
                 inviable for use in the Global South to defend against
                 persecution. Prescriptive recommendations are provided
                 for creating security tools that are universal, simple,
                 and effective.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Digital Society Challenges in Developing
                 Countries.",
}

@Article{Mikhailov:2020:TBA,
  author =       "Sergei Mikhailov and Alexey Kashevnik",
  title =        "Tourist Behaviour Analysis Based on Digital Pattern of
                 Life --- an Approach and Case Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "10",
  pages =        "165",
  day =          "28",
  month =        sep,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12100165",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/10/165",
  abstract =     "The tourism industry has been rapidly growing over the
                 last years and IT technologies have had a great affect
                 on tourists as well. Tourist behaviour analysis has
                 been the subject of different research studies in
                 recent years. This paper presents the digital pattern
                 of life concept which simplifies the tourist behaviour
                 models' construction and usage. The digital pattern of
                 life defines the general concepts of tourist behaviour,
                 connects the tourist and the digital world and allows
                 us to track behaviour changes over time. A literature
                 review of the current state of the research in selected
                 fields is performed for identifying the existing
                 problems. The case studies of behaviour analysis based
                 on classification, clustering and time series events
                 behaviour models are shown. An ontological approach and
                 artificial neural networks are used during behaviour
                 model construction, training and evaluation. The
                 gathered results can be used by smart tourism service
                 developers and business stakeholders.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Techno-Social Smart Systems.",
}

@Article{Sun:2020:PEO,
  author =       "Wei Sun and Hui Su and Huacheng Xie",
  title =        "Policy-Engineering Optimization with Visual
                 Representation and Separation-of-Duty Constraints in
                 Attribute-Based Access Control",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "10",
  pages =        "164",
  day =          "27",
  month =        sep,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12100164",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/10/164",
  abstract =     "Recently, attribute-based access control (ABAC) has
                 received increasingly more attention and has emerged as
                 the desired access control mechanism for many
                 organizations because of its flexibility and
                 scalability for authorization management, as well as
                 its security policies, such as separation-of-duty
                 constraints and mutually exclusive constraints.
                 Policy-engineering technology is an effective approach
                 for the construction of ABAC systems. However, most
                 conventional methods lack interpretability, and their
                 constructing processes are complex. Furthermore, they
                 do not consider the separation-of-duty constraints. To
                 address these issues in ABAC, this paper proposes a
                 novel method called policy engineering optimization
                 with visual representation and separation of duty
                 constraints (PEO\_VR\&SOD). First, to enhance
                 interpretability while mining a minimal set of rules,
                 we use the visual technique with Hamming distance to
                 reduce the policy mining scale and present a policy
                 mining algorithm. Second, to verify whether the
                 separation of duty constraints can be satisfied in a
                 constructed policy engineering system, we use the
                 method of SAT-based model counting to reduce the
                 constraints and construct mutually exclusive
                 constraints to implicitly enforce the given separation
                 of duty constraints. The experiments demonstrate the
                 efficiency and effectiveness of the proposed method and
                 show encouraging results.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Cybersecurity.",
}

@Article{Al-Ali:2020:DTC,
  author =       "A. R. Al-Ali and Ragini Gupta and Tasneem Zaman Batool
                 and Taha Landolsi and Fadi Aloul and Ahmad {Al
                 Nabulsi}",
  title =        "Digital Twin Conceptual Model within the Context of
                 {Internet of Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "10",
  pages =        "163",
  day =          "26",
  month =        sep,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12100163",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/10/163",
  abstract =     "As the Internet of Things (IoT) is gaining ground and
                 becoming increasingly popular in smart city
                 applications such as smart energy, smart buildings,
                 smart factories, smart transportation, smart farming,
                 and smart healthcare, the digital twin concept is
                 evolving as complementary to its counter physical part.
                 While an object is on the move, its operational and
                 surrounding environmental parameters are collected by
                 an edge computing device for local decision. A virtual
                 replica of such object (digital twin) is based in the
                 cloud computing platform and hosts the real-time
                 physical object data, 2D and 3D models, historical
                 data, and bill of materials (BOM) for further
                 processing, analytics, and visualization. This paper
                 proposes an end-to-end digital twin conceptual model
                 that represents its complementary physical object from
                 the ground to the cloud. The paper presents the
                 proposed digital twin model's multi-layers, namely,
                 physical, communication, virtual space, data analytic
                 and visualization, and application as well as the
                 overlapping security layer. The hardware and software
                 technologies that are used in building such a model
                 will be explained in detail. A use case will be
                 presented to show how the layers collect, exchange, and
                 process the physical object data from the ground to the
                 cloud.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Feature Papers for Future
                 Internet-Internet of Things Section.",
}

@Article{Villegas-Ch:2020:ITM,
  author =       "William Villegas-Ch and Xavier Palacios-Pacheco and
                 Milton Rom{\'a}n-Ca{\~n}izares",
  title =        "An {Internet of Things} Model for Improving Process
                 Management on University Campus",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "10",
  pages =        "162",
  day =          "25",
  month =        sep,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12100162",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/10/162",
  abstract =     "Currently, there are several emerging technologies
                 that seek to improve quality of life. To achieve this,
                 it is important to establish the various technologies'
                 fields of action and to determine which technology
                 meets the conditions established by the environment in
                 which it is designed to operate in order to satisfy the
                 needs of society. One type of environment is the
                 university campus. This particular environment is
                 conducive to the development and testing of
                 technological innovations that might later be
                 replicated in larger environments such as smart cities.
                 The technology that has experienced the greatest
                 development and introduction of applications is the
                 Internet of Things. The wide variety of available
                 devices and the wide reach of the Internet have become
                 ideal parameters for the application of the Internet of
                 Things in areas that previously required the work of
                 people. The Internet of Things is seen as an assistant
                 to, or a substitute for, processes that are generally
                 routine and which require the effort of one or more
                 people. This work focuses specifically on processes to
                 improve administrative management in a university
                 through the use of the Internet of Things.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Feature Papers for Future
                 Internet-Internet of Things Section.",
}

@Article{Jahedi:2020:VSH,
  author =       "Zahra Jahedi and Thomas Kunz",
  title =        "The Value of Simple Heuristics for Virtualized Network
                 Function Placement",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "10",
  pages =        "161",
  day =          "25",
  month =        sep,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12100161",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/10/161",
  abstract =     "Network Function Virtualization (NFV) can lower the
                 CAPEX and/or OPEX for service providers and allow for
                 quick deployment of services. Along with the advantages
                 come some challenges. The main challenge in the use of
                 Virtualized Network Functions (VNF) is the VNFs'
                 placement in the network. There is a wide range of
                 mathematical models proposed to place the Network
                 Functions (NF) optimally. However, the critical problem
                 of mathematical models is that they are NP-hard, and
                 consequently not applicable to larger networks. In
                 wireless networks, we are considering the scarcity of
                 Bandwidth (BW) as another constraint that is due to the
                 presence of interference. While there exist many
                 efforts in designing a heuristic model that can provide
                 solutions in a timely manner, the primary focus with
                 such heuristics was almost always whether they provide
                 results almost as good as optimal solution.
                 Consequently, the heuristics themselves become quite
                 non-trivial, and solving the placement problem for
                 larger networks still takes a significant amount of
                 time. In this paper, in contrast, we focus on designing
                 a simple and scalable heuristic. We propose four
                 heuristics, which are gradually becoming more complex.
                 We compare their performance with each other, a related
                 heuristic proposed in the literature, and a
                 mathematical optimization model. Our results
                 demonstrate that while more complex placement
                 heuristics do not improve the performance of the
                 algorithm in terms of the number of accepted placement
                 requests, they take longer to solve and therefore are
                 not applicable to larger networks.In contrast, a very
                 simple heuristic can find near-optimal solutions much
                 faster than the other more complicated heuristics while
                 keeping the number of accepted requests close to the
                 results achieved with an NP-hard optimization model.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Machine Learning Advances Applied to
                 Wireless Multi-hop IoT Networks.",
}

@Article{Ali:2020:TFA,
  author =       "Guma Ali and Mussa Ally Dida and Anael Elikana Sam",
  title =        "Two-Factor Authentication Scheme for Mobile Money: a
                 Review of Threat Models and Countermeasures",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "10",
  pages =        "160",
  day =          "24",
  month =        sep,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12100160",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/10/160",
  abstract =     "The proliferation of digital financial innovations
                 like mobile money has led to the rise in mobile
                 subscriptions and transactions. It has also increased
                 the security challenges associated with the current
                 two-factor authentication (2FA) scheme for mobile money
                 due to the high demand. This review paper aims to
                 determine the threat models in the 2FA scheme for
                 mobile money. It also intends to identify the
                 countermeasures to overcome the threat models. A
                 comprehensive literature search was conducted from the
                 Google Scholar and other leading scientific databases
                 such as IEEE Xplore, MDPI, Emerald Insight, Hindawi,
                 ACM, Elsevier, Springer, and Specific and International
                 Journals, where 97 papers were reviewed that focused on
                 the topic. Descriptive research papers and studies
                 related to the theme were selected. Three reviewers
                 extracted information independently on authentication,
                 mobile money system architecture, mobile money access,
                 the authentication scheme for mobile money, various
                 attacks on the mobile money system (MMS), threat models
                 in the 2FA scheme for mobile money, and
                 countermeasures. Through literature analysis, it was
                 found that the threat models in the 2FA scheme for
                 mobile money were categorised into five, namely,
                 attacks against privacy, attacks against
                 authentication, attacks against confidentiality,
                 attacks against integrity, and attacks against
                 availability. The countermeasures include use of
                 cryptographic functions (e.g., asymmetric encryption
                 function, symmetric encryption function, and hash
                 function) and personal identification (e.g.,
                 number-based and biometric-based countermeasures). This
                 review study reveals that the current 2FA scheme for
                 mobile money has security gaps that need to be
                 addressed since it only uses a personal identification
                 number (PIN) and a subscriber identity module (SIM) to
                 authenticate users, which are susceptible to attacks.
                 This work, therefore, will help mobile money service
                 providers (MMSPs), decision-makers, and governments
                 that wish to improve their current 2FA scheme for
                 mobile money.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gameiro:2020:NFI,
  author =       "Lu{\'\i}s Gameiro and Carlos Senna and Miguel
                 Lu{\'\i}s",
  title =        "{ndnIoT-FC}: {IoT} Devices as First-Class Traffic in
                 Name Data Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "207",
  day =          "21",
  month =        nov,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110207",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/207",
  abstract =     "In recent years we have been assisting a radical
                 change in the way devices are connected to the
                 Internet. In this new scope, the traditional TCP/IP
                 host-centric network fails in large-scale mobile
                 wireless distributed environments, such as IoT
                 scenarios, due to node mobility, dynamic topologies and
                 intermittent connectivity, and the Information-Centric
                 Networking (ICN) paradigm has been considered the most
                 promising candidate to overcome the drawbacks of
                 host-centric architectures. Despite bringing efficient
                 solutions for content distribution, the basic ICN
                 operating principle, where content must always be
                 associated with an interest, has serious restrictions
                 in IoT environments in relation to scale, performance,
                 and naming, among others. To address such drawbacks, we
                 are presenting ndnIoT-FC, an NDN-based architecture
                 that respects the ICN rules but offers special
                 treatment for IoT traffic. It combines efficient hybrid
                 naming with strategies to minimize the number of
                 interests and uses caching strategies that virtually
                 eliminates copies of IoT data from intermediate nodes.
                 The ndnIoT-FC makes available new NDN-based
                 application-to-application protocol to implement a
                 signature model operation and tools to manage its life
                 cycle, following a publisher-subscriber scheme. To
                 demonstrate the versatility of the proposed
                 architecture, we show the results of the efficient
                 gathering of environmental information in a simulation
                 environment considering different and distinct use
                 cases.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Feature Papers for Future
                 Internet-Internet of Things Section.",
}

@Article{Lousado:2020:MSE,
  author =       "Jos{\'e} Paulo Lousado and Sandra Antunes",
  title =        "Monitoring and Support for Elderly People Using {LoRa}
                 Communication Technologies: {IoT} Concepts and
                 Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "206",
  day =          "20",
  month =        nov,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110206",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/206",
  abstract =     "The pandemic declared by the World Health Organization
                 due to the SARS-CoV-2 virus (COVID-19) awakened us to a
                 reality that most of us were previously unaware
                 of---isolation, confinement and the massive use of
                 information and communication technologies, as well as
                 increased knowledge of the difficulties and limitations
                 of their use. This article focuses on the rapid
                 implementation of low-cost technologies, which allow us
                 to answer a fundamental question: how can near
                 real-time monitoring and follow-up of the elderly and
                 their health conditions, as well as their homes,
                 especially for those living in isolated and remote
                 areas, be provided within their care and protect them
                 from risky events? The system proposed here as a proof
                 of concept uses low-cost devices for communication and
                 data processing, supported by Long-Range (LoRa)
                 technology and connection to The Things Network,
                 incorporating various sensors, both personal and in the
                 residence, allowing family members, neighbors and
                 authorized entities, including security forces, to have
                 access to the health condition of system users and the
                 habitability of their homes, as well as their urgent
                 needs, thus evidencing that it is possible, using
                 low-cost systems, to implement sensor networks for
                 monitoring the elderly using the LoRa gateway and other
                 support infrastructures.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Data Science and Knowledge Discovery.",
}

@Article{Oliveira:2020:FME,
  author =       "Jo{\~a}o Oliveira and Gon{\c{c}}alo Carvalho and Bruno
                 Cabral and Jorge Bernardino",
  title =        "Failure Mode and Effect Analysis for Cyber-Physical
                 Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "205",
  day =          "20",
  month =        nov,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110205",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/205",
  abstract =     "Cyber-Physical Systems (CPS) are a prominent component
                 of the modern digital transformation, which combines
                 the dynamics of the physical processes with those of
                 software and networks. Critical infrastructures have
                 built-in CPS, and assessing its risk is crucial to
                 avoid significant losses, both economic and social. As
                 CPS are increasingly attached to the world's main
                 industries, these systems' criticality depends not only
                 on software efficiency and availability but also on
                 cyber-security awareness. Given this, and because
                 Failure Mode and Effect Analysis (FMEA) is one of the
                 most effective methods to assess critical
                 infrastructures' risk, in this paper, we show how this
                 method performs in the analysis of CPS threats, also
                 exposing the main drawbacks concerning CPS risk
                 assessment. We first propose a risk prevention analysis
                 to the Communications-Based Train Control (CBTC)
                 system, which involves exploiting cyber
                 vulnerabilities, and we introduce a novel approach to
                 the failure modes' Risk Priority Number (RPN)
                 estimation. We also propose how to adapt the FMEA
                 method to the requirement of CPS risk evaluation. We
                 applied the proposed procedure to the CBTC system use
                 case since it is a CPS with a substantial cyber
                 component and network data transfer.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Feature Papers for Future
                 Internet---Cybersecurity Section.",
}

@Article{Grande-de-Prado:2020:DCG,
  author =       "Mario Grande-de-Prado and Ruth Ca{\~n}{\'o}n and
                 Sheila Garc{\'\i}a-Mart{\'\i}n and Isabel Cant{\'o}n",
  title =        "Digital Competence and Gender: Teachers in Training.
                 {A} Case Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "204",
  day =          "20",
  month =        nov,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110204",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/204",
  abstract =     "The ICTs are simultaneously an important tool and
                 subject in teacher training. It, therefore, follows
                 that digital competence is fundamental and constitutes
                 a significant educational challenge, particularly the
                 digital divide or gap by gender. The aim is to identify
                 and analyze self-perceptions of digital skills, and the
                 possible relationship of these to gender, in first-year
                 university students taking a degree in primary
                 education teacher training at a Spanish faculty of
                 education. This is a descriptive study using
                 ex-post-facto method and collecting data from a
                 questionnaire administered for four consecutive years
                 to the above-mentioned subjects. The results revealed
                 gender differences in the students' reported
                 perceptions. Men were more likely to perceive
                 themselves as competent in the use of ICTs, reporting
                 better information management and online collaboration
                 skills using digital media. Besides, they made more use
                 of computers as their sole device for browsing,
                 downloading, and streaming and felt more confident
                 about solving problems with devices. In contrast, women
                 reported making more use of mobile phones and were more
                 familiar with social media and aspects related to image
                 and text processing and graphic design.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Education Responses to Technological
                 Challenges and Their Impact on Classrooms.",
}

@Article{Casadei:2020:PCP,
  author =       "Roberto Casadei and Danilo Pianini and Andrea Placuzzi
                 and Mirko Viroli and Danny Weyns",
  title =        "Pulverization in Cyber-Physical Systems: Engineering
                 the Self-Organizing Logic Separated from Deployment",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "203",
  day =          "19",
  month =        nov,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110203",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/203",
  abstract =     "Emerging cyber-physical systems, such as robot swarms,
                 crowds of augmented people, and smart cities, require
                 well-crafted self-organizing behavior to properly deal
                 with dynamic environments and pervasive disturbances.
                 However, the infrastructures providing networking and
                 computing services to support these systems are
                 becoming increasingly complex, layered and
                 heterogeneous---consider the case of the
                 edge--fog--cloud interplay. This typically hinders the
                 application of self-organizing mechanisms and patterns,
                 which are often designed to work on flat networks. To
                 promote reuse of behavior and flexibility in
                 infrastructure exploitation, we argue that
                 self-organizing logic should be largely independent of
                 the specific application deployment. We show that this
                 separation of concerns can be achieved through a
                 proposed `` pulverization approach '': the global
                 system behavior of application services gets broken
                 into smaller computational pieces that are continuously
                 executed across the available hosts. This model can
                 then be instantiated in the aggregate computing
                 framework, whereby self-organizing behavior is
                 specified compositionally. We showcase how the proposed
                 approach enables expressing the application logic of a
                 self-organizing cyber-physical system in a
                 deployment-independent fashion, and simulate its
                 deployment on multiple heterogeneous infrastructures
                 that include cloud, edge, and LoRaWAN network
                 elements.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Special Issue on Cyber Physical Systems:
                 Prospects, Challenges, and Role in Software Defined
                 Networking and Blockchain.",
}

@Article{Pan:2020:PLB,
  author =       "Wei Pan and Jide Li and Xiaoqiang Li",
  title =        "Portfolio Learning Based on Deep Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "202",
  day =          "18",
  month =        nov,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110202",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/202",
  abstract =     "Traditional portfolio theory divides stocks into
                 different categories using indicators such as industry,
                 market value, and liquidity, and then selects
                 representative stocks according to them. In this paper,
                 we propose a novel portfolio learning approach based on
                 deep learning and apply it to China's stock market.
                 Specifically, this method is based on the similarity of
                 deep features extracted from candlestick charts. First,
                 we obtained whole stock information from Tushare, a
                 professional financial data interface. These raw time
                 series data are then plotted into candlestick charts to
                 make an image dataset for studying the stock market.
                 Next, the method extracts high-dimensional features
                 from candlestick charts through an autoencoder. After
                 that, K-means is used to cluster these high-dimensional
                 features. Finally, we choose one stock from each
                 category according to the Sharpe ratio and a low-risk,
                 high-return portfolio is obtained. Extensive
                 experiments are conducted on stocks in the Chinese
                 stock market for evaluation. The results demonstrate
                 that the proposed portfolio outperforms the market's
                 leading funds and the Shanghai Stock Exchange Composite
                 Index (SSE Index) in a number of metrics.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Computer Vision, Deep Learning and
                 Machine Learning with Applications.",
}

@Article{Karpinski:2020:GAT,
  author =       "Mikolaj Karpinski and Svitlana Kuznichenko and Nadiia
                 Kazakova and Oleksii Fraze-Frazenko and Daniel
                 Jancarczyk",
  title =        "Geospatial Assessment of the Territorial Road Network
                 by Fractal Method",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "201",
  day =          "17",
  month =        nov,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110201",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/201",
  abstract =     "This paper proposes an approach to the geospatial
                 assessment of a territorial road network based on the
                 fractals theory. This approach allows us to obtain
                 quantitative values of spatial complexity for any
                 transport network and, in contrast to the classical
                 indicators of the transport provisions of a territory
                 (Botcher, Henkel, Engel, Goltz, Uspensky, etc.),
                 consider only the complexity level of the network
                 itself, regardless of the area of the territory. The
                 degree of complexity is measured by a fractal
                 dimension. A method for calculating the fractal
                 dimension based on a combination of box counting and
                 GIS analysis is proposed. We created a geoprocessing
                 script tool for the GIS software system ESRI ArcGIS
                 10.7, and a study of the spatial pattern of the
                 transport network of the Ukraine territory, and other
                 countries of the world, was made. The results of the
                 study will help to better understand the different
                 aspects of the development of transport networks, their
                 changes over time and the impact on the socioeconomic
                 indicators of urban development.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Data Science and Knowledge Discovery.",
}

@Article{Li:2020:TAT,
  author =       "Haiyan Li and Hongtao Lu",
  title =        "{AT-Text}: Assembling Text Components for Efficient
                 Dense Scene Text Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "200",
  day =          "17",
  month =        nov,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110200",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/200",
  abstract =     "Text detection is a prerequisite for text recognition
                 in scene images. Previous segmentation-based methods
                 for detecting scene text have already achieved a
                 promising performance. However, these kinds of
                 approaches may produce spurious text instances, as they
                 usually confuse the boundary of dense text instances,
                 and then infer word/text line instances relying heavily
                 on meticulous heuristic rules. We propose a novel
                 Assembling Text Components (AT-text) that accurately
                 detects dense text in scene images. The AT-text
                 localizes word/text line instances in a bottom-up
                 mechanism by assembling a parsimonious component set.
                 We employ a segmentation model that encodes multi-scale
                 text features, considerably improving the
                 classification accuracy of text/non-text pixels. The
                 text candidate components are finely classified and
                 selected via discriminate segmentation results. This
                 allows the AT-text to efficiently filter out
                 false-positive candidate components, and then to
                 assemble the remaining text components into different
                 text instances. The AT-text works well on
                 multi-oriented and multi-language text without complex
                 post-processing and character-level annotation.
                 Compared with the existing works, it achieves
                 satisfactory results and a considerable balance between
                 precision and recall without a large margin in
                 ICDAR2013 and MSRA-TD 500 public benchmark datasets.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Saripalle:2020:IUT,
  author =       "Rishi Saripalle and Mehdi Sookhak and Mahboobeh
                 Haghparast",
  title =        "An Interoperable {UMLS} Terminology Service Using
                 {FHIR}",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "199",
  day =          "16",
  month =        nov,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110199",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/199",
  abstract =     "The Unified Medical Language System (UMLS) is an
                 internationally recognized medical vocabulary that
                 enables semantic interoperability across various
                 biomedical terminologies. To use its knowledge, the
                 users must understand its complex knowledge structure,
                 a structure that is not interoperable or is not
                 compliant with any known biomedical and healthcare
                 standard. Further, the users also need to have good
                 technical skills to understand its inner working and
                 interact with UMLS in general. These barriers might
                 cause UMLS usage concerns among inter-disciplinary
                 users in biomedical and healthcare informatics.
                 Currently, there exists no terminology service that
                 normalizes UMLS's complex knowledge structure to a
                 widely accepted interoperable healthcare standard and
                 allows easy access to its knowledge, thus hiding its
                 workings. The objective of this research is to design
                 and implement a light-weight terminology service that
                 allows easy access to UMLS knowledge structured using
                 the fast health interoperability resources (FHIR)
                 standard, a widely accepted interoperability healthcare
                 standard. The developed terminology service, named UMLS
                 FHIR, leverages FHIR resources and features, and can
                 easily be integrated into any application to consume
                 UMLS knowledge in the FHIR format without the need to
                 understand UMLS's native knowledge structure and its
                 internal working.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Recent Advances of Machine Learning
                 Techniques on Smartphones.",
}

@Article{Hao:2020:MAS,
  author =       "Jingjing Hao and Guangsheng Han",
  title =        "On the Modeling of Automotive Security: a Survey of
                 Methods and Perspectives",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "198",
  day =          "16",
  month =        nov,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110198",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/198",
  abstract =     "As the intelligent car-networking represents the new
                 direction of the future vehicular development,
                 automotive security plays an increasingly important
                 role in the whole car industry chain. On condition that
                 the accompanying problems of security are proofed,
                 vehicles will provide more convenience while ensuring
                 safety. Security models can be utilized as tools to
                 rationalize the security of the automotive system and
                 represent it in a structured manner. It is essential to
                 improve the knowledge about security models by
                 comparing them besides proposing new methods. This
                 paper aims to give a comprehensive introduction to the
                 topic of security models for the Intelligent Transport
                 System (ITS). A survey of the current methodologies for
                 security modeling is conducted and a classification
                 scheme is subsequently proposed. Furthermore, the
                 existing framework and methods to build automotive
                 security models are broadly examined according to the
                 features of automotive electronic system. A number of
                 fundamental aspects are defined to compare the
                 presented methods in order to comprehend the automotive
                 security modeling in depth.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Cybersecurity.",
}

@Article{Pierro:2020:ORE,
  author =       "Giuseppe Antonio Pierro and Roberto Tonelli and
                 Michele Marchesi",
  title =        "An Organized Repository of {Ethereum} Smart Contracts'
                 Source Codes and Metrics",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "197",
  day =          "15",
  month =        nov,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110197",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/197",
  abstract =     "Many empirical software engineering studies show that
                 there is a need for repositories where source codes are
                 acquired, filtered and classified. During the last few
                 years, Ethereum block explorer services have emerged as
                 a popular project to explore and search for Ethereum
                 blockchain data such as transactions, addresses,
                 tokens, smart contracts' source codes, prices and other
                 activities taking place on the Ethereum blockchain.
                 Despite the availability of this kind of service,
                 retrieving specific information useful to empirical
                 software engineering studies, such as the study of
                 smart contracts' software metrics, might require many
                 subtasks, such as searching for specific transactions
                 in a block, parsing files in HTML format, and filtering
                 the smart contracts to remove duplicated code or unused
                 smart contracts. In this paper, we afford this problem
                 by creating Smart Corpus, a corpus of smart contracts
                 in an organized, reasoned and up-to-date repository
                 where Solidity source code and other metadata about
                 Ethereum smart contracts can easily and systematically
                 be retrieved. We present Smart Corpus's design and its
                 initial implementation, and we show how the data set of
                 smart contracts' source codes in a variety of
                 programming languages can be queried and processed to
                 get useful information on smart contracts and their
                 software metrics. Smart Corpus aims to create a
                 smart-contract repository where smart-contract data
                 (source code, application binary interface (ABI) and
                 byte code) are freely and immediately available and are
                 classified based on the main software metrics
                 identified in the scientific literature. Smart
                 contracts' source codes have been validated by
                 EtherScan, and each contract comes with its own
                 associated software metrics as computed by the freely
                 available software PASO. Moreover, Smart Corpus can be
                 easily extended as the number of new smart contracts
                 increases day by day.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Eramo:2020:PIA,
  author =       "Vincenzo Eramo and Francesco Giacinto Lavacca and
                 Tiziana Catena and Paul Jaime Perez Salazar",
  title =        "Proposal and Investigation of an Artificial
                 Intelligence ({AI})-Based Cloud Resource Allocation
                 Algorithm in Network Function Virtualization
                 Architectures",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "196",
  day =          "13",
  month =        nov,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110196",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/196",
  abstract =     "The high time needed to reconfigure cloud resources in
                 Network Function Virtualization network environments
                 has led to the proposal of solutions in which a
                 prediction based-resource allocation is performed. All
                 of them are based on traffic or needed resource
                 prediction with the minimization of symmetric loss
                 functions like Mean Squared Error. When inevitable
                 prediction errors are made, the prediction
                 methodologies are not able to differently weigh
                 positive and negative prediction errors that could
                 impact the total network cost. In fact if the predicted
                 traffic is higher than the real one then an over
                 allocation cost, referred to as over-provisioning cost,
                 will be paid by the network operator; conversely, in
                 the opposite case, Quality of Service degradation cost,
                 referred to as under-provisioning cost, will be due to
                 compensate the users because of the resource under
                 allocation. In this paper we propose and investigate a
                 resource allocation strategy based on a Long Short Term
                 Memory algorithm in which the training operation is
                 based on the minimization of an asymmetric cost
                 function that differently weighs the positive and
                 negative prediction errors and the corresponding
                 over-provisioning and under-provisioning costs. In a
                 typical traffic and network scenario, the proposed
                 solution allows for a cost saving by 30\% with respect
                 to the case of solution with symmetric cost function.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Cognitive Software Defined Networking
                 and Network Function Virtualization and Applications.",
}

@Article{Martins:2020:MTR,
  author =       "Nuno Martins and Daniel Brand{\~a}o and Heitor Alvelos
                 and Sara Silva",
  title =        "E-Marketplace as a Tool for the Revitalization of
                 {Portuguese} Craft Industry: The Design Process in the
                 Development of an Online Platform",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "195",
  day =          "12",
  month =        nov,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110195",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/195",
  abstract =     "The craft trade in Portugal faces challenges that
                 compromise its productive and economic sustainability
                 and may result in the disappearance of millenary
                 techniques, traditions, and industrial practices of
                 high symbolic and historical value. The growing
                 incompatibility of these traditional activities with
                 digital technologies, the lack of resources, and a
                 growing age gap are among the main problems identified.
                 This situation made worse by various restrictions
                 pertaining to the COVID-19 pandemic points towards the
                 possibility of extinction of this type of manual arts.
                 The goal of this research is to demonstrate how the
                 design process of an e-marketplace platform, throughout
                 its different phases, may contribute to the
                 revitalization of traditional industries. The
                 methodologies adopted in the framework consisted in the
                 study of UX and UI best design practices, including
                 wireframe design, user flows, definition of personas,
                 development of prototypes, and style guides. The
                 results of the conducted usability tests to the
                 prototype allowed a gradual improvement of the
                 solution, culminating in the confirmation of its
                 effectiveness. The study concluded that digital
                 technology, namely a designed e-marketplace solution,
                 could potentially bring buyers and sellers closer
                 together, thus being a tool with high potential for the
                 dissemination and sustainability of the craft
                 industry.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Techno-Social Smart Systems.",
}

@Article{Pires:2020:HDN,
  author =       "Ivan Miguel Pires and Faisal Hussain and Nuno M.
                 Garcia and Petre Lameski and Eftim Zdravevski",
  title =        "Homogeneous Data Normalization and Deep Learning: a
                 Case Study in Human Activity Classification",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "194",
  day =          "10",
  month =        nov,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110194",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/194",
  abstract =     "One class of applications for human activity
                 recognition methods is found in mobile devices for
                 monitoring older adults and people with special needs.
                 Recently, many studies were performed to create
                 intelligent methods for the recognition of human
                 activities. However, the different mobile devices in
                 the market acquire the data from sensors at different
                 frequencies. This paper focuses on implementing four
                 data normalization techniques, i.e., MaxAbsScaler,
                 MinMaxScaler, RobustScaler, and Z-Score. Subsequently,
                 we evaluate the impact of the normalization algorithms
                 with deep neural networks (DNN) for the classification
                 of the human activities. The impact of the data
                 normalization was counterintuitive, resulting in a
                 degradation of performance. Namely, when using the
                 accelerometer data, the accuracy dropped from about
                 79\% to only 53\% for the best normalization approach.
                 Similarly, for the gyroscope data, the accuracy without
                 normalization was about 81.5\%, whereas with the best
                 normalization, it was only 60\%. It can be concluded
                 that data normalization techniques are not helpful in
                 classification problems with homogeneous data.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future Intelligent Systems and Networks
                 2020-2021.",
}

@Article{Jiang:2020:HTD,
  author =       "Fenyu Jiang and Chris Phillips",
  title =        "High Throughput Data Relay in {UAV} Wireless
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "193",
  day =          "09",
  month =        nov,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110193",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/193",
  abstract =     "As a result of their high mobility and reduced cost,
                 Unmanned Aerial Vehicles (UAVs) have been found to be a
                 promising tool in wireless networks. A UAV can perform
                 the role of a base station as well as a mobile relay,
                 connecting distant ground terminals. In this paper, we
                 dispatch a UAV to a disaster area to help relay
                 information for victims. We involve a bandwidth
                 efficient technique called the Dual-Sampling (DS)
                 method when planning the UAV flight trajectory, trying
                 to maximize the data transmission throughput. We
                 propose an iterative algorithm for solving this
                 problem. The victim bandwidth scheduling and the UAV
                 trajectory are alternately optimized in each iteration,
                 meanwhile a power balance mechanism is implemented in
                 the algorithm to ensure the proper functioning of the
                 DS method. We compare the results of the DS-enabled
                 scheme with two non-DS schemes, namely a fair bandwidth
                 allocation scheme and a bandwidth contention scheme.
                 The DS scheme outperforms the other two non-DS schemes
                 regarding max-min average data rate among all the
                 ground victims. Furthermore, we derive the theoretical
                 optimal performance of the DS scheme for a given
                 scenario, and find that the proposed approach can be
                 regarded as a general method to solve this optimization
                 problem. We also observe that the optimal UAV
                 trajectory for the DS scheme is quite different from
                 that of the non-DS bandwidth contention scheme.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Internet of Things.",
}

@Article{Azzoug:2020:PVR,
  author =       "Youcef Azzoug and Abdelmadjid Boukra and Vasco N. G.
                 J. Soares",
  title =        "A Probabilistic {VDTN} Routing Scheme Based on Hybrid
                 Swarm-Based Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "192",
  day =          "07",
  month =        nov,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110192",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/192",
  abstract =     "The probabilistic Delay Tolerant Network (DTN) routing
                 has been adjusted for vehicular network (VANET) routing
                 through numerous works exploiting the historic routing
                 profile of nodes to forward bundles through better
                 Store-Carry-and-Forward (SCF) relay nodes. In this
                 paper, we propose a new hybrid swarm-inspired
                 probabilistic Vehicular DTN (VDTN) router to optimize
                 the next-SCF vehicle selection using the combination of
                 two bio-metaheuristic techniques called the Firefly
                 Algorithm (FA) and the Glowworm Swarm Optimization
                 (GSO). The FA-based strategy exploits the stochastic
                 intelligence of fireflies in moving toward better
                 individuals, while the GSO-based strategy mimics the
                 movement of glowworm towards better area for displacing
                 and food foraging. Both FA and GSO are executed
                 simultaneously on each node to track better SCF
                 vehicles towards each bundle's destination. A
                 geography-based recovery method is performed in case no
                 better SCF vehicles are found using the hybrid FA--GSO
                 approach. The proposed FA--GSO VDTN scheme is compared
                 to ProPHET and GeoSpray routers. The simulation results
                 indicated optimized bundles flooding levels and higher
                 profitability of combined delivery delay and delivery
                 probability.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Delay-Tolerant Networking.",
}

@Article{Tsourela:2020:ITI,
  author =       "Maria Tsourela and Dafni-Maria Nerantzaki",
  title =        "An {Internet of Things (IoT)} Acceptance Model.
                 {Assessing} Consumer's Behavior toward {IoT} Products
                 and Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "191",
  day =          "03",
  month =        nov,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110191",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/191",
  abstract =     "A common managerial and theoretical concern is to know
                 how individuals perceive Internet of Things (IoT)
                 products and applications and how to accelerate
                 adoption of them. The purpose of the current study is
                 to answer, ``What are the factors that define
                 behavioral intention to adopt IoT products and
                 applications among individuals?'' An IoT adoption model
                 was developed and tested, incorporating pull factors
                 from two different information impact sources:
                 technical and psychological. This study employs
                 statistical structural equation modeling (SEM) in order
                 to examine the conceptual IoT acceptance model. It is
                 demonstrated that facilitated appropriation, perceived
                 usefulness and perceived ease of use, as mediators,
                 significantly influence consumers' attitude and
                 behavioral intention towards IoT products and
                 applications. User character, cyber resilience,
                 cognitive instrumentals, social influence and trust,
                 all with different significance rates, exhibited an
                 indirect effect, through the three mediators. The IoT
                 acceptance model (IoTAM) upgrades current knowledge on
                 consumers' behavioral intention and equips
                 practitioners with the knowledge needed to create
                 successful integrated marketing tactics and
                 communication strategies. It provides a solid base for
                 examining multirooted models for the acceptance of
                 newly formed technologies, as it bridges the
                 discontinuity in migrating from information and
                 communication technologies (ICTs) to IoT adoption
                 studies, causing distortions to societies' abilities to
                 make informed decisions about IoT adoption and use.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Feature Papers for Future
                 Internet-Internet of Things Section.",
}

@Article{Badidi:2020:FCS,
  author =       "Elarbi Badidi and Zineb Mahrez and Essaid Sabir",
  title =        "Fog Computing for Smart Cities' Big Data Management
                 and Analytics: a Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "190",
  day =          "31",
  month =        oct,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110190",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/190",
  abstract =     "Demographic growth in urban areas means that modern
                 cities face challenges in ensuring a steady supply of
                 water and electricity, smart transport, livable space,
                 better health services, and citizens' safety. Advances
                 in sensing, communication, and digital technologies
                 promise to mitigate these challenges. Hence, many smart
                 cities have taken a new step in moving away from
                 internal information technology (IT) infrastructure to
                 utility-supplied IT delivered over the Internet. The
                 benefit of this move is to manage the vast amounts of
                 data generated by the various city systems, including
                 water and electricity systems, the waste management
                 system, transportation system, public space management
                 systems, health and education systems, and many more.
                 Furthermore, many smart city applications are
                 time-sensitive and need to quickly analyze data to
                 react promptly to the various events occurring in a
                 city. The new and emerging paradigms of edge and fog
                 computing promise to address big data storage and
                 analysis in the field of smart cities. Here, we review
                 existing service delivery models in smart cities and
                 present our perspective on adopting these two emerging
                 paradigms. We specifically describe the design of a
                 fog-based data pipeline to address the issues of
                 latency and network bandwidth required by
                 time-sensitive smart city applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Emerging Trends of Fog Computing in
                 Internet of Things Applications.",
}

@Article{Alodhyani:2020:PMA,
  author =       "Fahad Alodhyani and George Theodorakopoulos and
                 Philipp Reinecke",
  title =        "Password Managers --- It's All about Trust and
                 Transparency",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "189",
  day =          "30",
  month =        oct,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110189",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/189",
  abstract =     "A password is considered to be the first line of
                 defence in protecting online accounts, but there are
                 problems when people handle their own passwords, for
                 example, password reuse and difficult to memorize.
                 Password managers appear to be a promising solution to
                 help people handle their passwords. However, there is
                 low adoption of password managers, even though they are
                 widely available, and there are fewer studies on users
                 of password managers. Therefore, the issues that cause
                 people not to use password managers must be
                 investigated and, more generally, what users think
                 about them and the user interfaces of password
                 managers. In this paper, we report three studies that
                 we conducted: on user interfaces and the functions of
                 three password managers; a usability test and an
                 interview study; and an online questionnaire study
                 about users and non-users of password managers, which
                 also compares experts and non-experts regarding their
                 use (or non-use) of password managers. Our findings
                 show that usability is not a major problem, rather lack
                 of trust and transparency are the main reasons for the
                 low adoption of password managers. Users of password
                 managers have trust and security concerns, while there
                 are a few issues with the user interfaces and functions
                 of password managers.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Privacy in Social Networks
                 and Solutions.",
}

@Article{Zhang:2020:IDB,
  author =       "Yue Zhang and Fangai Liu",
  title =        "An Improved Deep Belief Network Prediction Model Based
                 on Knowledge Transfer",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "188",
  day =          "29",
  month =        oct,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110188",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/188",
  abstract =     "A deep belief network (DBN) is a powerful generative
                 model based on unlabeled data. However, it is difficult
                 to quickly determine the best network structure and
                 gradient dispersion in traditional DBN. This paper
                 proposes an improved deep belief network (IDBN): first,
                 the basic DBN structure is pre-trained and the learned
                 weight parameters are fixed; secondly, the learned
                 weight parameters are transferred to the new neuron and
                 hidden layer through the method of knowledge transfer,
                 thereby constructing the optimal network width and
                 depth of DBN; finally, the top-down layer-by-layer
                 partial least squares regression method is used to
                 fine-tune the weight parameters obtained by the
                 pre-training, which avoids the traditional fine-tuning
                 problem based on the back-propagation algorithm. In
                 order to verify the prediction performance of the
                 model, this paper conducts benchmark experiments on the
                 Movielens-20M (ML-20M) and Last.fm-1k (LFM-1k) public
                 data sets. Compared with other traditional algorithms,
                 IDBN is better than other fixed models in terms of
                 prediction performance and training time. The proposed
                 IDBN model has higher prediction accuracy and
                 convergence speed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Future Networks: Latest Trends and
                 Developments.",
}

@Article{Muneer:2020:CAM,
  author =       "Amgad Muneer and Suliman Mohamed Fati",
  title =        "A Comparative Analysis of Machine Learning Techniques
                 for Cyberbullying Detection on {Twitter}",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "187",
  day =          "29",
  month =        oct,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110187",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/187",
  abstract =     "The advent of social media, particularly Twitter,
                 raises many issues due to a misunderstanding regarding
                 the concept of freedom of speech. One of these issues
                 is cyberbullying, which is a critical global issue that
                 affects both individual victims and societies. Many
                 attempts have been introduced in the literature to
                 intervene in, prevent, or mitigate cyberbullying;
                 however, because these attempts rely on the victims'
                 interactions, they are not practical. Therefore,
                 detection of cyberbullying without the involvement of
                 the victims is necessary. In this study, we attempted
                 to explore this issue by compiling a global dataset of
                 37,373 unique tweets from Twitter. Moreover, seven
                 machine learning classifiers were used, namely,
                 Logistic Regression (LR), Light Gradient Boosting
                 Machine (LGBM), Stochastic Gradient Descent (SGD),
                 Random Forest (RF), AdaBoost (ADB), Naive Bayes (NB),
                 and Support Vector Machine (SVM). Each of these
                 algorithms was evaluated using accuracy, precision,
                 recall, and F1 score as the performance metrics to
                 determine the classifiers' recognition rates applied to
                 the global dataset. The experimental results show the
                 superiority of LR, which achieved a median accuracy of
                 around 90.57\%. Among the classifiers, logistic
                 regression achieved the best F1 score (0.928), SGD
                 achieved the best precision (0.968), and SVM achieved
                 the best recall (1.00).",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Artificial Intelligence and Machine
                 Learning in Cybercrime Detection.",
}

@Article{Ponce:2020:ASO,
  author =       "Alan Ponce and Raul Alberto Ponce Rodriguez",
  title =        "An Analysis of the Supply of Open Government Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "186",
  day =          "29",
  month =        oct,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110186",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/186",
  abstract =     "An index of the release of open government data,
                 published in 2016 by the Open Knowledge Foundation,
                 shows that there is significant variability in the
                 country's supply of this public good. What explains
                 these cross-country differences? Adopting an
                 interdisciplinary approach based on data science and
                 economic theory, we developed the following research
                 workflow. First, we gather, clean, and merge different
                 datasets released by institutions such as the Open
                 Knowledge Foundation, World Bank, United Nations, World
                 Economic Forum, Transparency International, Economist
                 Intelligence Unit, and International Telecommunication
                 Union. Then, we conduct feature extraction and variable
                 selection founded on economic domain knowledge. Next,
                 we perform several linear regression models, testing
                 whether cross-country differences in the supply of open
                 government data can be explained by differences in the
                 country's economic, social, and institutional
                 structures. Our analysis provides evidence that the
                 country's civil liberties, government transparency,
                 quality of democracy, efficiency of government
                 intervention, economies of scale in the provision of
                 public goods, and the size of the economy are
                 statistically significant to explain the cross-country
                 differences in the supply of open government data. Our
                 analysis also suggests that political participation,
                 sociodemographic characteristics, and demographic and
                 global income distribution dummies do not help to
                 explain the country's supply of open government data.
                 In summary, we show that cross-country differences in
                 governance, social institutions, and the size of the
                 economy can explain the global distribution of open
                 government data.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Data Science and Knowledge Discovery.",
}

@Article{Coelho:2020:MMB,
  author =       "Vitor Naz{\'a}rio Coelho and Rodolfo Pereira
                 Ara{\'u}jo and Haroldo Gambini Santos and Wang Yong
                 Qiang and Igor Machado Coelho",
  title =        "A {MILP} Model for a {Byzantine} Fault Tolerant
                 Blockchain Consensus",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "185",
  day =          "29",
  month =        oct,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110185",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/185",
  abstract =     "Mixed-integer mathematical programming has been widely
                 used to model and solve challenging optimization
                 problems. One interesting feature of this technique is
                 the ability to prove the optimality of the achieved
                 solution, for many practical scenarios where a linear
                 programming model can be devised. This paper explores
                 its use to model very strong Byzantine adversaries, in
                 the context of distributed consensus systems. In
                 particular, we apply the proposed technique to find
                 challenging adversarial conditions on a
                 state-of-the-art blockchain consensus: the Neo dBFT.
                 Neo Blockchain has been using the dBFT algorithm since
                 its foundation, but, due to the complexity of the
                 algorithm, it is challenging to devise definitive
                 algebraic proofs that guarantee safety/liveness of the
                 system (and adjust for every change proposed by the
                 community). Core developers have to manually devise and
                 explore possible adversarial attacks scenarios as an
                 exhaustive task. The proposed multi-objective model is
                 intended to assist the search of possible faulty
                 scenario, which includes three objective functions that
                 can be combined as a maximization problem for testing
                 one-block finality or a minimization problem for
                 ensuring liveness. Automated graphics help developers
                 to visually observe attack conditions and to quickly
                 find a solution. This paper proposes an exact
                 adversarial model that explores current limits for
                 practical blockchain consensus applications such as
                 dBFT, with ideas that can also be extended to other
                 decentralized ledger technologies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Special Issue on Cyber Physical Systems:
                 Prospects, Challenges, and Role in Software Defined
                 Networking and Blockchain.",
}

@Article{Paligu:2020:BFI,
  author =       "Furkan Paligu and Cihan Varol",
  title =        "Browser Forensic Investigations of {WhatsApp} {Web}
                 Utilizing {IndexedDB} Persistent Storage",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "184",
  day =          "28",
  month =        oct,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110184",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/184",
  abstract =     "Digital Evidence is becoming an indispensable factor
                 in most legal cases. However, technological
                 advancements that lead to artifact complexity, are
                 forcing investigators to create sophisticated
                 connections between the findings and the suspects for
                 admissibility of evidence in court. This paper
                 scrutinizes whether IndexedDB, an emerging browser
                 technology, can be a source of digital evidence to
                 provide additional and correlating support for
                 traditional investigation methods. It particularly
                 focuses on the artifacts of the worldwide popular
                 application, WhatsApp. A single case pretest--posttest
                 quasi experiment is applied with WhatsApp Messenger and
                 Web Application to populate and investigate artifacts
                 in IndexedDB storage of Google Chrome. The findings are
                 characterized and presented with their potential to be
                 utilized in forensic investigation verifications. The
                 storage locations of the artifacts are laid out and
                 operations of extraction, conversion and presentation
                 are systematized. Additionally, a proof of concept tool
                 is developed for demonstration. The results show that
                 WhatsApp Web IndexedDB storage can be employed for time
                 frame analysis, demonstrating its value in evidence
                 verification.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Information and Future Internet
                 Security, Trust and Privacy.",
}

@Article{Rinaldi:2020:KDM,
  author =       "Antonio Maria Rinaldi and Cristiano Russo and Cristian
                 Tommasino",
  title =        "A Knowledge-Driven Multimedia Retrieval System Based
                 on Semantics and Deep Features",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "183",
  day =          "28",
  month =        oct,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110183",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/183",
  abstract =     "In recent years the information user needs have been
                 changed due to the heterogeneity of web contents which
                 increasingly involve in multimedia contents. Although
                 modern search engines provide visual queries, it is not
                 easy to find systems that allow searching from a
                 particular domain of interest and that perform such
                 search by combining text and visual queries. Different
                 approaches have been proposed during years and in the
                 semantic research field many authors proposed
                 techniques based on ontologies. On the other hand, in
                 the context of image retrieval systems techniques based
                 on deep learning have obtained excellent results. In
                 this paper we presented novel approaches for image
                 semantic retrieval and a possible combination for
                 multimedia document analysis. Several results have been
                 presented to show the performance of our approach
                 compared with literature baselines.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Data Science and Knowledge Discovery.",
}

@Article{Agafonova:2020:PTR,
  author =       "Yana Agafonova and Alexey Tikhonov and Ivan P.
                 Yamshchikov",
  title =        "Paranoid Transformer: Reading Narrative of Madness as
                 Computational Approach to Creativity",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "182",
  day =          "27",
  month =        oct,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110182",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/182",
  abstract =     "This paper revisits the receptive theory in the
                 context of computational creativity. It presents a case
                 study of a Paranoid Transformer---a fully autonomous
                 text generation engine with raw output that could be
                 read as the narrative of a mad digital persona without
                 any additional human post-filtering. We describe
                 technical details of the generative system, provide
                 examples of output, and discuss the impact of receptive
                 theory, chance discovery, and simulation of fringe
                 mental state on the understanding of computational
                 creativity.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Nature Language Engineering: Methods,
                 Tasks and Applications.",
}

@Article{Cavazza:2020:DIA,
  author =       "Francesco Cavazza and Francesco Galioto and Meri Raggi
                 and Davide Viaggi",
  title =        "Digital Irrigated Agriculture: Towards a Framework for
                 Comprehensive Analysis of Decision Processes under
                 Uncertainty",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "181",
  day =          "26",
  month =        oct,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110181",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/181",
  abstract =     "Several studies address the topic of Information and
                 Communication Technologies (ICT) adoption in irrigated
                 agriculture. Many of these studies testify on the
                 growing importance of ICT in influencing the evolution
                 of the sector, especially by bringing down information
                 barriers. While the potentialities of such technologies
                 are widely investigated and confirmed, there is still a
                 gap in understanding and modeling decisions on ICT
                 information implementation. This gap concerns, in
                 particular, accounting for all the aspects of
                 uncertainty which are mainly due to a lack of knowledge
                 on the reliability of ICT and on the errors of
                 ICT-information. Overall, such uncertainties might
                 affect Decision Makers' (DM's) behavior and hamper ICT
                 uptake. To support policy makers in the designing of
                 uncertainty-management policies for the achievement of
                 the benefits of a digital irrigated agriculture, we
                 further investigated the topic of uncertainty modelling
                 in ICT uptake decisions. To do so, we reviewed the
                 economic literature on ambiguity, in the context of the
                 wider literature on decision making under uncertainty
                 in order to explore its potential for better modeling
                 ICT uptake decisions. Findings from the discussed
                 literature confirm the capabilities of this approach to
                 yield a deeper understanding of decision processes when
                 the reliability of ICT is unknown and provides better
                 insights on how behavioral barriers to the achievement
                 of potential ICT-benefits can be overcome. Policy
                 implications to accompany the sector in the
                 digitalization process include mainly: (a) defining new
                 approaches for ICT-developers to tailor platforms to
                 answer heterogeneous DMs' needs; (b) establish
                 uncertainty-management policies complementary to DM
                 tools adoption.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Artificial Intelligence (AI) in
                 Agriculture.",
}

@Article{Mahfouz:2020:ECN,
  author =       "Ahmed Mahfouz and Abdullah Abuhussein and Deepak
                 Venugopal and Sajjan Shiva",
  title =        "Ensemble Classifiers for Network Intrusion Detection
                 Using a Novel Network Attack Dataset",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "180",
  day =          "26",
  month =        oct,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110180",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/180",
  abstract =     "Due to the extensive use of computer networks, new
                 risks have arisen, and improving the speed and accuracy
                 of security mechanisms has become a critical need.
                 Although new security tools have been developed, the
                 fast growth of malicious activities continues to be a
                 pressing issue that creates severe threats to network
                 security. Classical security tools such as firewalls
                 are used as a first-line defense against security
                 problems. However, firewalls do not entirely or
                 perfectly eliminate intrusions. Thus, network
                 administrators rely heavily on intrusion detection
                 systems (IDSs) to detect such network intrusion
                 activities. Machine learning (ML) is a practical
                 approach to intrusion detection that, based on data,
                 learns how to differentiate between abnormal and
                 regular traffic. This paper provides a comprehensive
                 analysis of some existing ML classifiers for
                 identifying intrusions in network traffic. It also
                 produces a new reliable dataset called GTCS (Game
                 Theory and Cyber Security) that matches real-world
                 criteria and can be used to assess the performance of
                 the ML classifiers in a detailed experimental
                 evaluation. Finally, the paper proposes an ensemble and
                 adaptive classifier model composed of multiple
                 classifiers with different learning paradigms to
                 address the issue of the accuracy and false alarm rate
                 in IDSs. Our classifiers show high precision and recall
                 rates and use a comprehensive set of features compared
                 to previous work.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Artificial Intelligence and Machine
                 Learning in Cybercrime Detection.",
}

@Article{Garlinska:2020:MFS,
  author =       "Magdalena Garlinska and Agnieszka Pregowska and Karol
                 Masztalerz and Magdalena Osial",
  title =        "From Mirrors to Free-Space Optical
                 Communication-Historical Aspects in Data Transmission",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "179",
  day =          "22",
  month =        oct,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110179",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/179",
  abstract =     "Fast communication is of high importance. Recently,
                 increased data demand and crowded radio frequency
                 spectrum have become crucial issues. Free-Space Optical
                 Communication (FSOC) has diametrically changed the way
                 people exchange information. As an alternative to wire
                 communication systems, it allows efficient voice,
                 video, and data transmission using a medium like air.
                 Due to its large bandwidth, FSOC can be used in various
                 applications and has therefore become an important part
                 of our everyday life. The main advantages of FSOC are a
                 high speed, cost savings, compact structures, low
                 power, energy efficiency, a maximal transfer capacity,
                 and applicability. The rapid development of the
                 high-speed connection technology allows one to reduce
                 the repair downtime and gives the ability to quickly
                 establish a backup network in an emergency.
                 Unfortunately, FSOC is susceptible to disruption due to
                 atmospheric conditions or direct sunlight. Here, we
                 briefly discuss Free-Space Optical Communication from
                 mirrors and optical telegraphs to modern wireless
                 systems and outline the future development directions
                 of optical communication.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Wireless Internet, Multimedia, and
                 Artificial Intelligence: New Applications and
                 Infrastructures.",
}

@Article{Cao:2020:LHG,
  author =       "Kerang Cao and Jingyu Gao and Kwang-nam Choi and Lini
o                 Duan",
  title =        "Learning a Hierarchical Global Attention for Image
                 Classification",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "11",
  pages =        "178",
  day =          "22",
  month =        oct,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12110178",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:25:59 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/11/178",
  abstract =     "To classify the image material on the internet, the
                 deep learning methodology, especially deep neural
                 network, is the most optimal and costliest method of
                 all computer vision methods. Convolutional neural
                 networks (CNNs) learn a comprehensive feature
                 representation by exploiting local information with a
                 fixed receptive field, demonstrating distinguished
                 capacities on image classification. Recent works
                 concentrate on efficient feature exploration, which
                 neglect the global information for holistic
                 consideration. There is large effort to reduce the
                 computational costs of deep neural networks. Here, we
                 provide a hierarchical global attention mechanism that
                 improve the network representation with restricted
                 increase of computation complexity. Different from
                 nonlocal-based methods, the hierarchical global
                 attention mechanism requires no matrix multiplication
                 and can be flexibly applied in various modern network
                 designs. Experimental results demonstrate that proposed
                 hierarchical global attention mechanism can
                 conspicuously improve the image classification
                 precision---a reduction of 7.94\% and 16.63\% percent
                 in Top 1 and Top 5 errors separately---with little
                 increase of computation complexity (6.23\%) in
                 comparison to competing approaches.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Big Data and Augmented Intelligence.",
}

@Article{Tariq:2020:VAU,
  author =       "Muhammad Atiq Ur Rehman Tariq and Cheuk Yin Wai and
                 Nitin Muttil",
  title =        "Vulnerability Assessment of Ubiquitous Cities Using
                 the Analytic Hierarchy Process",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "12",
  pages =        "235",
  day =          "21",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12120235",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/12/235",
  abstract =     "Urbanization is a challenge faced by most countries
                 worldwide and leads to several problems. Due to rapid
                 communication capabilities, conforming the megacities
                 into Ubiquitous cities (U-cities) seems to be a
                 potential solution to mitigate the problems caused by
                 urbanization. Extensive reliance and dependencies of
                 U-cities on information and communication technologies
                 (ICTs) bring forth a new set of risks and
                 vulnerabilities to these megacities. This research
                 investigates the vulnerabilities of ICTs against
                 man-made and natural hazards in a systematic way using
                 the Analytic Hierarchy Process. The study identifies
                 the vulnerabilities of different ICTs in U-cities and
                 helps in improving the system's resistivity against
                 various hazards. The task is performed by evaluating
                 the level of disruption on the different technologies
                 and areas under the identified man-made and natural
                 hazards. The research provides an insight into the
                 working mechanisms of involved ICTs. It also helps to
                 manage U-cities with more secure and sustainable
                 services. The research identified that the new
                 ICTs-based hazards have emerged and have become among
                 the most influential hazards. The research has
                 concluded that the vulnerabilities of U-cities are
                 significantly different from that of conventional
                 cities and need further studies to develop further
                 understandings. The research recommends similar
                 vulnerability studies for regional areas as well.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Sustainable Smart City.",
}

@Article{Chaves:2020:EEC,
  author =       "Ricardo Chaves and Carlos Senna and Miguel Lu{\'\i}s
                 and Susana Sargento and Andr{\'e} Moreira and Diogo
                 Recharte and Ricardo Matos",
  title =        "{EmuCD}: an Emulator for Content Dissemination
                 Protocols in Vehicular Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "12",
  pages =        "234",
  day =          "21",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12120234",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/12/234",
  abstract =     "The development of protocols for mobile networks,
                 especially for vehicular ad-hoc networks (VANETs),
                 presents great challenges in terms of testing in real
                 conditions. Using a production network for testing
                 communication protocols may not be feasible, and the
                 use of small networks does not meet the requirements
                 for mobility and scale found in real networks. The
                 alternative is to use simulators and emulators, but
                 vehicular network simulators do not meet all the
                 requirements for effective testing. Aspects closely
                 linked to the behaviour of the network nodes (mobility,
                 radio communication capabilities, etc.) are
                 particularly important in mobile networks, where a
                 delay tolerance capability is desired. This paper
                 proposes a distributed emulator, EmuCD, where each
                 network node is built in a container that consumes a
                 data trace that defines the node's mobility and
                 connectivity in a real network (but also allowing the
                 use of data from simulated networks). The emulated
                 nodes interact directly with the container's operating
                 system, updating the network conditions at each step of
                 the emulation. In this way, our emulator allows the
                 development and testing of protocols, without any
                 relation to the emulator, whose code is directly
                 portable to any hardware without requiring changes or
                 customizations. Using the facilities of our emulator,
                 we tested InterPlanetary File System (IPFS), Sprinkler
                 and BitTorrent content dissemination protocols with
                 real mobility and connectivity data from a real
                 vehicular network. The tests with a real VANET and with
                 the emulator have shown that, under similar conditions,
                 EmuCD performs closely to the real VANET, only lacking
                 in the finer details that are extremely hard to
                 emulate, such as varying loads in the hardware.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Delay-Tolerant Networking.",
}

@Article{Li:2020:JOR,
  author =       "Long Li and Gaochao Xu and Peng Liu and Yang Li and
                 Jiaqi Ge",
  title =        "Jointly Optimize the Residual Energy of Multiple
                 Mobile Devices in the {MEC-WPT} System",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "12",
  pages =        "233",
  day =          "20",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12120233",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/12/233",
  abstract =     "With the rapid popularity of mobile devices (MDs),
                 mobile edge computing (MEC) networks and wireless power
                 transmission (WPT) will receive more attention.
                 Naturally, by integrating these two technologies, the
                 inherent energy consumption during task execution can
                 be effectively reduced, and the collected energy can be
                 provided to charge the MD. In this article, our
                 research focuses on extending the battery time of MDs
                 by maximizing the harvested energy and minimizing the
                 consumed energy in the MEC--WPT system, which is
                 formulated as a residual energy maximization problem
                 and also a non-convex optimization problem. On the
                 basis of study on maximizing the residual energy under
                 multi-users and multi-time blocks, we propose an
                 effective jointly optimization method (i.e., jointly
                 optimize the energy harvesting time, task-offloading
                 time, task-offloading size and the MDs' CPU frequency),
                 which combines the convex optimization method and the
                 augmented Lagrangian to solve the residual energy
                 maximum problem. We leverage Time Division Multiple
                 Access (TMDA) mode to coordinate computation
                 offloading. Simulation results show that our scheme has
                 better performance than the benchmark schemes on
                 maximizing residual energy. In particular, our proposed
                 scheme is outstanding in the failure rate of multiple
                 MDs and can adapt to the task size to minimize the
                 failure rate.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Fog and Mobile Edge Computing.",
}

@Article{Torres-Madronero:2020:CPI,
  author =       "Esperanza Milena Torres-Madro{\~n}ero and Maria C.
                 Torres-Madro{\~n}ero and Luz Dary Ruiz Botero",
  title =        "Challenges and Possibilities of {ICT}-Mediated
                 Assessment in Virtual Teaching and Learning Processes",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "12",
  pages =        "232",
  day =          "18",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12120232",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/12/232",
  abstract =     "The transformations in educational environments due to
                 the immersion of information and communication
                 technologies (ICT) make it necessary to analyze the
                 limits and possibilities of the assessment of the
                 virtual training process. This paper presents an
                 analysis of the meanings of ICT-mediated assessment,
                 establishing what kinds of knowledge are suitable for
                 this type of evaluation, and the challenges and
                 possibilities of virtual tools. For this, we present a
                 systematic review of ICT-mediated evaluation and
                 assessment according to the educational paradigms and
                 their implementation. We highlight that contemporary
                 pedagogical models and their implementation in ICT
                 mediation tools show a trend towards quantitative and
                 summative valuation. The commonly used learning
                 management systems (LMS) include several types of
                 questions oriented to quantitative evaluation, with
                 multiple-choice being the most common. However, new
                 technological approaches like gamification, virtual
                 reality and mobile learning open new assessment
                 possibilities. The ICT educational platforms and new
                 technologies demand new skills for all educational
                 actors, such as digital literacy.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue E-Learning and Technology Enhanced
                 Learning.",
}

@Article{Miranda:2020:PSM,
  author =       "Juli{\'a}n Miranda and Ang{\'e}lica Fl{\'o}rez and
                 Gustavo Ospina and Ciro Gamboa and Carlos Fl{\'o}rez
                 and Miguel Altuve",
  title =        "Proposal for a System Model for Offline Seismic Event
                 Detection in {Colombia}",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "12",
  pages =        "231",
  day =          "18",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12120231",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/12/231",
  abstract =     "This paper presents an integrated model for seismic
                 events detection in Colombia using machine learning
                 techniques. Machine learning is used to identify P-wave
                 windows in historic records and hence detect seismic
                 events. The proposed model has five modules that group
                 the basic detection system procedures: the seeking,
                 gathering, and storage seismic data module, the reading
                 of seismic records module, the analysis of
                 seismological stations module, the sample selection
                 module, and the classification process module. An
                 explanation of each module is given in conjunction with
                 practical recommendations for its implementation. The
                 resulting model allows understanding the integration of
                 the phases required for the design and development of
                 an offline seismic event detection system.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Collaborative Networks, Decision
                 Systems, Web Applications and Services for Supporting
                 Engineering and Production Management.",
}

@Article{Zhang:2020:INP,
  author =       "Ping Zhang and Rongqin Wang and Nianfeng Shi",
  title =        "{IgA} Nephropathy Prediction in Children with Machine
                 Learning Algorithms",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "12",
  pages =        "230",
  day =          "17",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12120230",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/12/230",
  abstract =     "Immunoglobulin A nephropathy (IgAN) is the most common
                 primary glomerular disease all over the world and it is
                 a major cause of renal failure. IgAN prediction in
                 children with machine learning algorithms has been
                 rarely studied. We retrospectively analyzed the
                 electronic medical records from the Nanjing Eastern War
                 Zone Hospital, chose eXtreme Gradient Boosting
                 (XGBoost), random forest (RF), CatBoost, support vector
                 machines (SVM), k-nearest neighbor (KNN), and extreme
                 learning machine (ELM) models in order to predict the
                 probability that the patient would not reach or reach
                 end-stage renal disease (ESRD) within five years, used
                 the chi-square test to select the most relevant 16
                 features as the input of the model, and designed a
                 decision-making system (DMS) of IgAN prediction in
                 children that is based on XGBoost and Django framework.
                 The receiver operating characteristic (ROC) curve was
                 used in order to evaluate the performance of the models
                 and XGBoost had the best performance by comparison. The
                 AUC value, accuracy, precision, recall, and f1-score of
                 XGBoost were 85.11\%, 78.60\%, 75.96\%, 76.70\%, and
                 76.33\%, respectively. The XGBoost model is useful for
                 physicians and pediatric patients in providing
                 predictions regarding IgAN. As an advantage, a DMS can
                 be designed based on the XGBoost model to assist a
                 physician to effectively treat IgAN in children for
                 preventing deterioration.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Curative Power of Medical Data 2020.",
}

@Article{Marotta:2020:BAQ,
  author =       "Lorena Marotta and Andrea Pesce and Andrea Guazzini",
  title =        "Before and after the Quarantine: an Approximate Study
                 on the Psychological Impact of {COVID-19} on the
                 {Italian} Population during the Lockdown Period",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "12",
  pages =        "229",
  day =          "15",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12120229",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/12/229",
  abstract =     "COVID-19 (Corona-Virus Disease 2019) in Italy and the
                 measures that were adopted to contain its diffusion had
                 a strong impact on people's quality of life and mental
                 health. The objective of the study was to quantify the
                 psychological impact of the lockdown period on the
                 general Italian population during the two weeks when
                 the COVID-19 emergency in Italy was at its peak. The
                 study (1556 adults) was conducted from April 6th to
                 April 12th, 2020. A survey was developed through Google
                 Forms in order to assess different psychological
                 measures (Self Efficacy, Locus of Control, Social
                 Connectedness, Sense of Virtual Community, Flourishing,
                 Positive and Negative Affect, Life Satisfaction, and
                 Risk Propensity). The results were then compared to
                 reference data. Thelockdown period increased arousal
                 mainly for negative emotions, but also for positive
                 emotions, and quality of life seemed to be reduced.
                 From a psychosocial point of view, while social
                 connectedness has decreased during lockdown, probably
                 because of isolation and social distancing, the virtual
                 social community seemed to increase in the same period.
                 Interestingly, we revealed how self efficacy increased
                 during the lockdown period, and, at the same time, the
                 Locus of control appeared as externalized, and the risk
                 propensity as reduced. The results are discussed
                 considering previous literature, and a coherent
                 theoretical framework is proposed in order to refine
                 the forecasting model for the psychological impact of
                 the lockdown.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue 2020 Selected Papers from Future
                 Internet Editorial Board Members and Guest Editors.",
}

@Article{Ce:2020:AMI,
  author =       "Peng Ce and Bao Tie",
  title =        "An Analysis Method for Interpretability of {CNN} Text
                 Classification Model",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "12",
  pages =        "228",
  day =          "13",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12120228",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/12/228",
  abstract =     "With continuous development of artificial
                 intelligence, text classification has gradually changed
                 from a knowledge-based method to a method based on
                 statistics and machine learning. Among them, it is a
                 very important and efficient way to classify text based
                 on the convolutional neural network (CNN) model. Text
                 data are a kind of sequence data, while time
                 sequentiality of the general text data is relatively
                 weak, so text classification is usually less relevant
                 to the sequential structure of the full text.
                 Therefore, CNN-based text classification has gradually
                 become a research hotspot when dealing with issues of
                 text classification. For machine learning, especially
                 deep learning, model interpretability has increasingly
                 become the focus of academic research and industrial
                 applications, and also become a key issue for further
                 development and application of deep learning
                 technology. Therefore, we recommend using the
                 backtracking analysis method to conduct in-depth
                 research on deep learning models. This paper proposes
                 an analysis method for interpretability of a CNN text
                 classification model. The method proposed by us can
                 perform multi-angle analysis on the discriminant
                 results of multi-classified text and multi-label
                 classification tasks through backtracking analysis on
                 model prediction results. Finally, the analysis results
                 of the model can be displayed using visualization
                 technology from multiple dimensions based on
                 interpretability. The representative data set IMDB
                 (Internet Movie Database) in text classification is
                 verified by examples, and the results show that the
                 model can be effectively analyzed when using our
                 method.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Smart System Infrastructure and
                 Applications.",
}

@Article{Yovita:2020:PAC,
  author =       "Leanna Vidya Yovita and Nana Rachmana Syambas and Ian
                 Joseph Matheus Edward and Noriaki Kamiyama",
  title =        "Performance Analysis of Cache Based on Popularity and
                 Class in Named Data Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "12",
  pages =        "227",
  day =          "09",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12120227",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/12/227",
  abstract =     "The communication network is growing with some unique
                 characteristics, such as consumers repeatedly request
                 the same content to the server, similarity in local
                 demand trend, and dynamic changes to requests within a
                 specific period. Therefore, a different network
                 paradigm is needed to replace the IP network, namely
                 Named Data Network (NDN). The content store, which acts
                 as a crucial component in the NDN nodes is a limited
                 resource. In addition, a cache mechanism is needed to
                 optimize the router's content store by exploiting the
                 different content services characters in the network.
                 This paper proposes a new caching algorithm called
                 Cache Based on Popularity and Class (CAPIC) with
                 dynamic mechanism, and the detail explanation about the
                 static method also presented. The goal of Static-CAPIC
                 was to enhance the total cache hit ratio on the network
                 by pre-determining the cache proportion for each
                 content class. However, this technique is not
                 appropriate to control the cache hit ratio for priority
                 class. Therefore, the Dynamic-CAPIC is used to provide
                 flexibility to change the cache proportion based on the
                 frequency of requests in real-time. The formula
                 involves considering the consumers' request all the
                 time. It gives a higher cache hit ratio for the
                 priority content class. This method outperforms
                 Static-CAPIC, and the LCD+sharing scheme in the total
                 network cache hit ratio parameter and channels it to
                 the priority class.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Internet of Things.",
}

@Article{Khrais:2020:RAI,
  author =       "Laith T. Khrais",
  title =        "Role of Artificial Intelligence in Shaping Consumer
                 Demand in E-Commerce",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "12",
  pages =        "226",
  day =          "08",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12120226",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/12/226",
  abstract =     "The advent and incorporation of technology in
                 businesses have reformed operations across industries.
                 Notably, major technical shifts in e-commerce aim to
                 influence customer behavior in favor of some products
                 and brands. Artificial intelligence (AI) comes on board
                 as an essential innovative tool for personalization and
                 customizing products to meet specific demands. This
                 research finds that, despite the contribution of AI
                 systems in e-commerce, its ethical soundness is a
                 contentious issue, especially regarding the concept of
                 explainability. The study adopted the use of word cloud
                 analysis, voyance analysis, and concordance analysis to
                 gain a detailed understanding of the idea of
                 explainability as has been utilized by researchers in
                 the context of AI. Motivated by a corpus analysis, this
                 research lays the groundwork for a uniform front, thus
                 contributing to a scientific breakthrough that seeks to
                 formulate Explainable Artificial Intelligence (XAI)
                 models. XAI is a machine learning field that inspects
                 and tries to understand the models and steps involved
                 in how the black box decisions of AI systems are made;
                 it provides insights into the decision points,
                 variables, and data used to make a recommendation. This
                 study suggested that, to deploy explainable XAI
                 systems, ML models should be improved, making them
                 interpretable and comprehensible.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Data Science and Knowledge Discovery.",
}

@Article{Velusamy:2020:SSD,
  author =       "Gandhimathi Velusamy and Ricardo Lent",
  title =        "Smart Site Diversity for a High Throughput Satellite
                 System with Software-Defined Networking and a Virtual
                 Network Function",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "12",
  pages =        "225",
  day =          "07",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12120225",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/12/225",
  abstract =     "High Throughput Satellite (HTS) systems aim to push
                 data rates to the order of Terabit/s, making use of
                 Extremely High Frequencies (EHF) or free-space optical
                 (FSO) in the feeder links. However, one challenge that
                 needs to be addressed is that the use of such high
                 frequencies makes the feeder links vulnerable to
                 atmospheric conditions, which can effectively disable
                 channels at times or temporarily increases the bit
                 error rates. One way to cope with the problem is to
                 introduce site diversity and to forward the data
                 through the gateways not affected, or at least less
                 constrained, by adverse conditions. In this paper, a
                 virtual network function (VNF) introduced through
                 reinforcement learning defines a smart routing service
                 for an HTS system. Experiments were conducted on an
                 emulated ground-satellite system in CloudLab, testing a
                 VNF implementation of the approach with
                 software-defined networking virtual switches, which
                 indicate the expected performance of the proposed
                 method.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Cognitive Software Defined Networking
                 and Network Function Virtualization and Applications.",
}

@Article{Niyonambaza:2020:PMP,
  author =       "Irene Niyonambaza and Marco Zennaro and Alfred
                 Uwitonze",
  title =        "Predictive Maintenance ({PdM}) Structure Using
                 {Internet of Things} ({IoT}) for Mechanical Equipment
                 Used into Hospitals in Rwanda",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "12",
  pages =        "224",
  day =          "07",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12120224",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/12/224",
  abstract =     "The success of all industries relates to attaining the
                 satisfaction to clients with a high level of services
                 and productivity. The success main factor depends on
                 the extent of maintaining their equipment. To date, the
                 Rwandan hospitals that always have a long queue of
                 patients that are waiting for service perform a repair
                 after failure as common maintenance practice that may
                 involve unplanned resources, cost, time, and completely
                 or partially interrupt the remaining hospital
                 activities. Aiming to reduce unplanned equipment
                 downtime and increase their reliability, this paper
                 proposes the Predictive Maintenance (PdM) structure
                 while using Internet of Things (IoT) in order to
                 predict early failure before it happens for mechanical
                 equipment that is used in Rwandan hospitals. Because
                 prediction relies on data, the structure design
                 consists of a simplest developed real time data
                 collector prototype with the purpose of collecting real
                 time data for predictive model construction and
                 equipment health status classification. The real time
                 data in the form of time series have been collected
                 from selected equipment components in King Faisal
                 Hospital and then later used to build a proposed
                 predictive time series model to be employed in proposed
                 structure. The Long Short Term Memory (LSTM) Neural
                 Network model is used to learn data and perform with an
                 accuracy of 90\% and 96\% to different two selected
                 components.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Internet of Things (IoT) for Industry
                 4.0.",
}

@Article{Sarasa-Cabezuelo:2020:MCI,
  author =       "Antonio Sarasa-Cabezuelo",
  title =        "A Model for Creating Interactive {eBooks} for
                 {eLearning}",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "12",
  pages =        "223",
  day =          "07",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12120223",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/12/223",
  abstract =     "In recent decades, electronic books have
                 revolutionized the publishing world. In this sense, an
                 area of application is education, where electronic
                 books can be used as educational resources to implement
                 learning strategies about content and in eLearning
                 environments. For this, it is necessary to introduce
                 interactive elements in the electronic books that turn
                 the reader into an active actor in the reading process.
                 However, ebooks have a limitation regarding their
                 creation process. In this sense, the tools can be
                 user-oriented or programmer-oriented. The former are
                 intuitive to use and have user-friendly interfaces, but
                 they offer a reduced number of functionalities to add
                 to books. The second are aimed at programmers, allowing
                 for the implementation of any functionality, but
                 limiting the number of content creators who can use
                 them. The main motivation of this work is to propose an
                 intermediate solution that offers a wide number of
                 functionalities while not requiring deep programming
                 knowledge to use them. In this sense, the solution of
                 this article is novel since it proposes the use of
                 extensible markup language (XML) documents to specify
                 the structure of the electronic book in such a way that
                 its processing will lead to the electronic book.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue E-Learning and Technology Enhanced
                 Learning.",
}

@Article{Konig:2020:CBS,
  author =       "Lukas K{\"o}nig and Yuliia Korobeinikova and Simon
                 Tjoa and Peter Kieseberg",
  title =        "Comparing Blockchain Standards and Recommendations",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "12",
  pages =        "222",
  day =          "07",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12120222",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/12/222",
  abstract =     "Since the introduction of Bitcoin, the term
                 ``blockchain'' has attracted many start-ups and
                 companies over the years, especially in the financial
                 sector. However, technology is evolving faster than
                 standardization frameworks. This left the industry in
                 the position of having to use this emerging technology,
                 without being backed by any international standards
                 organization regarding for neither the technology
                 itself, nor for a blockchain specific information
                 security framework. In times of the General Data
                 Protection Regulation and growing international trade
                 conflicts, protecting information is more relevant than
                 ever. Standardization of blockchains is an appeal to
                 raise the development of information technologies to
                 the next level. Therefore, this paper shall provide an
                 overview of standardization organization's publications
                 about blockchains/distributed ledger technologies, a
                 set of comparison criteria for future work and a
                 comparison of the existing standards work itself. With
                 that information, aligning to existing standardization
                 efforts becomes easier, and might even present the
                 possibility to create frameworks where there are none
                 at the moment.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Information and Future Internet
                 Security, Trust and Privacy.",
}

@Article{Song:2020:BAB,
  author =       "Yang Song and Yawen Wang and Dahai Jin",
  title =        "A {Bayesian} Approach Based on {Bayes} Minimum Risk
                 Decision for Reliability Assessment of {Web} Service
                 Composition",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "12",
  pages =        "221",
  day =          "04",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12120221",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/12/221",
  abstract =     "Web service composition is the process of combining
                 and reusing existing web services to create new
                 business processes to satisfy specific user
                 requirements. Reliability plays an important role in
                 ensuring the quality of web service composition.
                 However, owing to the flexibility and complexity of
                 such architecture, sufficient estimation of reliability
                 is difficult. In this paper, the authors propose a
                 method to estimate the reliability of web service
                 compositions based on Bayes reliability assessment by
                 considering it to be a decision-making problem. This
                 improves the testing efficiency and accuracy of such
                 methods. To this end, the authors focus on fully
                 utilizing prior information of web services to increase
                 the accuracy of prior distributions, and construct a
                 Markov model in terms of the reliabilities of the web
                 composition and each web service to integrate the
                 limited test data. The authors further propose a method
                 of minimum risk (MMR) to calculate the initial values
                 of hyperparameters satisfying the constraint of minimal
                 risk of the wrong decision. Experiments demonstrate
                 that the proposed method is capable of efficiently
                 utilizing prior module-level failure information,
                 comparing with the Bayesian Monte Carlo method (BMCM)
                 and expert scoring method (ESM), when the number of
                 failures increased from 0 to 5, reducing the required
                 number of test cases from 19.8\% to 28.9\% and 6.1\% to
                 14.1\% separately, improving the reliability assessment
                 of web service compositions, and reducing the expenses
                 incurred by system-level reliability testing and
                 demonstration.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Big Data and Augmented Intelligence.",
}

@Article{Harborth:2020:EIE,
  author =       "David Harborth and Sebastian Pape",
  title =        "Empirically Investigating Extraneous Influences on the
                 {``APCO''} Model --- Childhood Brand Nostalgia and the
                 Positivity Bias",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "12",
  pages =        "220",
  day =          "02",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12120220",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/12/220",
  abstract =     "Pok{\'e}mon Go is one of the most successful mobile
                 games of all time. Millions played and still play this
                 mobile augmented reality (AR) application, although
                 severe privacy issues are pervasive in the app due to
                 its use of several sensors such as location data and
                 camera. In general, individuals regularly use online
                 services and mobile apps although they might know that
                 the use is associated with high privacy risks. This
                 seemingly contradictory behavior of users is analyzed
                 from a variety of different perspectives in the
                 information systems domain. One of these perspectives
                 evaluates privacy-related decision making processes
                 based on concepts from behavioral economics. We follow
                 this line of work by empirically testing one exemplary
                 extraneous factor within the ``enhanced APCO model''
                 (antecedents-privacy concerns-outcome). Specific
                 empirical tests on such biases are rare in the
                 literature which is why we propose and empirically
                 analyze the extraneous influence of a positivity bias.
                 In our case, we hypothesize that the bias is induced by
                 childhood brand nostalgia towards the Pok{\'e}mon
                 franchise. We analyze our proposition in the context of
                 an online survey with 418 active players of the game.
                 Our results indicate that childhood brand nostalgia
                 influences the privacy calculus by exerting a large
                 effect on the benefits within the trade-off and,
                 therefore, causing a higher use frequency. Our work
                 shows two important implications. First, the behavioral
                 economics perspective on privacy provides additional
                 insights relative to previous research. However, the
                 effects of several other biases and heuristics have to
                 be tested in future work. Second, relying on nostalgia
                 represents an important, but also double-edged,
                 instrument for practitioners to market new services and
                 applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yang:2020:MCB,
  author =       "Pin Yang and Huiyu Zhou and Yue Zhu and Liang Liu and
                 Lei Zhang",
  title =        "Malware Classification Based on Shallow Neural
                 Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "12",
  pages =        "219",
  day =          "02",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12120219",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/12/219",
  abstract =     "The emergence of a large number of new malicious code
                 poses a serious threat to network security, and most of
                 them are derivative versions of existing malicious
                 code. The classification of malicious code is helpful
                 to analyze the evolutionary trend of malicious code
                 families and trace the source of cybercrime. The
                 existing methods of malware classification emphasize
                 the depth of the neural network, which has the problems
                 of a long training time and large computational cost.
                 In this work, we propose the shallow neural
                 network-based malware classifier (SNNMAC), a malware
                 classification model based on shallow neural networks
                 and static analysis. Our approach bridges the gap
                 between precise but slow methods and fast but less
                 precise methods in existing works. For each sample, we
                 first generate n-grams from their opcode sequences of
                 the binary file with a decompiler. An improved n-gram
                 algorithm based on control transfer instructions is
                 designed to reduce the n-gram dataset. Then, the SNNMAC
                 exploits a shallow neural network, replacing the full
                 connection layer and softmax with the average pooling
                 layer and hierarchical softmax, to learn from the
                 dataset and perform classification. We perform
                 experiments on the Microsoft malware dataset. The
                 evaluation result shows that the SNNMAC outperforms
                 most of the related works with 99.21\% classification
                 precision and reduces the training time by more than
                 half when compared with the methods using DNN (Deep
                 Neural Networks).",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Cybersecurity.",
}

@Article{Onorati:2020:PLD,
  author =       "Dario Onorati and Pierfrancesco Tommasino and Leonardo
                 Ranaldi and Francesca Fallucchi and Fabio Massimo
                 Zanzotto",
  title =        "Pat-in-the-Loop: Declarative Knowledge for Controlling
                 Neural Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "12",
  pages =        "218",
  day =          "02",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12120218",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/12/218",
  abstract =     "The dazzling success of neural networks over natural
                 language processing systems is imposing an urgent need
                 to control their behavior with simpler, more direct
                 declarative rules. In this paper, we propose
                 Pat-in-the-Loop as a model to control a specific class
                 of syntax-oriented neural networks by adding
                 declarative rules. In Pat-in-the-Loop, distributed tree
                 encoders allow to exploit parse trees in neural
                 networks, heat parse trees visualize activation of
                 parse trees, and parse subtrees are used as declarative
                 rules in the neural network. Hence, Pat-in-the-Loop is
                 a model to include human control in specific natural
                 language processing (NLP)-neural network (NN) systems
                 that exploit syntactic information, which we will
                 generically call Pat. A pilot study on question
                 classification showed that declarative rules
                 representing human knowledge, injected by Pat, can be
                 effectively used in these neural networks to ensure
                 correctness, relevance, and cost-effective.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Nature Language Engineering: Methods,
                 Tasks and Applications.",
}

@Article{Martinez:2020:IBV,
  author =       "Juan Miguel Mart{\'\i}nez Mart{\'\i}nez and Antonio
                 Tudela Sancho",
  title =        "Interactions between Virtual Spaces and Schools: a
                 Collective Case Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "12",
  pages =        "217",
  day =          "02",
  month =        dec,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12120217",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/12/217",
  abstract =     "Information and Communication Technologies (ICT) play
                 an important role in the current educational panorama.
                 Their presence in educational centers has increased in
                 the last decade due to the constant development of
                 educational policies focused on their inclusion in the
                 classroom. However, the integration of ICT in
                 educational spaces and practices has still not reach
                 the levels desired by international organizations such
                 as the OECD and UNESCO. The aim of this study is to
                 understand the nature of the interaction between
                 virtual spaces and school spaces, and how this
                 interaction affects the development of students'
                 learning processes. To this end, we follow an
                 interpretive research methodology using a collective
                 case study with four students from Spain. The results
                 highlight the scarce integration of ICT into
                 educational centers and teaching practices. However,
                 virtual spaces play an important role in the
                 development of other learning processes, such as
                 informed learning, informal learning, and learning
                 outside of the school context. In this work, we also
                 provide a brief overview of changes in the current
                 educational situation due to the COVID-19 pandemic.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Education Responses to Technological
                 Challenges and Their Impact on Classrooms.",
}

@Article{Han:2020:ECF,
  author =       "Junyan Han and Jinglei Zhang and Xiaoyuan Wang and
                 Yaqi Liu and Quanzheng Wang and Fusheng Zhong",
  title =        "An Extended Car-Following Model Considering
                 Generalized Preceding Vehicles in {V2X} Environment",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "12",
  pages =        "216",
  day =          "28",
  month =        nov,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12120216",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/12/216",
  abstract =     "Vehicle-to-everything (V2X) technology will
                 significantly enhance the information perception
                 ability of drivers and assist them in optimizing
                 car-following behavior. Utilizing V2X technology,
                 drivers could obtain motion state information of the
                 front vehicle, non-neighboring front vehicle, and front
                 vehicles in the adjacent lanes (these vehicles are
                 collectively referred to as generalized preceding
                 vehicles in this research). However, understanding of
                 the impact exerted by the above information on
                 car-following behavior and traffic flow is limited. In
                 this paper, a car-following model considering the
                 average velocity of generalized preceding vehicles
                 (GPV) is proposed to explore the impact and then
                 calibrated with the next generation simulation (NGSIM)
                 data utilizing the genetic algorithm. The neutral
                 stability condition of the model is derived via linear
                 stability analysis. Numerical simulation on the
                 starting, braking and disturbance propagation process
                 is implemented to further study features of the
                 established model and traffic flow stability. Research
                 results suggest that the fitting accuracy of the GPV
                 model is 40.497\% higher than the full velocity
                 difference (FVD) model. Good agreement between the
                 theoretical analysis and the numerical simulation
                 reveals that motion state information of GPV can
                 stabilize traffic flow of following vehicles and thus
                 alleviate traffic congestion.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhang:2020:KMC,
  author =       "Wenbo Zhang and Xiao Li and Yating Yang and Rui Dong
                 and Gongxu Luo",
  title =        "Keeping Models Consistent between Pretraining and
                 Translation for Low-Resource Neural Machine
                 Translation",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "12",
  pages =        "215",
  day =          "27",
  month =        nov,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12120215",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/12/215",
  abstract =     "Recently, the pretraining of models has been
                 successfully applied to unsupervised and
                 semi-supervised neural machine translation. A
                 cross-lingual language model uses a pretrained masked
                 language model to initialize the encoder and decoder of
                 the translation model, which greatly improves the
                 translation quality. However, because of a mismatch in
                 the number of layers, the pretrained model can only
                 initialize part of the decoder's parameters. In this
                 paper, we use a layer-wise coordination transformer and
                 a consistent pretraining translation transformer
                 instead of a vanilla transformer as the translation
                 model. The former has only an encoder, and the latter
                 has an encoder and a decoder, but the encoder and
                 decoder have exactly the same parameters. Both models
                 can guarantee that all parameters in the translation
                 model can be initialized by the pretrained model.
                 Experiments on the Chinese--English and English--German
                 datasets show that compared with the vanilla
                 transformer baseline, our models achieve better
                 performance with fewer parameters when the parallel
                 corpus is small.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Semantic Aspects in Natural Language
                 Processing.",
}

@Article{Chua:2020:PAD,
  author =       "Sook-Ling Chua and Lee Kien Foo and Hans W. Guesgen",
  title =        "Predicting Activities of Daily Living with
                 Spatio-Temporal Information",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "12",
  pages =        "214",
  day =          "27",
  month =        nov,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12120214",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/12/214",
  abstract =     "The smart home has begun playing an important role in
                 supporting independent living by monitoring the
                 activities of daily living, typically for the elderly
                 who live alone. Activity recognition in smart homes has
                 been studied by many researchers with much effort spent
                 on modeling user activities to predict behaviors. Most
                 people, when performing their daily activities,
                 interact with multiple objects both in space and
                 through time. The interactions between user and objects
                 in the home can provide rich contextual information in
                 interpreting human activity. This paper shows the
                 importance of spatial and temporal information for
                 reasoning in smart homes and demonstrates how such
                 information is represented for activity recognition.
                 Evaluation was conducted on three publicly available
                 smart-home datasets. Our method achieved an average
                 recognition accuracy of more than 81\% when predicting
                 user activities given the spatial and temporal
                 information.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Data Science and Knowledge Discovery.",
}

@Article{Minati:2020:CCS,
  author =       "Gianfranco Minati",
  title =        "Complex Cognitive Systems and Their Unconscious.
                 Related Inspired Conjectures for Artificial
                 Intelligence",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "12",
  pages =        "213",
  day =          "27",
  month =        nov,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12120213",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/12/213",
  abstract =     "The aim of the article is to propose a conceptual
                 framework, constructs, and conjectures to act as a
                 guide for future, related research finalized to design
                 and implement versions of Artificial Intelligence
                 encompassing an artificially simulated unconscious
                 suitable for human-like artificial cognitive
                 processing. This article considers the concept of the
                 unconscious in psychoanalysis. The interdisciplinary
                 understanding of this concept is considered to be the
                 unavoidable property of sufficiently complex, cognitive
                 processing. We elaborate on the possibility of an
                 artificial unconscious, able to both self-acquired
                 properties through usage, and self-profile through a
                 supposed implicit, parasitic usage of explicit
                 cognitive processing. Memory activities are considered
                 to be integrated into cognitive processing, with memory
                 no longer only being storage and reminding no longer
                 only being finding. We elaborate on the artificial
                 unconscious as an implicit, usage-dependent,
                 self-profiling, and emergent process. Conceptual
                 characteristics of the research project are the
                 implementation of weighted networked, fuzzified
                 memorizations; self-generated networks of links of
                 inter-relationships as nodes, self-variation of the
                 intensity of the links according to the use, and
                 activation of internal self-processes such as the
                 introduction of fictitious links intended as variations
                 and combinations of the current ones. Application
                 examples suitable for experimental implementation are
                 also discussed with reference to chatbot technology
                 that has been extended with features of an artificial
                 unconscious. Thus, we introduce the concept of the
                 AU-chatbot. The main purpose is to allow the artificial
                 cognitive processing to acquire suitable human-like
                 attitudes in representing, interfacing, and learning,
                 potentially important in supporting and complementing
                 human-centered activities. Examples of expected
                 features are the ability to combine current and
                 unconscious links to perform cognitive processing such
                 as representing, deciding, memorizing, and solving
                 equivalencies, and also learning meta-profiles, such as
                 in supporting doctor--patient interactions and
                 educational activities. We also discuss possible
                 technologies suitable for implementing experiments for
                 the artificial unconscious.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Smart System Infrastructure and
                 Applications.",
}

@Article{Artiemjew:2020:ARB,
  author =       "Piotr Artiemjew and Lada Rudikova and Oleg Myslivets",
  title =        "About Rule-Based Systems: Single Database Queries for
                 Decision Making",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "12",
  pages =        "212",
  day =          "27",
  month =        nov,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12120212",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/12/212",
  abstract =     "One of the developmental directions of Future Internet
                 technologies is the implementation of artificial
                 intelligence systems for manipulating data and the
                 surrounding world in a more complex way. Rule-based
                 systems, very accessible for people's decision-making,
                 play an important role in the family of computational
                 intelligence methods. The use of decision-making rules
                 along with decision trees are one of the simplest forms
                 of presenting complex decision-making processes.
                 Decision support systems, according to the
                 cross-industry standard process for data mining
                 (CRISP-DM) framework, require final embedding of the
                 learned model in a given computer infrastructure,
                 integrated circuits, etc. In this work, we deal with
                 the topic concerning placing the learned rule-based
                 model of decision support in the database
                 environment-exactly in the SQL database tables. Our
                 main goal is to place the previously trained model in
                 the database and apply it by means of single queries.
                 In our work we assume that the decision-making rules
                 applied are mutually consistent and additionally the
                 Minimal Description Length (MDL) rule is introduced. We
                 propose a universal solution for any IF THEN rule
                 induction algorithm.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Data Science and Knowledge Discovery.",
}

@Article{Nyblom:2020:RPS,
  author =       "Philip Nyblom and Gaute Wangen and Vasileios
                 Gkioulos",
  title =        "Risk Perceptions on Social Media Use in {Norway}",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "12",
  pages =        "211",
  day =          "26",
  month =        nov,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12120211",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/12/211",
  abstract =     "Social media are getting more and more ingrained into
                 everybody's lives. With people's more substantial
                 presence on social media, threat actors exploit the
                 platforms and the information that people share there
                 to deploy and execute various types of attacks. This
                 paper focuses on the Norwegian population, exploring
                 how people perceive risks arising from the use of
                 social media, focusing on the analysis of specific
                 indicators such as age, sexes and differences among the
                 users of distinct social media platforms. For data
                 collection, a questionnaire was structured and deployed
                 towards the users of multiple social media platforms
                 (total n = 329). The analysis compares risk perceptions
                 of using the social media platforms Facebook (n = 288),
                 Twitter (n = 134), Reddit (n = 189) and Snapchat (n =
                 267). Furthermore, the paper analyses the differences
                 between the sexes and between the digital natives and
                 non-natives. Our sample also includes sufferers of ID
                 theft (n = 50). We analyse how account compromise
                 occurs and how suffering ID theft changes behaviour and
                 perception. The results show significant discrepancies
                 in the risk perception among the social media platform
                 users across the examined indicators, but also explicit
                 variations on how this affects the associated usage
                 patterns. Based on the results, we propose a generic
                 risk ranking of social media platforms, activities,
                 sharing and a threat model for SoMe users. The results
                 show the lack of a unified perception of risk on social
                 media, indicating the need for targeted security
                 awareness enhancement mechanisms focusing on this
                 topic.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Security and Privacy in Social Networks
                 and Solutions.",
}

@Article{Mazumdar:2020:CST,
  author =       "Suvodeep Mazumdar and Dhavalkumar Thakker",
  title =        "Citizen Science on {Twitter}: Using Data Analytics to
                 Understand Conversations and Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "12",
  pages =        "210",
  day =          "26",
  month =        nov,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12120210",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/12/210",
  abstract =     "This paper presents a long-term study on how the
                 public engage with discussions around citizen science
                 and crowdsourcing topics. With progress in sensor
                 technologies and IoT, our cities and neighbourhoods are
                 increasingly sensed, measured and observed. While such
                 data are often used to inform citizen science projects,
                 it is still difficult to understand how citizens and
                 communities discuss citizen science activities and
                 engage with citizen science projects. Understanding
                 these engagements in greater depth will provide citizen
                 scientists, project owners, practitioners and the
                 generic public with insights around how social media
                 can be used to share citizen science related topics,
                 particularly to help increase visibility, influence
                 change and in general and raise awareness on topics. To
                 the knowledge of the authors, this is the first
                 large-scale study on understanding how such information
                 is discussed on Twitter, particularly outside the scope
                 of individual projects. The paper reports on the wide
                 variety of topics (e.g., politics, news, ecological
                 observations) being discussed on social media and a
                 wide variety of network types and the varied roles
                 played by users in sharing information in Twitter.
                 Based on these findings, the paper highlights
                 recommendations for stakeholders for engaging with
                 citizen science topics.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue AI and IoT technologies in Smart
                 Cities.",
}

@Article{Zhao:2020:UAI,
  author =       "Jie Zhao and Can Yan",
  title =        "User Acceptance of Information Feed Advertising: a
                 Hybrid Method Based on {SEM} and {QCA}",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "12",
  pages =        "209",
  day =          "26",
  month =        nov,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12120209",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/spss.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/12/209",
  abstract =     "It is of great significance for enterprises'
                 development to effectively use mobile Internet to carry
                 out information feed advertising. This paper aims to
                 study the influence factors and effect of the users'
                 acceptance intention of information feed advertising
                 through empirical analysis to provide references for
                 further optimizing information feed advertising
                 strategy. Traditional quantitative analysis methods,
                 such as the Structural Equation Model (SEM), can only
                 measure a single factor's influence from an individual
                 perspective. Therefore, we introduce the Qualitative
                 Comparative Analysis (QCA) and present a two-stage
                 hybrid method based on SEM and QCA. In the first stage,
                 we analyze the influence of a single variable on the
                 acceptance intention of information feed advertising by
                 SEM. Then, in the second stage, we analyze the impact
                 of different variable combinations by QCA. Based on the
                 actual questionnaire data, we define six independent
                 variables and use AMOS, SPSS, and fsQCA to carry out
                 SEM analysis and the fuzzy-set-based QCA analysis,
                 respectively. The SEM analysis results show that the
                 four factors (including consistency, informativeness,
                 sociability, and advertising reward) have a significant
                 positive impact on user acceptance of information feed
                 advertising. On the contrary, perceived advertising
                 clustering has a significant negative impact. In
                 addition, accuracy has no considerable effect. The QCA
                 analysis reveals that seven constructs of six variables
                 can all significantly enhance information feed ads'
                 acceptance intention.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Network Economics and Utility
                 Maximization.",
}

@Article{Bigini:2020:RBI,
  author =       "Gioele Bigini and Valerio Freschi and Emanuele
                 Lattanzi",
  title =        "A Review on Blockchain for the {Internet of Medical
                 Things}: Definitions, Challenges, Applications, and
                 Vision",
  journal =      j-FUTURE-INTERNET,
  volume =       "12",
  number =       "12",
  pages =        "208",
  day =          "25",
  month =        nov,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi12120208",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/12/12/208",
  abstract =     "Nowadays, there are a lot of new mobile devices that
                 have the potential to assist healthcare professionals
                 when working and help to increase the well-being of the
                 people. These devices comprise the Internet of Medical
                 Things, but it is generally difficult for healthcare
                 institutions to meet compliance of their systems with
                 new medical solutions efficiently. A technology that
                 promises the sharing of data in a trust-less scenario
                 is the Distributed Ledger Technology through its
                 properties of decentralization, immutability, and
                 transparency. The Blockchain and the Internet of
                 Medical Things can be considered as at an early stage,
                 and the implementations successfully applying the
                 technology are not so many. Some aspects covered by
                 these implementations are data sharing,
                 interoperability of systems, security of devices, the
                 opportunity of data monetization and data ownership
                 that will be the focus of this review. This work aims
                 at giving an overview of the current state-of-the-art
                 of the Blockchain-based systems for the Internet of
                 Medical Things, specifically addressing the challenges
                 of reaching user-centricity for these combined systems,
                 and thus highlighting the potential future directions
                 to follow for full ownership of data by users.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue The Future Internet of Medical Things.",
}

@Article{Bakaev:2021:WMU,
  author =       "Maxim Bakaev and Olga Razumnikova",
  title =        "What Makes a {UI} Simple? {Difficulty} and Complexity
                 in Tasks Engaging Visual--Spatial Working Memory",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "1",
  pages =        "21",
  day =          "19",
  month =        jan,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13010021",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/1/21",
  abstract =     "Tasks that imply engagement of visual-spatial working
                 memory (VSWM) are common in interaction with
                 two-dimensional graphical user interfaces. In our
                 paper, we consider two groups of factors as predictors
                 of user performance in such tasks: (1) the metrics
                 based on compression algorithms (RLE and Deflate) plus
                 the Hick's law, which are known to be characteristic of
                 visual complexity, and (2) metrics based on Gestalt
                 groping principle of proximity, operationalized as von
                 Neumann and Moore range 1 neighborhoods from the
                 cellular automata theory. We involved 88 subjects who
                 performed about 5000 VSWM-engaging tasks and 78
                 participants who assessed the complexity of the tasks'
                 configurations. We found that the Gestalt-based
                 predictors had a notable advantage over the visual
                 complexity-based ones, as the memorized chunks best
                 corresponded to von Neumann neighborhood groping. The
                 latter was further used in the formulation of index of
                 difficulty and throughput for VSWM-engaging tasks,
                 which we proposed by analogy with the infamous Fitts'
                 law. In our experimental study, throughput amounted to
                 3.75 bit/s, and we believe that it can be utilized for
                 comparing and assessing UI designs.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue VR, AR, and 3-D User Interfaces for
                 Measurement and Control.",
}

@Article{Alghamdi:2021:PIS,
  author =       "Abdulelah A. Alghamdi and Margaret Plunkett",
  title =        "The Perceived Impact of Social Networking Sites and
                 Apps on the Social Capital of {Saudi} Postgraduate
                 Students: a Case Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "1",
  pages =        "20",
  day =          "16",
  month =        jan,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13010020",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/1/20",
  abstract =     "With the increased use of Social Networking Sites and
                 Apps (SNSAs) in Saudi Arabia, it is important to
                 consider the impact of this on the social lives of
                 tertiary students, who are heavy users of such
                 technology. A mixed methods study exploring the effect
                 of SNSAs use on the social capital of Saudi
                 postgraduate students was conducted using a
                 multidimensional construct of social capital, which
                 included the components of life satisfaction, social
                 trust, civic participation, and political engagement.
                 Data were collected through surveys and interviews
                 involving 313 male and 293 female postgraduate students
                 from Umm Al-Qura University (UQU) in Makkah. Findings
                 show that male and female participants perceived SNSAs
                 use impacting all components of social capital at a
                 moderate and mainly positive level. Correlational
                 analysis demonstrated medium to large positive
                 correlations among components of social capital. Gender
                 differences were not evident in the life satisfaction
                 and social trust components; however, females reported
                 more involvement with SNSAs for the purposes of
                 political engagement while males reported more use for
                 civic participation, which is an interesting finding,
                 in light of the norms and traditional culture of Saudi
                 society.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Techno-Social Smart Systems.",
}

@Article{Karajeh:2021:CDI,
  author =       "Ola Karajeh and Dirar Darweesh and Omar Darwish and
                 Noor Abu-El-Rub and Belal Alsinglawi and Nasser
                 Alsaedi",
  title =        "A Classifier to Detect Informational vs.
                 Non-Informational Heart Attack Tweets",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "1",
  pages =        "19",
  day =          "16",
  month =        jan,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13010019",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/1/19",
  abstract =     "Social media sites are considered one of the most
                 important sources of data in many fields, such as
                 health, education, and politics. While surveys provide
                 explicit answers to specific questions, posts in social
                 media have the same answers implicitly occurring in the
                 text. This research aims to develop a method for
                 extracting implicit answers from large tweet
                 collections, and to demonstrate this method for an
                 important concern: the problem of heart attacks. The
                 approach is to collect tweets containing ``heart
                 attack'' and then select from those the ones with
                 useful information. Informational tweets are those
                 which express real heart attack issues, e.g.,
                 ``Yesterday morning, my grandfather had a heart attack
                 while he was walking around the garden.'' On the other
                 hand, there are non-informational tweets such as
                 ``Dropped my iPhone for the first time and almost had a
                 heart attack.'' The starting point was to manually
                 classify around 7000 tweets as either informational
                 (11\%) or non-informational (89\%), thus yielding a
                 labeled dataset to use in devising a machine learning
                 classifier that can be applied to our large collection
                 of over 20 million tweets. Tweets were cleaned and
                 converted to a vector representation, suitable to be
                 fed into different machine-learning algorithms: Deep
                 neural networks, support vector machine (SVM), J48
                 decision tree and na{\"\i}ve Bayes. Our experimentation
                 aimed to find the best algorithm to use to build a
                 high-quality classifier. This involved splitting the
                 labeled dataset, with 2/3 used to train the classifier
                 and 1/3 used for evaluation besides cross-validation
                 methods. The deep neural network (DNN) classifier
                 obtained the highest accuracy (95.2\%). In addition, it
                 obtained the highest F1-scores with (73.6\%) and
                 (97.4\%) for informational and non-informational
                 classes, respectively.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Wireless Internet, Multimedia, and
                 Artificial Intelligence: New Applications and
                 Infrastructures.",
}

@Article{Peker:2021:ECE,
  author =       "Serhat Peker and Gonca Gokce Menekse Dalveren and
                 Yavuz Inal",
  title =        "The Effects of the Content Elements of Online Banner
                 Ads on Visual Attention: Evidence from An-Eye-Tracking
                 Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "1",
  pages =        "18",
  day =          "15",
  month =        jan,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13010018",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/1/18",
  abstract =     "The aim of this paper is to examine the influence of
                 the content elements of online banner ads on customers'
                 visual attention, and to evaluate the impacts of
                 gender, discount rate and brand familiarity on this
                 issue. An eye-tracking study with 34 participants (18
                 male and 16 female) was conducted, in which the
                 participants were presented with eight types of online
                 banner ads comprising three content elements---namely
                 brand, discount rate and image---while their eye
                 movements were recorded. The results showed that the
                 image was the most attractive area among the three main
                 content elements. Furthermore, the middle areas of the
                 banners were noticed first, and areas located on the
                 left side were mostly noticed earlier than those on the
                 right side. The results also indicated that the
                 discount areas of banners with higher discount rates
                 were more attractive and eye-catching compared to those
                 of banners with lower discount rates. In addition to
                 these, the participants who were familiar with the
                 brand mostly concentrated on the discount area, while
                 those who were unfamiliar with the brand mostly paid
                 attention to the image area. The findings from this
                 study will assist marketers in creating more effective
                 and efficient online banner ads that appeal to
                 customers, ultimately fostering positive attitudes
                 towards the advertisement.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Human-Computer Interaction Theory and
                 Applications.",
}

@Article{Sun:2021:MNP,
  author =       "Jiachen Sun and Peter Gloor",
  title =        "E-Mail Network Patterns and Body Language Predict
                 Risk-Taking Attitude",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "1",
  pages =        "17",
  day =          "14",
  month =        jan,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13010017",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/1/17",
  abstract =     "As the Enron scandal and Bernie Madoff's pyramid
                 scheme have shown, individuals' attitude towards
                 ethical risks can have a huge impact on society at
                 large. In this paper, we compare risk-taking attitudes
                 assessed with the Domain-Specific Risk-Taking (DOSPERT)
                 survey with individual e-mail networking patterns and
                 body language measured with smartwatches. We find that
                 e-mail communication signals such as network structure
                 and dynamics, and content features as well as
                 real-world behavioral signals measured through a
                 smartwatch such as heart rate, acceleration, and mood
                 state demonstrate a strong correlation with the
                 individuals' risk-preference in the different domains
                 of the DOSPERT survey. For instance, we found that
                 people with higher degree centrality in the e-mail
                 network show higher likelihood to take social risks,
                 while using language expressing a ``you live only
                 once'' attitude indicates lower willingness to take
                 risks in some domains. Our results show that analyzing
                 the human interaction in organizational networks
                 provides valuable information for decision makers and
                 managers to support an increase in ethical behavior of
                 the organization's members.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Information Processing and Management
                 for Large and Complex Networks.",
}

@Article{Li:2021:PSB,
  author =       "Wei Li and Peng Sun and Rui Han",
  title =        "Path Segmentation-Based Hybrid Caching in
                 Information-Centric Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "1",
  pages =        "16",
  day =          "12",
  month =        jan,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13010016",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/1/16",
  abstract =     "Information-centric networks (ICNs) have received wide
                 interest from researchers, and in-network caching is an
                 important characteristic of ICN. The management and
                 placement of contents are essential due to cache nodes'
                 limited cache space and the huge Internet traffic. This
                 paper focuses on coordinating two cache metrics, namely
                 user access latency and network resource utilization,
                 and proposes a hybrid caching scheme called the path
                 segmentation-based hybrid caching scheme (PSBC). We
                 temporarily divide each data transmit path into a
                 user-edge area and non-edge area. The user-edge area
                 adopts a heuristic caching scheme to reduce user access
                 latency. In contrast, the non-edge area implements
                 caching network content migration and optimization to
                 improve network resource utilization. The simulation
                 results show that the proposed method positively
                 affects both the cache hit ratio and access latency.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Emerging Architectures and Technologies
                 for Evolving Mobile Internet and 6G.",
}

@Article{Ortiz-Marcos:2021:CAI,
  author =       "Jos{\'e} Manuel Ortiz-Marcos and Mar{\'\i}a
                 Tom{\'e}-Fern{\'a}ndez and Christian
                 Fern{\'a}ndez-Leyva",
  title =        "Cyberbullying Analysis in Intercultural Educational
                 Environments Using Binary Logistic Regressions",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "1",
  pages =        "15",
  day =          "09",
  month =        jan,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13010015",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/spss.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/1/15",
  abstract =     "The goal of this study is to analyze how religion,
                 ethnic group, and race influence the likelihood of
                 becoming either a cybervictim or cyberbully in
                 intercultural educational environments. In the
                 research, 755 students in secondary education were
                 analyzed in the south of Spain through the
                 Cyberbullying Scale for students with Cultural and
                 Religious Diversity (CSCRD). The analyses were carried
                 out using the Statistical Package SPSS and the STATA
                 software. The results obtained from the Kruskal--Wallis
                 H test showed significant differences according to
                 these aspects, for both the cybervictim and cyberbully
                 parameters. The results stemming from binary logistic
                 regressions confirmed such differences and regarded
                 those students who belong to the Muslim religion, the
                 gypsy ethnic group and the Asian race as being more
                 likely to become cybervictims. Furthermore, these
                 analyses showed that Gypsy and Asian students were also
                 more likely to be cyberbullies than other groups. The
                 main conclusions state that minority groups are more
                 likely to suffer cyberbullying in intercultural
                 educational environments, and that students from these
                 groups are also more likely to become cyberbullies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Education Responses to Technological
                 Challenges and Their Impact on Classrooms.",
}

@Article{Zhang:2021:DRP,
  author =       "Xiaolin Zhang and Chao Che",
  title =        "Drug Repurposing for {Parkinson}'s Disease by
                 Integrating Knowledge Graph Completion Model and
                 Knowledge Fusion of Medical Literature",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "1",
  pages =        "14",
  day =          "08",
  month =        jan,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13010014",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/1/14",
  abstract =     "The prevalence of Parkinson's disease increases a
                 tremendous medical and economic burden to society.
                 Therefore, the effective drugs are urgently required.
                 However, the traditional development of effective drugs
                 is costly and risky. Drug repurposing, which identifies
                 new applications for existing drugs, is a feasible
                 strategy for discovering new drugs for Parkinson's
                 disease. Drug repurposing is based on sufficient
                 medical knowledge. The local medical knowledge base
                 with manually labeled data contains a large number of
                 accurate, but not novel, medical knowledge, while the
                 medical literature containing the latest knowledge is
                 difficult to utilize, because of unstructured data.
                 This paper proposes a framework, named D rug R
                 epurposing for Parkinson's disease by integrating
                 Knowledge Graph Completion method and Knowledge Fusion
                 of medical literature data (DRKF) in order to make full
                 use of a local medical knowledge base containing
                 accurate knowledge and medical literature with novel
                 knowledge. DRKF first extracts the relations that are
                 related to Parkinson's disease from medical literature
                 and builds a medical literature knowledge graph. After
                 that, the literature knowledge graph is fused with a
                 local medical knowledge base that integrates several
                 specific medical knowledge sources in order to
                 construct a fused medical knowledge graph.
                 Subsequently, knowledge graph completion methods are
                 leveraged to predict the drug candidates for
                 Parkinson's disease by using the fused knowledge graph.
                 Finally, we employ classic machine learning methods to
                 repurpose the drug for Parkinson's disease and compare
                 the results with the method only using the
                 literature-based knowledge graph in order to confirm
                 the effectiveness of knowledge fusion. The experiment
                 results demonstrate that our framework can achieve
                 competitive performance, which confirms the
                 effectiveness of our proposed DRKF for drug repurposing
                 against Parkinson's disease. It could be a supplement
                 to traditional drug discovery methods.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Curative Power of Medical Data 2020.",
}

@Article{Che:2021:KGB,
  author =       "Mingxuan Che and Kui Yao and Chao Che and Zhangwei Cao
                 and Fanchen Kong",
  title =        "Knowledge-Graph-Based Drug Repositioning against
                 {COVID-19} by Graph Convolutional Network with
                 Attention Mechanism",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "1",
  pages =        "13",
  day =          "07",
  month =        jan,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13010013",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/1/13",
  abstract =     "The current global crisis caused by COVID-19 almost
                 halted normal life in most parts of the world. Due to
                 the long development cycle for new drugs, drug
                 repositioning becomes an effective method of screening
                 drugs for COVID-19. To find suitable drugs for
                 COVID-19, we add COVID-19-related information into our
                 medical knowledge graph and utilize a
                 knowledge-graph-based drug repositioning method to
                 screen potential therapeutic drugs for COVID-19.
                 Specific steps are as follows. Firstly, the information
                 about COVID-19 is collected from the latest published
                 literature, and gene targets of COVID-19 are added to
                 the knowledge graph. Then, the information of COVID-19
                 of the knowledge graph is extracted and a drug--disease
                 interaction prediction model based on Graph
                 Convolutional Network with Attention (Att-GCN) is
                 established. Att-GCN is used to extract features from
                 the knowledge graph and the prediction matrix
                 reconstructed through matrix operation. We evaluate the
                 model by predicting drugs for both ordinary diseases
                 and COVID-19. The model can achieve area under curve
                 (AUC) of 0.954 and area under the precise recall area
                 curve (AUPR) of 0.851 for ordinary diseases. On the
                 drug repositioning experiment for COVID-19, five drugs
                 predicted by the models have proved effective in
                 clinical treatment. The experimental results confirm
                 that the model can predict drug--disease interaction
                 effectively for both normal diseases and COVID-19.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Curative Power of Medical Data 2020.",
}

@Article{Wang:2021:DIV,
  author =       "Juan Wang and Yang Yu and Yi Li and Chengyang Fan and
                 Shirong Hao",
  title =        "Design and Implementation of Virtual Security Function
                 Based on Multiple Enclaves",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "1",
  pages =        "12",
  day =          "06",
  month =        jan,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13010012",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/1/12",
  abstract =     "Network function virtualization (NFV) provides
                 flexible and scalable network function for the emerging
                 platform, such as the cloud computing, edge computing,
                 and IoT platforms, while it faces more security
                 challenges, such as tampering with network policies and
                 leaking sensitive processing states, due to running in
                 a shared open environment and lacking the protection of
                 proprietary hardware. Currently, Intel {\reg} Software
                 Guard Extensions (SGX) provides a promising way to
                 build a secure and trusted VNF (virtual network
                 function) by isolating VNF or sensitive data into an
                 enclave. However, directly placing multiple VNFs in a
                 single enclave will lose the scalability advantage of
                 NFV. This paper combines SGX and click technology to
                 design the virtual security function architecture based
                 on multiple enclaves. In our design, the sensitive
                 modules of a VNF are put into different enclaves and
                 communicate by local attestation. The system can freely
                 combine these modules according to user requirements,
                 and increase the scalability of the system while
                 protecting its running state security. In addition, we
                 design a new hot-swapping scheme to enable the system
                 to dynamically modify the configuration function at
                 runtime, so that the original VNFs do not need to stop
                 when the function of VNFs is modified. We implement an
                 IDS (intrusion detection system) based on our
                 architecture to verify the feasibility of our system
                 and evaluate its performance. The results show that the
                 overhead introduced by the system architecture is
                 within an acceptable range.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Feature Papers for Future
                 Internet-Internet of Things Section.",
}

@Article{Tomczyk:2021:EDP,
  author =       "Lukasz Tomczyk",
  title =        "Evaluation of Digital Piracy by Youths",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "1",
  pages =        "11",
  day =          "04",
  month =        jan,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13010011",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/1/11",
  abstract =     "This paper sets out to explain how adolescents
                 interpret piracy. Digital piracy is one of the most
                 important risk behaviours mediated by new media to be
                 found among adolescents. It is global, and changes
                 dynamically due to the continued development of the
                 information society. To explore the phenomena related
                 to piracy among adolescent Internet users we need to
                 apply qualitative research methods. The sample
                 contained 1320 Polish respondents. The research used
                 the technique of qualitative research. Data was
                 collected using a form containing an open question.
                 Adolescents will answer in the form how they interpret
                 digital piracy. The categories characterize how piracy
                 is perceived, and includes downloading various
                 files---whether video or music files or even software
                 (also games)---from unauthorized sources
                 (P2P---Peer-to-peer `warez' servers---websites which
                 serve as repositories of illegal files). The
                 qualitative data analysis allowed the identification of
                 the following constructs in the perception of digital
                 piracy by adolescents: ethical (giving value to the
                 phenomenon), economical (showing profits and losses),
                 legal (connected with punitive consequences and
                 criminal liability), praxeological (facilitating daily
                 life), technical (referring to the hardware necessary),
                 social (the scale of the phenomenon and interpersonal
                 relations), and personal benefits. The results fit into
                 the discussion on the standard and hidden factors
                 connected with piracy. The presented seven categories
                 of the perception of piracy help us better understand
                 the phenomenon of the infringement of intellectual
                 property law and will help to develop appropriate
                 preventive measures. Qualitative research makes it
                 possible to understand the phenomenon of piracy from a
                 deeper perspective, which can be translated into the
                 design of effective educational measures. Preventive
                 guidance on minimising risky behaviour is part of the
                 development of one of the key competences, namely
                 digital knowledge and skills. The research allowed us
                 to enrich the theoretical knowledge on risky behaviours
                 in cyberspace among adolescents (theoretical aim), to
                 understand how to interpret risky behaviours in
                 cyberspace (understanding of micro-worlds---cognitive
                 aim), and to gather new knowledge that will be useful
                 for prevention (practical aim).",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Education Responses to Technological
                 Challenges and Their Impact on Classrooms.",
}

@Article{Javed:2021:PPA,
  author =       "Yousra Javed and Elham {Al Qahtani} and Mohamed
                 Shehab",
  title =        "Privacy Policy Analysis of Banks and Mobile Money
                 Services in the {Middle East}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "1",
  pages =        "10",
  day =          "03",
  month =        jan,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13010010",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/1/10",
  abstract =     "Privacy compliance of the Middle East's financial
                 sector has been relatively unexplored. This paper
                 evaluates the privacy compliance and readability of
                 privacy statements for top banks and mobile money
                 services in the Middle East. Our analysis shows that,
                 overall, Middle Eastern banks have better privacy
                 policy availability and language distribution, and are
                 more privacy compliant compared to mobile money
                 services. However, both the banks and mobile money
                 services need to improve (1) compliance with the
                 principles of children/adolescent's data protection,
                 accountability and enforcement, and data
                 minimization/retention, and (2) privacy statement texts
                 to be comprehensible for a reader with $ \approx 8 $
                 years of education or less.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Cybersecurity.",
}

@Article{Matosevic:2021:UML,
  author =       "Goran Matosevi{\'c} and Jasminka Dobsa and Dunja
                 Mladeni{\'c}",
  title =        "Using Machine Learning for {Web} Page Classification
                 in Search Engine Optimization",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "1",
  pages =        "9",
  day =          "02",
  month =        jan,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13010009",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/1/9",
  abstract =     "This paper presents a novel approach of using machine
                 learning algorithms based on experts' knowledge to
                 classify web pages into three predefined classes
                 according to the degree of content adjustment to the
                 search engine optimization (SEO) recommendations. In
                 this study, classifiers were built and trained to
                 classify an unknown sample (web page) into one of the
                 three predefined classes and to identify important
                 factors that affect the degree of page adjustment. The
                 data in the training set are manually labeled by domain
                 experts. The experimental results show that machine
                 learning can be used for predicting the degree of
                 adjustment of web pages to the SEO
                 recommendations---classifier accuracy ranges from
                 54.59\% to 69.67\%, which is higher than the baseline
                 accuracy of classification of samples in the majority
                 class (48.83\%). Practical significance of the proposed
                 approach is in providing the core for building software
                 agents and expert systems to automatically detect web
                 pages, or parts of web pages, that need improvement to
                 comply with the SEO guidelines and, therefore,
                 potentially gain higher rankings by search engines.
                 Also, the results of this study contribute to the field
                 of detecting optimal values of ranking factors that
                 search engines use to rank web pages. Experiments in
                 this paper suggest that important factors to be taken
                 into consideration when preparing a web page are page
                 title, meta description, H1 tag (heading), and body
                 text---which is aligned with the findings of previous
                 research. Another result of this research is a new data
                 set of manually labeled web pages that can be used in
                 further research.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Digital Marketing and App-based
                 Marketing.",
}

@Article{Venu:2021:EDC,
  author =       "Sagar Kora Venu and Sridhar Ravula",
  title =        "Evaluation of Deep Convolutional Generative
                 Adversarial Networks for Data Augmentation of Chest
                 {X}-ray Images",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "1",
  pages =        "8",
  day =          "31",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13010008",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/1/8",
  abstract =     "Medical image datasets are usually imbalanced due to
                 the high costs of obtaining the data and time-consuming
                 annotations. Training a deep neural network model on
                 such datasets to accurately classify the medical
                 condition does not yield the desired results as they
                 often over-fit the majority class samples' data. Data
                 augmentation is often performed on the training data to
                 address the issue by position augmentation techniques
                 such as scaling, cropping, flipping, padding, rotation,
                 translation, affine transformation, and color
                 augmentation techniques such as brightness, contrast,
                 saturation, and hue to increase the dataset sizes.
                 Radiologists generally use chest X-rays for the
                 diagnosis of pneumonia. Due to patient privacy
                 concerns, access to such data is often protected. In
                 this study, we performed data augmentation on the Chest
                 X-ray dataset to generate artificial chest X-ray images
                 of the under-represented class through generative
                 modeling techniques such as the Deep Convolutional
                 Generative Adversarial Network (DCGAN). With just 1341
                 chest X-ray images labeled as Normal, artificial
                 samples were created by retaining similar
                 characteristics to the original data with this
                 technique. Evaluating the model resulted in a
                 Fr{\'e}chet Distance of Inception (FID) score of 1.289.
                 We further show the superior performance of a CNN
                 classifier trained on the DCGAN augmented dataset.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Computer Vision, Deep Learning and
                 Machine Learning with Applications.",
}

@Article{Jimenez:2021:CUE,
  author =       "Ivonne Angelica Castiblanco Jimenez and Laura Cristina
                 Cepeda Garc{\'\i}a and Maria Grazia Violante and
                 Federica Marcolin and Enrico Vezzetti",
  title =        "Commonly Used External {TAM} Variables in e-Learning,
                 Agriculture and Virtual Reality Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "1",
  pages =        "7",
  day =          "31",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13010007",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/1/7",
  abstract =     "In recent years information and communication
                 technologies (ICT) have played a significant role in
                 all aspects of modern society and have impacted
                 socioeconomic development in sectors such as education,
                 administration, business, medical care and agriculture.
                 The benefits of such technologies in agriculture can be
                 appreciated only if farmers use them. In order to
                 predict and evaluate the adoption of these new
                 technological tools, the technology acceptance model
                 (TAM) can be a valid aid. This paper identifies the
                 most commonly used external variables in e-learning,
                 agriculture and virtual reality applications for
                 further validation in an e-learning tool designed for
                 EU farmers and agricultural entrepreneurs. Starting
                 from a literature review of the technology acceptance
                 model, the analysis based on Quality Function
                 Deployment (QFD) shows that computer self-efficacy,
                 individual innovativeness, computer anxiety, perceived
                 enjoyment, social norm, content and system quality,
                 experience and facilitating conditions are the most
                 common determinants addressing technology acceptance.
                 Furthermore, findings evidenced that the external
                 variables have a different impact on the two main
                 beliefs of the TAM Model, Perceived Usefulness (PU) and
                 Perceived Ease of Use (PEOU). This study is expected to
                 bring theoretical support for academics when
                 determining the variables to be included in TAM
                 extensions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue VR, AR, and 3-D User Interfaces for
                 Measurement and Control.",
}

@Article{Hu:2021:UBM,
  author =       "Rui Hu and Bruno Michel and Dario Russo and
                 Niccol{\`o} Mora and Guido Matrella and Paolo
                 Ciampolini and Francesca Cocchi and Enrico Montanari
                 and Stefano Nunziata and Thomas Brunschwiler",
  title =        "An Unsupervised Behavioral Modeling and Alerting
                 System Based on Passive Sensing for Elderly Care",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "1",
  pages =        "6",
  day =          "30",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13010006",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/1/6",
  abstract =     "Artificial Intelligence in combination with the
                 Internet of Medical Things enables remote healthcare
                 services through networks of environmental and/or
                 personal sensors. We present a remote healthcare
                 service system which collects real-life data through an
                 environmental sensor package, including binary motion,
                 contact, pressure, and proximity sensors, installed at
                 households of elderly people. Its aim is to keep the
                 caregivers informed of subjects' health-status
                 progressive trajectory, and alert them of
                 health-related anomalies to enable objective on-demand
                 healthcare service delivery at scale. The system was
                 deployed in 19 households inhabited by an elderly
                 person with post-stroke condition in the
                 Emilia--Romagna region in Italy, with maximal and
                 median observation durations of 98 and 55 weeks. Among
                 these households, 17 were multi-occupancy residences,
                 while the other 2 housed elderly patients living alone.
                 Subjects' daily behavioral diaries were extracted and
                 registered from raw sensor signals, using rule-based
                 data pre-processing and unsupervised algorithms.
                 Personal behavioral habits were identified and compared
                 to typical patterns reported in behavioral science, as
                 a quality-of-life indicator. We consider the activity
                 patterns extracted across all users as a dictionary,
                 and represent each patient's behavior as a `Bag of
                 Words', based on which patients can be categorized into
                 sub-groups for precision cohort treatment. Longitudinal
                 trends of the behavioral progressive trajectory and
                 sudden abnormalities of a patient were detected and
                 reported to care providers. Due to the sparse sensor
                 setting and the multi-occupancy living condition, the
                 sleep profile was used as the main indicator in our
                 system. Experimental results demonstrate the ability to
                 report on subjects' daily activity pattern in terms of
                 sleep, outing, visiting, and health-status
                 trajectories, as well as predicting/detecting 75\%
                 hospitalization sessions up to 11 days in advance. 65\%
                 of the alerts were confirmed to be semantically
                 meaningful by the users. Furthermore, reduced social
                 interaction (outing and visiting), and lower sleep
                 quality could be observed during the COVID-19 lockdown
                 period across the cohort.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue The Future Internet of Medical Things.",
}

@Article{Paakkonen:2021:AEE,
  author =       "Pekka P{\"a}{\"a}kk{\"o}nen and Daniel Pakkala and
                 Jussi Kiljander and Roope Sarala",
  title =        "Architecture for Enabling Edge Inference via Model
                 Transfer from Cloud Domain in a {Kubernetes}
                 Environment",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "1",
  pages =        "5",
  day =          "29",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13010005",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/1/5",
  abstract =     "The current approaches for energy consumption
                 optimisation in buildings are mainly reactive or focus
                 on scheduling of daily/weekly operation modes in
                 heating. Machine Learning (ML)-based advanced control
                 methods have been demonstrated to improve energy
                 efficiency when compared to these traditional methods.
                 However, placing of ML-based models close to the
                 buildings is not straightforward. Firstly, edge-devices
                 typically have lower capabilities in terms of
                 processing power, memory, and storage, which may limit
                 execution of ML-based inference at the edge. Secondly,
                 associated building information should be kept private.
                 Thirdly, network access may be limited for serving a
                 large number of edge devices. The contribution of this
                 paper is an architecture, which enables training of
                 ML-based models for energy consumption prediction in
                 private cloud domain, and transfer of the models to
                 edge nodes for prediction in Kubernetes environment.
                 Additionally, predictors at the edge nodes can be
                 automatically updated without interrupting operation.
                 Performance results with sensor-based devices
                 (Raspberry Pi 4 and Jetson Nano) indicated that a
                 satisfactory prediction latency ($ \approx 7$--$9$ s)
                 can be achieved within the research context. However,
                 model switching led to an increase in prediction
                 latency ($ \approx 9$--$ 13$ s). Partial evaluation of
                 a Reference Architecture for edge computing systems,
                 which was used as a starting point for architecture
                 design, may be considered as an additional contribution
                 of the paper.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Network Virtualization and Edge/Fog
                 Computing.",
}

@Article{Zannou:2021:SNS,
  author =       "Abderrahim Zannou and Abdelhak Boulaalam and El Habib
                 Nfaoui",
  title =        "{SIoT}: a New Strategy to Improve the Network Lifetime
                 with an Efficient Search Process",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "1",
  pages =        "4",
  day =          "29",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13010004",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/1/4",
  abstract =     "The Social Internet of Things (SIoT) means that every
                 node can use a set of nodes that are considered as
                 friends to search for a specific service. However, this
                 is a slow process because each node is required to
                 manage a high number of friends. Thus, the SIoT issue
                 consists of how to select the right friends that
                 improve the network navigability. The enhancement of
                 the network navigability boosts the search for a
                 service to be rapid but not guaranteed. Furthermore,
                 sending requests from the shortest paths involves the
                 rapid search, but the network lifetime can be reduced
                 due to the number of requests that can be transmitted
                 and processed by the nodes that have low power energy.
                 This paper proposes a new approach that improves the
                 network navigability, speeds up the search process, and
                 increases the network lifetime. This approach aims at
                 creating groups dynamically by nodes where each group
                 has a master node, second, using a consensus algorithm
                 between master nodes to agree with a specific
                 capability, finally adopting a friendship selection
                 method to create a social network. Thus, the friends
                 will be sorted periodically for the objective of
                 creating simultaneously a balance between the energy
                 consumption and the rapid search process. Simulation
                 results on the Brightkite location-based online social
                 network dataset demonstrate that our proposal
                 outperforms baseline methods in terms of some
                 parameters of network navigability, path length to
                 reach the providers, and network lifetime.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Internet of Things.",
}

@Article{Romanov:2021:AIR,
  author =       "Aleksandr Romanov and Anna Kurtukova and Alexander
                 Shelupanov and Anastasia Fedotova and Valery
                 Goncharov",
  title =        "Authorship Identification of a {Russian}-Language Text
                 Using Support Vector Machine and Deep Neural Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "1",
  pages =        "3",
  day =          "25",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13010003",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/1/3",
  abstract =     "The article explores approaches to determining the
                 author of a natural language text and the advantages
                 and disadvantages of these approaches. The importance
                 of the considered problem is due to the active
                 digitalization of society and reassignment of most
                 parts of the life activities online. Text authorship
                 methods are particularly useful for information
                 security and forensics. For example, such methods can
                 be used to identify authors of suicide notes, and other
                 texts are subjected to forensic examinations. Another
                 area of application is plagiarism detection. Plagiarism
                 detection is a relevant issue both for the field of
                 intellectual property protection in the digital space
                 and for the educational process. The article describes
                 identifying the author of the Russian-language text
                 using support vector machine (SVM) and deep neural
                 network architectures (long short-term memory (LSTM),
                 convolutional neural networks (CNN) with attention,
                 Transformer). The results show that all the considered
                 algorithms are suitable for solving the authorship
                 identification problem, but SVM shows the best
                 accuracy. The average accuracy of SVM reaches 96\%.
                 This is due to thoroughly chosen parameters and feature
                 space, which includes statistical and semantic features
                 (including those extracted as a result of an aspect
                 analysis). Deep neural networks are inferior to SVM in
                 accuracy and reach only 93\%. The study also includes
                 an evaluation of the impact of attacks on the method on
                 models' accuracy. Experiments show that the SVM-based
                 methods are unstable to deliberate text anonymization.
                 In comparison, the loss in accuracy of deep neural
                 networks does not exceed 20\%. Transformer architecture
                 is the most effective for anonymized texts and allows
                 81\% accuracy to be achieved.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Data Science and Knowledge Discovery.",
}

@Article{Santamaria-Granados:2021:TRS,
  author =       "Luz Santamaria-Granados and Juan Francisco
                 Mendoza-Moreno and Gustavo Ramirez-Gonzalez",
  title =        "Tourist Recommender Systems Based on Emotion
                 Recognition --- a Scientometric Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "1",
  pages =        "2",
  day =          "24",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13010002",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/1/2",
  abstract =     "Recommendation systems have overcome the overload of
                 irrelevant information by considering users'
                 preferences and emotional states in the fields of
                 tourism, health, e-commerce, and entertainment. This
                 article reviews the principal recommendation approach
                 documents found in scientific databases (Elsevier's
                 Scopus and Clarivate Web of Science) through a
                 scientometric analysis in ScientoPy. Research
                 publications related to the recommenders of
                 emotion-based tourism cover the last two decades. The
                 review highlights the collection, processing, and
                 feature extraction of data from sensors and wearables
                 to detect emotions. The study proposes the thematic
                 categories of recommendation systems, emotion
                 recognition, wearable technology, and machine learning.
                 This paper also presents the evolution, trend analysis,
                 theoretical background, and algorithmic approaches used
                 to implement recommenders. Finally, the discussion
                 section provides guidelines for designing
                 emotion-sensitive tourist recommenders.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Recent Advances of Machine Learning
                 Techniques on Smartphones.",
}

@Article{Wang:2021:DAA,
  author =       "Jing Wang and ZhongCheng Wu and Fang Li and Jun
                 Zhang",
  title =        "A Data Augmentation Approach to Distracted Driving
                 Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "1",
  pages =        "1",
  day =          "22",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13010001",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jan 22 11:26:00 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/1/1",
  abstract =     "Distracted driving behavior has become a leading cause
                 of vehicle crashes. This paper proposes a data
                 augmentation method for distracted driving detection
                 based on the driving operation area. First, the class
                 activation mapping method is used to show the key
                 feature areas of driving behavior analysis, and then
                 the driving operation areas are detected by the faster
                 R-CNN detection model for data augmentation. Finally,
                 the convolutional neural network classification mode is
                 implemented and evaluated to detect the original
                 dataset and the driving operation area dataset. The
                 classification result achieves a 96.97\% accuracy using
                 the distracted driving dataset. The results show the
                 necessity of driving operation area extraction in the
                 preprocessing stage, which can effectively remove the
                 redundant information in the images to get a higher
                 classification accuracy rate. The method of this
                 research can be used to detect drivers in actual
                 application scenarios to identify dangerous driving
                 behaviors, which helps to give early warning of unsafe
                 driving behaviors and avoid accidents.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Data Science and Knowledge Discovery.",
}

@Article{Lei:2021:VCB,
  author =       "Zhou Lei and Yiyong Huang",
  title =        "Video Captioning Based on Channel Soft Attention and
                 Semantic Reconstructor",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "55",
  day =          "23",
  month =        feb,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020055",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/55",
  abstract =     "Video captioning is a popular task which automatically
                 generates a natural-language sentence to describe video
                 content. Previous video captioning works mainly use the
                 encoder-decoder framework and exploit special
                 techniques such as attention mechanisms to improve the
                 quality of generated sentences. In addition, most
                 attention mechanisms focus on global features and
                 spatial features. However, global features are usually
                 fully connected features. Recurrent convolution
                 networks (RCNs) receive 3-dimensional features as input
                 at each time step, but the temporal structure of each
                 channel at each time step has been ignored, which
                 provide temporal relation information of each channel.
                 In this paper, a video captioning model based on
                 channel soft attention and semantic reconstructor is
                 proposed, which considers the global information for
                 each channel. In a video feature map sequence, the same
                 channel of every time step is generated by the same
                 convolutional kernel. We selectively collect the
                 features generated by each convolutional kernel and
                 then input the weighted sum of each channel to RCN at
                 each time step to encode video representation.
                 Furthermore, a semantic reconstructor is proposed to
                 rebuild semantic vectors to ensure the integrity of
                 semantic information in the training process, which
                 takes advantage of both forward (semantic to sentence)
                 and backward (sentence to semantic) flows. Experimental
                 results on popular datasets MSVD and MSR-VTT
                 demonstrate the effectiveness and feasibility of our
                 model.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Techno-Social Smart Systems.",
}

@Article{Liu:2021:LBO,
  author =       "Yazhi Liu and Jiye Zhang and Wei Li and Qianqian Wu
                 and Pengmiao Li",
  title =        "Load Balancing Oriented Predictive Routing Algorithm
                 for Data Center Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "54",
  day =          "22",
  month =        feb,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020054",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/54",
  abstract =     "A data center undertakes increasing background
                 services of various applications, and the data flows
                 transmitted between the nodes in data center networks
                 (DCNs) are consequently increased. At the same time,
                 the traffic of each link in a DCN changes dynamically
                 over time. Flow scheduling algorithms can improve the
                 distribution of data flows among the network links so
                 as to improve the balance of link loads in a DCN.
                 However, most current load balancing works achieve flow
                 scheduling decisions to the current links on the basis
                 of past link flow conditions. This situation impedes
                 the existing link scheduling methods from implementing
                 optimal decisions for scheduling data flows among the
                 network links in a DCN. This paper proposes a
                 predictive link load balance routing algorithm for a
                 DCN based on residual networks (ResNet), i.e., the link
                 load balance route (LLBR) algorithm. The LLBR algorithm
                 predicts the occupancy of the network links in the next
                 duty cycle, according to the ResNet architecture, and
                 then the optimal traffic route is selected according to
                 the predictive network environment. The LLBR algorithm,
                 round-robin scheduling (RRS), and weighted round-robin
                 scheduling (WRRS) are used in the same experimental
                 environment. Experimental results show that compared
                 with the WRRS and RRS, the LLBR algorithm can reduce
                 the transmission time by approximately 50\%, reduce the
                 packet loss rate from 0.05\% to 0.02\%, and improve the
                 bandwidth utilization by 30\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Big Data and Augmented Intelligence.",
}

@Article{Goudosis:2021:AOR,
  author =       "Athanasios Goudosis and Sokratis Katsikas",
  title =        "{ARIBC}: Online Reporting Based on Identity-Based
                 Cryptography",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "53",
  day =          "21",
  month =        feb,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020053",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/53",
  abstract =     "The reporting of incidents of misconduct, violence,
                 sexual assault, harassment, and other types of crime
                 that constitute a major concern in modern society is of
                 significant value when investigating such incidents.
                 Unfortunately, people involved in such incidents,
                 either as witnesses or victims, are often reluctant to
                 report them when such reporting demands revealing the
                 reporter's true identity. In this paper, we propose an
                 online reporting system that leverages Identity-Based
                 Cryptography (IBC) and offers data authentication, data
                 integrity, and data confidentiality services to both
                 eponymous and anonymous users. The system, called
                 ARIBC, is founded on a certificate-less, public-key,
                 IBC infrastructure, implemented by employing the
                 Sakai-Kasahara approach and by following the IEEE
                 1363.3-2013 standard. We develop a proof-of-concept
                 implementation of the proposed scheme, and demonstrate
                 its applicability in environments with constrained
                 human, organizational and/or computational resources.
                 The computational overheads imposed by the scheme are
                 found to be well within the capabilities of modern
                 fixed or mobile devices.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Feature Papers for Future
                 Internet---Cybersecurity Section.",
}

@Article{Rodriguez-Abitia:2021:ADT,
  author =       "Guillermo Rodr{\'\i}guez-Abitia and Graciela
                 Bribiesca-Correa",
  title =        "Assessing Digital Transformation in Universities",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "52",
  day =          "20",
  month =        feb,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020052",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/52",
  abstract =     "Industry 4.0 and Society 5.0 are reshaping the way
                 organizations function and interact with the
                 communities they serve. The massive penetration of
                 computer and network applications forces organizations
                 to digitalize their processes and provide innovative
                 products, services, and business models. The education
                 market is suffering changes as well, but universities
                 seem slow to react. This paper proposes the application
                 of an integrated digital transformation model to assess
                 the maturity level that educational institutions have
                 in their digital transformation processes and compares
                 them to other industries. Particular considerations to
                 address when using the model for higher-education
                 institutions are discussed. Our results show that
                 universities fall behind other sectors, probably due to
                 a lack of effective leadership and changes in culture.
                 This is complemented negatively by an insufficient
                 degree of innovation and financial support.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Education 4.0 in the Transformation of
                 Universities: Educational and Research Applications.",
}

@Article{Sun:2021:IVG,
  author =       "Lili Sun and Xueyan Liu and Min Zhao and Bo Yang",
  title =        "Interpretable Variational Graph Autoencoder with
                 Noninformative Prior",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "51",
  day =          "18",
  month =        feb,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020051",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/51",
  abstract =     "Variational graph autoencoder, which can encode
                 structural information and attribute information in the
                 graph into low-dimensional representations, has become
                 a powerful method for studying graph-structured data.
                 However, most existing methods based on variational
                 (graph) autoencoder assume that the prior of latent
                 variables obeys the standard normal distribution which
                 encourages all nodes to gather around 0. That leads to
                 the inability to fully utilize the latent space.
                 Therefore, it becomes a challenge on how to choose a
                 suitable prior without incorporating additional expert
                 knowledge. Given this, we propose a novel
                 noninformative prior-based interpretable variational
                 graph autoencoder (NPIVGAE). Specifically, we exploit
                 the noninformative prior as the prior distribution of
                 latent variables. This prior enables the posterior
                 distribution parameters to be almost learned from the
                 sample data. Furthermore, we regard each dimension of a
                 latent variable as the probability that the node
                 belongs to each block, thereby improving the
                 interpretability of the model. The correlation within
                 and between blocks is described by a block-block
                 correlation matrix. We compare our model with
                 state-of-the-art methods on three real datasets,
                 verifying its effectiveness and superiority.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Big Data and Augmented Intelligence.",
}

@Article{Jahromi:2021:STC,
  author =       "Hamed Z. Jahromi and Declan Delaney and Andrew Hines",
  title =        "A Sign of Things to Come: Predicting the Perception of
                 Above-the-Fold Time in {Web} Browsing",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "50",
  day =          "17",
  month =        feb,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020050",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/50",
  abstract =     "Content is a key influencing factor in Web Quality of
                 Experience (QoE) estimation. A web user's satisfaction
                 can be influenced by how long it takes to render and
                 visualize the visible parts of the web page in the
                 browser. This is referred to as the Above-the-fold
                 (ATF) time. SpeedIndex (SI) has been widely used to
                 estimate perceived web page loading speed of ATF
                 content and a proxy metric for Web QoE estimation. Web
                 application developers have been actively introducing
                 innovative interactive features, such as animated and
                 multimedia content, aiming to capture the users'
                 attention and improve the functionality and utility of
                 the web applications. However, the literature shows
                 that, for the websites with animated content, the
                 estimated ATF time using the state-of-the-art metrics
                 may not accurately match completed ATF time as
                 perceived by users. This study introduces a new metric,
                 Plausibly Complete Time (PCT), that estimates ATF time
                 for a user's perception of websites with and without
                 animations. PCT can be integrated with SI and web QoE
                 models. The accuracy of the proposed metric is
                 evaluated based on two publicly available datasets. The
                 proposed metric holds a high positive Spearman's
                 correlation ( rs=0.89 ) with the Perceived ATF reported
                 by the users for websites with and without animated
                 content. This study demonstrates that using PCT as a
                 KPI in QoE estimation models can improve the robustness
                 of QoE estimation in comparison to using the
                 state-of-the-art ATF time metric. Furthermore,
                 experimental result showed that the estimation of SI
                 using PCT improves the robustness of SI for websites
                 with animated content. The PCT estimation allows web
                 application designers to identify where poor design has
                 significantly increased ATF time and refactor their
                 implementation before it impacts end-user experience.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Quality of Experience (QoE) Management
                 in Softwarized Network Environments.",
}

@Article{Cui:2021:STP,
  author =       "Guowei Cui and Wei Shuai and Xiaoping Chen",
  title =        "Semantic Task Planning for Service Robots in Open
                 Worlds",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "49",
  day =          "17",
  month =        feb,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020049",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/49",
  abstract =     "This paper presents a planning system based on
                 semantic reasoning for a general-purpose service robot,
                 which is aimed at behaving more intelligently in
                 domains that contain incomplete information,
                 under-specified goals, and dynamic changes. First, Two
                 kinds of data are generated by Natural Language
                 Processing module from the speech: (i) action frames
                 and their relationships; (ii) the modifier used to
                 indicate some property or characteristic of a variable
                 in the action frame. Next, the task's goals are
                 generated from these action frames and modifiers. These
                 goals are represented as AI symbols, combining world
                 state and domain knowledge, which are used to generate
                 plans by an Answer Set Programming solver. Finally, the
                 plan's actions are executed one by one, and continuous
                 sensing grounds useful information, which makes the
                 robot use contingent knowledge to adapt to dynamic
                 changes and faults. For each action in the plan, the
                 planner gets its preconditions and effects from domain
                 knowledge, so during the execution of the task, the
                 environmental changes, especially those conflict with
                 the actions, not only the action being performed but
                 also the subsequent actions, can be detected and
                 handled as early as possible. A series of case studies
                 are used to evaluate the system and verify its ability
                 to acquire knowledge through dialogue with users, solve
                 problems with the acquired causal knowledge, and plan
                 for complex tasks autonomously in the open world.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Service-Oriented Systems and
                 Applications.",
}

@Article{Du:2021:BEE,
  author =       "Yao Du and Zehua Wang and Victor C. M. Leung",
  title =        "Blockchain-Enabled Edge Intelligence for {IoT}:
                 Background, Emerging Trends and Open Issues",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "48",
  day =          "17",
  month =        feb,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020048",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/48",
  abstract =     "Blockchain, a distributed ledger technology (DLT),
                 refers to a list of records with consecutive time
                 stamps. This decentralization technology has become a
                 powerful model to establish trust among trustless
                 entities, in a verifiable manner. Motivated by the
                 recent advancement of multi-access edge computing (MEC)
                 and artificial intelligence (AI), blockchain-enabled
                 edge intelligence has become an emerging technology for
                 the Internet of Things (IoT). We review how
                 blockchain-enabled edge intelligence works in the IoT
                 domain, identify the emerging trends, and suggest open
                 issues for further research. To be specific: (1) we
                 first offer some basic knowledge of DLT, MEC, and AI;
                 (2) a comprehensive review of current peer-reviewed
                 literature is given to identify emerging trends in this
                 research area; and (3) we discuss some open issues and
                 research gaps for future investigations. We expect that
                 blockchain-enabled edge intelligence will become an
                 important enabler of future IoT, providing trust and
                 intelligence to satisfy the sophisticated needs of
                 industries and society.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Feature Papers for Future
                 Internet-Internet of Things Section.",
}

@Article{Yang:2021:AAB,
  author =       "Zhi-Peng Yang and Lu Hua and Ning-Jie Gao and Ru Huo
                 and Jiang Liu and Tao Huang",
  title =        "An Accelerating Approach for Blockchain Information
                 Transmission Based on {NDN}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "47",
  day =          "14",
  month =        feb,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020047",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/47",
  abstract =     "Blockchain is becoming more and more popular in
                 various fields. Since the information transmission mode
                 of the blockchain is data broadcasting, the traditional
                 TCP/IP network cannot support the blockchain system
                 well, but the Named-Data Networking (NDN) could be a
                 good choice because of its multi-path forwarding and
                 intra-network caching functions. In this article, we
                 propose a new blockchain information transmission
                 acceleration strategy (AITS) combining with graph
                 theory and probability theory based on the NDN
                 architecture. We select some more important nodes in
                 the network as ``secondary nodes'', and give them more
                 bandwidth and cache space to assist the NDN network in
                 data transmission. In order to select the correct node
                 as the secondary node, we present a method to calculate
                 the number of secondary nodes, and give the function to
                 calculate the importance of each node. The simulation
                 results show that in complex networks, the proposed
                 method has superior performance in accelerating
                 information transmission and reducing data overhead.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue The Next Blockchain Wave Current
                 Challenges and Future Prospects.",
}

@Article{Phengsuwan:2021:USM,
  author =       "Jedsada Phengsuwan and Tejal Shah and Nipun Balan
                 Thekkummal and Zhenyu Wen and Rui Sun and Divya
                 Pullarkatt and Hemalatha Thirugnanam and Maneesha
                 Vinodini Ramesh and Graham Morgan and Philip James and
                 Rajiv Ranjan",
  title =        "Use of Social Media Data in Disaster Management: a
                 Survey",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "46",
  day =          "12",
  month =        feb,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020046",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/46",
  abstract =     "Social media has played a significant role in disaster
                 management, as it enables the general public to
                 contribute to the monitoring of disasters by reporting
                 incidents related to disaster events. However, the vast
                 volume and wide variety of generated social media data
                 create an obstacle in disaster management by limiting
                 the availability of actionable information from social
                 media. Several approaches have therefore been proposed
                 in the literature to cope with the challenges of social
                 media data for disaster management. To the best of our
                 knowledge, there is no published literature on social
                 media data management and analysis that identifies the
                 research problems and provides a research taxonomy for
                 the classification of the common research issues. In
                 this paper, we provide a survey of how social media
                 data contribute to disaster management and the
                 methodologies for social media data management and
                 analysis in disaster management. This survey includes
                 the methodologies for social media data classification
                 and event detection as well as spatial and temporal
                 information extraction. Furthermore, a taxonomy of the
                 research dimensions of social media data management and
                 analysis for disaster management is also proposed,
                 which is then applied to a survey of existing
                 literature and to discuss the core advantages and
                 disadvantages of the various methodologies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue AI and IoT technologies in Smart
                 Cities.",
}

@Article{daCosta:2021:DCM,
  author =       "Nuno Marques da Costa and Nelson Mileu and Andr{\'e}
                 Alves",
  title =        "Dashboard {COMPRIME\_COMPRI\_MOv}: Multiscalar
                 Spatio-Temporal Monitoring of the {COVID-19} Pandemic
                 in {Portugal}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "45",
  day =          "12",
  month =        feb,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020045",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/45",
  abstract =     "Due to its novelty, the recent pandemic of the
                 coronavirus disease (COVID-19), which is associated
                 with the spread of the new severe acute respiratory
                 syndrome coronavirus (SARS-CoV-2), triggered the
                 public's interest in accessing information,
                 demonstrating the importance of obtaining and analyzing
                 credible and updated information from an
                 epidemiological surveillance context. For this purpose,
                 health authorities, international organizations, and
                 university institutions have published online various
                 graphic and cartographic representations of the
                 evolution of the pandemic with daily updates that allow
                 the almost real-time monitoring of the evolutionary
                 behavior of the spread, lethality, and territorial
                 distribution of the disease. The purpose of this
                 article is to describe the technical solution and the
                 main results associated with the publication of the
                 COMPRIME\_COMPRI\_MOv dashboard for the dissemination
                 of information and multi-scale knowledge of COVID-19.
                 Under two rapidly implementing research projects for
                 innovative solutions to respond to the COVID-19
                 pandemic, promoted in Portugal by the FCT (Foundation
                 for Science and Technology), a website was created.
                 That website brings together a diverse set of variables
                 and indicators in a dynamic and interactive way that
                 reflects the evolutionary behavior of the pandemic from
                 a multi-scale perspective, in Portugal, constituting
                 itself as a system for monitoring the evolution of the
                 pandemic. In the current situation, this type of
                 exploratory solutions proves to be crucial to guarantee
                 everyone's access to information while simultaneously
                 emerging as an epidemiological surveillance tool that
                 is capable of assisting decision-making by public
                 authorities with competence in defining control
                 policies and fight the spread of the new coronavirus.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Data Science and Knowledge Discovery.",
}

@Article{Pokrovskaia:2021:DRI,
  author =       "Nadezhda N. Pokrovskaia and Olga N. Korableva and
                 Lucio Cappelli and Denis A. Fedorov",
  title =        "Digital Regulation of Intellectual Capital for Open
                 Innovation: Industries' Expert Assessments of Tacit
                 Knowledge for Controlling and Networking Outcome",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "44",
  day =          "10",
  month =        feb,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020044",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/44",
  abstract =     "Digital regulation implies the quantified measuring
                 and the network infrastructure allowing managers to
                 control the processes of value creation. Digital
                 regulation needs to take into account tacit elements of
                 the value creation process, including unconscious
                 competency, creativity, and intuitive anticipation, to
                 assure the resulting network's innovation growth.
                 Digital society in developing countries is built on the
                 ground of fact change of the economy and social
                 relations, of transition towards an emerging market
                 within the global offline network of interactions and
                 online activities through Internet; the innovative
                 growth imposes the evolution of managerial behavior and
                 attitudes. The main objective of the paper is to obtain
                 indications on the perception of intellectual capital
                 by corporate managers. The exploratory study was
                 carried out in Russian companies operating in different
                 sectors, with the use of the open-ended approach,
                 including focused interviews and group discussion among
                 experts, middle and senior managers from marketing or
                 corporate governance background. The data were
                 complemented by documentary analysis of descriptions of
                 internal processes of the implementation of digital
                 tools of accounting, which includes the human resources
                 control applied for the remote work during the
                 pandemic. Networking helps to coordinate functions
                 between team members at remote work and between teams
                 and administrators. The interviews demonstrated the
                 administrative tendency to under-estimate the
                 non-formalized factors of innovation activity, such as
                 awareness of corporate strategy, creativity,
                 motivation, and affective and behavioral components of
                 communication of the persons involved in the enrichment
                 of intellectual capital. The results show fuzzy
                 boundaries between the intellectual capital components
                 that are difficult to control. This difficulty provokes
                 the preference for the use of ``traditional''
                 quantitative indicators that had been implemented at
                 the stage of the financial digitalization, instead of
                 developing new parameters or measuring approaches. The
                 networking emerges synergetic effect if the
                 administrators refuse their monopoly on the uncertainty
                 zones and are oriented to construct the trustful
                 atmosphere of personal responsibility within the
                 network.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Digital Society Challenges in Developing
                 Countries.",
}

@Article{Pokrovskaia:2021:DCT,
  author =       "Nadezhda N. Pokrovskaia and Veronika L. Leontyeva and
                 Marianna Yu. Ababkova and Lucio Cappelli and Fabrizio
                 D'Ascenzo",
  title =        "Digital Communication Tools and Knowledge Creation
                 Processes for Enriched Intellectual Outcome-Experience
                 of Short-Term E-Learning Courses during Pandemic",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "43",
  day =          "05",
  month =        feb,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020043",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/43",
  abstract =     "Social isolation during the pandemic contributed to
                 the transition of educational processes to e-learning.
                 A short-term e-marketing education program for a
                 variety of students was introduced in May 2020 and is
                 taught entirely online. A survey was conducted
                 regularly in the last week of training using Google
                 Forms, and three cohorts were surveyed in July,
                 September, and December 2020. A high level of
                 satisfaction indicates an interest in the content and a
                 positive assessment of the level of comfort of an
                 organization adapted to the needs of students; this
                 positive result contrasted with the negative opinion of
                 the remote learning in Russia since March 2020, and
                 this surprising satisfaction of students has motivated
                 the study to try to explain its reasons. This result
                 was compared with the short-term course taught through
                 the educational pedagogical platform of a university.
                 The students of traditional short- and long-term
                 university programs were asked to assess their
                 satisfaction with different digital communication tools
                 used for e-learning. They showed low satisfaction with
                 the pedagogical platform and a positive reaction to the
                 e-communication tools (messengers, social media, short
                 surveys, video conferences, etc.). The qualitative
                 responses helped to better understand the real problems
                 of the cognitive process and the triple structure of
                 intellectual production during e-learning, including
                 interest in the intellectual outcome, the need for
                 emotional and motivational elements of cooperation and
                 competition between students, and smooth behavioral
                 enrichment, which requires special efforts from
                 students and their leading from teachers. The main
                 conclusion concerns a practical decision to continue
                 the implementation of the educational program in the
                 form of an online course with the use of the mixed
                 digital communication tools of social media,
                 messengers, and video conferences, which most likely
                 meets the expectations and capabilities of students.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue E-Learning and Technology Enhanced
                 Learning.",
}

@Article{Duan:2021:IAM,
  author =       "Qiang Duan",
  title =        "Intelligent and Autonomous Management in Cloud-Native
                 Future Networks --- a Survey on Related Standards from
                 an Architectural Perspective",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "42",
  day =          "05",
  month =        feb,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020042",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/42",
  abstract =     "Cloud-native network design, which leverages network
                 virtualization and softwarization together with the
                 service-oriented architectural principle, is
                 transforming communication networks to a versatile
                 platform for converged network-cloud/edge service
                 provisioning. Intelligent and autonomous management is
                 one of the most challenging issues in cloud-native
                 future networks, and a wide range of machine learning
                 (ML)-based technologies have been proposed for
                 addressing different aspects of the management
                 challenge. It becomes critical that the various
                 management technologies are applied on the foundation
                 of a consistent architectural framework with a holistic
                 vision. This calls for standardization of new
                 management architecture that supports seamless the
                 integration of diverse ML-based technologies in
                 cloud-native future networks. The goal of this paper is
                 to provide a big picture of the recent developments of
                 architectural frameworks for intelligent and autonomous
                 management for future networks. The paper surveys the
                 latest progress in the standardization of network
                 management architectures including works by 3GPP, ETSI,
                 and ITU-Tand analyzes how cloud-native network design
                 may facilitate the architecture development for
                 addressing management challenges. Open issues related
                 to intelligent and autonomous management in
                 cloud-native future networks are also discussed in this
                 paper to identify some possible directions for future
                 research and development.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Cloud-Native Applications and
                 Services.",
}

@Article{Delgado:2021:RPS,
  author =       "Gabriela Torres Delgado and Neil Hern{\'a}ndez-Gress",
  title =        "Research Professors' Self-Assessment of Competencies",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "41",
  day =          "04",
  month =        feb,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020041",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/41",
  abstract =     "Research professors develop scientific products that
                 impact and benefit society, but their competencies in
                 doing so are rarely evaluated. Therefore, by employing
                 a mixed two-stage sequential design, this study
                 developed a self-assessment model of research
                 professors' competencies with four domains, seven
                 competencies, and 30 competency elements. Next, we
                 conducted descriptive statistical analysis of those
                 elements. In the first year, 320 respondents rated
                 themselves on four levels: initial, basic, autonomous,
                 and consolidated. In the assessment model's second
                 year, we compared 30 respondents' results with those of
                 their initial self-assessment. The main developmental
                 challenge was Originality and Innovation, which
                 remained at the initial level. Both Training of
                 Researchers and Transformation of Society were at the
                 basic level, and Digital Competency was at the
                 autonomous level. Both Teaching Competence and Ethics
                 and Citizenship attained the consolidated level. This
                 information helps establish priorities for accelerating
                 researchers' training and the quality of their
                 research.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Education 4.0 in the Transformation of
                 Universities: Educational and Research Applications.",
}

@Article{Sun:2021:AGA,
  author =       "Tianfang Sun and Pin Yang and Mengming Li and Shan
                 Liao",
  title =        "An Automatic Generation Approach of the Cyber Threat
                 Intelligence Records Based on Multi-Source Information
                 Fusion",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "40",
  day =          "02",
  month =        feb,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020040",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/40",
  abstract =     "With the progressive deterioration of cyber threats,
                 collecting cyber threat intelligence (CTI) from
                 open-source threat intelligence publishing platforms
                 (OSTIPs) can help information security personnel grasp
                 public opinions with specific pertinence, handle
                 emergency events, and even confront the advanced
                 persistent threats. However, due to the explosive
                 growth of information shared on multi-type OSTIPs,
                 manually collecting the CTI has had low efficiency.
                 Articles published on the OSTIPs are unstructured,
                 leading to an imperative challenge to automatically
                 gather CTI records only through natural language
                 processing (NLP) methods. To remedy these limitations,
                 this paper proposes an automatic approach to generate
                 the CTI records based on multi-type OSTIPs (GCO),
                 combing the NLP method, machine learning method, and
                 cybersecurity threat intelligence knowledge. The
                 experiment results demonstrate that the proposed GCO
                 outperformed some state-of-the-art approaches on
                 article classification and cybersecurity intelligence
                 details (CSIs) extraction, with accuracy, precision,
                 and recall all over 93\%; finally, the generated
                 records in the Neo4j-based CTI database can help reveal
                 malicious threat groups.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Feature Papers for Future
                 Internet---Cybersecurity Section.",
}

@Article{Ulven:2021:SRC,
  author =       "Joachim Bj{\o}rge Ulven and Gaute Wangen",
  title =        "A Systematic Review of Cybersecurity Risks in Higher
                 Education",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "39",
  day =          "02",
  month =        feb,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020039",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/39",
  abstract =     "The demands for information security in higher
                 education will continue to increase. Serious data
                 breaches have occurred already and are likely to happen
                 again without proper risk management. This paper
                 applies the Comprehensive Literature Review (CLR) Model
                 to synthesize research within cybersecurity risk by
                 reviewing existing literature of known assets, threat
                 events, threat actors, and vulnerabilities in higher
                 education. The review included published studies from
                 the last twelve years and aims to expand our
                 understanding of cybersecurity's critical risk areas.
                 The primary finding was that empirical research on
                 cybersecurity risks in higher education is scarce, and
                 there are large gaps in the literature. Despite this
                 issue, our analysis found a high level of agreement
                 regarding cybersecurity issues among the reviewed
                 sources. This paper synthesizes an overview of
                 mission-critical assets, everyday threat events,
                 proposes a generic threat model, and summarizes common
                 cybersecurity vulnerabilities. This report concludes
                 nine strategic cyber risks with descriptions of
                 frequencies from the compiled dataset and consequence
                 descriptions. The results will serve as input for
                 security practitioners in higher education, and the
                 research contains multiple paths for future work. It
                 will serve as a starting point for security researchers
                 in the sector.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Feature Papers for Future
                 Internet---Cybersecurity Section.",
}

@Article{Xu:2021:AWM,
  author =       "Yao Xu and Qin Yu",
  title =        "Adaptive Weighted Multi-Level Fusion of Multi-Scale
                 Features: a New Approach to Pedestrian Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "38",
  day =          "02",
  month =        feb,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020038",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/38",
  abstract =     "Great achievements have been made in pedestrian
                 detection through deep learning. For detectors based on
                 deep learning, making better use of features has become
                 the key to their detection effect. While current
                 pedestrian detectors have made efforts in feature
                 utilization to improve their detection performance, the
                 feature utilization is still inadequate. To solve the
                 problem of inadequate feature utilization, we proposed
                 the Multi-Level Feature Fusion Module (MFFM) and its
                 Multi-Scale Feature Fusion Unit (MFFU) sub-module,
                 which connect feature maps of the same scale and
                 different scales by using horizontal and vertical
                 connections and shortcut structures. All of these
                 connections are accompanied by weights that can be
                 learned; thus, they can be used as adaptive multi-level
                 and multi-scale feature fusion modules to fuse the best
                 features. Then, we built a complete pedestrian
                 detector, the Adaptive Feature Fusion Detector
                 (AFFDet), which is an anchor-free one-stage pedestrian
                 detector that can make full use of features for
                 detection. As a result, compared with other methods,
                 our method has better performance on the challenging
                 Caltech Pedestrian Detection Benchmark (Caltech) and
                 has quite competitive speed. It is the current
                 state-of-the-art one-stage pedestrian detection
                 method.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Computer Vision, Deep Learning and
                 Machine Learning with Applications.",
}

@Article{Yang:2021:CFB,
  author =       "FengLei Yang and Fei Liu and ShanShan Liu",
  title =        "Collaborative Filtering Based on a Variational
                 {Gaussian} Mixture Model",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "37",
  day =          "01",
  month =        feb,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020037",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/37",
  abstract =     "Collaborative filtering (CF) is a widely used method
                 in recommendation systems. Linear models are still the
                 mainstream of collaborative filtering research methods,
                 but non-linear probabilistic models are beyond the
                 limit of linear model capacity. For example,
                 variational autoencoders (VAEs) have been extensively
                 used in CF, and have achieved excellent results. Aiming
                 at the problem of the prior distribution for the latent
                 codes of VAEs in traditional CF is too simple, which
                 makes the implicit variable representations of users
                 and items too poor. This paper proposes a variational
                 autoencoder that uses a Gaussian mixture model for
                 latent factors distribution for CF, GVAE-CF. On this
                 basis, an optimization function suitable for GVAE-CF is
                 proposed. In our experimental evaluation, we show that
                 the recommendation performance of GVAE-CF outperforms
                 the previously proposed VAE-based models on several
                 popular benchmark datasets in terms of recall and
                 normalized discounted cumulative gain (NDCG), thus
                 proving the effectiveness of the algorithm.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Computer Vision, Deep Learning and
                 Machine Learning with Applications.",
}

@Article{Zhou:2021:HPG,
  author =       "Chao Zhou and Tao Zhang",
  title =        "High Performance Graph Data Imputation on Multiple
                 {GPUs}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "36",
  day =          "31",
  month =        jan,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020036",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/36",
  abstract =     "In real applications, massive data with graph
                 structures are often incomplete due to various
                 restrictions. Therefore, graph data imputation
                 algorithms have been widely used in the fields of
                 social networks, sensor networks, and MRI to solve the
                 graph data completion problem. To keep the data
                 relevant, a data structure is represented by a
                 graph-tensor, in which each matrix is the vertex value
                 of a weighted graph. The convolutional imputation
                 algorithm has been proposed to solve the low-rank
                 graph-tensor completion problem that some data matrices
                 are entirely unobserved. However, this data imputation
                 algorithm has limited application scope because it is
                 compute-intensive and low-performance on CPU. In this
                 paper, we propose a scheme to perform the convolutional
                 imputation algorithm with higher time performance on
                 GPUs (Graphics Processing Units) by exploiting
                 multi-core GPUs of CUDA architecture. We propose
                 optimization strategies to achieve coalesced memory
                 access for graph Fourier transform (GFT) computation
                 and improve the utilization of GPU SM resources for
                 singular value decomposition (SVD) computation.
                 Furthermore, we design a scheme to extend the
                 GPU-optimized implementation to multiple GPUs for
                 large-scale computing. Experimental results show that
                 the GPU implementation is both fast and accurate. On
                 synthetic data of varying sizes, the GPU-optimized
                 implementation running on a single Quadro RTX6000 GPU
                 achieves up to 60.50$ \times $ speedups over the
                 GPU-baseline implementation. The multi-GPU
                 implementation achieves up to 1.81$ \times $ speedups
                 on two GPUs versus the GPU-optimized implementation on
                 a single GPU. On the ego-Facebook dataset, the
                 GPU-optimized implementation achieves up to 77.88$
                 \times $ speedups over the GPU-baseline implementation.
                 Meanwhile, the GPU implementation and the CPU
                 implementation achieve similar, low recovery errors.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Smart System Infrastructure and
                 Applications.",
}

@Article{Delgado:2021:TPC,
  author =       "Francisco Delgado",
  title =        "Teaching Physics for Computer Science Students in
                 Higher Education During the {COVID-19} Pandemic: a
                 Fully {Internet}-Supported Course",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "35",
  day =          "29",
  month =        jan,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020035",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/35",
  abstract =     "The COVID-19 pandemic has modified and diversified the
                 ways that students receive education. During
                 confinements, complex courses integrating previous
                 knowledge must be carefully designed and implemented to
                 effectively replace the elements present in
                 face-to-face learning to improve the students'
                 experience. This work assesses the implementation of a
                 digital-learning physics course for computer science
                 students in a skill-based education program in higher
                 education. The assessment was useful for the
                 institution to evaluate if the digital strategy
                 implemented in the course fulfilled the original
                 premises and objectives. The analyses performed provide
                 useful knowledge of theoretical and operational actions
                 applied in this methodology that could be adapted to
                 similar courses for the younger generations in this
                 university. COVID-19 confinement will continue in
                 Mexico in 2021. This assessment resulted in a positive
                 evaluation of the digital strategy being followed,
                 which can be continued while the contingency lasts.
                 Three teachers came together to design math, physics,
                 and computational sciences content for various sections
                 of a physics course. The analysis was developed and
                 implemented according to an institutional digital
                 delivery model for the COVID-19 pandemic. Elements
                 related to attendance, digital access, performance
                 distribution by gender, activity types, and the course
                 learning sections were considered. The analysis was
                 performed with some techniques found in the literature
                 for small groups, complemented when necessary by
                 standard statistical tests to discern meaningful
                 trends. A primary goal was to assess skill-based
                 learning in the course delivered digitally due to the
                 COVID-19 confinement. Furthermore, additional issues
                 concerning the learning dynamics were searched,
                 reported, and analyzed. Finally, the outcomes of an
                 institutional exit survey collecting students' opinions
                 supported certain observed behaviors. The analysis
                 produced meaningful evidence that the course's
                 skill-based development was well supported by the
                 digital delivery during the confinement. Furthermore,
                 differences in the students' performances in the
                 various course content sections proved statistically
                 significant and are discussed in this work.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Education Responses to Technological
                 Challenges and Their Impact on Classrooms.",
}

@Article{Rodriguez-Breijo:2021:CPO,
  author =       "Vanessa Rodr{\'\i}guez-Breijo and N{\'u}ria Simelio
                 and Pedro Molina-Rodr{\'\i}guez-Navas",
  title =        "{Council Press Offices} as Sources of Political
                 Information: Between Journalism for Accountability and
                 Propaganda",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "34",
  day =          "29",
  month =        jan,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020034",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/34",
  abstract =     "This study uses a qualitative approach to examine what
                 political and technical leaders of municipalities
                 understand transparency and public information to mean,
                 and what role they believe the different subjects
                 involved (government, opposition, and the public)
                 should have. The websites of 605 Spanish councils with
                 more than 100,000 inhabitants were analysed and three
                 focus groups were held with political and technical
                 leaders from a selection of sample councils. The
                 results show that the technical and political leaders
                 of the councils do not have a clear awareness of their
                 function of management accountability or of the need to
                 apply journalistic criteria to the information they
                 publish, defending with nuances the use of propaganda
                 criteria to focus on the actions of the local
                 government, its information, the lack of space
                 dedicated to public debate and the opposition's
                 actions. In relation to accountability and citizen
                 participation, they have a negative view of citizens,
                 who they describe as being disengaged. However, they
                 emphasize that internally it is essential to continue
                 improving in terms of the culture of transparency and
                 the public information they provide citizens.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Guo:2021:CSD,
  author =       "Dongwei Guo and Mengmeng Fu and Hai Li",
  title =        "Cooperation in Social Dilemmas: a Group Game Model
                 with Double-Layer Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "33",
  day =          "27",
  month =        jan,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020033",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/33",
  abstract =     "The combination of complex networks and game theory is
                 one of the most suitable ways to describe the
                 evolutionary laws of various complex systems. In order
                 to explore the evolution of group cooperation in
                 multiple social dilemmas, a model of a group game with
                 a double-layer network is proposed here. Firstly, to
                 simulate a multiplayer game under multiple identities,
                 we combine a double-layer network and public goods
                 game. Secondly, in order to make an individual's
                 strategy selection process more in line with a
                 practical context, a new strategy learning method that
                 incorporates individual attributes is designed here,
                 referred to as a ``public goods game with selection
                 preferences'' (PGG-SP), which makes strategic choices
                 that are more humane and diversified. Finally, a
                 co-evolution mechanism for strategies and topologies is
                 introduced based on the double-layer network, which
                 effectively explains the dynamic game process in real
                 life. To verify the role of multiple double-layer
                 networks with a PGG-SP, four types of double-layer
                 networks are applied in this paper. In addition, the
                 corresponding game results are compared between
                 single-layer, double-layer, static, and dynamic
                 networks. Accordingly, the results show that
                 double-layer networks can facilitate cooperation in
                 group games.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Recupero:2021:TEL,
  author =       "Diego Reforgiato Recupero",
  title =        "Technology Enhanced Learning Using Humanoid Robots",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "32",
  day =          "27",
  month =        jan,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020032",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/32",
  abstract =     "In this paper we present a mixture of technologies
                 tailored for e-learning related to the Deep Learning,
                 Sentiment Analysis, and Semantic Web domains, which we
                 have employed to show four different use cases that we
                 have validated in the field of Human-Robot Interaction.
                 The approach has been designed using Zora, a humanoid
                 robot that can be easily extended with new software
                 behaviors. The goal is to make the robot able to engage
                 users through natural language for different tasks.
                 Using our software the robot can (i) talk to the user
                 and understand their sentiments through a dedicated
                 Semantic Sentiment Analysis engine; (ii) answer to
                 open-dialog natural language utterances by means of a
                 Generative Conversational Agent; (iii) perform action
                 commands leveraging a defined Robot Action ontology and
                 open-dialog natural language utterances; and (iv)
                 detect which objects the user is handing by using
                 convolutional neural networks trained on a huge
                 collection of annotated objects. Each module can be
                 extended with more data and information and the overall
                 architectural design is general, flexible, and scalable
                 and can be expanded with other components, thus
                 enriching the interaction with the human. Different
                 applications within the e-learning domains are
                 foreseen: The robot can either be a trainer and
                 autonomously perform physical actions (e.g., in
                 rehabilitation centers) or it can interact with the
                 users (performing simple tests or even identifying
                 emotions) according to the program developed by the
                 teachers.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue E-Learning and Technology Enhanced
                 Learning.",
}

@Article{Rovira:2021:LBG,
  author =       "Crist{\`o}fol Rovira and Llu{\'\i}s Codina and Carlos
                 Lopezosa",
  title =        "Language Bias in the {Google Scholar} Ranking
                 Algorithm",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "31",
  day =          "27",
  month =        jan,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020031",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/31",
  abstract =     "The visibility of academic articles or conference
                 papers depends on their being easily found in academic
                 search engines, above all in Google Scholar. To enhance
                 this visibility, search engine optimization (SEO) has
                 been applied in recent years to academic search engines
                 in order to optimize documents and, thereby, ensure
                 they are better ranked in search pages (i.e., academic
                 search engine optimization or ASEO). To achieve this
                 degree of optimization, we first need to further our
                 understanding of Google Scholar's relevance ranking
                 algorithm, so that, based on this knowledge, we can
                 highlight or improve those characteristics that
                 academic documents already present and which are taken
                 into account by the algorithm. This study seeks to
                 advance our knowledge in this line of research by
                 determining whether the language in which a document is
                 published is a positioning factor in the Google Scholar
                 relevance ranking algorithm. Here, we employ a reverse
                 engineering research methodology based on a statistical
                 analysis that uses Spearman's correlation coefficient.
                 The results obtained point to a bias in multilingual
                 searches conducted in Google Scholar with documents
                 published in languages other than in English being
                 systematically relegated to positions that make them
                 virtually invisible. This finding has important
                 repercussions, both for conducting searches and for
                 optimizing positioning in Google Scholar, being
                 especially critical for articles on subjects that are
                 expressed in the same way in English and other
                 languages, the case, for example, of trademarks,
                 chemical compounds, industrial products, acronyms,
                 drugs, diseases, etc.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue The Current State of Search Engines and
                 Search Engine Optimization.",
}

@Article{Papamartzivanos:2021:PMC,
  author =       "Dimitrios Papamartzivanos and Sofia Anna Menesidou and
                 Panagiotis Gouvas and Thanassis Giannetsos",
  title =        "A Perfect Match: Converging and Automating Privacy and
                 Security Impact Assessment On-the-Fly",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "30",
  day =          "27",
  month =        jan,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020030",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/30",
  abstract =     "As the upsurge of information and communication
                 technologies has become the foundation of all modern
                 application domains, fueled by the unprecedented amount
                 of data being processed and exchanged, besides security
                 concerns, there are also pressing privacy
                 considerations that come into play. Compounding this
                 issue, there is currently a documented gap between the
                 cybersecurity and privacy risk assessment (RA) avenues,
                 which are treated as distinct management processes and
                 capitalise on rather rigid and make-like approaches. In
                 this paper, we aim to combine the best of both worlds
                 by proposing the APSIA (Automated Privacy and Security
                 Impact Assessment) methodology, which stands for
                 Automated Privacy and Security Impact Assessment. APSIA
                 is powered by the use of interdependency graph models
                 and data processing flows used to create a digital
                 reflection of the cyber-physical environment of an
                 organisation. Along with this model, we present a novel
                 and extensible privacy risk scoring system for
                 quantifying the privacy impact triggered by the
                 identified vulnerabilities of the ICT infrastructure of
                 an organisation. We provide a prototype implementation
                 and demonstrate its applicability and efficacy through
                 a specific case study in the context of a heavily
                 regulated sector (i.e., assistive healthcare domain)
                 where strict security and privacy considerations are
                 not only expected but mandated so as to better showcase
                 the beneficial characteristics of APSIA. Our approach
                 can complement any existing security-based RA tool and
                 provide the means to conduct an enhanced, dynamic and
                 generic assessment as an integral part of an iterative
                 and unified risk assessment process on-the-fly. Based
                 on our findings, we posit open issues and challenges,
                 and discuss possible ways to address them, so that such
                 holistic security and privacy mechanisms can reach
                 their full potential towards solving this conundrum.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Special Issue Information and Future Internet
                 Security, Trust and Privacy.",
}

@Article{Basile:2021:HDE,
  author =       "Valerio Basile and Francesco Cauteruccio and Giorgio
                 Terracina",
  title =        "How Dramatic Events Can Affect Emotionality in Social
                 Posting: The Impact of {COVID-19} on {Reddit}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "29",
  day =          "27",
  month =        jan,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020029",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/29",
  abstract =     "The COVID-19 outbreak impacted almost all the aspects
                 of ordinary life. In this context, social networks
                 quickly started playing the role of a sounding board
                 for the content produced by people. Studying how
                 dramatic events affect the way people interact with
                 each other and react to poorly known situations is
                 recognized as a relevant research task. Since
                 automatically identifying country-based COVID-19 social
                 posts on generalized social networks, like Twitter and
                 Facebook, is a difficult task, in this work we
                 concentrate on Reddit megathreads, which provide a
                 unique opportunity to study focused reactions of people
                 by both topic and country. We analyze specific
                 reactions and we compare them with a ``normal'' period,
                 not affected by the pandemic; in particular, we
                 consider structural variations in social posting
                 behavior, emotional reactions under the Plutchik model
                 of basic emotions, and emotional reactions under
                 unconventional emotions, such as skepticism,
                 particularly relevant in the COVID-19 context.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Techno-Social Smart Systems.",
}

@Article{FIEO:2021:ARF,
  author =       "{Future Internet Editorial Office}",
  title =        "Acknowledgment to Reviewers of {{\booktitle{Future
                 Internet}}} in 2020",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "28",
  day =          "24",
  month =        jan,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020028",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/28",
  abstract =     "The COVID-19 outbreak impacted almost all the aspects
                 of ordinary life. In this context, social networks
                 quickly started playing the role of a sounding board
                 for the content produced by people. Studying how
                 dramatic events affect the way people interact with
                 each other and react to poorly known situations is
                 recognized as a relevant research task. Since
                 automatically identifying country-based COVID-19 social
                 posts on generalized social networks, like Twitter and
                 Facebook, is a difficult task, in this work we
                 concentrate on Reddit megathreads, which provide a
                 unique opportunity to study focused reactions of people
                 by both topic and country. We analyze specific
                 reactions and we compare them with a ``normal'' period,
                 not affected by the pandemic; in particular, we
                 consider structural variations in social posting
                 behavior, emotional reactions under the Plutchik model
                 of basic emotions, and emotional reactions under
                 unconventional emotions, such as skepticism,
                 particularly relevant in the COVID-19 context.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hao:2021:EIS,
  author =       "Chuanyan Hao and Anqi Zheng and Yuqi Wang and Bo
                 Jiang",
  title =        "Experiment Information System Based on an Online
                 Virtual Laboratory",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "27",
  day =          "24",
  month =        jan,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020027",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/27",
  abstract =     "In the information age, MOOCs (Massive Open Online
                 Courses), micro-classes, flipping classroom, and other
                 blended teaching scenes have improved students learning
                 outcomes. However, incorporating technologies into
                 experimental courses, especially electronic and
                 electrical experiments, has its own characteristics and
                 difficulties. The focus of this paper is to introduce
                 virtual technology into an electronic circuit
                 experiment course and to explore its teaching strategy,
                 thereby realizing the informatization of experiment
                 teaching. First, this paper explores the design
                 concepts and implementation details of the digital
                 circuit virtual laboratory, which is then developed
                 based on previous literature and a prequestionnaire to
                 users. Second, the informatization process of the
                 experiment learning model based on traditional custom
                 lab benches is shown through a blended learning scheme
                 that integrates the online virtual laboratory. Finally,
                 the experiment information system is verified and
                 analyzed with a control group experiment and
                 questionnaires. The blended program turned out to be an
                 effective teaching model to complement the deficiencies
                 in existing physical laboratories. The research
                 conclusions show that the virtual experiment system
                 provides students with a rich, efficient, and expansive
                 experimental experience, in particular, the
                 flexibility, repeatability, and visual appeal of a
                 virtual platform could promote the development of
                 students' abilities in active learning, reflective
                 thinking, and creativity.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
  remark =       "Section Smart System Infrastructure and
                 Applications.",
}

@Article{Riana:2021:IFH,
  author =       "Dwiza Riana and Achmad Nizar Hidayanto and Sri
                 Hadianti and Darmawan Napitupulu",
  title =        "Integrative Factors of E-Health Laboratory Adoption: a
                 Case of {Indonesia}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "2",
  pages =        "26",
  day =          "24",
  month =        jan,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13020026",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 26 10:54:58 MST 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/2/26",
  abstract =     "Around the world, the adoption of digital health
                 applications is growing very fast. The use of e-health
                 laboratory systems is increasing while research on the
                 factors that impact users to use e-health laboratory
                 systems in Indonesia has not been done much. The
                 objective of this study is to analyze the behavioral
                 factors of e-health laboratory users. This study
                 includes a survey conducted on Indonesian users, and
                 data analysis was carried out thoroughly. Based on the
                 Technology Acceptance Model, this research framework
                 explores a combination of variables consisting of
                 task-driven, technology-driven, human-driven, and
                 adoption variables to form the model proposed in this
                 study. This model was verified using the Structural
                 Equation Modeling (SEM) method for factor analysis,
                 path analysis, and regression. A total of 163
                 respondents were collected to evaluate this research
                 model empirically and the level of this study were
                 individuals. These three problems are all essential in
                 affecting usage intentions in adopting an e-health
                 laboratory system. Specifically, task technology fit,
                 information quality, and accessibility show a direct
                 effect on both perceived usefulness and perceived ease
                 of use factors perceived by the user, and have an
                 indirect influence on the adoption of an e-health
                 laboratory system through these two factors. The design
                 of an online laboratory system affects perceived ease
                 of use and personal innovativeness factors affect the
                 perceived usefulness that users feel when adopting a
                 laboratory system, while task technology fit and
                 personal innovativeness factors do not affect the
                 perceived ease of use. However, overall technology
                 characteristic and perceived usefulness followed by
                 design are the main predictors of adopting an e-health
                 laboratory system on e-health systems in Indonesia.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chetty:2021:VNF,
  author =       "Swarna Bindu Chetty and Hamed Ahmadi and Sachin Sharma
                 and Avishek Nag",
  title =        "Virtual Network Function Embedding under Nodal Outage
                 Using Deep {Q}-Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "3",
  pages =        "82",
  day =          "23",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13030082",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 26 12:47:18 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/3/82",
  abstract =     "With the emergence of various types of applications
                 such as delay-sensitive applications, future
                 communication networks are expected to be increasingly
                 complex and dynamic. Network Function Virtualization
                 (NFV) provides the necessary support towards efficient
                 management of such complex networks, by virtualizing
                 network functions and placing them on shared commodity
                 servers. However, one of the critical issues in NFV is
                 the resource allocation for the highly complex
                 services; moreover, this problem is classified as an
                 NP-Hard problem. To solve this problem, our work
                 investigates the potential of Deep Reinforcement
                 Learning (DRL) as a swift yet accurate approach (as
                 compared to integer linear programming) for deploying
                 Virtualized Network Functions (VNFs) under several
                 Quality-of-Service (QoS) constraints such as latency,
                 memory, CPU, and failure recovery requirements. More
                 importantly, the failure recovery requirements are
                 focused on the node-outage problem where outage can be
                 either due to a disaster or unavailability of network
                 topology information (e.g., due to proprietary and
                 ownership issues). In DRL, we adopt a Deep Q-Learning
                 (DQL) based algorithm where the primary network
                 estimates the action-value function Q, as well as the
                 predicted Q, highly causing divergence in Q-value's
                 updates. This divergence increases for the larger-scale
                 action and state-space causing inconsistency in
                 learning, resulting in an inaccurate output. Thus, to
                 overcome this divergence, our work has adopted a
                 well-known approach, i.e., introducing Target Neural
                 Networks and Experience Replay algorithms in DQL. The
                 constructed model is simulated for two real network
                 topologies-Netrail Topology and BtEurope Topology-with
                 various capacities of the nodes (e.g., CPU core, VNFs
                 per Core), links (e.g., bandwidth and latency), several
                 VNF Forwarding Graph (VNF-FG) complexities, and
                 different degrees of the nodal outage from 0\% to 50\%.
                 We can conclude from our work that, with the increase
                 in network density or nodal capacity or VNF-FG's
                 complexity, the model took extremely high computation
                 time to execute the desirable results. Moreover, with
                 the rise in complexity of the VNF-FG, the resources
                 decline much faster. In terms of the nodal outage, our
                 model provided almost 70-90\% Service Acceptance Rate
                 (SAR) even with a 50\% nodal outage for certain
                 combinations of scenarios.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Naudts:2021:VCM,
  author =       "Dries Naudts and Vasilis Maglogiannis and Seilendria
                 Hadiwardoyo and Daniel van den Akker and Simon Vanneste
                 and Siegfried Mercelis and Peter Hellinckx and Bart
                 Lannoo and Johann Marquez-Barja and Ingrid Moerman",
  title =        "Vehicular Communication Management Framework: a
                 Flexible Hybrid Connectivity Platform for {CCAM}
                 Services",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "3",
  pages =        "81",
  day =          "22",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13030081",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 26 12:47:18 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/3/81",
  abstract =     "In the upcoming decade and beyond, the Cooperative,
                 Connected and Automated Mobility (CCAM) initiative will
                 play a huge role in increasing road safety, traffic
                 efficiency and comfort of driving in Europe. While
                 several individual vehicular wireless communication
                 technologies exist, there is still a lack of real
                 flexible and modular platforms that can support the
                 need for hybrid communication. In this paper, we
                 propose a novel vehicular communication management
                 framework (CAMINO), which incorporates flexible support
                 for both short-range direct and long-range cellular
                 technologies and offers built-in Cooperative
                 Intelligent Transport Systems' (C-ITS) services for
                 experimental validation in real-life settings.
                 Moreover, integration with vehicle and infrastructure
                 sensors/actuators and external services is enabled
                 using a Distributed Uniform Streaming (DUST) framework.
                 The framework is implemented and evaluated in the Smart
                 Highway test site for two targeted use cases, proofing
                 the functional operation in realistic environments. The
                 flexibility and the modular architecture of the hybrid
                 CAMINO framework offers valuable research potential in
                 the field of vehicular communications and CCAM services
                 and can enable cross-technology vehicular
                 connectivity.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Vrysis:2021:WIA,
  author =       "Lazaros Vrysis and Nikolaos Vryzas and Rigas Kotsakis
                 and Theodora Saridou and Maria Matsiola and Andreas
                 Veglis and Carlos Arcila-Calder{\'o}n and Charalampos
                 Dimoulas",
  title =        "A {Web} Interface for Analyzing Hate Speech",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "3",
  pages =        "80",
  day =          "22",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13030080",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 26 12:47:18 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/3/80",
  abstract =     "Social media services make it possible for an
                 increasing number of people to express their opinion
                 publicly. In this context, large amounts of hateful
                 comments are published daily. The PHARM project aims at
                 monitoring and modeling hate speech against refugees
                 and migrants in Greece, Italy, and Spain. In this
                 direction, a web interface for the creation and the
                 query of a multi-source database containing hate
                 speech-related content is implemented and evaluated.
                 The selected sources include Twitter, YouTube, and
                 Facebook comments and posts, as well as comments and
                 articles from a selected list of websites. The
                 interface allows users to search in the existing
                 database, scrape social media using keywords, annotate
                 records through a dedicated platform and contribute new
                 content to the database. Furthermore, the functionality
                 for hate speech detection and sentiment analysis of
                 texts is provided, making use of novel methods and
                 machine learning models. The interface can be accessed
                 online with a graphical user interface compatible with
                 modern internet browsers. For the evaluation of the
                 interface, a multifactor questionnaire was formulated,
                 targeting to record the users' opinions about the web
                 interface and the corresponding functionality.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Safavi:2021:RPR,
  author =       "Sadaf Safavi and Mehrdad Jalali",
  title =        "{RecPOID}: {POI} Recommendation with Friendship Aware
                 and Deep {CNN}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "3",
  pages =        "79",
  day =          "22",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13030079",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 26 12:47:18 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/3/79",
  abstract =     "In location-based social networks (LBSNs), exploit
                 several key features of points-of-interest (POIs) and
                 users on precise POI recommendation be significant. In
                 this work, a novel POI recommendation pipeline based on
                 the convolutional neural network named RecPOID is
                 proposed, which can recommend an accurate sequence of
                 top-k POIs and considers only the effect of the most
                 similar pattern friendship rather than all user's
                 friendship. We use the fuzzy c-mean clustering method
                 to find the similarity. Temporal and spatial features
                 of similar friends are fed to our Deep CNN model. The
                 10-layer convolutional neural network can predict
                 longitude and latitude and the Id of the next proper
                 locations; after that, based on the shortest time
                 distance from a similar pattern's friendship, select
                 the smallest distance locations. The proposed structure
                 uses six features, including user's ID, month, day,
                 hour, minute, and second of visiting time by each user
                 as inputs. RecPOID based on two accessible LBSNs
                 datasets is evaluated. Experimental outcomes illustrate
                 considering most similar friendship could improve the
                 accuracy of recommendations and the proposed RecPOID
                 for POI recommendation outperforms state-of-the-art
                 approaches.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2021:ATF,
  author =       "Chuanhong Li and Lei Song and Xuewen Zeng",
  title =        "An Adaptive Throughput-First Packet Scheduling
                 Algorithm for {DPDK}-Based Packet Processing Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "3",
  pages =        "78",
  day =          "19",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13030078",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 26 12:47:18 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/3/78",
  abstract =     "The continuous increase in network traffic has sharply
                 increased the demand for high-performance packet
                 processing systems. For a high-performance packet
                 processing system based on multi-core processors, the
                 packet scheduling algorithm is critical because of the
                 significant role it plays in load distribution, which
                 is related to system throughput, attracting intensive
                 research attention. However, it is not an easy task
                 since the canonical flow-level packet scheduling
                 algorithm is vulnerable to traffic locality, while the
                 packet-level packet scheduling algorithm fails to
                 maintain cache affinity. In this paper, we propose an
                 adaptive throughput-first packet scheduling algorithm
                 for DPDK-based packet processing systems. Combined with
                 the feature of DPDK burst-oriented packet receiving and
                 transmitting, we propose using Subflow as the
                 scheduling unit and the adjustment unit making the
                 proposed algorithm not only maintain the advantages of
                 flow-level packet scheduling algorithms when the
                 adjustment does not happen but also avoid packet loss
                 as much as possible when the target core may be
                 overloaded Experimental results show that the proposed
                 method outperforms Round-Robin, HRW (High Random
                 Weight), and CRC32 on system throughput and packet loss
                 rate.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Khrais:2021:RMA,
  author =       "Laith T. Khrais and Abdullah M. Alghamdi",
  title =        "The Role of Mobile Application Acceptance in Shaping
                 E-Customer Service",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "3",
  pages =        "77",
  day =          "19",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13030077",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 26 12:47:18 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/3/77",
  abstract =     "Most retailers are integrating their practices with
                 modern technologies to enhance the effectiveness of
                 their operations. The adoption of technology aims to
                 enable businesses to accurately meet customer needs and
                 expectations. This study focused on examining the role
                 of mobile application (app) acceptance in shaping
                 customer electronic experience. A mixed method was
                 adopted, in which qualitative data were collected using
                 interviews, and quantitative data were gathered using
                 the questionnaires. The results indicate that mobile
                 app acceptance contributes to a positive customer
                 experience while purchasing products and services from
                 online retailers. Mobile apps are associated with
                 benefits, such as convenience, ease of use, and the
                 ability to access various products and services. With
                 the rapid development in technology, e-commerce
                 retailers should leverage such innovations to meet
                 customer needs.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lotito:2021:RAS,
  author =       "Quintino Francesco Lotito and Davide Zanella and Paolo
                 Casari",
  title =        "Realistic Aspects of Simulation Models for Fake News
                 Epidemics over Social Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "3",
  pages =        "76",
  day =          "17",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13030076",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 26 12:47:18 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/3/76",
  abstract =     "The pervasiveness of online social networks has
                 reshaped the way people access information. Online
                 social networks make it common for users to inform
                 themselves online and share news among their peers, but
                 also favor the spreading of both reliable and fake news
                 alike. Because fake news may have a profound impact on
                 the society at large, realistically simulating their
                 spreading process helps evaluate the most effective
                 countermeasures to adopt. It is customary to model the
                 spreading of fake news via the same epidemic models
                 used for common diseases; however, these models often
                 miss concepts and dynamics that are peculiar to fake
                 news spreading. In this paper, we fill this gap by
                 enriching typical epidemic models for fake news
                 spreading with network topologies and dynamics that are
                 typical of realistic social networks. Specifically, we
                 introduce agents with the role of influencers and bots
                 in the model and consider the effects of dynamical
                 network access patterns, time-varying engagement, and
                 different degrees of trust in the sources of
                 circulating information. These factors concur with
                 making the simulations more realistic. Among other
                 results, we show that influencers that share fake news
                 help the spreading process reach nodes that would
                 otherwise remain unaffected. Moreover, we emphasize
                 that bots dramatically speed up the spreading process
                 and that time-varying engagement and network access
                 change the effectiveness of fake news spreading.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhao:2021:DPP,
  author =       "Yuexuan Zhao and Jing Huang",
  title =        "{Dirichlet} Process Prior for {Student}'s $t$ Graph
                 Variational Autoencoders",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "3",
  pages =        "75",
  day =          "16",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13030075",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 26 12:47:18 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/3/75",
  abstract =     "Graph variational auto-encoder (GVAE) is a model that
                 combines neural networks and Bayes methods, capable of
                 deeper exploring the influential latent features of
                 graph reconstruction. However, several pieces of
                 research based on GVAE employ a plain prior
                 distribution for latent variables, for instance,
                 standard normal distribution (N(0,1)). Although this
                 kind of simple distribution has the advantage of
                 convenient calculation, it will also make latent
                 variables contain relatively little helpful
                 information. The lack of adequate expression of nodes
                 will inevitably affect the process of generating
                 graphs, which will eventually lead to the discovery of
                 only external relations and the neglect of some complex
                 internal correlations. In this paper, we present a
                 novel prior distribution for GVAE, called Dirichlet
                 process (DP) construction for Student's t (St)
                 distribution. The DP allows the latent variables to
                 adapt their complexity during learning and then
                 cooperates with heavy-tailed St distribution to
                 approach sufficient node representation. Experimental
                 results show that this method can achieve a relatively
                 better performance against the baselines.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hernandez-Orellana:2021:CDI,
  author =       "Marisol Hern{\'a}ndez-Orellana and Adolfina
                 P{\'e}rez-Garcias and {\'A}ngel Roco-Videla",
  title =        "Characterization of the Digital Identity of {Chilean}
                 University Students Considering Their Personal Learning
                 Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "3",
  pages =        "74",
  day =          "16",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13030074",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 26 12:47:18 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/3/74",
  abstract =     "At present, our online activity is almost constant,
                 either producing information or consuming it, both for
                 the social and academic fields. The spaces in which
                 people move and travel every day, innocently divided
                 between the face-to-face and the virtual, affect the
                 way we communicate and perceive ourselves. In this
                 document, a characterization of the academic digital
                 identity of Chilean university students is proposed and
                 an invitation to teachers to redefine learning spaces
                 is made, allowing integrating all those technological
                 tools that the student actually uses. This study was
                 developed within the logic of pragmatism based on mixed
                 methodology, non-experimental design, and a
                 descriptive-quantitative cross-sectional approach. A
                 non-probabilistic sample was made up of 509 students,
                 who participated voluntarily with an online
                 questionnaire. The Stata Version-14 program was used,
                 applying the Mann-Whitney-Wilcoxon and Kruskal-Wallis U
                 tests. To develop characterizations, a conglomerate
                 analysis was performed with a hierarchical dissociative
                 method. In general, Chilean university students are
                 highly truthful on the Internet without making
                 significant differences between face-to-face and
                 digital interactions, with low awareness of their ID,
                 being easily recognizable on the Web. Regarding their
                 educational process, they manage it with
                 analogical/face-to-face mixing formal and informal
                 technological tools to optimize their learning process.
                 These students manifest a hybrid academic digital
                 identity, without gender difference in the deployment
                 of their PLEs, but maintaining stereotypical gender
                 behaviors in the construction of their digital identity
                 on the Web, which shows a human-technological
                 development similar to that of young Asians and
                 Europeans.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhou:2021:DMP,
  author =       "Xingchen Zhou and Ming Xu and Yiming Wu and Ning
                 Zheng",
  title =        "Deep Model Poisoning Attack on Federated Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "3",
  pages =        "73",
  day =          "14",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13030073",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 26 12:47:18 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/3/73",
  abstract =     "Federated learning is a novel distributed learning
                 framework, which enables thousands of participants to
                 collaboratively construct a deep learning model. In
                 order to protect confidentiality of the training data,
                 the shared information between server and participants
                 are only limited to model parameters. However, this
                 setting is vulnerable to model poisoning attack, since
                 the participants have permission to modify the model
                 parameters. In this paper, we perform systematic
                 investigation for such threats in federated learning
                 and propose a novel optimization-based model poisoning
                 attack. Different from existing methods, we primarily
                 focus on the effectiveness, persistence and stealth of
                 attacks. Numerical experiments demonstrate that the
                 proposed method can not only achieve high attack
                 success rate, but it is also stealthy enough to bypass
                 two existing defense methods.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chen:2021:PRIa,
  author =       "Shengbo Chen and Hongchang Zhang and Zhou Lei",
  title =        "Person Re-Identification Based on Attention Mechanism
                 and Context Information Fusion",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "3",
  pages =        "72",
  day =          "13",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13030072",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 26 12:47:18 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/3/72",
  abstract =     "Person re-identification (ReID) plays a significant
                 role in video surveillance analysis. In the real world,
                 due to illumination, occlusion, and deformation,
                 pedestrian features extraction is the key to person
                 ReID. Considering the shortcomings of existing methods
                 in pedestrian features extraction, a method based on
                 attention mechanism and context information fusion is
                 proposed. A lightweight attention module is introduced
                 into ResNet50 backbone network equipped with a small
                 number of network parameters, which enhance the
                 significant characteristics of person and suppress
                 irrelevant information. Aiming at the problem of person
                 context information loss due to the over depth of the
                 network, a context information fusion module is
                 designed to sample the shallow feature map of
                 pedestrians and cascade with the high-level feature
                 map. In order to improve the robustness, the model is
                 trained by combining the loss of margin sample mining
                 with the loss function of cross entropy. Experiments
                 are carried out on datasets Market1501 and
                 DukeMTMC-reID, our method achieves rank-1 accuracy of
                 95.9\% on the Market1501 dataset, and 90.1\% on the
                 DukeMTMC-reID dataset, outperforming the current
                 mainstream method in case of only using global
                 feature.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wu:2021:TLM,
  author =       "Pin Wu and Rukang Zhu and Zhidan Lei",
  title =        "Transfer Learning for Multi-Premise Entailment with
                 Relationship Processing Module",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "3",
  pages =        "71",
  day =          "13",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13030071",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 26 12:47:18 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/3/71",
  abstract =     "Using the single premise entailment (SPE) model to
                 accomplish the multi-premise entailment (MPE) task can
                 alleviate the problem that the neural network cannot be
                 effectively trained due to the lack of labeled
                 multi-premise training data. Moreover, the abundant
                 judgment methods for the relationship between sentence
                 pairs can also be applied in this task. However, the
                 single-premise pre-trained model does not have a
                 structure for processing multi-premise relationships,
                 and this structure is a crucial technique for solving
                 MPE problems. This paper proposes adding a
                 multi-premise relationship processing module based on
                 not changing the structure of the pre-trained model to
                 compensate for this deficiency. Moreover, we proposed a
                 three-step training method combining this module, which
                 ensures that the module focuses on dealing with the
                 multi-premise relationship during matching, thus
                 applying the single-premise model to multi-premise
                 tasks. Besides, this paper also proposes a specific
                 structure of the relationship processing module, i.e.,
                 we call it the attention-backtracking mechanism.
                 Experiments show that this structure can fully consider
                 the context of multi-premise, and the structure
                 combined with the three-step training can achieve
                 better accuracy on the MPE test set than other transfer
                 methods.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yu:2021:JOE,
  author =       "Zhiyan Yu and Gaochao Xu and Yang Li and Peng Liu and
                 Long Li",
  title =        "Joint Offloading and Energy Harvesting Design in
                 Multiple Time Blocks for {FDMA} Based Wireless Powered
                 {MEC}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "3",
  pages =        "70",
  day =          "12",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13030070",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 26 12:47:18 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/3/70",
  abstract =     "The combination of mobile edge computing (MEC) and
                 wireless power transfer (WPT) is recognized as a
                 promising technology to solve the problem of limited
                 battery capacities and insufficient computation
                 capabilities of mobile devices. This technology can
                 transfer energy to users by radio frequency (RF) in
                 wireless powered mobile edge computing. The user
                 converts the harvested energy, stores it in the
                 battery, and utilizes the harvested energy to execute
                 corresponding local computing and offloading tasks.
                 This paper adopts the Frequency Division Multiple
                 Access (FDMA) technique to achieve task offloading from
                 multiple mobile devices to the MEC server
                 simultaneously. Our objective is to study multiuser
                 dynamic joint optimization of computation and wireless
                 resource allocation under multiple time blocks to solve
                 the problem of maximizing residual energy. To this end,
                 we formalize it as a nonconvex problem that jointly
                 optimizes the number of offloaded bits, energy
                 harvesting time, and transmission bandwidth. We adopt
                 convex optimization technology, combine with
                 Karush--Kuhn--Tucker (KKT) conditions, and finally
                 transform the problem into a univariate constrained
                 convex optimization problem. Furthermore, to solve the
                 problem, we propose a combined method of Bisection
                 method and sequential unconstrained minimization based
                 on Reformulation-Linearization Technique (RLT).
                 Numerical results demonstrate that the performance of
                 our joint optimization method outperforms other
                 benchmark schemes for the residual energy maximization
                 problem. Besides, the algorithm can maximize the
                 residual energy, reduce the computation complexity, and
                 improve computation efficiency.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lin:2021:ETN,
  author =       "Yi-Bing Lin and Chien-Chao Tseng and Ming-Hung Wang",
  title =        "Effects of Transport Network Slicing on {5G}
                 Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "3",
  pages =        "69",
  day =          "11",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13030069",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 26 12:47:18 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/3/69",
  abstract =     "Network slicing is considered a key technology in
                 enabling the underlying 5G mobile network
                 infrastructure to meet diverse service requirements. In
                 this article, we demonstrate how transport network
                 slicing accommodates the various network service
                 requirements of Massive IoT (MIoT), Critical IoT
                 (CIoT), and Mobile Broadband (MBB) applications. Given
                 that most of the research conducted previously to
                 measure 5G network slicing is done through simulations,
                 we utilized SimTalk, an IoT application traffic
                 emulator, to emulate large amounts of realistic traffic
                 patterns in order to study the effects of transport
                 network slicing on IoT and MBB applications.
                 Furthermore, we developed several MIoT, CIoT, and MBB
                 applications that operate sustainably on several
                 campuses and directed both real and emulated traffic
                 into a Programming Protocol-Independent Packet
                 Processors (P4)-based 5G testbed. We then examined the
                 performance in terms of throughput, packet loss, and
                 latency. Our study indicates that applications with
                 different traffic characteristics need different
                 corresponding Committed Information Rate (CIR) ratios.
                 The CIR ratio is the CIR setting for a P4 meter in
                 physical switch hardware over the aggregated data rate
                 of applications of the same type. A low CIR ratio
                 adversely affects the application's performance because
                 P4 switches will dispatch application packets to the
                 low-priority queue if the packet arrival rate exceeds
                 the CIR setting for the same type of applications. In
                 our testbed, both exemplar MBB applications required a
                 CIR ratio of 140\% to achieve, respectively, a near
                 100\% throughput percentage with a 0.0035\% loss rate
                 and an approximate 100\% throughput percentage with a
                 0.0017\% loss rate. However, the exemplar CIoT and MIoT
                 applications required a CIR ratio of 120\% and 100\%,
                 respectively, to reach a 100\% throughput percentage
                 without any packet loss. With the proper CIR settings
                 for the P4 meters, the proposed transport network
                 slicing mechanism can enforce the committed rates and
                 fulfill the latency and reliability requirements for 5G
                 MIoT, CIoT, and MBB applications in both TCP and UDP.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Flanagan:2021:IMC,
  author =       "Steven Knowles Flanagan and Zuoyin Tang and Jianhua He
                 and Irfan Yusoff",
  title =        "Investigating and Modeling of Cooperative
                 Vehicle-to-Vehicle Safety Stopping Distance",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "3",
  pages =        "68",
  day =          "10",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13030068",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 26 12:47:18 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/3/68",
  abstract =     "Dedicated Short-Range Communication (DSRC) or IEEE
                 802.11p/OCB (Out of the Context of a Base-station) is
                 widely considered to be a primary technology for
                 Vehicle-to-Vehicle (V2V) communication, and it is aimed
                 toward increasing the safety of users on the road by
                 sharing information between one another. The
                 requirements of DSRC are to maintain real-time
                 communication with low latency and high reliability. In
                 this paper, we investigate how communication can be
                 used to improve stopping distance performance based on
                 fieldwork results. In addition, we assess the impacts
                 of reduced reliability, in terms of distance
                 independent, distance dependent and density-based
                 consecutive packet losses. A model is developed based
                 on empirical measurements results depending on
                 distance, data rate, and traveling speed. With this
                 model, it is shown that cooperative V2V communications
                 can effectively reduce reaction time and increase
                 safety stop distance, and highlight the importance of
                 high reliability. The obtained results can be further
                 used for the design of cooperative V2V-based driving
                 and safety applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hitimana:2021:IIF,
  author =       "Eric Hitimana and Gaurav Bajpai and Richard Musabe and
                 Louis Sibomana and Jayavel Kayalvizhi",
  title =        "Implementation of {IoT} Framework with Data Analysis
                 Using Deep Learning Methods for Occupancy Prediction in
                 a Building",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "3",
  pages =        "67",
  day =          "09",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13030067",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 26 12:47:18 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/3/67",
  abstract =     "Many countries worldwide face challenges in
                 controlling building incidence prevention measures for
                 fire disasters. The most critical issues are the
                 localization, identification, detection of the room
                 occupant. Internet of Things (IoT) along with machine
                 learning proved the increase of the smartness of the
                 building by providing real-time data acquisition using
                 sensors and actuators for prediction mechanisms. This
                 paper proposes the implementation of an IoT framework
                 to capture indoor environmental parameters for
                 occupancy multivariate time-series data. The
                 application of the Long Short Term Memory (LSTM) Deep
                 Learning algorithm is used to infer the knowledge of
                 the presence of human beings. An experiment is
                 conducted in an office room using multivariate
                 time-series as predictors in the regression forecasting
                 problem. The results obtained demonstrate that with the
                 developed system it is possible to obtain, process, and
                 store environmental information. The information
                 collected was applied to the LSTM algorithm and
                 compared with other machine learning algorithms. The
                 compared algorithms are Support Vector Machine,
                 Na{\"\i}ve Bayes Network, and Multilayer Perceptron
                 Feed-Forward Network. The outcomes based on the
                 parametric calibrations demonstrate that LSTM performs
                 better in the context of the proposed application.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Georgiou:2021:DPI,
  author =       "Dimitra Georgiou and Costas Lambrinoudakis",
  title =        "Data Protection Impact Assessment ({DPIA}) for
                 Cloud-Based Health Organizations",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "3",
  pages =        "66",
  day =          "07",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13030066",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 26 12:47:18 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/3/66",
  abstract =     "The General Data Protection Regulation (GDPR)
                 harmonizes personal data protection laws across the
                 European Union, affecting all sectors including the
                 healthcare industry. For processing operations that
                 pose a high risk for data subjects, a Data Protection
                 Impact Assessment (DPIA) is mandatory from May 2018.
                 Taking into account the criticality of the process and
                 the importance of its results, for the protection of
                 the patients' health data, as well as the complexity
                 involved and the lack of past experience in applying
                 such methodologies in healthcare environments, this
                 paper presents the main steps of a DPIA study and
                 provides guidelines on how to carry them out
                 effectively. To this respect, the Privacy Impact
                 Assessment, Commission Nationale de l'Informatique et
                 des Libert{\'e}s (PIA-CNIL) methodology has been
                 employed, which is also compliant with the privacy
                 impact assessment tasks described in ISO/IEC
                 29134:2017. The work presented in this paper focuses on
                 the first two steps of the DPIA methodology and more
                 specifically on the identification of the Purposes of
                 Processing and of the data categories involved in each
                 of them, as well as on the evaluation of the
                 organization's GDPR compliance level and of the gaps (
                 Gap Analysis ) that must be filled-in. The main
                 contribution of this work is the identification of the
                 main organizational and legal requirements that must be
                 fulfilled by the health care organization. This
                 research sets the legal grounds for data processing,
                 according to the GDPR and is highly relevant to any
                 processing of personal data, as it helps to structure
                 the process, as well as be aware of data protection
                 issues and the relevant legislation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lin:2021:ETB,
  author =       "Jhan-Jia Lin and Yu-Tse Lee and Ja-Ling Wu",
  title =        "The Effect of Thickness-Based Dynamic Matching
                 Mechanism on a Hyperledger Fabric-Based {TimeBank}
                 System",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "3",
  pages =        "65",
  day =          "06",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13030065",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 26 12:47:18 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/3/65",
  abstract =     "In a community with an aging population, helping each
                 other is a must society function. Lacking mutual trust
                 makes the need for a fair and transparent service
                 exchange platform on top of the public service
                 administration's list. We present an efficient
                 blockchain-based TimeBank realization with a newly
                 proposed dynamic service matching algorithm (DSMA) in
                 this work. The Hyperledger Fabric (or Fabric in short),
                 one of the well-known Consortium Blockchains, is chosen
                 as our system realization platform. It provides the
                 identity certification mechanism and has an extendable
                 network structure. The performance of a DSMA is
                 measured by the waiting time for a service to get a
                 match, called the service-matching waiting time (SMWT).
                 In our DSMA, the decision as to whether a service is to
                 get a match or wait for a later chance depends
                 dynamically on the total number of contemporarily
                 available services (i.e., the thickness of the service
                 market). To better the proposed TimeBank system's
                 service quality, a Dynamic Tuning Strategy (DTS) is
                 designed to thicken the market size. Experimental
                 results show that a thicker market makes on-chain nodes
                 have more links, and in turn, they find a match easier
                 (i.e., consume a shorter SMWT).",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yu:2021:CMA,
  author =       "Jie Yu and Yaliu Li and Chenle Pan and Junwei Wang",
  title =        "A Classification Method for Academic Resources Based
                 on a Graph Attention Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "3",
  pages =        "64",
  day =          "04",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13030064",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 26 12:47:18 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/3/64",
  abstract =     "Classification of resource can help us effectively
                 reduce the work of filtering massive academic
                 resources, such as selecting relevant papers and
                 focusing on the latest research by scholars in the same
                 field. However, existing graph neural networks do not
                 take into account the associations between academic
                 resources, leading to unsatisfactory classification
                 results. In this paper, we propose an Association
                 Content Graph Attention Network (ACGAT), which is based
                 on the association features and content attributes of
                 academic resources. The semantic relevance and academic
                 relevance are introduced into the model. The ACGAT
                 makes full use of the association commonality and the
                 influence information of resources and introduces an
                 attention mechanism to improve the accuracy of academic
                 resource classification. We conducted experiments on a
                 self-built scholar network and two public citation
                 networks. Experimental results show that the ACGAT has
                 better effectiveness than existing classification
                 methods.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Morshedi:2021:EPV,
  author =       "Maghsoud Morshedi and Josef Noll",
  title =        "Estimating {PQoS} of Video Conferencing on {Wi-Fi}
                 Networks Using Machine Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "3",
  pages =        "63",
  day =          "03",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13030063",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 26 12:47:18 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/3/63",
  abstract =     "Video conferencing services based on web real-time
                 communication (WebRTC) protocol are growing in
                 popularity among Internet users as multi-platform
                 solutions enabling interactive communication from
                 anywhere, especially during this pandemic era.
                 Meanwhile, Internet service providers (ISPs) have
                 deployed fiber links and customer premises equipment
                 that operate according to recent 802.11ac/ax standards
                 and promise users the ability to establish
                 uninterrupted video conferencing calls with
                 ultra-high-definition video and audio quality. However,
                 the best-effort nature of 802.11 networks and the high
                 variability of wireless medium conditions hinder users
                 experiencing uninterrupted high-quality video
                 conferencing. This paper presents a novel approach to
                 estimate the perceived quality of service (PQoS) of
                 video conferencing using only 802.11-specific network
                 performance parameters collected from Wi-Fi access
                 points (APs) on customer premises. This study produced
                 datasets comprising 802.11-specific network performance
                 parameters collected from off-the-shelf Wi-Fi APs
                 operating at 802.11g/n/ac/ax standards on both 2.4 and
                 5 GHz frequency bands to train machine learning
                 algorithms. In this way, we achieved classification
                 accuracies of 92-98\% in estimating the level of PQoS
                 of video conferencing services on various Wi-Fi
                 networks. To efficiently troubleshoot wireless issues,
                 we further analyzed the machine learning model to
                 correlate features in the model with the root cause of
                 quality degradation. Thus, ISPs can utilize the
                 approach presented in this study to provide predictable
                 and measurable wireless quality by implementing a
                 non-intrusive quality monitoring approach in the form
                 of edge computing that preserves customers' privacy
                 while reducing the operational costs of monitoring and
                 data analytics.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Antal:2021:DLT,
  author =       "Claudia Antal and Tudor Cioara and Ionut Anghel and
                 Marcel Antal and Ioan Salomie",
  title =        "Distributed Ledger Technology Review and Decentralized
                 Applications Development Guidelines",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "3",
  pages =        "62",
  day =          "27",
  month =        feb,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13030062",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 26 12:47:18 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/3/62",
  abstract =     "The Distributed Ledger Technology (DLT) provides an
                 infrastructure for developing decentralized
                 applications with no central authority for registering,
                 sharing, and synchronizing transactions on digital
                 assets. In the last years, it has drawn high interest
                 from the academic community, technology developers, and
                 startups mostly by the advent of its most popular type,
                 blockchain technology. In this paper, we provide a
                 comprehensive overview of DLT analyzing the challenges,
                 provided solutions or alternatives, and their usage for
                 developing decentralized applications. We define a
                 three-tier based architecture for DLT applications to
                 systematically classify the technology solutions
                 described in over 100 papers and startup initiatives.
                 Protocol and Network Tier contains solutions for
                 digital assets registration, transactions, data
                 structure, and privacy and business rules
                 implementation and the creation of peer-to-peer
                 networks, ledger replication, and consensus-based state
                 validation. Scalability and Interoperability Tier
                 solutions address the scalability and interoperability
                 issues with a focus on blockchain technology, where
                 they manifest most often, slowing down its large-scale
                 adoption. The paper closes with a discussion on
                 challenges and opportunities for developing
                 decentralized applications by providing a multi-step
                 guideline for decentralizing the design and
                 implementation of traditional systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Cappellari:2021:CBD,
  author =       "Max Cappellari and John Belstner and Bryan Rodriguez
                 and Jeff Sedayao",
  title =        "A Cloud-Based Data Collaborative to Combat the
                 {COVID-19} Pandemic and to Solve Major Technology
                 Challenges",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "3",
  pages =        "61",
  day =          "27",
  month =        feb,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13030061",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 26 12:47:18 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/3/61",
  abstract =     "The XPRIZE Foundation designs and operates
                 multi-million-dollar, global competitions to
                 incentivize the development of technological
                 breakthroughs that accelerate humanity toward a better
                 future. To combat the COVID-19 pandemic, the foundation
                 coordinated with several organizations to make datasets
                 about different facets of the disease available and to
                 provide the computational resources needed to analyze
                 those datasets. This paper is a case study of the
                 requirements, design, and implementation of the XPRIZE
                 Data Collaborative, which is a Cloud-based
                 infrastructure that enables the XPRIZE to meet its
                 COVID-19 mission and host future data-centric
                 competitions. We examine how a Cloud Native Application
                 can use an unexpected variety of Cloud technologies,
                 ranging from containers, serverless computing, to even
                 older ones such as Virtual Machines. We also search and
                 document the effects that the pandemic had on
                 application development in the Cloud. We include our
                 experiences of having users successfully exercise the
                 Data Collaborative, detailing the challenges
                 encountered and areas for improvement and future
                 work.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Axelsson:2021:LHS,
  author =       "Carl-Anton Werner Axelsson and Mona Guath and Thomas
                 Nygren",
  title =        "Learning How to Separate Fake from Real News: Scalable
                 Digital Tutorials Promoting Students' Civic Online
                 Reasoning",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "3",
  pages =        "60",
  day =          "27",
  month =        feb,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13030060",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 26 12:47:18 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/3/60",
  abstract =     "With the rise of misinformation, there is a great need
                 for scalable educational interventions supporting
                 students' abilities to determine the trustworthiness of
                 digital news. We address this challenge in our study by
                 developing an online intervention tool based on
                 tutorials in civic online reasoning that aims to teach
                 adolescents how to critically assess online information
                 comprising text, videos and images. Our findings from
                 an online intervention with 209 upper secondary
                 students highlight how observational learning and
                 feedback support their ability to read laterally and
                 improve their performance in determining the
                 credibility of digital news and social media posts.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Weichselbraun:2021:ADD,
  author =       "Albert Weichselbraun and Philipp Kuntschik and
                 Vincenzo Francolino and Mirco Saner and Urs Dahinden
                 and Vinzenz Wyss",
  title =        "Adapting Data-Driven Research to the Fields of Social
                 Sciences and the Humanities",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "3",
  pages =        "59",
  day =          "26",
  month =        feb,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13030059",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 26 12:47:18 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/3/59",
  abstract =     "Recent developments in the fields of computer science,
                 such as advances in the areas of big data, knowledge
                 extraction, and deep learning, have triggered the
                 application of data-driven research methods to
                 disciplines such as the social sciences and humanities.
                 This article presents a collaborative,
                 interdisciplinary process for adapting data-driven
                 research to research questions within other
                 disciplines, which considers the methodological
                 background required to obtain a significant impact on
                 the target discipline and guides the systematic
                 collection and formalization of domain knowledge, as
                 well as the selection of appropriate data sources and
                 methods for analyzing, visualizing, and interpreting
                 the results. Finally, we present a case study that
                 applies the described process to the domain of
                 communication science by creating approaches that aid
                 domain experts in locating, tracking, analyzing, and,
                 finally, better understanding the dynamics of media
                 criticism. The study clearly demonstrates the potential
                 of the presented method, but also shows that
                 data-driven research approaches require a tighter
                 integration with the methodological framework of the
                 target discipline to really provide a significant
                 impact on the target discipline.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chatzoglou:2021:MTS,
  author =       "Efstratios Chatzoglou and Georgios Kambourakis and
                 Vasileios Kouliaridis",
  title =        "A Multi-Tier Security Analysis of Official Car
                 Management Apps for {Android}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "3",
  pages =        "58",
  day =          "25",
  month =        feb,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13030058",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 26 12:47:18 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/3/58",
  abstract =     "Using automotive smartphone applications (apps)
                 provided by car manufacturers may offer numerous
                 advantages to the vehicle owner, including improved
                 safety, fuel efficiency, anytime monitoring of vehicle
                 data, and timely over-the-air delivery of software
                 updates. On the other hand, the continuous tracking of
                 the vehicle data by such apps may also pose a risk to
                 the car owner, if, say, sensitive pieces of information
                 are leaked to third parties or the app is vulnerable to
                 attacks. This work contributes the first to our
                 knowledge full-fledged security assessment of all the
                 official single-vehicle management apps offered by
                 major car manufacturers who operate in Europe. The apps
                 are scrutinised statically with the purpose of not only
                 identifying surfeits, say, in terms of the permissions
                 requested, but also from a vulnerability assessment
                 viewpoint. On top of that, we run each app to identify
                 possible weak security practices in the owner-to-app
                 registration process. The results reveal a multitude of
                 issues, ranging from an over-claim of sensitive
                 permissions and the use of possibly privacy-invasive
                 API calls, to numerous potentially exploitable CWE and
                 CVE-identified weaknesses and vulnerabilities, the, in
                 some cases, excessive employment of third-party
                 trackers, and a number of other flaws related to the
                 use of third-party software libraries, unsanitised
                 input, and weak user password policies, to mention just
                 a few.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Samala:2021:IDU,
  author =       "Thirupathi Samala and Vijaya Kumar Manupati and Maria
                 Leonilde R. Varela and Goran Putnik",
  title =        "Investigation of Degradation and Upgradation Models
                 for Flexible Unit Systems: a Systematic Literature
                 Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "3",
  pages =        "57",
  day =          "25",
  month =        feb,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13030057",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 26 12:47:18 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/3/57",
  abstract =     "Research on flexible unit systems (FUS) with the
                 context of descriptive, predictive, and prescriptive
                 analysis have remarkably progressed in recent times,
                 being now reinforced in the current Industry 4.0 era
                 with the increased focus on integration of distributed
                 and digitalized systems. In the existing literature,
                 most of the work focused on the individual
                 contributions of the above mentioned three analyses.
                 Moreover, the current literature is unclear with
                 respect to the integration of degradation and
                 upgradation models for FUS. In this paper, a systematic
                 literature review on degradation, residual life
                 distribution, workload adjustment strategy,
                 upgradation, and predictive maintenance as major
                 performance measures to investigate the performance of
                 the FUS has been considered. In order to identify the
                 key issues and research gaps in the existing
                 literature, the 59 most relevant papers from 2009 to
                 2020 have been sorted and analyzed. Finally, we
                 identify promising research opportunities that could
                 expand the scope and depth of FUS.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ahadi:2021:OPL,
  author =       "Alireza Ahadi and Matt Bower and Abhay Singh and
                 Michael Garrett",
  title =        "Online Professional Learning in Response to {COVID-19}
                 --- Towards Robust Evaluation",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "3",
  pages =        "56",
  day =          "24",
  month =        feb,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13030056",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 26 12:47:18 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/3/56",
  abstract =     "As COVID-19 continues to impact upon education
                 worldwide, systems and organizations are rapidly
                 transiting their professional learning to online mode.
                 This raises concerns, not simply about whether online
                 professional learning can result in equivalent outcomes
                 to face-to-face learning, but more importantly about
                 how to best evaluate online professional learning so we
                 can iteratively improve our approaches. This case study
                 analyses the evaluation of an online teacher
                 professional development workshop for the purpose of
                 critically reflecting upon the efficacy of workshop
                 evaluation techniques. The evaluation approach was
                 theoretically based in a synthesis of six seminal
                 workshop evaluation models, and structured around eight
                 critical dimensions of educational technology
                 evaluation. The approach involving collection of
                 pre-workshop participant background information,
                 pre-/post-teacher perceptions data, and post-workshop
                 focus group perceptions, enabled the changes in teacher
                 knowledge, skills, and beliefs to be objectively
                 evaluated, at the same time as providing qualitative
                 information to effectively improve future iterations of
                 the workshops along a broad range of dimensions. The
                 evaluation approach demonstrated that the professional
                 learning that was shifted into online mode in response
                 to COVID-19 could unequivocally result in significant
                 improvements to professional learning outcomes. More
                 importantly, the evaluation approach is critically
                 contrasted with previous evaluation models, and a
                 series of recommendations for the evaluation of
                 technology-enhanced teacher professional development
                 workshops are proposed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ferreira:2021:PIM,
  author =       "Ana Teresa Ferreira and Carlos Fernandes and Jos{\'e}
                 Vieira and Filipe Portela",
  title =        "Pervasive Intelligent Models to Predict the Outcome of
                 {COVID-19} Patients",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "4",
  pages =        "102",
  day =          "20",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13040102",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 23 17:52:28 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/4/102",
  abstract =     "Nowadays, there is an increasing need to understand
                 the behavior of COVID-19. After the Directorate-General
                 of Health of Portugal made available the infected
                 patient's data, it became possible to analyze it and
                 gather some conclusions, obtaining a better
                 understanding of the matter. In this context, the
                 project developed-ioCOVID19-Intelligent Decision
                 Support Platform aims to identify patterns and develop
                 intelligent models to predict and support clinical
                 decisions. This article explores which typologies are
                 associated with different outcomes to help clinicians
                 fight the virus with a decision support system. So, to
                 achieve this purpose, classification algorithms were
                 used, and one target was studied-Patients outcome, that
                 is, to predict if the patient will die or recover.
                 Regarding the obtained results, the model that stood
                 out is composed of scenario s4 (composed of all
                 comorbidities, symptoms, and age), the decision tree
                 algorithm, and the oversampling sampling method. The
                 obtained results by the studied metrics were (in order
                 of importance): Sensitivity of 95.20\%, Accuracy of
                 90.67\%, and Specificity of 86.08\%. The models were
                 deployed as a service, and they are part of a clinical
                 decision support system that is available for
                 authorized users anywhere and anytime.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Dorobantiu:2021:CCE,
  author =       "Alexandru Dorobantiu and Valentin Ogrean and Remus
                 Brad",
  title =        "Coronary Centerline Extraction from {CCTA} Using
                 {$3$D-UNet}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "4",
  pages =        "101",
  day =          "19",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13040101",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 23 17:52:28 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/4/101",
  abstract =     "The mesh-type coronary model, obtained from
                 three-dimensional reconstruction using the sequence of
                 images produced by computed tomography (CT), can be
                 used to obtain useful diagnostic information, such as
                 extracting the projection of the lumen (planar
                 development along an artery). In this paper, we have
                 focused on automated coronary centerline extraction
                 from cardiac computed tomography angiography (CCTA)
                 proposing a {$3$D} version of U-Net architecture,
                 trained with a novel loss function and with augmented
                 patches. We have obtained promising results for
                 accuracy (between 90-95\%) and overlap (between
                 90-94\%) with various network training configurations
                 on the data from the Rotterdam Coronary Artery
                 Centerline Extraction benchmark. We have also
                 demonstrated the ability of the proposed network to
                 learn despite the huge class imbalance and sparse
                 annotation present in the training data.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sansevere:2021:LPB,
  author =       "Kayla S. Sansevere and Nathan Ward",
  title =        "Linking Phubbing Behavior to Self-Reported Attentional
                 Failures and Media Multitasking",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "4",
  pages =        "100",
  day =          "14",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13040100",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 23 17:52:28 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/4/100",
  abstract =     "Phubbing, or using a phone to snub another person, has
                 been investigated through social and personality
                 frameworks. Phubbing involves attending to and
                 performing competing tasks, implying the involvement of
                 attentional abilities. Yet, past research has not yet
                 used a cognitive framework to establish a link between
                 phubbing and attention. Using self-report data from a
                 large online sample, we explored the associations
                 between phubbing and everyday attentional failures.
                 Phubbing was associated with difficulties in
                 attentional shifting and distractibility, frequent
                 attentional lapses, spontaneous and deliberate mind
                 wandering, and attention-related cognitive errors. When
                 examining these attention variables alongside several
                 psychosocial and personality variables,
                 attention-related cognitive errors acted as the biggest
                 predictor of phubbing behavior. Phubbing was also
                 positively correlated with media multitasking, which is
                 a conceptually similar yet distinct technology use
                 behavior. The results suggest that perceived everyday
                 attentional failures are strongly associated with, and
                 to an extent can predict, phubbing behavior, even more
                 so than some social and personality variables.
                 Technology has incorporated itself as a necessity, or
                 at the very least a favored convenience, in most
                 people's lives. Characterizing technology multitasking
                 behaviors from a variety of frameworks can help us
                 better understand who is engaging in these behaviors
                 and why.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Vazquez-Lopez:2021:IRA,
  author =       "Alba V{\'a}zquez-L{\'o}pez and Mart{\'\i}n
                 Barrasa-Rioja and Manuel Marey-Perez",
  title =        "{ICT} in Rural Areas from the Perspective of Dairy
                 Farming: a Systematic Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "4",
  pages =        "99",
  day =          "13",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13040099",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 23 17:52:28 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/4/99",
  abstract =     "This study presents a systematic review of 169 papers
                 concerning the ICT (Information and Communication
                 Technologies) related to rural areas, specifically to
                 dairy farms. The objective was to delve into the
                 relationship between dairy farmers and the
                 administrative authorities via e-government, comparing
                 this area to another eight concerning the farmer's
                 needs and expectations in relation to the ICT in
                 different fields of their business. We observed that
                 areas such as connectivity and digital inclusion are
                 the most covered areas not only at the study level but
                 also at the government level since countries all over
                 the world are trying to develop politics to put an end
                 to the so-called ``digital divide,'' which affects
                 rural areas more intensely. This is increasing due to
                 the growing technological innovations. The areas of the
                 market, production, financial development, management
                 and counseling, Smart Farming, and Internet of Things
                 have been approached, associated with the ICT in dairy
                 farms, showing in the latter two an increasing number
                 of papers in the last few years. The area of public
                 administration in relation to dairy farms has also been
                 covered, being remarkable the low number of pieces of
                 research concerning the interaction by the farmers,
                 more specifically by dairy farmers, with the public
                 administration, which is surprising due to the new
                 global need and especially in the European Union (EU)
                 of interacting with it telematically by all legal
                 entities. The results show that there are still
                 barriers to the implementation of the electronic
                 government (e-government) since the websites do not
                 meet the user's expectations. Therefore, this study
                 lays the ground for future research on this area. As a
                 graphical abstract of the contributions of this paper,
                 we present a graphic summary, where the different
                 contributions by areas and expressed in percentage
                 values are shown.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Jimenez:2021:DTB,
  author =       "Mar{\'\i}a Artemisa Sangerm{\'a}n Jim{\'e}nez and
                 Pedro Ponce",
  title =        "Differentiated Teaching Based on Standardized Metrics
                 Integrating Fuzzy Logic Type 2 Detection Theory: High
                 School Case-{PrepaTec}, {Mexico}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "4",
  pages =        "98",
  day =          "13",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13040098",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 23 17:52:28 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/4/98",
  abstract =     "Universities and high schools constantly research and
                 develop educational methods to improve the student
                 learning process. This paper presents a novel
                 educational methodology for students to obtain better
                 learning results in Spanish grammar through an
                 intervention that fuses differentiated instructions,
                 standardized evaluation, and a Fuzzy Logic Type 2
                 system. This successful case study in a Mexico City
                 high school reports improved Spanish grammar outcomes
                 after the intervention. Before then, 79\% of the
                 students did not obtain satisfactory scores in a
                 national Spanish evaluation. This educational
                 methodology uses a flexible intervention plan that
                 could be replicated or tailored for various educational
                 scenarios and topics using the same framework.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Villegas-Ch:2021:IVA,
  author =       "William Villegas-Ch and Joselin Garc{\'\i}a-Ortiz and
                 Karen Mullo-Ca and Santiago S{\'a}nchez-Viteri and
                 Milton Roman-Ca{\~n}izares",
  title =        "Implementation of a Virtual Assistant for the Academic
                 Management of a University with the Use of Artificial
                 Intelligence",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "4",
  pages =        "97",
  day =          "13",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13040097",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 23 17:52:28 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/4/97",
  abstract =     "Currently, private universities, as a result of the
                 pandemic that the world is facing, are going through
                 very delicate moments in several areas, both academic
                 and financial. Academically, there are learning
                 problems and these are directly related to the dropout
                 rate, which brings financial problems. Added to this
                 are the economic problems caused by the pandemic, where
                 the rates of students who want to access a private
                 education have dropped considerably. For this reason,
                 it is necessary for all private universities to have
                 support to improve their student income and avoid cuts
                 in budgets and resources. However, the academic part
                 represents a great effort to fulfill their academic
                 activities, which are the priority, with attention on
                 those interested in pursuing a training programs. To
                 solve these problems, it is important to integrate
                 technologies such as Chatbots, which use artificial
                 intelligence in such a way that tasks such as providing
                 information on an academic courses are addressed by
                 them, reducing the administrative burden and improving
                 the user experience. At the same time, this encourages
                 people to be a part of the college.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Khan:2021:SCL,
  author =       "Shawal Khan and Ishita Sharma and Mazzamal Aslam and
                 Muhammad Zahid Khan and Shahzad Khan",
  title =        "Security Challenges of Location Privacy in {VANETs}
                 and State-of-the-Art Solutions: a Survey",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "4",
  pages =        "96",
  day =          "10",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13040096",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 23 17:52:28 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/4/96",
  abstract =     "A Vehicular Ad-hoc Network (VANET) comprises a group
                 of moving or stationary vehicles connected by a
                 wireless network. VANETs play a vital role in providing
                 safety and comfort to drivers in vehicular
                 environments. They provide smart traffic control and
                 real-time information, event allocation. VANETs have
                 received attention in support of safe driving,
                 intelligent navigation, emergency and entertainment
                 applications in vehicles. Nevertheless, these
                 increasingly linked vehicles pose a range of new safety
                 and security risks to both the host and its associated
                 properties and may even have fatal consequences.
                 Violations of national privacy and vehicle identities
                 are a major obstacle to introducing forced contact
                 protocols in vehicles. Location privacy refers to the
                 privacy of the vehicle (driver) and the location of the
                 vehicle. Whenever a vehicle sends a message, no one but
                 authorized entities should know their real identity and
                 location of the vehicle. All the messages sent by the
                 vehicle must be authenticated before processing, hence
                 location privacy is an important design aspect to be
                 considered in VANETs operations. The novelty of this
                 paper is that it specifically reviews location privacy
                 in VANETs in terms of operational and safety concerns.
                 Furthermore, it presents a critical analysis of various
                 attacks, identity thefts, manipulation and other
                 techniques in vogue for location privacy protection
                 available in state-of-the-art solutions for VANETs. The
                 efforts in this paper will help researchers to develop
                 a great breadth of understanding pertaining to location
                 privacy issues and various security threats encountered
                 by VANETs and present the critical analysis of the
                 available state-of-the- art solutions to maintain
                 location privacy in VANETs.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rocha:2021:BAA,
  author =       "Geneci da Silva Ribeiro Rocha and Let{\'\i}cia de
                 Oliveira and Edson Talamini",
  title =        "Blockchain Applications in Agribusiness: a Systematic
                 Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "4",
  pages =        "95",
  day =          "08",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13040095",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 23 17:52:28 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/4/95",
  abstract =     "Blockchain is a technology that can be applied in
                 different sectors to solve various problems. As a
                 complex system, agribusiness presents many
                 possibilities to take advantage of blockchain
                 technology. The main goal of this paper is to identify
                 the purposes for which blockchain has been applied in
                 the agribusiness sector, for which a PRISMA-based
                 systematic review was carried out. The scientific
                 literature corpus was accessed and selected from
                 Elsevier's Scopus and ISI of Knowledge's Web of Science
                 (WoS) platforms, using the PRISMA protocol procedures.
                 Seventy-one articles were selected for analysis.
                 Blockchain application in agribusiness is a novel
                 topic, with the first publication dating from 2016. The
                 technological development prevails more than blockchain
                 applications since it has been addressed mainly in the
                 Computer Sciences and Engineering. Blockchain
                 applications for agribusiness management of financial,
                 energy, logistical, environmental, agricultural,
                 livestock, and industrial purposes have been reported
                 in the literature. The findings suggest that blockchain
                 brings many benefits when used in agribusiness supply
                 chains. We concluded that the research on blockchain
                 applications in agribusiness is only at an early stage,
                 as many prototypes are being developed and tested in
                 the laboratory. In the near future, blockchain will be
                 increasingly applied across all economic sectors,
                 including agribusiness, promoting greater reliability
                 and agility in information with a reduced cost. Several
                 gaps for future studies were observed, with significant
                 value for science, industry, and society.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fang:2021:PPM,
  author =       "Haokun Fang and Quan Qian",
  title =        "Privacy Preserving Machine Learning with Homomorphic
                 Encryption and Federated Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "4",
  pages =        "94",
  day =          "08",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13040094",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 23 17:52:28 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/4/94",
  abstract =     "Privacy protection has been an important concern with
                 the great success of machine learning. In this paper,
                 it proposes a multi-party privacy preserving machine
                 learning framework, named PFMLP, based on partially
                 homomorphic encryption and federated learning. The core
                 idea is all learning parties just transmitting the
                 encrypted gradients by homomorphic encryption. From
                 experiments, the model trained by PFMLP has almost the
                 same accuracy, and the deviation is less than 1\%.
                 Considering the computational overhead of homomorphic
                 encryption, we use an improved Paillier algorithm which
                 can speed up the training by 25-28\%. Moreover,
                 comparisons on encryption key length, the learning
                 network structure, number of learning clients, etc. are
                 also discussed in detail in the paper.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Khalil:2021:IDI,
  author =       "Samar Samir Khalil and Sherin M. Youssef and Sherine
                 Nagy Saleh",
  title =        "{iCaps-Dfake}: an Integrated Capsule-Based Model for
                 Deepfake Image and Video Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "4",
  pages =        "93",
  day =          "05",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13040093",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 23 17:52:28 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/4/93",
  abstract =     "Fake media is spreading like wildfire all over the
                 internet as a result of the great advancement in
                 deepfake creation tools and the huge interest
                 researchers and corporations are showing to explore its
                 limits. Now anyone can create manipulated unethical
                 media forensics, defame, humiliate others or even scam
                 them out of their money with a click of a button. In
                 this research a new deepfake detection approach,
                 iCaps-Dfake, is proposed that competes with
                 state-of-the-art techniques of deepfake video detection
                 and addresses their low generalization problem. Two
                 feature extraction methods are combined, texture-based
                 Local Binary Patterns (LBP) and Convolutional Neural
                 Networks (CNN) based modified High-Resolution Network
                 (HRNet), along with an application of capsule neural
                 networks (CapsNets) implementing a concurrent routing
                 technique. Experiments have been conducted on large
                 benchmark datasets to evaluate the performance of the
                 proposed model. Several performance metrics are applied
                 and experimental results are analyzed. The proposed
                 model was primarily trained and tested on the
                 DeepFakeDetectionChallenge-Preview (DFDC-P) dataset
                 then tested on Celeb-DF to examine its generalization
                 capability. Experiments achieved an Area-Under Curve
                 (AUC) score improvement of 20.25\% over
                 state-of-the-art models.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Augello:2021:SEE,
  author =       "Agnese Augello and Ignazio Infantino and Giovanni
                 Pilato and Gianpaolo Vitale",
  title =        "Site Experience Enhancement and Perspective in
                 Cultural Heritage Fruition --- a Survey on New
                 Technologies and Methodologies Based on a
                 {``Four-Pillars''} Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "4",
  pages =        "92",
  day =          "04",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13040092",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 23 17:52:28 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/4/92",
  abstract =     "This paper deals with innovative fruition modalities
                 of cultural heritage sites. Based on two ongoing
                 experiments, four pillars are considered, that is, User
                 Localization, Multimodal Interaction, User
                 Understanding and Gamification. A survey of the
                 existing literature regarding one or more issues
                 related to the four pillars is proposed. It aims to put
                 in evidence the exploitation of these contributions to
                 cultural heritage. It is discussed how a cultural site
                 can be enriched, extended and transformed into an
                 intelligent multimodal environment in this perspective.
                 This new augmented environment can focus on the
                 visitor, analyze his activity and behavior, and make
                 his experience more satisfying, fulfilling and unique.
                 After an in-depth overview of the existing technologies
                 and methodologies for the fruition of cultural interest
                 sites, the two experiments are described in detail and
                 the authors' vision of the future is proposed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ramirez-Montoya:2021:CTP,
  author =       "Mar{\'\i}a Soledad Ram{\'\i}rez-Montoya and Mar{\'\i}a
                 Isabel Loaiza-Aguirre and Alexandra
                 Z{\'u}{\~n}iga-Ojeda and May Portuguez-Castro",
  title =        "Characterization of the Teaching Profile within the
                 Framework of Education 4.0",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "4",
  pages =        "91",
  day =          "01",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13040091",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 23 17:52:28 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/4/91",
  abstract =     "The authors of the Education 4.0 concept postulated a
                 flexible combination of digital literacy, critical
                 thinking, and problem-solving in educational
                 environments linked to real-world scenarios. Therefore,
                 teachers have been challenged to develop new methods
                 and resources to integrate into their planning in order
                 to help students develop these desirable and necessary
                 skills; hence, the question: What are the
                 characteristics of a teacher to consider within the
                 framework of Education 4.0? This study was conducted in
                 a higher education institution in Ecuador, with the aim
                 to identify the teaching profile required in new
                 undergraduate programs within the framework of
                 Education 4.0 in order to contribute to decision-making
                 about teacher recruitment, professional training and
                 evaluation, human talent management, and institutional
                 policies interested in connecting competencies with the
                 needs of society. Descriptive and exploratory
                 approaches, where we applied quantitative and
                 qualitative instruments (surveys) to 337 undergraduate
                 students in education programs and 313 graduates, were
                 used. We also included interviews with 20 experts in
                 the educational field and five focus groups with 32
                 chancellors, school principals, university professors,
                 and specialists in the educational area. The data were
                 triangulated, and the results were organized into the
                 categories of (a) processes as facilitators (b), soft
                 skills, (c) human sense, and (d) the use of
                 technologies. The results outlined the profile of a
                 professor as a specialized professional with
                 competencies for innovation, complex problem solving,
                 entrepreneurship, collaboration, international
                 perspective, leadership, and connection with the needs
                 of society. This research study may be of value to
                 administrators, educational and social entrepreneurs,
                 trainers, and policy-makers interested in implementing
                 innovative training programs and in supporting
                 management and policy decisions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kaddoura:2021:PDD,
  author =       "Sanaa Kaddoura and Ramzi A. Haraty and Karam {Al
                 Kontar} and Omar Alfandi",
  title =        "A Parallelized Database Damage Assessment Approach
                 after Cyberattack for Healthcare Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "4",
  pages =        "90",
  day =          "31",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13040090",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 23 17:52:28 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/4/90",
  abstract =     "In the current Internet of things era, all companies
                 shifted from paper-based data to the electronic format.
                 Although this shift increased the efficiency of data
                 processing, it has security drawbacks. Healthcare
                 databases are a precious target for attackers because
                 they facilitate identity theft and cybercrime. This
                 paper presents an approach for database damage
                 assessment for healthcare systems. Inspired by the
                 current behavior of COVID-19 infections, our approach
                 views the damage assessment problem the same way. The
                 malicious transactions will be viewed as if they are
                 COVID-19 viruses, taken from infection onward. The
                 challenge of this research is to discover the infected
                 transactions in a minimal time. The proposed parallel
                 algorithm is based on the transaction dependency
                 paradigm, with a time complexity $ O((M + N Q + N^3) /
                 L) $ ($M$ = total number of transactions under
                 scrutiny, $N$ = number of malicious and affected
                 transactions in the testing list, $Q$ = time for
                 dependency check, and $L$ = number of threads used).
                 The memory complexity of the algorithm is $ O(N + K L)$
                 ($N$ = number of malicious and affected transactions,
                 $K$ = number of transactions in one area handled by one
                 thread, and $L$ = number of threads). Since the damage
                 assessment time is directly proportional to the
                 denial-of-service time, the proposed algorithm provides
                 a minimized execution time. Our algorithm is a novel
                 approach that outperforms other existing algorithms in
                 this domain in terms of both time and memory, working
                 up to four times faster in terms of time and with
                 120,000 fewer bytes in terms of memory.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Peng:2021:OCD,
  author =       "Yubo Peng and Bofeng Zhang and Furong Chang",
  title =        "Overlapping Community Detection of Bipartite Networks
                 Based on a Novel Community Density",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "4",
  pages =        "89",
  day =          "31",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13040089",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 23 17:52:28 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/4/89",
  abstract =     "Community detection plays an essential role in
                 understanding network topology and mining underlying
                 information. A bipartite network is a complex network
                 with more important authenticity and applicability than
                 a one-mode network in the real world. There are many
                 communities in the network that present natural
                 overlapping structures in the real world. However, most
                 of the research focuses on detecting non-overlapping
                 community structures in the bipartite network, and the
                 resolution of the existing evaluation function for the
                 community structure's merits are limited. So, we
                 propose a novel function for community detection and
                 evaluation of the bipartite network, called community
                 density D. And based on community density, a bipartite
                 network community detection algorithm DSNE (Density
                 Sub-community Node-pair Extraction) is proposed, which
                 is effective for overlapping community detection from a
                 micro point of view. The experiments based on
                 artificially-generated networks and real-world networks
                 show that the DSNE algorithm is superior to some
                 existing excellent algorithms; in comparison, the
                 community density (D) is better than the bipartite
                 network's modularity.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2021:RIG,
  author =       "Xiaoyuan Wang and Junyan Han and Chenglin Bai and
                 Huili Shi and Jinglei Zhang and Gang Wang",
  title =        "Research on the Impacts of Generalized Preceding
                 Vehicle Information on Traffic Flow in {V2X}
                 Environment",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "4",
  pages =        "88",
  day =          "30",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13040088",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 23 17:52:28 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/4/88",
  abstract =     "With the application of vehicles to everything (V2X)
                 technologies, drivers can obtain massive traffic
                 information and adjust their car-following behavior
                 according to the information. The macro-characteristics
                 of traffic flow are essentially the overall expression
                 of the micro-behavior of drivers. There are some
                 shortcomings in the previous researches on traffic flow
                 in the V2X environment, which result in difficulties to
                 employ the related models or methods in exploring the
                 characteristics of traffic flow affected by the
                 information of generalized preceding vehicles (GPV).
                 Aiming at this, a simulation framework based on the
                 car-following model and the cellular automata (CA) is
                 proposed in this work, then the traffic flow affected
                 by the information of GPV is simulated and analyzed
                 utilizing this framework. The research results suggest
                 that the traffic flow, which is affected by the
                 information of GPV in the V2X environment, would
                 operate with a higher value of velocity, volume as well
                 as jamming density and can maintain the free flow state
                 with a much higher density of vehicles. The simulation
                 framework constructed in this work can provide a
                 reference for further research on the characteristics
                 of traffic flow affected by various information in the
                 V2X environment.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bouloukakis:2021:PAI,
  author =       "Georgios Bouloukakis and Ioannis Moscholios and
                 Nikolaos Georgantas and Val{\'e}rie Issarny",
  title =        "Performance Analysis of {Internet of Things}
                 Interactions via Simulation-Based Queueing Models",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "4",
  pages =        "87",
  day =          "29",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13040087",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 23 17:52:28 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/4/87",
  abstract =     "Numerous middleware application programming interfaces
                 (APIs) and protocols were introduced in the literature
                 in order to facilitate the application development of
                 the Internet of Things (IoT). Such applications are
                 built on reliable or even unreliable protocols that may
                 implement different quality-of-service (QoS) delivery
                 modes. The exploitation of these protocols, APIs and
                 QoS modes, can satisfy QoS requirements in critical IoT
                 applications (e.g., emergency response operations). To
                 study QoS in IoT applications, it is essential to
                 leverage a performance analysis methodology.
                 Queueing-network models offer a modeling and analysis
                 framework that can be adopted for the IoT interactions
                 of QoS representation through either analytical or
                 simulation models. In this paper, various types of
                 queueing models are presented that can be used for the
                 representation of various QoS settings of IoT
                 interactions. In particular, we propose queueing models
                 to represent message-drop probabilities, intermittent
                 mobile connectivity, message availability or validity,
                 the prioritization of important information, and the
                 processing or transmission of messages. Our simulation
                 models demonstrate the significant effect on delivery
                 success rates and response times when QoS settings are
                 varied.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yiu:2021:TBE,
  author =       "Neo C. K. Yiu",
  title =        "Toward Blockchain-Enabled Supply Chain
                 Anti-Counterfeiting and Traceability",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "4",
  pages =        "86",
  day =          "29",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13040086",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 23 17:52:28 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/4/86",
  abstract =     "Existing product anti-counterfeiting and traceability
                 solutions across today's internationally spanning
                 supply chain networks are indeed developed and
                 implemented with centralized system architecture
                 relying on centralized authorities or intermediaries.
                 Vulnerabilities of centralized product
                 anti-counterfeiting solutions could possibly lead to
                 system failure or susceptibility of malicious
                 modifications performed on product records or various
                 potential attacks to the system components by dishonest
                 participant nodes traversing along the supply chain.
                 Blockchain technology has progressed from simply being
                 a use case of immutable ledger for cryptocurrency
                 transactions, to a programmable interactive environment
                 of developing decentralized and reliable applications
                 addressing different use cases globally. Key areas of
                 decentralization, fundamental system requirements, and
                 feasible mechanisms of developing decentralized product
                 anti-counterfeiting and traceability ecosystems
                 utilizing blockchain technology are identified in this
                 research, via a series of security analyses performed
                 against solutions currently implemented in supply chain
                 industry with centralized architecture. The
                 decentralized solution will be a secure and immutable
                 scientific data provenance tracking and management
                 platform where provenance records, providing compelling
                 properties on data integrity of luxurious goods, are
                 recorded and verified automatically across the supply
                 chain.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Reali:2021:TLN,
  author =       "Gianluca Reali and Mauro Femminella",
  title =        "Two-Layer Network Caching for Different Service
                 Requirements",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "4",
  pages =        "85",
  day =          "27",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13040085",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 23 17:52:28 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/4/85",
  abstract =     "Network caching is a technique used to speed-up user
                 access to frequently requested contents in complex data
                 networks. This paper presents a two-layer overlay
                 network caching system for content distribution. It is
                 used to define some caching scenarios with increasing
                 complexity, which refers to real situations, including
                 mobile 5G connectivity. For each scenario our aim is to
                 maximize the hit ratio, which leads to the formulation
                 of NP-complete optimization problems. The heuristic
                 solutions proposed are based on the theory of the
                 maximization of monotone submodular functions under
                 matroid constraints. After the determination of the
                 approximation ratio of the greedy heuristic algorithms
                 proposed, a numerical performance analysis is shown.
                 This analysis includes a comparison with the
                 Least-Frequently Used (LFU) eviction strategy adapted
                 to the analyzed systems. Results show very good
                 performance, under the hypotheses of either known or
                 unknown popularity of contents.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yiu:2021:DSC,
  author =       "Neo C. K. Yiu",
  title =        "Decentralizing Supply Chain Anti-Counterfeiting and
                 Traceability Systems Using Blockchain Technology",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "4",
  pages =        "84",
  day =          "25",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13040084",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 23 17:52:28 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/4/84",
  abstract =     "An interesting research problem in the supply chain
                 industry is evaluating and determining the provenance
                 of physical goods-demonstrating the authenticity of
                 luxury goods such as bottled wine. However, many supply
                 chain systems and networks have been built and
                 implemented with centralized system architecture,
                 relying on centralized authorities or any form of
                 intermediary, and leading to issues such as
                 single-point processing, storage and failure, which
                 could be susceptible to malicious modifications to
                 product records or various potential attacks to system
                 components by dishonest participant nodes traversing
                 along the supply chain. Blockchain technology has
                 evolved from merely being a decentralized, distributed
                 and immutable ledger of cryptocurrency transactions to
                 a programmable interactive environment for building
                 decentralized and reliable applications addressing
                 different use-cases and existing problems in the world.
                 In this research, with a chosen research method of
                 proof-by-demonstration, the Decentralized NFC-Enabled
                 Anti-Counterfeiting System (dNAS) is proposed and
                 developed, decentralizing a legacy anti-counterfeiting
                 system of the supply-chain industry using Blockchain
                 technology to facilitate trustworthy data provenance
                 retrieval, verification and management, as well as
                 strengthening the capability of the product's
                 anti-counterfeiting and traceability qualities in the
                 wine industry, with the capacity to further extend this
                 to the supply chain industry as a whole. The proposed
                 dNAS utilizes a decentralized blockchain network with a
                 consensus protocol compatible with the concept of
                 enterprise blockchain, programmable smart contracts and
                 a distributed file storage system to develop a secure
                 and immutable scientific-data provenance tracking and
                 management platform on which provenance records,
                 providing compelling properties of the data integrity
                 of luxurious goods, are recorded, verified and
                 validated automatically.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bendechache:2021:SER,
  author =       "Malika Bendechache and Sergej Svorobej and Patricia
                 Takako Endo and Adrian Mihai and Theo Lynn",
  title =        "Simulating and Evaluating a Real-World {ElasticSearch}
                 System Using the {RECAP DES} Simulator",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "4",
  pages =        "83",
  day =          "24",
  month =        mar,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13040083",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 23 17:52:28 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/4/83",
  abstract =     "Simulation has become an indispensable technique for
                 modelling and evaluating the performance of large-scale
                 systems efficiently and at a relatively low cost.
                 ElasticSearch (ES) is one of the most popular open
                 source large-scale distributed data indexing systems
                 worldwide. In this paper, we use the RECAP Discrete
                 Event Simulator (DES) simulator, an extension of
                 CloudSimPlus, to model and evaluate the performance of
                 a real-world cloud-based ES deployment by an Irish
                 small and medium-sized enterprise (SME), Opening.io.
                 Following simulation experiments that explored how much
                 query traffic the existing Opening.io architecture
                 could cater for before performance degradation, a
                 revised architecture was proposed, adding a new virtual
                 machine in order to dissolve the bottleneck. The
                 simulation results suggest that the proposed improved
                 architecture can handle significantly larger query
                 traffic (about 71\% more) than the current architecture
                 used by Opening.io. The results also suggest that the
                 RECAP DES simulator is suitable for simulating ES
                 systems and can help companies to understand their
                 infrastructure bottlenecks under various traffic
                 scenarios and inform optimisation and scalability
                 decisions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Libbi:2021:GST,
  author =       "Claudia Alessandra Libbi and Jan Trienes and Dolf
                 Trieschnigg and Christin Seifert",
  title =        "Generating Synthetic Training Data for Supervised
                 De-Identification of Electronic Health Records",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "136",
  day =          "20",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050136",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/136",
  abstract =     "A major hurdle in the development of natural language
                 processing (NLP) methods for Electronic Health Records
                 (EHRs) is the lack of large, annotated datasets.
                 Privacy concerns prevent the distribution of EHRs, and
                 the annotation of data is known to be costly and
                 cumbersome. Synthetic data presents a promising
                 solution to the privacy concern, if synthetic data has
                 comparable utility to real data and if it preserves the
                 privacy of patients. However, the generation of
                 synthetic text alone is not useful for NLP because of
                 the lack of annotations. In this work, we propose the
                 use of neural language models (LSTM and GPT-2) for
                 generating artificial EHR text jointly with annotations
                 for named-entity recognition. Our experiments show that
                 artificial documents can be used to train a supervised
                 named-entity recognition model for de-identification,
                 which outperforms a state-of-the-art rule-based
                 baseline. Moreover, we show that combining real data
                 with synthetic data improves the recall of the method,
                 without manual annotation effort. We conduct a user
                 study to gain insights on the privacy of artificial
                 text. We highlight privacy risks associated with
                 language models to inform future research on
                 privacy-preserving automated text generation and
                 metrics for evaluating privacy-preservation during text
                 generation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Scata:2021:CPN,
  author =       "Marialisa Scat{\'a} and Barbara Attanasio and Aurelio
                 {La Corte}",
  title =        "Cognitive Profiling of Nodes in {6G} through Multiplex
                 Social Network and Evolutionary Collective Dynamics",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "135",
  day =          "20",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050135",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/135",
  abstract =     "Complex systems are fully described by the
                 connectedness of their elements studying how these
                 develop a collective behavior, interacting with each
                 other following their inner features, and the structure
                 and dynamics of the entire system. The forthcoming 6G
                 will attempt to rewrite the communication networks'
                 perspective, focusing on a radical revolution in the
                 way entities and technologies are conceived, integrated
                 and used. This will lead to innovative approaches with
                 the aim of providing new directions to deal with future
                 network challenges posed by the upcoming 6G, thus the
                 complex systems could become an enabling set of tools
                 and methods to design a self-organized, resilient and
                 cognitive network, suitable for many application
                 fields, such as digital health or smart city living
                 scenarios. Here, we propose a complex profiling
                 approach of heterogeneous nodes belonging to the
                 network with the goal of including the multiplex social
                 network as a mathematical representation that enables
                 us to consider multiple types of interactions, the
                 collective dynamics of diffusion and competition,
                 through social contagion and evolutionary game theory,
                 and the mesoscale organization in communities to drive
                 learning and cognition. Through a framework, we detail
                 the step by step modeling approach and show and discuss
                 our findings, applying it to a real dataset, by
                 demonstrating how the proposed model allows us to
                 detect deeply complex knowable roles of nodes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kenyeres:2021:CSD,
  author =       "Martin Kenyeres and Jozef Kenyeres",
  title =        "Comparative Study of Distributed Consensus Gossip
                 Algorithms for Network Size Estimation in Multi-Agent
                 Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "134",
  day =          "18",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050134",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/134",
  abstract =     "Determining the network size is a critical process in
                 numerous areas (e.g., computer science, logistic,
                 epidemiology, social networking services, mathematical
                 modeling, demography, etc.). However, many modern
                 real-world systems are so extensive that measuring
                 their size poses a serious challenge. Therefore, the
                 algorithms for determining/estimating this parameter in
                 an effective manner have been gaining popularity over
                 the past decades. In the paper, we analyze five
                 frequently applied distributed consensus gossip-based
                 algorithms for network size estimation in multi-agent
                 systems (namely, the Randomized gossip algorithm, the
                 Geographic gossip algorithm, the Broadcast gossip
                 algorithm, the Push-Sum protocol, and the Push-Pull
                 protocol). We examine the performance of the mentioned
                 algorithms with bounded execution over random geometric
                 graphs by applying two metrics: the number of sent
                 messages required for consensus achievement and the
                 estimation precision quantified as the median deviation
                 from the real value of the network size. The
                 experimental part consists of two scenarios-the
                 consensus achievement is conditioned by either the
                 values of the inner states or the network size
                 estimates-and, in both scenarios, either the
                 best-connected or the worst-connected agent is chosen
                 as the leader. The goal of this paper is to identify
                 whether all the examined algorithms are applicable to
                 estimating the network size, which algorithm provides
                 the best performance, how the leader selection can
                 affect the performance of the algorithms, and how to
                 most effectively configure the applied stopping
                 criterion.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Jung:2021:BIM,
  author =       "Hyunjun Jung and Dongwon Jeong",
  title =        "Blockchain Implementation Method for Interoperability
                 between {CBDCs}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "133",
  day =          "18",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050133",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/133",
  abstract =     "Central Bank Digital Currency (CBDC) is a digital
                 currency issued by a central bank. Motivated by the
                 financial crisis and prospect of a cashless society,
                 countries are researching CBDC. Recently, global
                 consideration has been given to paying basic income to
                 avoid consumer sentiment shrinkage and recession due to
                 epidemics. CBDC is coming into the spotlight as the way
                 to manage the public finance policy of nations
                 comprehensively. CBDC is studied by many countries. The
                 bank of the Bahamas released Sand Dollar. Each
                 country's central bank should consider the situation in
                 which CBDCs are exchanged. The transaction of the CDDB
                 is open data. Transaction registers CBDC exchange
                 information of the central bank in the blockchain. Open
                 data on currency exchange between countries will
                 provide information on the flow of money between
                 countries. This paper proposes a blockchain system and
                 management method based on the ISO/IEC 11179 metadata
                 registry for exchange between CBDCs that records
                 transactions between registered CBDCs. Each country's
                 CBDC will have a different implementation and time of
                 publication. We implement the blockchain system and
                 experiment with the operation method, measuring the
                 block generation time of blockchains using the proposed
                 method.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Pickering:2021:TVI,
  author =       "Brian Pickering",
  title =        "Trust, but Verify: Informed Consent, {AI}
                 Technologies, and Public Health Emergencies",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "132",
  day =          "18",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050132",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/132",
  abstract =     "To use technology or engage with research or medical
                 treatment typically requires user consent: agreeing to
                 terms of use with technology or services, or providing
                 informed consent for research participation, for
                 clinical trials and medical intervention, or as one
                 legal basis for processing personal data. Introducing
                 AI technologies, where explainability and
                 trustworthiness are focus items for both government
                 guidelines and responsible technologists, imposes
                 additional challenges. Understanding enough of the
                 technology to be able to make an informed decision, or
                 consent, is essential but involves an acceptance of
                 uncertain outcomes. Further, the contribution of
                 AI-enabled technologies not least during the COVID-19
                 pandemic raises ethical concerns about the governance
                 associated with their development and deployment. Using
                 three typical scenarios-contact tracing, big data
                 analytics and research during public emergencies-this
                 paper explores a trust-based alternative to consent.
                 Unlike existing consent-based mechanisms, this approach
                 sees consent as a typical behavioural response to
                 perceived contextual characteristics. Decisions to
                 engage derive from the assumption that all relevant
                 stakeholders including research participants will
                 negotiate on an ongoing basis. Accepting dynamic
                 negotiation between the main stakeholders as proposed
                 here introduces a specifically socio-psychological
                 perspective into the debate about human responses to
                 artificial intelligence. This trust-based consent
                 process leads to a set of recommendations for the
                 ethical use of advanced technologies as well as for the
                 ethical review of applied research projects.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liu:2021:HCS,
  author =       "Hongyu Liu and Rui Han",
  title =        "A Hierarchical Cache Size Allocation Scheme Based on
                 Content Dissemination in Information-Centric Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "131",
  day =          "15",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050131",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/131",
  abstract =     "With the rapid growth of mass content retrieval on the
                 Internet, Information-Centric Network (ICN) has become
                 one of the hotspots in the field of future network
                 architectures. The in-network cache is an important
                 feature of ICN. For better network performance in ICN,
                 the cache size on each node should be allocated in
                 proportion to its importance. However, in some current
                 studies, the importance of cache nodes is usually
                 determined by their location in the network topology,
                 ignoring their roles in the actual content transmission
                 process. In this paper, we focus on the allocation of
                 cache size for each node within a given total cache
                 space budget. We explore the impact of heterogeneous
                 cache allocation on content dissemination under the
                 same ICN infrastructure and we quantify the importance
                 of nodes from content dissemination and network
                 topology. To this purpose, we implement a hierarchy
                 partitioning method based on content dissemination,
                 then we formulate a set of weight calculation methods
                 for these hierarchies and to provide a per-node cache
                 space allocation to allocate the total cache space
                 budget to each node in the network. The performance of
                 the scheme is evaluated on the Garr topology, and the
                 average hit ratio, latency, and load are compared to
                 show that the proposed scheme has better performance in
                 these aspects than other schemes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Goodell:2021:DCA,
  author =       "Geoffrey Goodell and Hazem Danny Al-Nakib and Paolo
                 Tasca",
  title =        "A Digital Currency Architecture for Privacy and
                 Owner-Custodianship",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "130",
  day =          "14",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050130",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/130",
  abstract =     "In recent years, electronic retail payment mechanisms,
                 especially e-commerce and card payments at the point of
                 sale, have increasingly replaced cash in many developed
                 countries. As a result, societies are losing a critical
                 public retail payment option, and retail consumers are
                 losing important rights associated with using cash. To
                 address this concern, we propose an approach to digital
                 currency that would allow people without banking
                 relationships to transact electronically and privately,
                 including both e-commerce purchases and point-of-sale
                 purchases that are required to be cashless. Our
                 proposal introduces a government-backed,
                 privately-operated digital currency infrastructure to
                 ensure that every transaction is registered by a bank
                 or money services business, and it relies upon
                 non-custodial wallets backed by privacy-enhancing
                 technology, such as blind signatures or zero-knowledge
                 proofs, to ensure that transaction counterparties are
                 not revealed. Our approach to digital currency can also
                 facilitate more efficient and transparent clearing,
                 settlement, and management of systemic risk. We argue
                 that our system can restore and preserve the salient
                 features of cash, including privacy,
                 owner-custodianship, fungibility, and accessibility,
                 while also preserving fractional reserve banking and
                 the existing two-tiered banking system. We also show
                 that it is possible to introduce regulation of digital
                 currency transactions involving non-custodial wallets
                 that unconditionally protect the privacy of
                 end-users.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alsini:2021:HRM,
  author =       "Areej Alsini and Du Q. Huynh and Amitava Datta",
  title =        "Hashtag Recommendation Methods for {Twitter} and {Sina
                 Weibo}: a Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "129",
  day =          "14",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050129",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/129",
  abstract =     "Hashtag recommendation suggests hashtags to users
                 while they write microblogs in social media platforms.
                 Although researchers have investigated various methods
                 and factors that affect the performance of hashtag
                 recommendations in Twitter and Sina Weibo, a systematic
                 review of these methods is lacking. The objectives of
                 this study are to present a comprehensive overview of
                 research on hashtag recommendation for tweets and
                 present insights from previous research papers. In this
                 paper, we search for articles related to our research
                 between 2010 and 2020 from CiteSeer, IEEE Xplore,
                 Springer and ACM digital libraries. From the 61
                 articles included in this study, we notice that most of
                 the research papers were focused on the textual content
                 of tweets instead of other data. Furthermore,
                 collaborative filtering methods are seldom used solely
                 in hashtag recommendation. Taking this perspective, we
                 present a taxonomy of hashtag recommendation based on
                 the research methodologies that have been used. We
                 provide a critical review of each of the classes in the
                 taxonomy. We also discuss the challenges remaining in
                 the field and outline future research directions in
                 this area of study.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liu:2021:RTO,
  author =       "Jun Liu and Xiaohui Lian and Chang Liu",
  title =        "Research on Task-Oriented Computation Offloading
                 Decision in Space--Air--Ground Integrated Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "128",
  day =          "13",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050128",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/128",
  abstract =     "In Space-Air-Ground Integrated Networks (SAGIN),
                 computation offloading technology is a new way to
                 improve the processing efficiency of node tasks and
                 improve the limitation of computing storage resources.
                 To solve the problem of large delay and energy
                 consumption cost of task computation offloading, which
                 caused by the complex and variable network offloading
                 environment and a large amount of offloading tasks, a
                 computation offloading decision scheme based on Markov
                 and Deep Q Networks (DQN) is proposed. First, we select
                 the optimal offloading network based on the
                 characteristics of the movement of the task offloading
                 process in the network. Then, the task offloading
                 process is transformed into a Markov state transition
                 process to build a model of the computational
                 offloading decision process. Finally, the delay and
                 energy consumption weights are introduced into the DQN
                 algorithm to update the computation offloading decision
                 process, and the optimal offloading decision under the
                 low cost is achieved according to the task attributes.
                 The simulation results show that compared with the
                 traditional Lyapunov-based offloading decision scheme
                 and the classical Q-learning algorithm, the delay and
                 energy consumption are respectively reduced by 68.33\%
                 and 11.21\%, under equal weights when the offloading
                 task volume exceeds 500 Mbit. Moreover, compared with
                 offloading to edge nodes or backbone nodes of the
                 network alone, the proposed mixed offloading model can
                 satisfy more than 100 task requests with low energy
                 consumption and low delay. It can be seen that the
                 computation offloading decision proposed in this paper
                 can effectively reduce the delay and energy consumption
                 during the task computation offloading in the
                 Space-Air-Ground Integrated Network environment, and
                 can select the optimal offloading sites to execute the
                 tasks according to the characteristics of the task
                 itself.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Al-Maroof:2021:UAS,
  author =       "Rana Saeed Al-Maroof and Khadija Alhumaid and Ahmad
                 Qasim Alhamad and Ahmad Aburayya and Said Salloum",
  title =        "User Acceptance of Smart Watch for Medical Purposes:
                 an Empirical Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "127",
  day =          "12",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050127",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/127",
  abstract =     "This study aims to investigate the most effective and
                 interesting variables that urge use of the smartwatch
                 (SW) in a medical environment. To achieve this aim, the
                 study was framed using an innovative and integrated
                 research model, which is based on combining constructs
                 from a well-established theoretical model's TAM and
                 other features that are critical to the effectiveness
                 of SW which are content richness and personal
                 innovativeness. The Technology Acceptance Model (TAM)
                 is used to detect the determinants affecting the
                 adoption of SW. The current study depends on an online
                 questionnaire that is composed of (20) items. The
                 questionnaire is distributed among a group of doctors,
                 nurses, and administration staff in medical centers
                 within the UAE. The total number of respondents is
                 (325). The collected data were implemented to test the
                 study model and the proposed constructs and hypotheses
                 depending on the Smart PLS Software. The results of the
                 current study show that the main constructs in the
                 model contribute differently to the acceptance of SW.
                 Based on the previous assumption, content richness and
                 innovativeness are critical factors that enrich the
                 user's perceived usefulness. In addition, perceived
                 ease of use was significantly predictive of either
                 perceived usefulness or behavioral intention. Overall
                 findings suggest that SW is in high demand in the
                 medical field and is used as a common channel among
                 doctors and their patients and it facilitates the role
                 of transmitting information among its users. The
                 outcomes of the current study indicate the importance
                 of certain external factors for the acceptance of the
                 technology. The genuine value of this study lies in the
                 fact that it is based on a conceptual framework that
                 emphasizes the close relationship between the TAM
                 constructs of perceived usefulness and perceived ease
                 of use to the construct of content richness, and
                 innovativeness. Finally, this study helps us recognize
                 the embedded motives for using SW in a medical
                 environment, where the main motive is to enhance and
                 facilitate the effective roles of doctors and
                 patients.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rossler:2021:RVF,
  author =       "Jannik R{\"o}{\ss}ler and Jiachen Sun and Peter
                 Gloor",
  title =        "Reducing Videoconferencing Fatigue through Facial
                 Emotion Recognition",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "126",
  day =          "12",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050126",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/126",
  abstract =     "In the last 14 months, COVID-19 made face-to-face
                 meetings impossible and this has led to rapid growth in
                 videoconferencing. As highly social creatures, humans
                 strive for direct interpersonal interaction, which
                 means that in most of these video meetings the webcam
                 is switched on and people are ``looking each other in
                 the eyes''. However, it is far from clear what the
                 psychological consequences of this shift to virtual
                 face-to-face communication are and if there are methods
                 to alleviate ``videoconferencing fatigue''. We have
                 studied the influence of emotions of meeting
                 participants on the perceived outcome of video
                 meetings. Our experimental setting consisted of 35
                 participants collaborating in eight teams over Zoom in
                 a one semester course on Collaborative Innovation
                 Networks in bi-weekly video meetings, where each team
                 presented its progress. Emotion was tracked through
                 Zoom face video snapshots using facial emotion
                 recognition that recognized six emotions (happy, sad,
                 fear, anger, neutral, and surprise). Our dependent
                 variable was a score given after each presentation by
                 all participants except the presenter. We found that
                 the happier the speaker is, the happier and less
                 neutral the audience is. More importantly, we found
                 that the presentations that triggered wide swings in
                 ``fear'' and ``joy'' among the participants are
                 correlated with a higher rating. Our findings provide
                 valuable input for online video presenters on how to
                 conduct better and less tiring meetings; this will lead
                 to a decrease in ``videoconferencing fatigue''.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Vladyko:2021:TPA,
  author =       "Andrei Vladyko and Anastasia Spirkina and Vasiliy
                 Elagin",
  title =        "Towards Practical Applications in Modeling Blockchain
                 System",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "125",
  day =          "12",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050125",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/125",
  abstract =     "Like multiservice networks, blockchain technology is
                 currently experiencing significant development because
                 of its decentralization and ability to organize secure,
                 seamless, reliable data exchange and storage. Due to
                 the significant demand for the technology, there is a
                 need to analyze the impact of these technology
                 processes on network characteristics to predict traffic
                 behavior and ensure required quality indicators, as
                 well as on the stability of public communication
                 network elements when blockchain technology operates.
                 Conducting a full-scale experiment is a time-consuming
                 task that cannot always be accomplished, so in this
                 paper, the authors propose considering approaches to
                 modeling these systems and, as an example, propose to
                 use a simulation system to assess the performance of
                 the network and its elements.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Son:2021:DKG,
  author =       "Jiseong Son and Chul-Su Lim and Hyoung-Seop Shim and
                 Ji-Sun Kang",
  title =        "Development of Knowledge Graph for Data Management
                 Related to Flooding Disasters Using Open Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "124",
  day =          "11",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050124",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/124",
  abstract =     "Despite the development of various technologies and
                 systems using artificial intelligence (AI) to solve
                 problems related to disasters, difficult challenges are
                 still being encountered. Data are the foundation to
                 solving diverse disaster problems using AI, big data
                 analysis, and so on. Therefore, we must focus on these
                 various data. Disaster data depend on the domain by
                 disaster type and include heterogeneous data and lack
                 interoperability. In particular, in the case of open
                 data related to disasters, there are several issues,
                 where the source and format of data are different
                 because various data are collected by different
                 organizations. Moreover, the vocabularies used for each
                 domain are inconsistent. This study proposes a
                 knowledge graph to resolve the heterogeneity among
                 various disaster data and provide interoperability
                 among domains. Among disaster domains, we describe the
                 knowledge graph for flooding disasters using Korean
                 open datasets and cross-domain knowledge graphs.
                 Furthermore, the proposed knowledge graph is used to
                 assist, solve, and manage disaster problems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Shi:2021:CMS,
  author =       "Yanjun Shi and Hao Yu and Yijia Guo and Zhiheng Yuan",
  title =        "A Collaborative Merging Strategy with Lane Changing in
                 Multilane Freeway On-Ramp Area with {V2X} Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "123",
  day =          "10",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050123",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/123",
  abstract =     "The merging area of the freeway is an area with a high
                 incidence of traffic accidents. With the development of
                 connected and automated vehicles (CAVs) and V2X
                 technology, the traffic efficiency of freeway ramp
                 areas has been significantly improved. However, current
                 research mostly focuses on merging a single mainline
                 lane and ramp, and there are few cases of multiple
                 lanes. In this paper, we present a collaborative
                 merging model with a rule-based lane-changing strategy
                 in a V2X environment. First, the vehicle selects the
                 appropriate gap to change lanes safely without
                 affecting other vehicles. Meanwhile, we established a
                 linear time discrete model to optimize the trajectory
                 of vehicles in real-time. Finally, the proposed model
                 and strategy were implemented in SUMO and Python. The
                 simulation results showed that the merging model we
                 proposed based on the lane-changing strategy had good
                 performance in terms of the number of stops, average
                 delay, and average speed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Polasko:2021:IMU,
  author =       "Ken Polasko and Pedro Ponce and Arturo Molina",
  title =        "An Income Model Using Historical Data, Power-Law
                 Distributions and {Monte Carlo} Method for University
                 Technology Transfer Offices",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "122",
  day =          "06",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050122",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/122",
  abstract =     "Engineering education pushes the creation of new
                 technology to solve community problems. The process of
                 technology transfer promotes educational innovation in
                 universities, a vital process that can improve
                 citizens' quality of life in cities and rural
                 communities. As a result, university technology
                 transfer offices (TTOs) have to create strategies that
                 motivate students and researchers to generate
                 technology. Thus, a primary challenge that TTOs face is
                 to know and communicate the income potential compared
                 to their much more predictable and limited expense
                 budgets. Institutional budgeting for a TTO's growth
                 would be simplified if the office were on a solid
                 financial footing, i.e., breaking even or making a
                 financial return. Many offices assume that income is
                 unpredictable, that it is a lottery, luck, and more
                 stakes in the fire improve the odds of hitting a
                 winner, etc. These common assumptions or beliefs
                 provide only a vague insight into how to move an
                 intellectual property (IP) portfolio strategy forward.
                 How can a TTO be assessed for quantitative value and
                 not just be a cost center adding qualitative value?
                 This paper illustrates the first steps to understanding
                 how to project potential income versus a much more
                 predictable expense budget, which would allow
                 universities to improve their technology transfer
                 strategy and results. As a result, TTOs would operate
                 under a more sustainable IP portfolio strategy, promote
                 educational innovation in universities, and generate a
                 more significant community impact.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Cantini:2021:EML,
  author =       "Riccardo Cantini and Fabrizio Marozzo and Alessio
                 Orsino and Domenico Talia and Paolo Trunfio",
  title =        "Exploiting Machine Learning for Improving In-Memory
                 Execution of Data-Intensive Workflows on Parallel
                 Machines",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "121",
  day =          "05",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050121",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/121",
  abstract =     "Workflows are largely used to orchestrate complex sets
                 of operations required to handle and process huge
                 amounts of data. Parallel processing is often vital to
                 reduce execution time when complex data-intensive
                 workflows must be run efficiently, and at the same
                 time, in-memory processing can bring important benefits
                 to accelerate execution. However, optimization
                 techniques are necessary to fully exploit in-memory
                 processing, avoiding performance drops due to memory
                 saturation events. This paper proposed a novel
                 solution, called the Intelligent In-memory Workflow
                 Manager (IIWM), for optimizing the in-memory execution
                 of data-intensive workflows on parallel machines. IIWM
                 is based on two complementary strategies: (1) a machine
                 learning strategy for predicting the memory occupancy
                 and execution time of workflow tasks; (2) a scheduling
                 strategy that allocates tasks to a computing node,
                 taking into account the (predicted) memory occupancy
                 and execution time of each task and the memory
                 available on that node. The effectiveness of the
                 machine learning-based predictor and the scheduling
                 strategy were demonstrated experimentally using as a
                 testbed, Spark, a high-performance Big Data processing
                 framework that exploits in-memory computing to speed up
                 the execution of large-scale applications. In
                 particular, two synthetic workflows were prepared for
                 testing the robustness of the IIWM in scenarios
                 characterized by a high level of parallelism and a
                 limited amount of memory reserved for execution.
                 Furthermore, a real data analysis workflow was used as
                 a case study, for better assessing the benefits of the
                 proposed approach. Thanks to high accuracy in
                 predicting resources used at runtime, the IIWM was able
                 to avoid disk writes caused by memory saturation,
                 outperforming a traditional strategy in which only
                 dependencies among tasks are taken into account.
                 Specifically, the IIWM achieved up to a 31\% 31\% 31\%
                 and a 40\% 40\% 40\% reduction of makespan and a
                 performance improvement up to 1.45$ \times $ 1.45$
                 \times $ 1.45$ \times $ and 1.66$ \times $ 1.66$ \times
                 $ 1.66$ \times $ on the synthetic workflows and the
                 real case study, respectively.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhao:2021:APA,
  author =       "Yulin Zhao and Junke Li and Jiang-E Wang",
  title =        "Analysis and Prediction of {``AI + Education''}
                 Attention Based on {Baidu} Index --- Taking {Guizhou
                 Province} as an Example",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "120",
  day =          "30",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050120",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/120",
  abstract =     "Studying the attention of ``artificial intelligence +
                 education'' in ethnic areas is of great significance
                 for China for promoting the integrated development of
                 new educational modes and modern technology in the
                 western region. Guizhou province is an area inhabited
                 by ethnic minorities, located in the heart of Southwest
                 China. The development of its intelligent education has
                 strong enlightenment for the whole country and the
                 region. Therefore, this paper selects the Baidu Index
                 of ``artificial intelligence (AI) + education'' in
                 Guizhou province from 2013 to 2020, analyzes the
                 spatial-temporal characteristics of its network
                 attention by using the elastic coefficient method, and
                 builds the ARIMA model on this basis to predict future
                 development. The results show that the public's
                 attention to ``AI + education'' differs significantly
                 in time and space. Then, according to the prediction
                 results, this paper puts forward relevant suggestions
                 for the country to promote the sustainable development
                 of education in western ethnic areas.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hueso-Romero:2021:STM,
  author =       "Jos{\'e} Javier Hueso-Romero and Javier Gil-Quintana
                 and Helen Hasbun and Sara Osuna-Acedo",
  title =        "The Social and Transfer Massive Open Online Course:
                 Post-Digital Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "119",
  day =          "30",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050119",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/119",
  abstract =     "This research provides a current view on post-digital
                 learning experiences with a massive open online course
                 (MOOC), in relation to user profiles, universal
                 instructional design, digital resources, inclusive
                 activities and collaborative assessment. The study is
                 based on a mixed research methodology, creating a
                 questionnaire aimed at people with experience in any
                 MOOC typology, in which the learning methodology, the
                 instructional didactic design of the MOOCs, the
                 resources, proposed activities, and accessibility are
                 analyzed. Additionally, interviews and focus groups
                 were carried out with the creators of massive open
                 online social courses alongside the students of the
                 official Master of Communication and Education on the
                 Internet, offered by the UNED (Universidad Nacional de
                 Educaci{\'o}n a Distancia-Spain), with the subject of
                 virtual participation scenarios. The data obtained are
                 subjected to statistical tests to determine the
                 scientific rigor, such as Cronbach's alpha, the
                 Kolmogorov--Smirnov normality test, and the
                 non-parametric tests of Spearman's correlation
                 coefficient and Kendall's Tau b. In conclusion, the
                 social massive open online course/transfer massive open
                 online course model is evidenced as a projected
                 approach in social networks. The sMOOC and tMOOC are
                 online training models, which are in constant
                 development and evolution, as a social, creative,
                 collaborative, interactive, and inclusive learning
                 methodology, offering new challenges for the digital
                 distance education of the future. The research carried
                 out is only related and linked to the experiences of
                 different people with the sMOOC and tMOOC.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Al-Ansi:2021:SIE,
  author =       "Ahmed Al-Ansi and Abdullah M. Al-Ansi and Ammar
                 Muthanna and Ibrahim A. Elgendy and Andrey
                 Koucheryavy",
  title =        "Survey on Intelligence Edge Computing in {6G}:
                 Characteristics, Challenges, Potential Use Cases, and
                 Market Drivers",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "118",
  day =          "30",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050118",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/118",
  abstract =     "Intelligence Edge Computing (IEC) is the key enabler
                 of emerging 5G technologies networks and beyond. IEC is
                 considered to be a promising backbone of future
                 services and wireless communication systems in 5G
                 integration. In addition, IEC enables various use cases
                 and applications, including autonomous vehicles,
                 augmented and virtual reality, big data analytic, and
                 other customer-oriented services. Moreover, it is one
                 of the 5G technologies that most enhanced market
                 drivers in different fields such as customer service,
                 healthcare, education methods, IoT in agriculture and
                 energy sustainability. However, 5G technological
                 improvements face many challenges such as traffic
                 volume, privacy, security, digitization capabilities,
                 and required latency. Therefore, 6G is considered to be
                 promising technology for the future. To this end,
                 compared to other surveys, this paper provides a
                 comprehensive survey and an inclusive overview of
                 Intelligence Edge Computing (IEC) technologies in 6G
                 focusing on main up-to-date characteristics,
                 challenges, potential use cases and market drivers.
                 Furthermore, we summarize research efforts on IEC in 5G
                 from 2014 to 2021, in which the integration of IEC and
                 5G technologies are highlighted. Finally, open research
                 challenges and new future directions in IEC with 6G
                 networks will be discussed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ferretti:2021:HSI,
  author =       "Marco Ferretti and Serena Nicolazzo and Antonino
                 Nocera",
  title =        "{H2O}: Secure Interactions in {IoT} via Behavioral
                 Fingerprinting",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "117",
  day =          "30",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050117",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/117",
  abstract =     "Sharing data and services in the Internet of Things
                 (IoT) can give rise to significant security concerns
                 with information being sensitive and vulnerable to
                 attacks. In such an environment, objects can be either
                 public resources or owned by humans. For this reason,
                 the need of monitoring the reliability of all involved
                 actors, both persons and smart objects, assuring that
                 they really are who they claim to be, is becoming an
                 essential property of the IoT, with the increase in the
                 pervasive adoption of such a paradigm. In this paper,
                 we tackle this problem by proposing a new framework,
                 called H2O (Human to Object). Our solution is able to
                 continuously authenticate an entity in the network,
                 providing a reliability assessment mechanism based on
                 behavioral fingerprinting. A detailed security analysis
                 evaluates the robustness of the proposed protocol;
                 furthermore, a performance analysis shows the
                 feasibility of our approach.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Nikou:2021:FMA,
  author =       "Stavros A. Nikou and Anastasios A. Economides",
  title =        "A Framework for Mobile-Assisted Formative Assessment
                 to Promote Students' Self-Determination",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "116",
  day =          "30",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050116",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/116",
  abstract =     "Motivation is an important issue to consider when
                 designing learning activities, including mobile
                 learning and assessment. While previous research
                 provides evidence for the motivational impact of mobile
                 learning, not many pedagogical frameworks exist for the
                 design of mobile-assisted learning and assessment. The
                 current study is grounded in the Self-Determination
                 Theory of motivation and proposes a pedagogical
                 framework for mobile-assisted formative assessment,
                 aiming at enhancing student motivation. For a
                 preliminary evaluation of the framework, fifty-one
                 students from a public European high school
                 participated in a series of formative assessment
                 activities. The tasks that were implemented according
                 to the proposed mobile-based formative assessment
                 framework had a significant positive impact on student
                 perceived levels of autonomy, competence, and
                 relatedness, enhancing students' intrinsic motivation
                 levels. Study findings highlighted the capacity of the
                 proposed framework to guide the design of mobile-based
                 formative assessment activities that enhance and
                 promote student motivation. The study makes a
                 theoretical contribution by proposing a framework that
                 aligns mobile learning and assessment with elements of
                 the Self-Determination Theory of motivation and also
                 has a practical contribution by implementing mobile
                 learning and assessment practices that have the
                 potential to promote student motivation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ojo:2021:EEL,
  author =       "Mike Oluwatayo Ojo and Davide Adami and Stefano
                 Giordano",
  title =        "Experimental Evaluation of a {LoRa} Wildlife
                 Monitoring Network in a Forest Vegetation Area",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "115",
  day =          "29",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050115",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/115",
  abstract =     "Smart agriculture and wildlife monitoring are one of
                 the recent trends of Internet of Things (IoT)
                 applications, which are evolving in providing
                 sustainable solutions from producers. This article
                 details the design, development and assessment of a
                 wildlife monitoring application for IoT animal
                 repelling devices that is able to cover large areas,
                 thanks to the low power wide area networks (LPWAN),
                 which bridge the gap between cellular technologies and
                 short range wireless technologies. LoRa, the global
                 de-facto LPWAN, continues to attract attention given
                 its open specification and ready availability of
                 off-the-shelf hardware, with claims of several
                 kilometers of range in harsh challenging environments.
                 At first, this article presents a survey of the LPWAN
                 for smart agriculture applications. We proceed to
                 evaluate the performance of LoRa transmission
                 technology operating in the 433 MHz and 868 MHz bands,
                 aimed at wildlife monitoring in a forest vegetation
                 area. To characterize the communication link, we mainly
                 use the signal-to-noise ratio (SNR), received signal
                 strength indicator (RSSI) and packet delivery ratio
                 (PDR). Findings from this study show that achievable
                 performance can greatly vary between the 433 MHz and
                 868 MHz bands, and prompt caution is required when
                 taking numbers at face value, as this can have
                 implications for IoT applications. In addition, our
                 results show that the link reaches up to 860 m in the
                 highly dense forest vegetation environment, while in
                 the not so dense forest vegetation environment, it
                 reaches up to 2050 m.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Helmstetter:2021:CLS,
  author =       "Stefan Helmstetter and Heiko Paulheim",
  title =        "Collecting a Large Scale Dataset for Classifying Fake
                 News Tweets Using Weak Supervision",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "114",
  day =          "29",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050114",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/114",
  abstract =     "The problem of automatic detection of fake news in
                 social media, e.g., on Twitter, has recently drawn some
                 attention. Although, from a technical perspective, it
                 can be regarded as a straight-forward, binary
                 classification problem, the major challenge is the
                 collection of large enough training corpora, since
                 manual annotation of tweets as fake or non-fake news is
                 an expensive and tedious endeavor, and recent
                 approaches utilizing distributional semantics require
                 large training corpora. In this paper, we introduce an
                 alternative approach for creating a large-scale dataset
                 for tweet classification with minimal user
                 intervention. The approach relies on weak supervision
                 and automatically collects a large-scale, but very
                 noisy, training dataset comprising hundreds of
                 thousands of tweets. As a weak supervision signal, we
                 label tweets by their source, i.e., trustworthy or
                 untrustworthy source, and train a classifier on this
                 dataset. We then use that classifier for a different
                 classification target, i.e., the classification of fake
                 and non-fake tweets. Although the labels are not
                 accurate according to the new classification target
                 (not all tweets by an untrustworthy source need to be
                 fake news, and vice versa), we show that despite this
                 unclean, inaccurate dataset, the results are comparable
                 to those achieved using a manually labeled set of
                 tweets. Moreover, we show that the combination of the
                 large-scale noisy dataset with a human labeled one
                 yields more advantageous results than either of the two
                 alone.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bonanni:2021:DCA,
  author =       "Michele Bonanni and Francesco Chiti and Romano
                 Fantacci and Laura Pierucci",
  title =        "Dynamic Control Architecture Based on Software Defined
                 Networking for the {Internet of Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "113",
  day =          "28",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050113",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/113",
  abstract =     "Software Defined Networking (SDN) provides a new
                 perspective for the Internet of Things (IoT), since,
                 with the separation of the control from the data
                 planes, it is viable to optimise the traditional
                 networks operation management. In particular, the SDN
                 Controller has a global vision of the network of
                 sensors/actuators domain, allowing real-time network
                 nodes and data flows reconfiguration. As a consequence,
                 devices, usually facing limited communications and
                 computing resources, are relieved of the route
                 selection task in a distributed and, thus, suboptimal
                 way. This paper proposes a SDN-IoT architecture,
                 specifically focusing on the Controller design, which
                 dynamically optimises in real time the end-to-end flows
                 delivery. In particular, the dynamic routing policy
                 adaptation is based on the real-time estimation of the
                 network status and it allows jointly minimising the
                 end-to-end latency and energy consumption and,
                 consequently, to improve the network life time. The
                 performance of the proposed approach is analysed in
                 terms of the average latency, energy consumption and
                 overhead, pointing out a better behaviour in comparison
                 with the existing distributed approaches.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Herrera:2021:ERL,
  author =       "Mauricio Herrera and Alex Godoy-Fa{\'u}ndez",
  title =        "Exploring the Roles of Local Mobility Patterns,
                 Socioeconomic Conditions, and Lockdown Policies in
                 Shaping the Patterns of {COVID-19} Spread",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "112",
  day =          "28",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050112",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/112",
  abstract =     "The COVID-19 crisis has shown that we can only prevent
                 the risk of mass contagion through timely, large-scale,
                 coordinated, and decisive actions. This pandemic has
                 also highlighted the critical importance of generating
                 rigorous evidence for decision-making, and actionable
                 insights from data, considering further the intricate
                 web of causes and drivers behind observed patterns of
                 contagion diffusion. Using mobility, socioeconomic, and
                 epidemiological data recorded throughout the pandemic
                 development in the Santiago Metropolitan Region, we
                 seek to understand the observed patterns of contagion.
                 We characterize human mobility patterns during the
                 pandemic through different mobility indices and
                 correlate such patterns with the observed contagion
                 diffusion, providing data-driven models for insights,
                 analysis, and inferences. Through these models, we
                 examine some effects of the late application of
                 mobility restrictions in high-income urban regions that
                 were affected by high contagion rates at the beginning
                 of the pandemic. Using augmented synthesis control
                 methods, we study the consequences of the early lifting
                 of mobility restrictions in low-income sectors
                 connected by public transport to high-risk and
                 high-income communes. The Santiago Metropolitan Region
                 is one of the largest Latin American metropolises with
                 features that are common to large cities. Therefore, it
                 can be used as a relevant case study to unravel complex
                 patterns of the spread of COVID-19.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alzahrani:2021:DNI,
  author =       "Abdulsalam O. Alzahrani and Mohammed J. F. Alenazi",
  title =        "Designing a Network Intrusion Detection System Based
                 on Machine Learning for Software Defined Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "111",
  day =          "28",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050111",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/111",
  abstract =     "Software-defined Networking (SDN) has recently
                 developed and been put forward as a promising and
                 encouraging solution for future internet architecture.
                 Managed, the centralized and controlled network has
                 become more flexible and visible using SDN. On the
                 other hand, these advantages bring us a more vulnerable
                 environment and dangerous threats, causing network
                 breakdowns, systems paralysis, online banking frauds
                 and robberies. These issues have a significantly
                 destructive impact on organizations, companies or even
                 economies. Accuracy, high performance and real-time
                 systems are essential to achieve this goal
                 successfully. Extending intelligent machine learning
                 algorithms in a network intrusion detection system
                 (NIDS) through a software-defined network (SDN) has
                 attracted considerable attention in the last decade.
                 Big data availability, the diversity of data analysis
                 techniques, and the massive improvement in the machine
                 learning algorithms enable the building of an
                 effective, reliable and dependable system for detecting
                 different types of attacks that frequently target
                 networks. This study demonstrates the use of machine
                 learning algorithms for traffic monitoring to detect
                 malicious behavior in the network as part of NIDS in
                 the SDN controller. Different classical and advanced
                 tree-based machine learning techniques, Decision Tree,
                 Random Forest and XGBoost are chosen to demonstrate
                 attack detection. The NSL-KDD dataset is used for
                 training and testing the proposed methods; it is
                 considered a benchmarking dataset for several
                 state-of-the-art approaches in NIDS. Several advanced
                 preprocessing techniques are performed on the dataset
                 in order to extract the best form of the data, which
                 produces outstanding results compared to other systems.
                 Using just five out of 41 features of NSL-KDD, a
                 multi-class classification task is conducted by
                 detecting whether there is an attack and classifying
                 the type of attack (DDoS, PROBE, R2L, and U2R),
                 accomplishing an accuracy of 95.95\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Duradoni:2021:RSI,
  author =       "Mirko Duradoni and Stefania Collodi and Serena
                 Coppolino Perfumi and Andrea Guazzini",
  title =        "Reviewing Stranger on the {Internet}: The Role of
                 Identifiability through {``Reputation''} in Online
                 Decision Making",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "110",
  day =          "27",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050110",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/110",
  abstract =     "The stranger on the Internet effect has been studied
                 in relation to self-disclosure. Nonetheless,
                 quantitative evidence about how people mentally
                 represent and perceive strangers online is still
                 missing. Given the dynamic development of web
                 technologies, quantifying how much strangers can be
                 considered suitable for pro-social acts such as
                 self-disclosure appears fundamental for a whole series
                 of phenomena ranging from privacy protection to fake
                 news spreading. Using a modified and online version of
                 the Ultimatum Game (UG), we quantified the mental
                 representation of the stranger on the Internet effect
                 and tested if people modify their behaviors according
                 to the interactors' identifiability (i.e., reputation).
                 A total of 444 adolescents took part in a 2 $ \times $
                 2 design experiment where reputation was set active or
                 not for the two traditional UG tasks. We discovered
                 that, when matched with strangers, people donate the
                 same amount of money as if the other has a good
                 reputation. Moreover, reputation significantly affected
                 the donation size, the acceptance rate and the feedback
                 decision making as well.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tosi:2021:HSA,
  author =       "Davide Tosi and Alessandro Siro Campi",
  title =        "How Schools Affected the {COVID-19} Pandemic in
                 {Italy}: Data Analysis for {Lombardy Region}, {Campania
                 Region}, and {Emilia Region}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "109",
  day =          "27",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050109",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/109",
  abstract =     "Background: Coronavirus Disease 2019 (COVID-19) is the
                 main discussed topic worldwide in 2020 and at the
                 beginning of the Italian epidemic, scientists tried to
                 understand the virus diffusion and the epidemic curve
                 of positive cases with controversial findings and
                 numbers. Objectives: In this paper, a data analytics
                 study on the diffusion of COVID-19 in Lombardy Region
                 and Campania Region is developed in order to identify
                 the driver that sparked the second wave in Italy.
                 Methods: Starting from all the available official data
                 collected about the diffusion of COVID-19, we analyzed
                 Google mobility data, school data and infection data
                 for two big regions in Italy: Lombardy Region and
                 Campania Region, which adopted two different approaches
                 in opening and closing schools. To reinforce our
                 findings, we also extended the analysis to the Emilia
                 Romagna Region. Results: The paper shows how different
                 policies adopted in school opening/closing may have had
                 an impact on the COVID-19 spread, while other factors
                 related to citizen mobility did not affect the second
                 Italian wave. Conclusions: The paper shows that a clear
                 correlation exists between the school contagion and the
                 subsequent temporal overall contagion in a geographical
                 area. Moreover, it is clear that highly populated
                 provinces have the greatest spread of the virus.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Guarino:2021:IUS,
  author =       "Stefano Guarino and Enrico Mastrostefano and Massimo
                 Bernaschi and Alessandro Celestini and Marco
                 Cianfriglia and Davide Torre and Lena Rebecca Zastrow",
  title =        "Inferring Urban Social Networks from Publicly
                 Available Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "108",
  day =          "26",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050108",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/108",
  abstract =     "The definition of suitable generative models for
                 synthetic yet realistic social networks is a widely
                 studied problem in the literature. By not being tied to
                 any real data, random graph models cannot capture all
                 the subtleties of real networks and are inadequate for
                 many practical contexts-including areas of research,
                 such as computational epidemiology, which are recently
                 high on the agenda. At the same time, the so-called
                 contact networks describe interactions, rather than
                 relationships, and are strongly dependent on the
                 application and on the size and quality of the sample
                 data used to infer them. To fill the gap between these
                 two approaches, we present a data-driven model for
                 urban social networks, implemented and released as open
                 source software. By using just widely available
                 aggregated demographic and social-mixing data, we are
                 able to create, for a territory of interest, an
                 age-stratified and geo-referenced synthetic population
                 whose individuals are connected by ``strong ties'' of
                 two types: intra-household (e.g., kinship) or
                 friendship. While household links are entirely
                 data-driven, we propose a parametric probabilistic
                 model for friendship, based on the assumption that
                 distances and age differences play a role, and that not
                 all individuals are equally sociable. The demographic
                 and geographic factors governing the structure of the
                 obtained network, under different configurations, are
                 thoroughly studied through extensive simulations
                 focused on three Italian cities of different size.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Carchiolo:2021:MIU,
  author =       "Vincenza Carchiolo and Alessandro Longheu and Michele
                 Malgeri and Giuseppe Mangioni and Marialaura Previti",
  title =        "Mutual Influence of Users Credibility and News
                 Spreading in Online Social Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "107",
  day =          "25",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050107",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/107",
  abstract =     "A real-time news spreading is now available for
                 everyone, especially thanks to Online Social Networks
                 (OSNs) that easily endorse gate watching, so the
                 collective intelligence and knowledge of dedicated
                 communities are exploited to filter the news flow and
                 to highlight and debate relevant topics. The main
                 drawback is that the responsibility for judging the
                 content and accuracy of information moves from editors
                 and journalists to online information users, with the
                 side effect of the potential growth of fake news. In
                 such a scenario, trustworthiness about information
                 providers cannot be overlooked anymore, rather it more
                 and more helps in discerning real news from fakes. In
                 this paper we evaluate how trustworthiness among OSN
                 users influences the news spreading process. To this
                 purpose, we consider the news spreading as a
                 Susceptible-Infected-Recovered (SIR) process in OSN,
                 adding the contribution credibility of users as a layer
                 on top of OSN. Simulations with both fake and true news
                 spreading on such a multiplex network show that the
                 credibility improves the diffusion of real news while
                 limiting the propagation of fakes. The proposed
                 approach can also be extended to real social
                 networks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Standl:2021:PMM,
  author =       "Bernhard Standl and Nadine Schlomske-Bodenstein",
  title =        "A Pattern Mining Method for Teaching Practices",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "106",
  day =          "23",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050106",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/106",
  abstract =     "When integrating digital technology into teaching,
                 many teachers experience similar challenges.
                 Nevertheless, sharing experiences is difficult as it is
                 usually not possible to transfer teaching scenarios
                 directly from one subject to another because
                 subject-specific characteristics make it difficult to
                 reuse them. To address this problem, instructional
                 scenarios can be described as patterns, which has
                 already been applied in educational contexts. Patterns
                 capture proven teaching strategies and describe
                 teaching scenarios in a unified structure that can be
                 reused. Since priorities for content, methods, and
                 tools are different in each subject, we show an
                 approach to develop a domain-independent graph database
                 to collect digital teaching practices from a taxonomic
                 structure via the intermediate step of an ontology.
                 Furthermore, we outline a method to identify effective
                 teaching practices from interdisciplinary data as
                 patterns from the graph database using an association
                 rule algorithm. The results show that an
                 association-based analysis approach can derive initial
                 indications of effective teaching scenarios.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yousif:2021:ITD,
  author =       "Mohamed Yousif and Chaminda Hewage and Liqaa Nawaf",
  title =        "{IoT} Technologies during and Beyond {COVID-19}: a
                 Comprehensive Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "105",
  day =          "23",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050105",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/105",
  abstract =     "The COVID-19 pandemic provided a much-needed sanity
                 check for IoT-inspired frameworks and solutions. IoT
                 solutions such as remote health monitoring and contact
                 tracing provided support for authorities to
                 successfully manage the spread of the coronavirus. This
                 article provides the first comprehensive review of key
                 IoT solutions that have had an impact on COVID-19 in
                 healthcare, contact tracing, and transportation during
                 the pandemic. Each sector is investigated in depth; and
                 potential applications, social and economic impact, and
                 barriers for mass adaptation are discussed in detail.
                 Furthermore, it elaborates on the challenges and
                 opportunities for IoT framework solutions in the
                 immediate post-COVID-19 era. To this end, privacy and
                 security concerns of IoT applications are analyzed in
                 depth and emerging standards and code of practices for
                 mass adaptation are also discussed. The main
                 contribution of this review paper is the in-depth
                 analysis and categorization of sector-wise IoT
                 technologies, which have the potential to be prominent
                 applications in the new normal. IoT applications in
                 each selected sector are rated for their potential
                 economic and social impact, timeline for mass
                 adaptation, and Technology Readiness Level (TRL). In
                 addition, this article outlines potential research
                 directions for next-generation IoT applications that
                 would facilitate improved performance with preserved
                 privacy and security, as well as wider adaptation by
                 the population at large.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Al-Naime:2021:RMM,
  author =       "Khalid Al-Naime and Adnan Al-Anbuky and Grant
                 Mawston",
  title =        "Remote Monitoring Model for the Preoperative
                 Prehabilitation Program of Patients Requiring Abdominal
                 Surgery",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "104",
  day =          "22",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050104",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/104",
  abstract =     "Physical fitness and level of activity are considered
                 important factors for patients with cancer undergoing
                 major abdominal surgery. Cancer patients with low
                 fitness capacity are at greater risk of postoperative
                 complications, longer hospital stays, and mortality.
                 One of the main challenges facing both healthcare
                 providers and patients is to improve the patient's
                 physical fitness within the available short period
                 (four to six weeks) prior to surgery. Supervised and
                 unsupervised physical prehabilitation programs are the
                 most common recommended methods for enhancing
                 postoperative outcomes in patients undergoing abdominal
                 surgery. Due to obstacles such as geographical
                 isolation, many patients have limited access to medical
                 centers and facilities that provide onsite
                 prehabilitation programs. This article presents a
                 review of the literature and the development of a model
                 that can remotely monitor physical activities during
                 the prehabilitation period. The mixed prehabilitation
                 model includes the identification of fundamental
                 parameters of physical activities (type, intensity,
                 frequency, and duration) over time. A mathematical
                 model has been developed to offer a solution for both
                 the healthcare provider and patients. This offers the
                 opportunity for physicians or physiotherapists to
                 monitor patients performing their prescribed physical
                 exercises in real time. The model that has been
                 developed is embedded within the internet of things
                 (IoT) system, which calculates the daily and weekly
                 efforts made by the patients and automatically stores
                 this in a comma-separated values (CSV) file that
                 medical staff can access. In addition, this model
                 allows the patient to compensate for missed prescribed
                 activity by adding additional efforts to meet the
                 prehabilitation requirements. As a result, healthcare
                 staff are provided with feedback on patient engagement
                 in prescribed exercise during the period of the
                 prehabilitation program.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bressan:2021:DLB,
  author =       "Giulia Bressan and Giulia Cisotto and Gernot R.
                 M{\"u}ller-Putz and Selina Christin Wriessnegger",
  title =        "Deep Learning-Based Classification of Fine Hand
                 Movements from Low Frequency {EEG}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "5",
  pages =        "103",
  day =          "21",
  month =        apr,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13050103",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 28 20:44:52 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/5/103",
  abstract =     "The classification of different fine hand movements
                 from electroencephalogram (EEG) signals represents a
                 relevant research challenge, e.g., in BCI applications
                 for motor rehabilitation. Here, we analyzed two
                 different datasets where fine hand movements (touch,
                 grasp, palmar, and lateral grasp) were performed in a
                 self-paced modality. We trained and tested a newly
                 proposed CNN, and we compared its classification
                 performance with two well-established machine learning
                 models, namely, shrinkage-linear discriminant analysis
                 (LDA) and Random Forest (RF). Compared to previous
                 literature, we included neuroscientific evidence, and
                 we trained our Convolutional Neural Network (CNN) model
                 on the so-called movement-related cortical potentials
                 (MRCPs). They are EEG amplitude modulations at low
                 frequencies, i.e., (0.3,3) Hz that have been proved to
                 encode several properties of the movements, e.g., type
                 of grasp, force level, and speed. We showed that CNN
                 achieved good performance in both datasets (accuracy of
                 0.70\pm 0.11 and 0.64\pm 0.10, for the two datasets,
                 respectively), and they were similar or superior to the
                 baseline models (accuracy of 0.68\pm 0.10 and 0.62\pm
                 0.07 with sLDA; accuracy of 0.70\pm 0.15 and 0.61\pm
                 0.07 with RF, with comparable performance in precision
                 and recall). In addition, compared to the baseline, our
                 CNN requires a faster pre-processing procedure, paving
                 the way for its possible use in online BCI
                 applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tsourma:2021:AEF,
  author =       "Maria Tsourma and Alexandros Zamichos and Efthymios
                 Efthymiadis and Anastasios Drosou and Dimitrios
                 Tzovaras",
  title =        "An {AI}-Enabled Framework for Real-Time Generation of
                 News Articles Based on Big {EO} Data for Disaster
                 Reporting",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "6",
  pages =        "161",
  day =          "19",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13060161",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Jun 26 11:42:17 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/6/161",
  abstract =     "In the field of journalism, the collection and
                 processing of information from different heterogeneous
                 sources are difficult and time-consuming processes. In
                 the context of the theory of journalism 3.0, where
                 multimedia data can be extracted from different sources
                 on the web, the possibility of creating a tool for the
                 exploitation of Earth observation (EO) data, especially
                 images by professionals belonging to the field of
                 journalism, is explored. With the production of massive
                 volumes of EO image data, the problem of their
                 exploitation and dissemination to the public,
                 specifically, by professionals in the media industry,
                 arises. In particular, the exploitation of satellite
                 image data from existing tools is difficult for
                 professionals who are not familiar with image
                 processing. In this scope, this article presents a new
                 innovative platform that automates some of the
                 journalistic practices. This platform includes several
                 mechanisms allowing users to early detect and receive
                 information about breaking news in real-time, retrieve
                 EO Sentinel-2 images upon request for a certain event,
                 and automatically generate a personalized article
                 according to the writing style of the author. Through
                 this platform, the journalists or editors can also make
                 any modifications to the generated article before
                 publishing. This platform is an added-value tool not
                 only for journalists and the media industry but also
                 for freelancers and article writers who use information
                 extracted from EO data in their articles.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hu:2021:SCA,
  author =       "Minda Hu and Ashwin Rao and Mayank Kejriwal and
                 Kristina Lerman",
  title =        "Socioeconomic Correlates of Anti-Science Attitudes in
                 the {US}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "6",
  pages =        "160",
  day =          "19",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13060160",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Jun 26 11:42:17 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/6/160",
  abstract =     "Successful responses to societal challenges require
                 sustained behavioral change. However, as responses to
                 the COVID-19 pandemic in the US showed, political
                 partisanship and mistrust of science can reduce public
                 willingness to adopt recommended behaviors such as
                 wearing a mask or receiving a vaccination. To better
                 understand this phenomenon, we explored attitudes
                 toward science using social media posts (tweets) that
                 were linked to counties in the US through their
                 locations. The data allowed us to study how attitudes
                 towards science relate to the socioeconomic
                 characteristics of communities in places from which
                 people tweet. Our analysis revealed three types of
                 communities with distinct behaviors: those in large
                 metro centers, smaller urban places, and rural areas.
                 While partisanship and race are strongly associated
                 with the share of anti-science users across all
                 communities, income was negatively and positively
                 associated with anti-science attitudes in suburban and
                 rural areas, respectively. We observed that emotions in
                 tweets, specifically negative high arousal emotions,
                 are expressed among suburban and rural communities by
                 many anti-science users, but not in communities in
                 large urban places. These trends were not apparent when
                 pooled across all counties. In addition, we found that
                 anti-science attitudes expressed five years earlier
                 were significantly associated with lower COVID-19
                 vaccination rates. Our analysis demonstrates the
                 feasibility of using spatially resolved social media
                 data to monitor public attitudes on issues of social
                 importance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Barakat:2021:OAI,
  author =       "Basel Barakat and Ahmad Taha and Ryan Samson and Aiste
                 Steponenaite and Shuja Ansari and Patrick M. Langdon
                 and Ian J. Wassell and Qammer H. Abbasi and Muhammad
                 Ali Imran and Simeon Keates",
  title =        "{6G} Opportunities Arising from {Internet of Things}
                 Use Cases: a Review Paper",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "6",
  pages =        "159",
  day =          "18",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13060159",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Jun 26 11:42:17 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/6/159",
  abstract =     "The race for the 6th generation of wireless networks
                 (6G) has begun. Researchers around the world have
                 started to explore the best solutions for the
                 challenges that the previous generations have
                 experienced. To provide the readers with a clear map of
                 the current developments, several review papers shared
                 their vision and critically evaluated the state of the
                 art. However, most of the work is based on general
                 observations and the big picture vision, and lack the
                 practical implementation challenges of the Internet of
                 Things (IoT) use cases. This paper takes a novel
                 approach in the review, as we present a sample of IoT
                 use cases that are representative of a wide variety of
                 its implementations. The chosen use cases are from the
                 most research-active sectors that can benefit from 6G
                 and its enabling technologies. These sectors are
                 healthcare, smart grid, transport, and Industry 4.0.
                 Additionally, we identified some of the practical
                 challenges and the lessons learned in the
                 implementation of these use cases. The review
                 highlights the cases' main requirements and how they
                 overlap with the key drivers for the future generation
                 of wireless networks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sikelis:2021:OBF,
  author =       "Konstantinos Sikelis and George E. Tsekouras and
                 Konstantinos Kotis",
  title =        "Ontology-Based Feature Selection: a Survey",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "6",
  pages =        "158",
  day =          "18",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13060158",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Jun 26 11:42:17 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/6/158",
  abstract =     "The Semantic Web emerged as an extension to the
                 traditional Web, adding meaning (semantics) to a
                 distributed Web of structured and linked information.
                 At its core, the concept of ontology provides the means
                 to semantically describe and structure information, and
                 expose it to software and human agents in a machine and
                 human-readable form. For software agents to be
                 realized, it is crucial to develop powerful artificial
                 intelligence and machine-learning techniques, able to
                 extract knowledge from information sources, and
                 represent it in the underlying ontology. This survey
                 aims to provide insight into key aspects of
                 ontology-based knowledge extraction from various
                 sources such as text, databases, and human expertise,
                 realized in the realm of feature selection. First,
                 common classification and feature selection algorithms
                 are presented. Then, selected approaches, which utilize
                 ontologies to represent features and perform feature
                 selection and classification, are described. The
                 selective and representative approaches span diverse
                 application domains, such as document classification,
                 opinion mining, manufacturing, recommendation systems,
                 urban management, information security systems, and
                 demonstrate the feasibility and applicability of such
                 methods. This survey, in addition to the criteria-based
                 presentation of related works, contributes a number of
                 open issues and challenges related to this still active
                 research topic.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Jussila:2021:TAM,
  author =       "Jari Jussila and Anu Helena Suominen and Atte Partanen
                 and Tapani Honkanen",
  title =        "Text Analysis Methods for Misinformation-Related
                 Research on {Finnish} Language {Twitter}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "6",
  pages =        "157",
  day =          "17",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13060157",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Jun 26 11:42:17 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/6/157",
  abstract =     "The dissemination of disinformation and fabricated
                 content on social media is growing. Yet little is known
                 of what the functional Twitter data analysis methods
                 are for languages (such as Finnish) that include word
                 formation with endings and word stems together with
                 derivation and compounding. Furthermore, there is a
                 need to understand which themes linked with
                 misinformation-and the concepts related to it-manifest
                 in different countries and language areas in Twitter
                 discourse. To address this issue, this study explores
                 misinformation and its related concepts:
                 disinformation, fake news, and propaganda in Finnish
                 language tweets. We utilized (1) word cloud clustering,
                 (2) topic modeling, and (3) word count analysis and
                 clustering to detect and analyze misinformation-related
                 concepts and themes connected to those concepts in
                 Finnish language Twitter discussions. Our results are
                 two-fold: (1) those concerning the functional data
                 analysis methods and (2) those about the themes
                 connected in discourse to the misinformation-related
                 concepts. We noticed that each utilized method
                 individually has critical limitations, especially all
                 the automated analysis methods processing for the
                 Finnish language, yet when combined they bring value to
                 the analysis. Moreover, we discovered that politics,
                 both internal and external, are prominent in the
                 Twitter discussions in connection with misinformation
                 and its related concepts of disinformation, fake news,
                 and propaganda.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Muller:2021:DCH,
  author =       "Romy M{\"u}ller and Franziska Kessler and David W.
                 Humphrey and Julian Rahm",
  title =        "Data in Context: How Digital Transformation Can
                 Support Human Reasoning in Cyber-Physical Production
                 Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "6",
  pages =        "156",
  day =          "17",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13060156",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Jun 26 11:42:17 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/6/156",
  abstract =     "In traditional production plants, current technologies
                 do not provide sufficient context to support
                 information integration and interpretation. Digital
                 transformation technologies have the potential to
                 support contextualization, but it is unclear how this
                 can be achieved. The present article presents a
                 selection of the psychological literature in four areas
                 relevant to contextualization: information sampling,
                 information integration, categorization, and causal
                 reasoning. Characteristic biases and limitations of
                 human information processing are discussed. Based on
                 this literature, we derive functional requirements for
                 digital transformation technologies, focusing on the
                 cognitive activities they should support. We then
                 present a selection of technologies that have the
                 potential to foster contextualization. These
                 technologies enable the modelling of system relations,
                 the integration of data from different sources, and the
                 connection of the present situation with historical
                 data. We illustrate how these technologies can support
                 contextual reasoning, and highlight challenges that
                 should be addressed when designing human-machine
                 cooperation in cyber-physical production systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Din:2021:ANA,
  author =       "Fareed Ud Din and David Paul and Joe Ryan and Frans
                 Henskens and Mark Wallis",
  title =        "{AOSR 2.0}: a Novel Approach and Thorough Validation
                 of an Agent-Oriented Storage and Retrieval {WMS}
                 Planner for {SMEs}, under {Industry 4.0}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "6",
  pages =        "155",
  day =          "15",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13060155",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Jun 26 11:42:17 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/6/155",
  abstract =     "The Fourth Industrial Revolution (Industry 4.0), with
                 the help of cyber-physical systems (CPS), the Internet
                 of Things (IoT), and Artificial Intelligence (AI), is
                 transforming the way industrial setups are designed.
                 Recent literature has provided insight about large
                 firms gaining benefits from Industry 4.0, but many of
                 these benefits do not translate to SMEs. The
                 agent-oriented smart factory (AOSF) framework provides
                 a solution to help bridge the gap between Industry 4.0
                 frameworks and SME-oriented setups by providing a
                 general and high-level supply chain (SC) framework and
                 an associated agent-oriented storage and retrieval
                 (AOSR)-based warehouse management strategy. This paper
                 presents the extended heuristics of the AOSR algorithm
                 and details how it improves the performance efficiency
                 in an SME-oriented warehouse. A detailed discussion on
                 the thorough validation via scenario-based
                 experimentation and test cases explain how AOSR yielded
                 60-148\% improved performance metrics in certain key
                 areas of a warehouse.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Butnaru:2021:TLU,
  author =       "Andrei Butnaru and Alexios Mylonas and Nikolaos
                 Pitropakis",
  title =        "Towards Lightweight {URL}-Based Phishing Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "6",
  pages =        "154",
  day =          "13",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13060154",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Jun 26 11:42:17 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/6/154",
  abstract =     "Nowadays, the majority of everyday computing devices,
                 irrespective of their size and operating system, allow
                 access to information and online services through web
                 browsers. However, the pervasiveness of web browsing in
                 our daily life does not come without security risks.
                 This widespread practice of web browsing in combination
                 with web users' low situational awareness against cyber
                 attacks, exposes them to a variety of threats, such as
                 phishing, malware and profiling. Phishing attacks can
                 compromise a target, individual or enterprise, through
                 social interaction alone. Moreover, in the current
                 threat landscape phishing attacks typically serve as an
                 attack vector or initial step in a more complex
                 campaign. To make matters worse, past work has
                 demonstrated the inability of denylists, which are the
                 default phishing countermeasure, to protect users from
                 the dynamic nature of phishing URLs. In this context,
                 our work uses supervised machine learning to block
                 phishing attacks, based on a novel combination of
                 features that are extracted solely from the URL. We
                 evaluate our performance over time with a dataset which
                 consists of active phishing attacks and compare it with
                 Google Safe Browsing (GSB), i.e., the default security
                 control in most popular web browsers. We find that our
                 work outperforms GSB in all of our experiments, as well
                 as performs well even against phishing URLs which are
                 active one year after our model's training.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Cretan:2021:ISE,
  author =       "Adina Cretan and Cristina Nica and Carlos Coutinho and
                 Ricardo Jardim-Goncalves and Ben Bratu",
  title =        "An Intelligent System to Ensure Interoperability for
                 the Dairy Farm Business Model",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "6",
  pages =        "153",
  day =          "12",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13060153",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Jun 26 11:42:17 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/6/153",
  abstract =     "Picking reliable partners, negotiating synchronously
                 with all partners, and managing similar proposals are
                 challenging tasks for any manager. This challenge is
                 even harder when it concerns small and medium
                 enterprises (SMEs) who need to deal with short budgets
                 and evident size limitations, often leading them to
                 avoid handling very large contracts. This size problem
                 can only be mitigated by collaboration efforts between
                 multiple SMEs, but then again this brings back the
                 initially stated issues. To address these problems,
                 this paper proposes a collaborative negotiation system
                 that automates the outsourcing part by assisting the
                 manager throughout a negotiation. The described system
                 provides a comprehensive view of all negotiations,
                 facilitates simultaneous bilateral negotiations, and
                 provides support for ensuring interoperability among
                 multiple partners negotiating on a task described by
                 multiple attributes. In addition, it relies on an
                 ontology to cope with the challenges of semantic
                 interoperability, it automates the selection of
                 reliable partners by using a lattice-based approach,
                 and it manages similar proposals by allowing domain
                 experts to define a satisfaction degree for each SME.
                 To showcase this method, this research focused on small
                 and medium-size dairy farms (DFs) and describes a
                 negotiation scenario in which a few DFs are able to
                 assess and generate proposals.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rodriguez-Ferrandiz:2021:MDS,
  author =       "Ra{\'u}l Rodr{\'\i}guez-Ferr{\'a}ndiz and Cande
                 S{\'a}nchez-Olmos and Tatiana Hidalgo-Mar{\'\i} and
                 Estela Saquete-Boro",
  title =        "Memetics of Deception: Spreading Local Meme Hoaxes
                 during {COVID-19} 1st Year",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "6",
  pages =        "152",
  day =          "10",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13060152",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Jun 26 11:42:17 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/6/152",
  abstract =     "The central thesis of this paper is that memetic
                 practices can be crucial to understanding deception at
                 present when hoaxes have increased globally due to
                 COVID-19. Therefore, we employ existing memetic theory
                 to describe the qualities and characteristics of meme
                 hoaxes in terms of the way they are replicated by
                 altering some aspects of the original, and then shared
                 on social media platforms in order to connect global
                 and local issues. Criteria for selecting the sample
                 were hoaxes retrieved from and related to the local
                 territory in the province of Alicante (Spain) during
                 the first year of the pandemic ( n = 35). Once
                 typology, hoax topics and their memetic qualities were
                 identified, we analysed their characteristics according
                 to form in terms of Shifman (2014) and, secondly, their
                 content and stance concordances both within and outside
                 our sample (Spain and abroad). The results show,
                 firstly, that hoaxes are mainly disinformation and they
                 are related to the pandemic. Secondly, despite the
                 notion that local hoaxes are linked to local
                 circumstances that are difficult to extrapolate, our
                 conclusions demonstrate their extraordinary memetic and
                 ``glocal'' capacity: they rapidly adapt other hoaxes
                 from other places to local areas, very often
                 supplanting reliable sources, and thereby demonstrating
                 consistency and opportunism.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Padilla-Cuevas:2021:OBC,
  author =       "Josu{\'e} Padilla-Cuevas and Jos{\'e} A. Reyes-Ortiz
                 and Maricela Bravo",
  title =        "Ontology-Based Context Event Representation,
                 Reasoning, and Enhancing in Academic Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "6",
  pages =        "151",
  day =          "10",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13060151",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Jun 26 11:42:17 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/6/151",
  abstract =     "An Ambient Intelligence responds to user requests
                 based on several contexts. A relevant context is
                 related to what has happened in the ambient; therefore,
                 it focuses a primordial interest on events. These
                 involve information about time, space, or people, which
                 is significant for modeling the context. In this paper,
                 we propose an event-driven approach for context
                 representation based on an ontological model. This
                 approach is extendable and adaptable for academic
                 domains. Moreover, the ontological model to be proposed
                 is used in reasoning and enrichment processes with the
                 context event information. Our event-driven approach
                 considers five contexts as a modular perspective in the
                 model: Person, temporal (time), physical space
                 (location), network (resources to acquire data from the
                 ambient), and academic events. We carried out an
                 evaluation process for the approach based on an
                 ontological model focused on (a) the extensibility and
                 adaptability of use case scenarios for events in an
                 academic environment, (b) the level of reasoning by
                 using competence questions related to events, (c) and
                 the consistency and coherence in the proposed model.
                 The evaluation process shows promising results for our
                 event-driven approach for context representation based
                 on the ontological model.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Pena-Fernandez:2021:REE,
  author =       "Sim{\'o}n Pe{\~n}a-Fern{\'a}ndez and Miguel {\'A}ngel
                 Casado-del-R{\'\i}o and Daniel
                 Garc{\'\i}a-Gonz{\'a}lez",
  title =        "From Rigidity to Exuberance: Evolution of News on
                 Online Newspaper Homepages",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "6",
  pages =        "150",
  day =          "09",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13060150",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Jun 26 11:42:17 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/6/150",
  abstract =     "Since their emergence in the mid-90s, online media
                 have evolved from simple digital editions that merely
                 served to dump content from print newspapers, to
                 sophisticated multi-format products with multimedia and
                 interactive features. In order to discover their visual
                 evolution, this article conducts a longitudinal study
                 of the design of online media by analyzing the front
                 pages of five general-information Spanish newspapers
                 (elpais.com, elmundo.es, abc.es, lavanguardia.com, and
                 elperiodico.com) over the past 25 years (1996-2020).
                 Moreover, some of their current features are listed. To
                 this end, six in-depth interviews were conducted with
                 managers of different online media outlets. The results
                 indicate that the media analysed have evolved from a
                 static, rigid format, to a dynamic, mobile, and
                 multi-format model. Regarding the language used, along
                 with increased multimedia and interactive
                 possibilities, Spanish online media currently display a
                 balance between text and images on their front pages.
                 Lastly, audience information consumption habits,
                 largely superficial and sporadic, and the increasing
                 technification and speed of production processes, means
                 that news media have lost in terms of the design part
                 of the individual personality they had in their print
                 editions. However, they maintain their index-type front
                 pages as one of their most characteristic elements,
                 which are very vertical and highly saturated.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Song:2021:TLC,
  author =       "Yaqin Song and Hong Ni and Xiaoyong Zhu",
  title =        "Two-Level Congestion Control Mechanism ({2LCCM}) for
                 Information-Centric Networking",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "6",
  pages =        "149",
  day =          "07",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13060149",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Jun 26 11:42:17 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/6/149",
  abstract =     "As an emerging network architecture,
                 Information-Centric Networking (ICN) is considered to
                 have the potential to meet the new requirements of the
                 Fifth Generation (5G) networks. ICN uses a name
                 decoupled from location to identify content, supports
                 the in-network caching technology, and adopts a
                 receiver-driven model for data transmission. Existing
                 ICN congestion control mechanisms usually first select
                 a nearby replica by opportunistic cache-hits and then
                 insist on adjusting the transmission rate regardless of
                 the congestion state, which cannot fully utilize the
                 characteristics of ICN to improve the performance of
                 data transmission. To solve this problem, this paper
                 proposes a two-level congestion control mechanism,
                 called 2LCCM. It switches the replica location based on
                 a node state table to avoid congestion paths when heavy
                 congestion happens. This 2LCCM mechanism also uses a
                 receiver-driven congestion control algorithm to adjust
                 the request sending rate, in order to avoid link
                 congestion under light congestion. In this paper, the
                 design and implementation of the proposed mechanism are
                 described in detail, and the experimental results show
                 that 2LCCM can effectively reduce the transmission
                 delay when heavy congestion occurs, and the
                 bandwidth-delay product-based congestion control
                 algorithm has better transmission performance compared
                 with a loss-based algorithm.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Popescu:2021:ISR,
  author =       "Traian Mihai Popescu and Alina Madalina Popescu and
                 Gabriela Prostean",
  title =        "{IoT} Security Risk Management Strategy Reference
                 Model ({IoTSRM2})",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "6",
  pages =        "148",
  day =          "04",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13060148",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Jun 26 11:42:17 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/6/148",
  abstract =     "Nowadays, Internet of Things (IoT) adoptions are
                 burgeoning and deemed the lynchpin towards achieving
                 ubiquitous connectivity. In this context, defining and
                 leveraging robust IoT security risk management
                 strategies are paramount for secure IoT adoptions.
                 Thus, this study aims to support IoT adopters from any
                 sector to formulate or reframe their IoT security risk
                 management strategies to achieve robust strategies that
                 effectively address IoT security issues. In a nutshell,
                 this article relies on a mixed methods research
                 methodology and proposes a reference model for IoT
                 security risk management strategy. The proposed IoT
                 security risk management strategy reference model
                 (IoTSRM2) relies on the 25 selected IoT security best
                 practices which are outlined using a proposed taxonomic
                 hierarchy, and on the proposed three-phased methodology
                 that consists of nine steps and outputs. The main
                 contribution of this work is the proposed IoTSRM2 which
                 consists of six domains, 16 objectives, and 30
                 prioritized controls. Furthermore, prior to providing
                 the related work, this article provides a critical
                 evaluation of selected informative references of
                 IoTSRM2 based on their percentage-wise linkage to the
                 IoTSRM2 domains and to the entire IoTSRM2. The findings
                 of the critical evaluation illustrate, inter alia, the
                 selected informative references that are the top three
                 most and least linked to the entire IoTSRM2.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chen:2021:MMA,
  author =       "Yanbo Chen and Jingsha He and Wei Wei and Nafei Zhu
                 and Cong Yu",
  title =        "A Multi-Model Approach for User Portrait",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "6",
  pages =        "147",
  day =          "31",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13060147",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Jun 26 11:42:17 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/6/147",
  abstract =     "Age, gender, educational background, and so on are the
                 most basic attributes for identifying and portraying
                 users. It is also possible to conduct in-depth mining
                 analysis and high-level predictions based on such
                 attributes to learn users' preferences and
                 personalities so as to enhance users' online experience
                 and to realize personalized services in real
                 applications. In this paper, we propose using
                 classification algorithms in machine learning to
                 predict users' demographic attributes, such as gender,
                 age, and educational background, based on one month of
                 data collected with the Sogou search engine with the
                 goal of making user portraits. A multi-model approach
                 using the fusion algorithms is adopted and hereby
                 described in the paper. The proposed model is a
                 two-stage structure using one month of data with
                 demographic labels as the training data. The first
                 stage of the structure is based on traditional machine
                 learning models and neural network models, whereas the
                 second one is a combination of the models from the
                 first stage. Experimental results show that our
                 proposed multi-model method can achieve more accurate
                 results than the single-model methods in predicting
                 user attributes. The proposed approach also has
                 stronger generalization ability in predicting users'
                 demographic attributes, making it more adequate to
                 profile users.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Dey:2021:TCM,
  author =       "Somdip Dey and Amit Kumar Singh and Klaus
                 McDonald-Maier",
  title =        "{ThermalAttackNet}: Are {CNNs} Making It Easy to
                 Perform Temperature Side-Channel Attack in Mobile Edge
                 Devices?",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "6",
  pages =        "146",
  day =          "31",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13060146",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Jun 26 11:42:17 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/6/146",
  abstract =     "Side-channel attacks remain a challenge to information
                 flow control and security in mobile edge devices till
                 this date. One such important security flaw could be
                 exploited through temperature side-channel attacks,
                 where heat dissipation and propagation from the
                 processing cores are observed over time in order to
                 deduce security flaws. In this paper, we study how
                 computer vision-based convolutional neural networks
                 (CNNs) could be used to exploit temperature (thermal)
                 side-channel attack on different Linux governors in
                 mobile edge device utilizing multi-processor
                 system-on-chip (MPSoC). We also designed a power- and
                 memory-efficient CNN model that is capable of
                 performing thermal side-channel attack on the MPSoC and
                 can be used by industry practitioners and academics as
                 a benchmark to design methodologies to secure against
                 such an attack in MPSoC.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Massaro:2021:IAE,
  author =       "Alessandro Massaro and Daniele Giannone and Vitangelo
                 Birardi and Angelo Maurizio Galiano",
  title =        "An Innovative Approach for the Evaluation of the {Web}
                 Page Impact Combining User Experience and Neural
                 Network Score",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "6",
  pages =        "145",
  day =          "31",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13060145",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Jun 26 11:42:17 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/6/145",
  abstract =     "The proposed paper introduces an innovative
                 methodology useful to assign intelligent scores to web
                 pages. The approach is based on the simultaneous use of
                 User eXperience (UX), Artificial Neural Network (ANN),
                 and Long Short-Term Memory (LSTM) algorithms, providing
                 the web page scoring and taking into account outlier
                 conditions to construct the training dataset.
                 Specifically, the UX tool analyses different parameters
                 addressing the score, such as navigation time, number
                 of clicks, and mouse movements for page, finding
                 possible outliers, the ANN are able to predict
                 outliers, and the LSTM processes the web pages tags
                 together with UX and user scores. The final web page
                 score is assigned by the LSTM model corrected by the UX
                 output and improved by the navigation user score. This
                 final score is useful for the designer by suggesting
                 the tags typologies structuring a new web page layout
                 of a specific topic. By using the proposed methodology,
                 the web designer is addressed to allocate contents in
                 the web page layout. The work has been developed within
                 a framework of an industry project oriented on the
                 formulation of an innovative AI interface for web
                 designers.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Aldabbagh:2021:RCD,
  author =       "Ghadah Aldabbagh and Nikos Dimitriou and Samar
                 Alkhuraiji and Omaimah Bamasag",
  title =        "Radio Coverage and Device Capacity Dimensioning
                 Methodologies for {IoT} {LoRaWAN} and {NB-IoT}
                 Deployments in Urban Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "6",
  pages =        "144",
  day =          "30",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13060144",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Jun 26 11:42:17 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/6/144",
  abstract =     "This paper focuses on the study of IoT network
                 deployments, in both unlicensed and licensed bands,
                 considering LoRaWAN and NB-IoT standards, respectively.
                 The objective is to develop a comprehensive and
                 detailed network planning and coverage dimensioning
                 methodology for assessing key metrics related to the
                 achieved throughput and capacity for specific
                 requirements in order to identify tradeoffs and key
                 issues that are related to the applicability of IoT
                 access technologies for representative use case types.
                 This paper will provide a concise overview of key
                 characteristics of IoT representative IoT access
                 network standards that are considered for being
                 deployed in unlicensed and licensed bands and will
                 present a methodology for modeling the characteristics
                 of both access network technologies in order to assess
                 their coverage and capacity considering different
                 parameters.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Shekhtman:2021:EBB,
  author =       "Louis Shekhtman and Erez Waisbard",
  title =        "{EngraveChain}: a Blockchain-Based Tamper-Proof
                 Distributed Log System",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "6",
  pages =        "143",
  day =          "29",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13060143",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Jun 26 11:42:17 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/6/143",
  abstract =     "A reliable log system is a prerequisite for many
                 applications. Financial systems need to have
                 transactions logged in a precise manner, medical
                 systems rely on having trusted medical records and
                 security logs record system access requests in order to
                 trace malicious attempts. Keeping multiple copies helps
                 to achieve availability and reliability against such
                 hackers. Unfortunately, maintaining redundant copies in
                 a distributed manner in a byzantine setting has always
                 been a challenging task, however it has recently become
                 simpler given advances in blockchain technologies. In
                 this work, we present a tamper-resistant log system
                 through the use of a blockchain. We leverage the
                 immutable write action and distributed storage provided
                 by the blockchain as a basis to develop a secure log
                 system, but we also add a privacy preserving layer that
                 is essential for many applications. We detail the
                 security and privacy aspects of our solution, as well
                 as how they relate to performance needs in relevant
                 settings. Finally, we implement our system over
                 Hyperledger Fabric and demonstrate the system's value
                 for several use cases. In addition, we provide a
                 scalability analysis for applying our solution in a
                 large-scale system.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Spradling:2021:PFN,
  author =       "Matthew Spradling and Jeremy Straub and Jay Strong",
  title =        "Protection from `Fake News': The Need for Descriptive
                 Factual Labeling for Online Content",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "6",
  pages =        "142",
  day =          "28",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13060142",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Jun 26 11:42:17 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/6/142",
  abstract =     "So-called `fake news'-deceptive online content that
                 attempts to manipulate readers-is a growing problem. A
                 tool of intelligence agencies, scammers and marketers
                 alike, it has been blamed for election interference,
                 public confusion and other issues in the United States
                 and beyond. This problem is made particularly
                 pronounced as younger generations choose social media
                 sources over journalistic sources for their
                 information. This paper considers the prospective
                 solution of providing consumers with `nutrition
                 facts'-style information for online content. To this
                 end, it reviews prior work in product labeling and
                 considers several possible approaches and the arguments
                 for and against such labels. Based on this analysis, a
                 case is made for the need for a nutrition facts-based
                 labeling scheme for online content.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sanchez-Romero:2021:SEC,
  author =       "Cristina S{\'a}nchez-Romero and Eva Mar{\'\i}a
                 Mu{\~n}oz-Jim{\'e}nez",
  title =        "Social and Educational Coexistence in Adolescents'
                 Perception in Current Social Problems through
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "6",
  pages =        "141",
  day =          "27",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13060141",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Jun 26 11:42:17 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/6/141",
  abstract =     "The use of social networks as a social and educational
                 environment emphasizes an approach to social problems
                 (bullying, cyberbullying, sexism, racism) that has
                 emerged in today's society. Social networks offer a
                 unique opportunity to increase channels for
                 communication and socialization. The aim of this study
                 is to analyze the adolescents' attitudes in sports
                 practice in their extracurricular environment, and it
                 highlights the importance of didactic communication as
                 a tool for social cohesion to guarantee the interaction
                 between adolescents. This objective has been evaluated
                 through the ``Sport and Social Integration. Survey on
                 Secondary Schools in Italy'' questionnaire. In this
                 paper, we focus our attention on Section II to go
                 deeper into the participants' opinion on previously
                 mentioned social problems. The methods of research for
                 this study were conducted through a descriptive,
                 inferential, quantitative, and ex post facto design.
                 The sample consisted of 286 Italian adolescents aged
                 between 12 and 15 years old. Results show that there
                 are positive correlations in the following variables:
                 gender and verbal, psychological, or physical violence
                 (Bullying) (r = 0.260) (Sig. = 0.000); gender and
                 threats, crimes, and persecutions through the Internet
                 (Cyberbullying) (r = 0.226) (Sig. = 0.000); gender and
                 discrimination against women (Sexism) (r = 0.133) (Sig.
                 = 0.025). In conclusion, this article underlines the
                 importance of investing more systematically in the
                 effort to prevent bullying and digital inclusion from
                 an early age for the critical use of mobile devices and
                 social networks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Villegas-Ch:2021:ASL,
  author =       "William Villegas-Ch. and Milton Roman-Ca{\~n}izares
                 and Santiago S{\'a}nchez-Viteri and Joselin
                 Garc{\'\i}a-Ortiz and Walter Gaibor-Naranjo",
  title =        "Analysis of the State of Learning in {University}
                 Students with the Use of a {Hadoop} Framework",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "6",
  pages =        "140",
  day =          "24",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13060140",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Jun 26 11:42:17 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/6/140",
  abstract =     "Currently, education is going through a critical
                 moment due to the 2019 coronavirus disease that has
                 been declared a pandemic. This has forced many
                 organizations to undergo a significant transformation,
                 rethinking key elements of their processes and the use
                 of technology to maintain operations. The continuity of
                 education has become dependent on technological tools,
                 as well as on the ability of universities to cope with
                 a precipitous transition to a remote educational model.
                 That has generated problems that affect student
                 learning. This work proposes the implementation of a
                 Big Data framework to identify the factors that affect
                 student performance and decision-making to improve
                 learning. Similar works cover two main research topics
                 under Big Data in education, the modeling and storage
                 of educational data. However, they do not consider
                 issues such as student performance and the improvement
                 of the educational system with the integration of Big
                 Data. In addition, this work provides a guide for
                 future studies and highlights new insights and
                 directions for the successful use of Big Data in
                 education. Real-world data were collected for the
                 evaluation of the proposed framework, the collection of
                 these being the existing limitation in all research due
                 to generalized rejection of data consent.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Contu:2021:ABA,
  author =       "Francesco Contu and Andrea Demontis and Stefano
                 Dess{\`\i} and Marco Muscas and Daniele Riboni",
  title =        "{AI}-Based Analysis of Policies and Images for
                 Privacy-Conscious Content Sharing",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "6",
  pages =        "139",
  day =          "21",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13060139",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Jun 26 11:42:17 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/6/139",
  abstract =     "Thanks to the popularity of personal mobile devices,
                 more and more of the different types of private
                 content, such as images and videos, are shared on
                 social networking applications. While content sharing
                 may be an effective practice to enhance social
                 relationships, it is also a source of relevant privacy
                 issues. Unfortunately, users find it difficult to
                 understanding the terms and implications of the privacy
                 policies of apps and services. Moreover, taking privacy
                 decisions about content sharing on social networks is
                 cumbersome and prone to errors that could determine
                 privacy leaks. In this paper, we propose two techniques
                 aimed at supporting the user in taking privacy choices
                 about sharing personal content online. Our techniques
                 are based on machine learning and natural language
                 processing to analyze privacy policies, and on computer
                 vision to assist the user in the privacy-conscious
                 sharing of multimedia content. Experiments with
                 real-world data show the potential of our solutions. We
                 also present ongoing work on a system prototype and
                 chatbot for natural language user assistance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Theodorou:2021:AES,
  author =       "Traianos-Ioannis Theodorou and Alexandros Zamichos and
                 Michalis Skoumperdis and Anna Kougioumtzidou and
                 Kalliopi Tsolaki and Dimitris Papadopoulos and Thanasis
                 Patsios and George Papanikolaou and Athanasios
                 Konstantinidis and Anastasios Drosou and Dimitrios
                 Tzovaras",
  title =        "An {AI}-Enabled Stock Prediction Platform Combining
                 News and Social Sensing with Financial Statements",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "6",
  pages =        "138",
  day =          "21",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13060138",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Jun 26 11:42:17 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/6/138",
  abstract =     "In recent years, the area of financial forecasting has
                 attracted high interest due to the emergence of huge
                 data volumes (big data) and the advent of more powerful
                 modeling techniques such as deep learning. To generate
                 the financial forecasts, systems are developed that
                 combine methods from various scientific fields, such as
                 information retrieval, natural language processing and
                 deep learning. In this paper, we present ASPENDYS, a
                 supportive platform for investors that combines various
                 methods from the aforementioned scientific fields
                 aiming to facilitate the management and the decision
                 making of investment actions through personalized
                 recommendations. To accomplish that, the system takes
                 into account both financial data and textual data from
                 news websites and the social networks Twitter and
                 Stocktwits. The financial data are processed using
                 methods of technical analysis and machine learning,
                 while the textual data are analyzed regarding their
                 reliability and then their sentiments towards an
                 investment. As an outcome, investment signals are
                 generated based on the financial data analysis and the
                 sensing of the general sentiment towards a certain
                 investment and are finally recommended to the
                 investors.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Dikhanbayeva:2021:CFI,
  author =       "Dinara Dikhanbayeva and Akmaral Tokbergenova and
                 Yevgeniy Lukhmanov and Essam Shehab and Zbigniew
                 Pastuszak and Ali Turkyilmaz",
  title =        "Critical Factors of {Industry 4.0} Implementation in
                 an Emerging Country: Empirical Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "6",
  pages =        "137",
  day =          "21",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13060137",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Jun 26 11:42:17 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/6/137",
  abstract =     "The concept of Industry 4.0 is becoming more and more
                 popular all over the world. The implementation of its
                 assumptions in business practice changes the way
                 companies operate. The enormous innovative potential of
                 the Industry 4.0 concept and the intensive use of
                 processes based on the implementation of advanced
                 technologies in its assumptions have an impact on
                 various industries in each country. The article
                 attempts to analyze the critical factors for the
                 implementation of Industry 4.0 in Kazakhstan. Primary
                 and secondary data sources were used for this purpose.
                 The majority of existing government initiatives and
                 reports do not reflect the actual situation.
                 Additionally, these materials do not always represent
                 the experiences or positions of all the parties
                 involved. Opinions of companies and organizations
                 implementing Industry 4.0 solutions remain unexplored.
                 The primary goal of the paper is to fill the cognitive
                 gap by analyzing stakeholder responses and identifying
                 the actual level of their awareness of the development
                 of Industry 4.0. An additional intention of the authors
                 was to empirically establish barriers that companies
                 face while implementing the most desirable
                 technologies, as well as to establish other critical
                 factors, taking into account the specificity of the
                 country under study. The results of the research can be
                 used by policymakers, scientists and other stakeholders
                 to develop forecasts and strategic plans, as well as to
                 develop and conduct further research on the
                 implementation processes of Industry 4.0 in
                 Kazakhstan.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Beschastnyi:2021:QDM,
  author =       "Vitalii Beschastnyi and Daria Ostrikova and Roman
                 Konyukhov and Elizaveta Golos and Alexander Chursin and
                 Dmitri Moltchanov and Yuliya Gaidamaka",
  title =        "Quantifying the Density of {mmWave} {NR} Deployments
                 for Provisioning Multi-Layer {VR} Services",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "7",
  pages =        "185",
  day =          "20",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13070185",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 23 15:16:13 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/7/185",
  abstract =     "The 5G New Radio (NR) technology operating in
                 millimeter wave (mmWave) frequency band is designed for
                 support bandwidth-greedy applications requiring
                 extraordinary rates at the access interface. However,
                 the use of directional antenna radiation patterns, as
                 well as extremely large path losses and blockage
                 phenomenon, requires efficient algorithms to support
                 these services. In this study, we consider the
                 multi-layer virtual reality (VR) service that utilizes
                 multicast capabilities for baseline layer and unicast
                 transmissions for delivering an enhanced experience. By
                 utilizing the tools of stochastic geometry and queuing
                 theory we develop a simple algorithm allowing to
                 estimate the deployment density of mmWave NR base
                 stations (BS) supporting prescribed delivery
                 guarantees. Our numerical results show that the highest
                 gains of utilizing multicast service for distributing
                 base layer is observed for high UE densities. Despite
                 of its simplicity, the proposed multicast group
                 formation scheme operates close to the state-of-the-art
                 algorithms utilizing the widest beams with longest
                 coverage distance in approximately 50-70\% of cases
                 when UE density is $ \lambda \geq 0.3 $. Among other
                 parameters, QoS profile and UE density have a profound
                 impact on the required density of NR BSs while the
                 effect of blockers density is non-linear having the
                 greatest impact on strict QoS profiles. Depending on
                 the system and service parameters the required density
                 of NR BSs may vary in the range of 20--250 BS/km 2.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sun:2021:APP,
  author =       "Jiachen Sun and Peter A. Gloor",
  title =        "Assessing the Predictive Power of Online Social Media
                 to Analyze {COVID-19} Outbreaks in the 50 {U.S.}
                 States",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "7",
  pages =        "184",
  day =          "20",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13070184",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 23 15:16:13 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/7/184",
  abstract =     "As the coronavirus disease 2019 (COVID-19) continues
                 to rage worldwide, the United States has become the
                 most affected country, with more than 34.1 million
                 total confirmed cases up to 1 June 2021. In this work,
                 we investigate correlations between online social media
                 and Internet search for the COVID-19 pandemic among 50
                 U.S. states. By collecting the state-level daily trends
                 through both Twitter and Google Trends, we observe a
                 high but state-different lag correlation with the
                 number of daily confirmed cases. We further find that
                 the accuracy measured by the correlation coefficient is
                 positively correlated to a state's demographic, air
                 traffic volume and GDP development. Most importantly,
                 we show that a state's early infection rate is
                 negatively correlated with the lag to the previous peak
                 in Internet searches and tweeting about COVID-19,
                 indicating that earlier collective awareness on
                 Twitter/Google correlates with a lower infection rate.
                 Lastly, we demonstrate that correlations between online
                 social media and search trends are sensitive to time,
                 mainly due to the attention shifting of the public.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Treiblmaier:2021:ENW,
  author =       "Horst Treiblmaier",
  title =        "Exploring the Next Wave of Blockchain and Distributed
                 Ledger Technology: The Overlooked Potential of Scenario
                 Analysis",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "7",
  pages =        "183",
  day =          "19",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13070183",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 23 15:16:13 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/7/183",
  abstract =     "Blockchain is predicted to disrupt industries,
                 economies, and societies. The properties of distributed
                 ledgers allow the creation of immutable data structures
                 that facilitate shared access in real time and enable a
                 plethora of innovative applications. However,
                 blockchain is not a uniform technology but rather a
                 bundle of evolving components whose implications are
                 notoriously hard to predict. At present, it is not
                 clear how current trends will evolve, with technical
                 evolution, legislation, and public policy being three
                 contingency factors that make ongoing disruptive
                 transformations particularly hard to predict. In light
                 of blockchain's potential disruptive impact, it is
                 surprising that scenario analysis has hitherto been
                 largely ignored in academic research. Therefore, in
                 this paper, we introduce the technique, clarify several
                 misconceptions, and provide examples illustrating how
                 this method can help to overcome the limitations of
                 existing technology impact research. We conclude that
                 if applied correctly, scenario analysis represents the
                 ideal tool to rigorously explore uncertain future
                 developments and to create a comprehensive foundation
                 for future research.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Isobe:2021:MAL,
  author =       "Shinnosuke Isobe and Satoshi Tamura and Satoru
                 Hayamizu and Yuuto Gotoh and Masaki Nose",
  title =        "Multi-Angle Lipreading with Angle Classification-Based
                 Feature Extraction and Its Application to Audio-Visual
                 Speech Recognition",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "7",
  pages =        "182",
  day =          "15",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13070182",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 23 15:16:13 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/7/182",
  abstract =     "Recently, automatic speech recognition (ASR) and
                 visual speech recognition (VSR) have been widely
                 researched owing to the development in deep learning.
                 Most VSR research works focus only on frontal face
                 images. However, assuming real scenes, it is obvious
                 that a VSR system should correctly recognize spoken
                 contents from not only frontal but also diagonal or
                 profile faces. In this paper, we propose a novel VSR
                 method that is applicable to faces taken at any angle.
                 Firstly, view classification is carried out to estimate
                 face angles. Based on the results, feature extraction
                 is then conducted using the best combination of
                 pre-trained feature extraction models. Next, lipreading
                 is carried out using the features. We also developed
                 audio-visual speech recognition (AVSR) using the VSR in
                 addition to conventional ASR. Audio results were
                 obtained from ASR, followed by incorporating audio and
                 visual results in a decision fusion manner. We
                 evaluated our methods using OuluVS2, a multi-angle
                 audio-visual database. We then confirmed that our
                 approach achieved the best performance among
                 conventional VSR schemes in a phrase classification
                 task. In addition, we found that our AVSR results are
                 better than ASR and VSR results.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yolchuyev:2021:DCP,
  author =       "Agil Yolchuyev and Janos Levendovszky",
  title =        "Data Chunks Placement Optimization for Hybrid Storage
                 Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "7",
  pages =        "181",
  day =          "11",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13070181",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 23 15:16:13 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/7/181",
  abstract =     "''Hybrid Cloud Storage'' (HCS) is a widely adopted
                 framework that combines the functionality of public and
                 private cloud storage models to provide storage
                 services. This kind of storage is especially ideal for
                 organizations that seek to reduce the cost of their
                 storage infrastructure with the use of ``Public Cloud
                 Storage'' as a backend to on-premises primary storage.
                 Despite the higher performance, the hybrid cloud has
                 latency issues, related to the distance and bandwidth
                 of the public storage, which may cause a significant
                 drop in the performance of the storage systems during
                 data transfer. This issue can become a major problem
                 when one or more private storage nodes fail. In this
                 paper, we propose a new framework for optimizing the
                 data uploading process that is currently used with
                 hybrid cloud storage systems. The optimization is
                 concerned with spreading the data over the multiple
                 storages in the HCS system according to some predefined
                 objective functions. Furthermore, we also used Network
                 Coding technics for minimizing data transfer latency
                 between the receiver (private storages) and transmitter
                 nodes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hoppari:2021:PGI,
  author =       "Mika Hoppari and Mikko Uitto and Jukka M{\"a}kel{\"a}
                 and Ilkka Harjula and Seppo Rantala",
  title =        "Performance of the 5th Generation Indoor Wireless
                 Technologies --- Empirical Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "7",
  pages =        "180",
  day =          "09",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13070180",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 23 15:16:13 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/7/180",
  abstract =     "The evolution of 5th generation (5G) cellular
                 technology has introduced several enhancements and
                 provides better performance compared to previous
                 generations. To understand the real capabilities, the
                 importance of the empirical studies is significant to
                 also understand the possible limitations. This is very
                 important especially from the service and use case
                 point of view. Several test sites exist around the
                 globe for introducing, testing, and evaluating new
                 features, use cases, and performance in restricted and
                 secure environments alongside the commercial operators.
                 Test sites equipped with the standard technology are
                 the perfect places for performing deep analysis of the
                 latest wireless and cellular technologies in real
                 operating environments. The testing sites provide
                 valuable information with sophisticated quality of
                 service (QoS) indicators when the 5G vertical use cases
                 are evaluated using the actual devices in the carrier
                 grade network. In addition, the Wi-Fi standards are
                 constantly evolving toward higher bit rates and reduced
                 latency, and their usage in 5G dedicated verticals can
                 even improve performance, especially when lower
                 coverage is sufficient. This work presents the detailed
                 comparative measurements between Wi-Fi 6 and 5G New
                 Radio (NR) performance in indoor facilities and
                 extensive results carried out in 5G and beyond test
                 site located in Finland. The results gathered from the
                 extensive test sets indicate that the Wi-Fi 6 can
                 outperform the 5G in the indoor environment in terms of
                 throughput and latency when distance and coverage do
                 not increase enormously. In addition, the usage of
                 wireless technologies allows improved uplink
                 performance, which is usually more limited in cellular
                 networks. The gained results of our measurements
                 provide valuable information for designing, developing,
                 and implementing the requirements for the
                 next-generation wireless applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Truong:2021:FFR,
  author =       "Thanh-Dat Truong and Chi Nhan Duong and Minh-Triet
                 Tran and Ngan Le and Khoa Luu",
  title =        "Fast Flow Reconstruction via Robust Invertible $ n
                 \times n $ Convolution",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "7",
  pages =        "179",
  day =          "08",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13070179",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 23 15:16:13 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/7/179",
  abstract =     "The evolution of 5th generation (5G) cellular
                 technology has introduced several enhancements and
                 provides better performance compared to previous
                 generations. To understand the real capabilities, the
                 importance of the empirical studies is significant to
                 also understand the possible limitations. This is very
                 important especially from the service and use case
                 point of view. Several test sites exist around the
                 globe for introducing, testing, and evaluating new
                 features, use cases, and performance in restricted and
                 secure environments alongside the commercial operators.
                 Test sites equipped with the standard technology are
                 the perfect places for performing deep analysis of the
                 latest wireless and cellular technologies in real
                 operating environments. The testing sites provide
                 valuable information with sophisticated quality of
                 service (QoS) indicators when the 5G vertical use cases
                 are evaluated using the actual devices in the carrier
                 grade network. In addition, the Wi-Fi standards are
                 constantly evolving toward higher bit rates and reduced
                 latency, and their usage in 5G dedicated verticals can
                 even improve performance, especially when lower
                 coverage is sufficient. This work presents the detailed
                 comparative measurements between Wi-Fi 6 and 5G New
                 Radio (NR) performance in indoor facilities and
                 extensive results carried out in 5G and beyond test
                 site located in Finland. The results gathered from the
                 extensive test sets indicate that the Wi-Fi 6 can
                 outperform the 5G in the indoor environment in terms of
                 throughput and latency when distance and coverage do
                 not increase enormously. In addition, the usage of
                 wireless technologies allows improved uplink
                 performance, which is usually more limited in cellular
                 networks. The gained results of our measurements
                 provide valuable information for designing, developing,
                 and implementing the requirements for the
                 next-generation wireless applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Portela:2021:DSK,
  author =       "Filipe Portela",
  title =        "Data Science and Knowledge Discovery",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "7",
  pages =        "178",
  day =          "07",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13070178",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 23 15:16:13 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/7/178",
  abstract =     "Nowadays, Data Science (DS) is gaining a relevant
                 impact on the community. The most recent developments
                 in Computer Science, such as advances in Machine and
                 Deep Learning, Big Data, Knowledge Discovery, and Data
                 Analytics, have triggered the development of several
                 innovative solutions (e.g., approaches, methods,
                 models, or paradigms). It is a trending topic with many
                 application possibilities and motivates the researcher
                 to conduct experiments in these most diverse areas.
                 This issue created an opportunity to expose some of the
                 most relevant achievements in the Knowledge Discovery
                 and Data Science field and contribute to such subjects
                 as Health, Smart Homes, Social Humanities, Government,
                 among others. The relevance of this field can be easily
                 observed by its current achieved numbers: thirteen
                 research articles, one technical note, and forty-six
                 authors from fifteen nationalities.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Aiosa:2021:CEE,
  author =       "Grazia Veronica Aiosa and Barbara Attanasio and
                 Aurelio {La Corte} and Marialisa Scat{\'a}",
  title =        "{CoKnowEMe}: an Edge Evaluation Scheme for {QoS} of
                 {IoMT} Microservices in {6G} Scenario",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "7",
  pages =        "177",
  day =          "07",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13070177",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 23 15:16:13 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/7/177",
  abstract =     "The forthcoming 6G will attempt to rewrite the
                 communication networks' perspective focusing on a shift
                 in paradigm in the way technologies and services are
                 conceived, integrated and used. In this viewpoint, the
                 Internet of Medical Things (IoMT) represents a merger
                 of medical devices and health applications that are
                 connected through networks, introducing an important
                 change in managing the disease, treatments and
                 diagnosis, reducing costs and faults. In 6G, the edge
                 intelligence moves the innovative abilities from the
                 central cloud to the edge and jointly with the complex
                 systems approach will enable the development of a new
                 category of lightweight applications as microservices.
                 It requires edge intelligence also for the service
                 evaluation in order to introduce the same degree of
                 adaptability. We propose a new evaluation model, called
                 CoKnowEMe (context knowledge evaluation model), by
                 introducing an architectural and analytical scheme,
                 modeled following a complex and dynamical approach,
                 consisting of three inter-operable level and different
                 networked attributes, to quantify the quality of IoMT
                 microservices depending on a changeable context of use.
                 We conduct simulations to display and quantify the
                 structural complex properties and performance
                 statistical estimators. We select and classify suitable
                 attributes through a further detailed procedure in a
                 supplementary information document.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Dong:2021:DDR,
  author =       "Shuai Dong and Zhihua Yang and Wensheng Li and Kun
                 Zou",
  title =        "Dynamic Detection and Recognition of Objects Based on
                 Sequential {RGB} Images",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "7",
  pages =        "176",
  day =          "07",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13070176",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 23 15:16:13 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/7/176",
  abstract =     "Conveyors are used commonly in industrial production
                 lines and automated sorting systems. Many applications
                 require fast, reliable, and dynamic detection and
                 recognition for the objects on conveyors. Aiming at
                 this goal, we design a framework that involves three
                 subtasks: one-class instance segmentation (OCIS),
                 multiobject tracking (MOT), and zero-shot fine-grained
                 recognition of 3D objects (ZSFGR3D). A new level set
                 map network (LSMNet) and a multiview redundancy-free
                 feature network (MVRFFNet) are proposed for the first
                 and third subtasks, respectively. The level set map
                 (LSM) is used to annotate instances instead of the
                 traditional multichannel binary mask, and each peak of
                 the LSM represents one instance. Based on the LSM,
                 LSMNet can adopt a pix2pix architecture to segment
                 instances. MVRFFNet is a generalized zero-shot learning
                 (GZSL) framework based on the Wasserstein generative
                 adversarial network for 3D object recognition.
                 Multi-view features of an object are combined into a
                 compact registered feature. By treating the registered
                 features as the category attribution in the GZSL
                 setting, MVRFFNet learns a mapping function that maps
                 original retrieve features into a new redundancy-free
                 feature space. To validate the performance of the
                 proposed methods, a segmentation dataset and a
                 fine-grained classification dataset about objects on a
                 conveyor are established. Experimental results on these
                 datasets show that LSMNet can achieve a recalling
                 accuracy close to the light instance segmentation
                 framework You Only Look At CoefficienTs (YOLACT), while
                 its computing speed on an NVIDIA GTX1660TI GPU is 80
                 fps, which is much faster than YOLACT's 25 fps.
                 Redundancy-free features generated by MVRFFNet perform
                 much better than original features in the retrieval
                 task.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Almuqren:2021:ESC,
  author =       "Latifah Almuqren and Fatma S. Alrayes and Alexandra I.
                 Cristea",
  title =        "An Empirical Study on Customer Churn Behaviours
                 Prediction Using {Arabic Twitter} Mining Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "7",
  pages =        "175",
  day =          "05",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13070175",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 23 15:16:13 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/7/175",
  abstract =     "With the rising growth of the telecommunication
                 industry, the customer churn problem has grown in
                 significance as well. One of the most critical
                 challenges in the data and voice telecommunication
                 service industry is retaining customers, thus reducing
                 customer churn by increasing customer satisfaction.
                 Telecom companies have depended on historical customer
                 data to measure customer churn. However, historical
                 data does not reveal current customer satisfaction or
                 future likeliness to switch between telecom companies.
                 The related research reveals that many studies have
                 focused on developing churner prediction models based
                 on historical data. These models face delay issues and
                 lack timelines for targeting customers in real-time. In
                 addition, these models lack the ability to tap into
                 Arabic language social media for real-time analysis. As
                 a result, the design of a customer churn model based on
                 real-time analytics is needed. Therefore, this study
                 offers a new approach to using social media mining to
                 predict customer churn in the telecommunication field.
                 This represents the first work using Arabic Twitter
                 mining to predict churn in Saudi Telecom companies. The
                 newly proposed method proved its efficiency based on
                 various standard metrics and based on a comparison with
                 the ground-truth actual outcomes provided by a telecom
                 company.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2021:NUA,
  author =       "Xiaohui Li and Andrey V. Savkin",
  title =        "Networked Unmanned Aerial Vehicles for Surveillance
                 and Monitoring: a Survey",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "7",
  pages =        "174",
  day =          "02",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13070174",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 23 15:16:13 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/7/174",
  abstract =     "As a typical cyber-physical system, networked unmanned
                 aerial vehicles (UAVs) have received much attention in
                 recent years. Emerging communication technologies and
                 high-performance control methods enable networked UAVs
                 to operate as aerial sensor networks to collect more
                 complete and consistent information with significantly
                 improved mobility and flexibility than traditional
                 sensing platforms. One of the main applications of
                 networked UAVs is surveillance and monitoring, which
                 constitute essential components of a well-functioning
                 public safety system and many industrial applications.
                 Although the existing literature on surveillance and
                 monitoring UAVs is extensive, a comprehensive survey on
                 this topic is lacking. This article classifies
                 publications on networked UAVs for surveillance and
                 monitoring using the targets of interest and analyzes
                 several typical problems on this topic, including the
                 control, navigation, and deployment optimization of
                 UAVs. The related research gaps and future directions
                 are also presented.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chua:2021:TUP,
  author =       "Jiaming Chua and Lee-Yeng Ong and Meng-Chew Leow",
  title =        "Telehealth Using {PoseNet}-Based System for In-Home
                 Rehabilitation",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "7",
  pages =        "173",
  day =          "02",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13070173",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 23 15:16:13 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/7/173",
  abstract =     "The increasing cost of healthcare services is
                 accelerating the development of the telehealth system
                 to fulfill the necessity of delivering an efficient and
                 cost-effective remote healthcare services. Moreover,
                 the ageing of the global population and the disruption
                 of the COVID-19 pandemic are creating a rapid rise of
                 demand for healthcare services. This includes those who
                 are in need of remote monitoring for chronic conditions
                 through rehabilitation exercises. Therefore, this paper
                 presents a telehealth system using PoseNet for in-home
                 rehabilitation, with built-in statistical computation
                 for doctors to analyze the patient's recovery status.
                 This system enables patients to perform rehabilitation
                 exercises at home using an ordinary webcam. The PoseNet
                 skeleton-tracking method is applied to detect and track
                 the patients' angular movements for both elbows and
                 knees. By using this system, the measurement of the
                 elbow and knee joint angles can be calculated and
                 recorded while patients are performing rehabilitation
                 exercises in front of the laptop webcam. After the
                 patients complete their rehabilitation exercises, the
                 skeleton results of four body parts will be generated.
                 Based on the same actions performed by patients on
                 selected days, the doctors can examine and evaluate the
                 deviation rate of patients' angular movements between
                 different days to determine the recovery rate.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Akbar:2021:ODP,
  author =       "Zaenal Akbar and Hani Febri Mustika and Dwi Setyo Rini
                 and Lindung Parningotan Manik and Ariani Indrawati and
                 Agusdin Dharma Fefirenta and Tutie Djarwaningsih",
  title =        "An Ontology-Driven Personalized Faceted Search for
                 Exploring Knowledge Bases of {Capsicum}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "7",
  pages =        "172",
  day =          "30",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13070172",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 23 15:16:13 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/7/172",
  abstract =     "Capsicum is a genus of flowering plants in the
                 Solanaceae family in which the members are well known
                 to have a high economic value. The Capsicum fruits,
                 which are popularly known as peppers or chili, have
                 been widely used by people worldwide. It serves as a
                 spice and raw material for many products such as sauce,
                 food coloring, and medicine. For many years, scientists
                 have studied this plant to optimize its production. A
                 tremendous amount of knowledge has been obtained and
                 shared, as reflected in multiple knowledge-based
                 systems, databases, or information systems. An approach
                 to knowledge-sharing is through the adoption of a
                 common ontology to eliminate knowledge understanding
                 discrepancy. Unfortunately, most of the
                 knowledge-sharing solutions are intended for scientists
                 who are familiar with the subject. On the other hand,
                 there are groups of potential users that could benefit
                 from such systems but have minimal knowledge of the
                 subject. For these non-expert users, finding relevant
                 information from a less familiar knowledge base would
                 be daunting. More than that, users have various degrees
                 of understanding of the available content in the
                 knowledge base. This understanding discrepancy raises a
                 personalization problem. In this paper, we introduce a
                 solution to overcome this challenge. First, we
                 developed an ontology to facilitate knowledge-sharing
                 about Capsicum to non-expert users. Second, we
                 developed a personalized faceted search algorithm that
                 provides multiple structured ways to explore the
                 knowledge base. The algorithm addresses the
                 personalization problem by identifying the degree of
                 understanding about the subject from each user. In this
                 way, non-expert users could explore a knowledge base of
                 Capsicum efficiently. Our solution characterized users
                 into four groups. As a result, our faceted search
                 algorithm defines four types of matching mechanisms,
                 including three ranking mechanisms as the core of our
                 solution. In order to evaluate the proposed method, we
                 measured the predictability degree of produced list of
                 facets. Our findings indicated that the proposed
                 matching mechanisms could tolerate various query types,
                 and a high degree of predictability can be achieved by
                 combining multiple ranking mechanisms. Furthermore, it
                 demonstrates that our approach has a high potential
                 contribution to biodiversity science in general, where
                 many knowledge-based systems have been developed with
                 limited access to users outside of the domain.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tsai:2021:SBE,
  author =       "Pang-Wei Tsai and Aris Cahyadi Risdianto and Meng Hui
                 Choi and Satis Kumar Permal and Teck Chaw Ling",
  title =        "{SD-BROV}: an Enhanced {BGP} Hijacking Protection with
                 Route Validation in Software-Defined {eXchange}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "7",
  pages =        "171",
  day =          "30",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13070171",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 23 15:16:13 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/7/171",
  abstract =     "In global networks, Border Gateway Protocol (BGP) is
                 widely used in exchanging routing information. While
                 the original design of BGP did not focus on security
                 protection against deliberate or accidental errors
                 regarding to routing disruption, one of fundamental
                 vulnerabilities in BGP is a lack of insurance in
                 validating authority for announcing network layer
                 reachability. Therefore, a distributed repository
                 system known as Resource Public Key Infrastructure
                 (RPKI) has been utilized to mitigate this issue.
                 However, such a validation requires further deployment
                 steps for Autonomous System (AS), and it might cause
                 performance and compatibility problems in legacy
                 network infrastructure. Nevertheless, with recent
                 advancements in network innovation, some traditional
                 networks are planning to be restructured with
                 Software-Defined Networking (SDN) technology for
                 gaining more benefits. By using SDN, Internet eXchange
                 Point (IXP) is able to enhance its capability of
                 management by applying softwarized control methods,
                 acting as a Software-Defined eXchange (SDX) center to
                 handle numerous advertisement adaptively. To use the
                 SDN method to strengthen routing security of IXP, this
                 paper proposed an alternative SDX development, SD-BROV,
                 an SDX-based BGP Route Origin Validation mechanism that
                 establishes a flexible route exchange scenario with
                 RPKI validation. The validating application built in
                 the SDN controller is capable of investigating received
                 routing information. It aims to support hybrid SDN
                 environments and help non-SDN BGP neighbors to get
                 trusted routes and drop suspicious ones in transition.
                 To verify proposed idea with emulated environment, the
                 proof-of-concept development is deployed on an SDN
                 testbed running over Research and Education Networks
                 (RENs). During BGP hijacking experiment, the results
                 show that developed SD-BROV is able to detect and stop
                 legitimate traffic to be redirected by attacker, making
                 approach to secure traffic forwarding on BGP routers.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mountaser:2021:SBE,
  author =       "Ghizlane Mountaser and Toktam Mahmoodi",
  title =        "An {SDR}-Based Experimental Study of Reliable and
                 Low-Latency {Ethernet}-Based Fronthaul with {MAC-PHY}
                 Split",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "7",
  pages =        "170",
  day =          "30",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13070170",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 23 15:16:13 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/7/170",
  abstract =     "Cloud-Radio Access Network (RAN) is one of the
                 architectural solutions for those mobile networks that
                 aim to provide an infrastructure that satisfies the
                 communication needs of a wide range of services and
                 deployments. In Cloud-RAN, functions can be flexibly
                 split between central and distributed units, which
                 enables the use of different types of transport
                 network. Ethernet-based fronthaul can be an attractive
                 solution for Cloud-RAN. On the one hand, the deployment
                 of Ethernet-based fronthaul enables Cloud-RAN to
                 provide more diverse, flexible and cost-efficient
                 solutions. On the other hand, Ethernet-based fronthaul
                 requires packetized communication, which imposes
                 challenges to delivering stringent latency requirements
                 between RAN functionalities. In this paper, we set up a
                 hardware experiment based on Cloud-RAN with a low layer
                 split, particularly between medium access control and
                 the physical layer. The aim is to demonstrate how
                 multi-path and channel coding over the fronthaul can
                 improve fronthaul reliability while ensuring that: (i)
                 latency results meet the standard requirements; and
                 (ii) the overall system operates properly. Our results
                 show that the proposed solution can improve fronthaul
                 reliability while latency remains below a strict
                 latency bound required by the 3rd Generation
                 Partnership Project for this functional split.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chiluveru:2021:DSM,
  author =       "Rajeshwari Chiluveru and Nishu Gupta and Ariel Soares
                 Teles",
  title =        "Distribution of Safety Messages Using Mobility-Aware
                 Multi-Hop Clustering in Vehicular Ad Hoc Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "7",
  pages =        "169",
  day =          "29",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13070169",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 23 15:16:13 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/7/169",
  abstract =     "Reliability and security when distributing safety
                 messages among vehicles in an extremely mobile
                 environment are prominent issues in Vehicular Ad-Hoc
                 Networks (VANETs). In VANET, data transfer becomes
                 challenging because of inherent features such as
                 excessive speed, geographically constrained topologies,
                 unsteady communication links, diversity in the capacity
                 of the channel, etc. A major challenge in the multi-hop
                 framework is maintaining and building a path under such
                 a rigid environment. With VANET, potency in the traffic
                 safety applications has performed well because of the
                 proper design of medium access control (MAC) protocols.
                 In this article, a protocol is proposed pertaining to
                 the distribution of safety messages named
                 mobility-aware multi-hop clustering-based MAC
                 (MAMC-MAC) to accomplish minimum communication
                 overhead, high reliability, and delivery of safety
                 messages in real-time environments. MAMC-MAC has the
                 ability to establish clustering-based multi-hop
                 sequence using the time-division multiple access (TDMA)
                 technique. The protocol was specially developed for
                 highway outlines to achieve network enhancement and
                 efficient channel usage and guarantees integrity among
                 the vehicles. The performance of the proposed protocol
                 is evaluated using Network Simulator (NS-2), and it
                 demonstrates its superiority over various standard
                 protocols in terms of a number of quality-of-service
                 (QoS)-based parameters. The criteria to select and
                 assess these parameters are their sensitivity and
                 importance to the safety-based applications they
                 provide.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chen:2021:DPB,
  author =       "Xuan Chen and Shujuan Tian and Kien Nguyen and Hiroo
                 Sekiya",
  title =        "Decentralizing Private Blockchain-{IoT} Network with
                 {OLSR}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "7",
  pages =        "168",
  day =          "28",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13070168",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 23 15:16:13 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/7/168",
  abstract =     "With data transparency and immutability, the
                 blockchain can provide trustless and decentralized
                 services for Internet of Things (IoT) applications.
                 However, most blockchain-IoT networks, especially those
                 with a private blockchain, are built on top of an
                 infrastructure-based wireless network (i.e., using
                 Wi-Fi access points or cellular base stations). Hence,
                 they are still under the risk of
                 Single-Point-of-Failure (SPoF) on the network layer,
                 hindering the decentralization merit, for example, when
                 the access points or base stations get failures. This
                 paper presents an Optimized Link State Routing (OLSR)
                 protocol-based solution for that issue in a private
                 blockchain-IoT application. By decentralizing the
                 underlying network with OLSR, the private blockchain
                 network can avoid SPoF and automatically recover after
                 a failure. Single blockchain connections can be
                 extended to multiple ad hoc hops. Services over
                 blockchain become flexible to fit various IoT
                 scenarios. We show the effectiveness of our solution by
                 constructing a private Ethereum blockchain network
                 running on IoT devices (i.e., Raspberry Pi model 4)
                 with environmental data sensing (i.e., Particular
                 Matter (PM)). The IoT devices use OLSR to form an ad
                 hoc network. The environment data are collected and
                 propagated in transactions to a pre-loaded smart
                 contract periodically. We then evaluate the IoT
                 blockchain network's recovery time when facing a link
                 error. The evaluation results show that OLSR can
                 automatically recover after the failure. We also
                 evaluate the transaction-oriented latency and
                 block-oriented latency, which indicates the blocks have
                 a high transmission quality, while transactions are
                 transferred individually.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sharma:2021:SMF,
  author =       "Gourav Prateek Sharma and Wouter Tavernier and Didier
                 Colle and Mario Pickavet",
  title =        "Scheduling for Media Function Virtualization",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "7",
  pages =        "167",
  day =          "28",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13070167",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 23 15:16:13 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/7/167",
  abstract =     "Broadcasters are building studio architectures based
                 on commercial off-the-shelf (COTS) IT hardware because
                 of advantages such as cost reduction, ease of
                 management, and upgradation. Media function
                 virtualization (MFV) leverages IP networking to
                 transport media streams between virtual media functions
                 (VMFs), where they are processed. Media service
                 deployment in an MFV environment entails solving the
                 VMF-FG scheduling problem to ensure that the required
                 broadcast quality guarantees are fulfilled. In this
                 paper, we formulate the VMF-FG scheduling problem and
                 propose a greedy-based algorithm to solve it. The
                 evaluation of the algorithm is carried in terms of the
                 end-to-end delay and VMF queuing delay. Moreover, the
                 importance of VMF-FG decomposition in upgradation to
                 higher-quality formats is also highlighted.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Albeshri:2021:IHB,
  author =       "Aiiad Albeshri",
  title =        "An Image Hashing-Based Authentication and Secure Group
                 Communication Scheme for {IoT}-Enabled {MANETs}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "7",
  pages =        "166",
  day =          "27",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13070166",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 23 15:16:13 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/hash.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/7/166",
  abstract =     "Mobile ad hoc networks (MANETs) play a highly
                 significant role in the Internet of Things (IoT) for
                 managing node mobility. MANET opens the pathway for
                 different IoT-based communication systems with
                 effective abilities for a variety of applications in
                 several domains. In IoT-based systems, it provides the
                 self-formation and self-connection of networks. A key
                 advantage of MANETs is that any device or node can
                 freely join or leave the network; however, this makes
                 the networks and applications vulnerable to security
                 attacks. Thus, authentication plays an essential role
                 in protecting the network or system from several
                 security attacks. Consequently, secure communication is
                 an important prerequisite for nodes in MANETs. The main
                 problem is that the node moving from one group to
                 another may be attacked on the way by misleading the
                 device to join the neighboring group. To address this,
                 in this paper, we present an authentication mechanism
                 based on image hashing where the network administrator
                 allows the crosschecking of the identity image of a
                 soldier (i.e., a node) in the joining group. We propose
                 the node joining and node migration algorithms where
                 authentication is involved to ensure secure
                 identification. The simulation tool NS-2 is employed to
                 conduct extensive simulations for extracting the
                 results from the trace files. The results demonstrate
                 the effectiveness of the proposed scheme based on the
                 memory storage communication overhead and computational
                 cost. In our scheme, the attack can be detected
                 effectively and also provides a highly robust
                 assurance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Cunha:2021:BCB,
  author =       "Paulo Rupino Cunha and Paulo Melo and Helder
                 Sebasti{\~a}o",
  title =        "From Bitcoin to Central Bank Digital Currencies:
                 Making Sense of the Digital Money Revolution",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "7",
  pages =        "165",
  day =          "27",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13070165",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 23 15:16:13 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/7/165",
  abstract =     "We analyze the path from cryptocurrencies to official
                 Central Bank Digital Currencies (CBDCs), to shed some
                 light on the ultimate dematerialization of money. To
                 that end, we made an extensive search that resulted in
                 a review of more than 100 academic and grey literature
                 references, including official positions from central
                 banks. We present and discuss the characteristics of
                 the different CBDC variants being considered-namely,
                 wholesale, retail, and, for the latter, the
                 account-based, and token-based-as well as ongoing
                 pilots, scenarios of interoperability, and open issues.
                 Our contribution enables decision-makers and society at
                 large to understand the potential advantages and risks
                 of introducing CBDCs, and how these vary according to
                 many technical and economic design choices. The
                 practical implication is that a debate becomes possible
                 about the trade-offs that the stakeholders are willing
                 to accept.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gwyn:2021:FRU,
  author =       "Tony Gwyn and Kaushik Roy and Mustafa Atay",
  title =        "Face Recognition Using Popular Deep Net Architectures:
                 a Brief Comparative Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "7",
  pages =        "164",
  day =          "25",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13070164",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 23 15:16:13 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/7/164",
  abstract =     "In the realm of computer security, the
                 username/password standard is becoming increasingly
                 antiquated. Usage of the same username and password
                 across various accounts can leave a user open to
                 potential vulnerabilities. Authentication methods of
                 the future need to maintain the ability to provide
                 secure access without a reduction in speed. Facial
                 recognition technologies are quickly becoming integral
                 parts of user security, allowing for a secondary level
                 of user authentication. Augmenting traditional username
                 and password security with facial biometrics has
                 already seen impressive results; however, studying
                 these techniques is necessary to determine how
                 effective these methods are within various parameters.
                 A Convolutional Neural Network (CNN) is a powerful
                 classification approach which is often used for image
                 identification and verification. Quite recently, CNNs
                 have shown great promise in the area of facial image
                 recognition. The comparative study proposed in this
                 paper offers an in-depth analysis of several
                 state-of-the-art deep learning based-facial recognition
                 technologies, to determine via accuracy and other
                 metrics which of those are most effective. In our
                 study, VGG-16 and VGG-19 showed the highest levels of
                 image recognition accuracy, as well as F1-Score. The
                 most favorable configurations of CNN should be
                 documented as an effective way to potentially augment
                 the current username/password standard by increasing
                 the current method's security with additional facial
                 biometrics.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Song:2021:SAC,
  author =       "Guizhe Song and Degen Huang",
  title =        "A Sentiment-Aware Contextual Model for Real-Time
                 Disaster Prediction Using {Twitter} Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "7",
  pages =        "163",
  day =          "25",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13070163",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 23 15:16:13 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/7/163",
  abstract =     "The massive amount of data generated by social media
                 present a unique opportunity for disaster analysis. As
                 a leading social platform, Twitter generates over 500
                 million Tweets each day. Due to its real-time
                 characteristic, more agencies employ Twitter to track
                 disaster events to make a speedy rescue plan. However,
                 it is challenging to build an accurate predictive model
                 to identify disaster Tweets, which may lack sufficient
                 context due to the length limit. In addition, disaster
                 Tweets and regular ones can be hard to distinguish
                 because of word ambiguity. In this paper, we propose a
                 sentiment-aware contextual model named
                 SentiBERT-BiLSTM-CNN for disaster detection using
                 Tweets. The proposed learning pipeline consists of
                 SentiBERT that can generate sentimental contextual
                 embeddings from a Tweet, a Bidirectional long
                 short-term memory (BiLSTM) layer with attention, and a
                 1D convolutional layer for local feature extraction. We
                 conduct extensive experiments to validate certain
                 design choices of the model and compare our model with
                 its peers. Results show that the proposed
                 SentiBERT-BiLSTM-CNN demonstrates superior performance
                 in the F1 score, making it a competitive model in
                 Tweets-based disaster prediction.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gao:2021:IQE,
  author =       "Hui-Li Gao",
  title =        "The Impact of Quality of Experience of {Chinese}
                 College Students on {Internet}-Based Resources
                 {English} Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "7",
  pages =        "162",
  day =          "22",
  month =        jun,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13070162",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jul 23 15:16:13 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/7/162",
  abstract =     "Since Internet-based resources provides various and
                 practical forms of English learning materials,
                 Internet-based resources English learning is a common
                 way for the younger generation. However, not like adult
                 learning, university students need stronger motivation
                 to learn English from Internet-based resources. This
                 study surveyed Chinese college students in Central
                 China to reveal the relationship between cultural
                 intelligence, hedonic motivation, English
                 self-efficacy, online experience quality, and
                 willingness to continue learning online English. Using
                 online media platforms and convenient sampling methods,
                 a total of 385 questionnaires were collected. The data
                 analysis was divided into three phases, descriptive
                 analysis, measurement model evaluation, and structural
                 equation model examination. The results showed Internet
                 quality of experience significantly impacted English
                 continuous learning intention. Cultural intelligence,
                 English self-efficacy, and hedonic motivation all
                 influenced significantly on Internet quality of
                 experience and hedonic motivation had the strongest
                 impact. In addition, the mediation effects of Internet
                 quality of experience to these three factors and
                 Internet-based resources English continuous learning
                 intention all existed. Finally, the research results
                 show cultural intelligence, English self-efficacy, and
                 hedonic motivation were all examined significantly
                 impacting Internet quality of experience statistically.
                 English learning hedonic motivation is the most
                 influencing factor. Therefore, English learning
                 material should be attractive, fun, and enjoyable. This
                 is what the teachers should think of and emphasize when
                 to recommend learning material for students.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Barchi:2021:SNN,
  author =       "Francesco Barchi and Luca Zanatta and Emanuele Parisi
                 and Alessio Burrello and Davide Brunelli and Andrea
                 Bartolini and Andrea Acquaviva",
  title =        "Spiking Neural Network-Based Near-Sensor Computing for
                 Damage Detection in Structural Health Monitoring",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "219",
  day =          "23",
  month =        aug,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080219",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/219",
  abstract =     "In this work, we present an innovative approach for
                 damage detection of infrastructures on-edge devices,
                 exploiting a brain-inspired algorithm. The proposed
                 solution exploits recurrent spiking neural networks
                 (LSNNs), which are emerging for their theoretical
                 energy efficiency and compactness, to recognise damage
                 conditions by processing data from low-cost
                 accelerometers (MEMS) directly on the sensor node. We
                 focus on designing an efficient coding of MEMS data to
                 optimise SNN execution on a low-power microcontroller.
                 We characterised and profiled LSNN performance and
                 energy consumption on a hardware prototype sensor node
                 equipped with an STM32 embedded microcontroller and a
                 digital MEMS accelerometer. We used a
                 hardware-in-the-loop environment with virtual sensors
                 generating data on an SPI interface connected to the
                 physical microcontroller to evaluate the system with a
                 data stream from a real viaduct. We exploited this
                 environment also to study the impact of different
                 on-sensor encoding techniques, mimicking a bio-inspired
                 sensor able to generate events instead of
                 accelerations. Obtained results show that the proposed
                 optimised embedded LSNN (eLSNN), when using a
                 spike-based input encoding technique, achieves 54\%
                 lower execution time with respect to a naive LSNN
                 algorithm implementation present in the
                 state-of-the-art. The optimised eLSNN requires around
                 47 kCycles, which is comparable with the data transfer
                 cost from the SPI interface. However, the spike-based
                 encoding technique requires considerably larger input
                 vectors to get the same classification accuracy,
                 resulting in a longer pre-processing and sensor access
                 time. Overall the event-based encoding techniques leads
                 to a longer execution time (1.49$ \times $) but similar
                 energy consumption. Moving this coding on the sensor
                 can remove this limitation leading to an overall more
                 energy-efficient monitoring system.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ghazal:2021:ISC,
  author =       "Taher M. Ghazal and Mohammad Kamrul Hasan and Muhammad
                 Turki Alshurideh and Haitham M. Alzoubi and Munir Ahmad
                 and Syed Shehryar Akbar and Barween {Al Kurdi} and Iman
                 A. Akour",
  title =        "{IoT} for Smart Cities: Machine Learning Approaches in
                 Smart Healthcare --- a Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "218",
  day =          "23",
  month =        aug,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080218",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/218",
  abstract =     "Smart city is a collective term for technologies and
                 concepts that are directed toward making cities
                 efficient, technologically more advanced, greener and
                 more socially inclusive. These concepts include
                 technical, economic and social innovations. This term
                 has been tossed around by various actors in politics,
                 business, administration and urban planning since the
                 2000s to establish tech-based changes and innovations
                 in urban areas. The idea of the smart city is used in
                 conjunction with the utilization of digital
                 technologies and at the same time represents a reaction
                 to the economic, social and political challenges that
                 post-industrial societies are confronted with at the
                 start of the new millennium. The key focus is on
                 dealing with challenges faced by urban society, such as
                 environmental pollution, demographic change, population
                 growth, healthcare, the financial crisis or scarcity of
                 resources. In a broader sense, the term also includes
                 non-technical innovations that make urban life more
                 sustainable. So far, the idea of using IoT-based sensor
                 networks for healthcare applications is a promising one
                 with the potential of minimizing inefficiencies in the
                 existing infrastructure. A machine learning approach is
                 key to successful implementation of the IoT-powered
                 wireless sensor networks for this purpose since there
                 is large amount of data to be handled intelligently.
                 Throughout this paper, it will be discussed in detail
                 how AI-powered IoT and WSNs are applied in the
                 healthcare sector. This research will be a baseline
                 study for understanding the role of the IoT in smart
                 cities, in particular in the healthcare sector, for
                 future research works.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Piao:2021:DSS,
  author =       "Yangheran Piao and Kai Ye and Xiaohui Cui",
  title =        "A Data Sharing Scheme for {GDPR}-Compliance Based on
                 Consortium Blockchain",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "217",
  day =          "21",
  month =        aug,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080217",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/217",
  abstract =     "After the General Data Protection Regulation (GDPR)
                 was introduced, some organizations and big data
                 companies shared data without conducting any privacy
                 protection and compliance authentication, which
                 endangered user data security, and were punished
                 financially for this reason. This study proposes a
                 blockchain-based GDPR compliance data sharing scheme,
                 aiming to promote compliance with regulations and
                 provide a tool for interaction between users and
                 service providers to achieve data security sharing. The
                 zero-knowledge Succinct Non-Interactive Arguments of
                 Knowledge (zk-SNARK) algorithm is adopted for
                 protecting data and ensure that the user's private data
                 can satisfy the individual requirements of the service
                 provider without exposing user data. The proposed
                 scheme ensures mutual authentication through the Proof
                 of Authority consensus based on the Committee
                 Endorsement Mechanism (CEM-PoA), and prevents nodes
                 from doing evil using the reputation incentive
                 mechanism. Theoretical analysis and performance
                 comparison indicate that the scheme meets the
                 confidentiality, availability, and other indicators. It
                 has superiority in efficiency and privacy protection
                 compared with other schemes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhao:2021:CPD,
  author =       "Yu Zhao and Yi Zhu and Qiao Yu and Xiaoying Chen",
  title =        "Cross-Project Defect Prediction Method Based on
                 Manifold Feature Transformation",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "216",
  day =          "20",
  month =        aug,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080216",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/216",
  abstract =     "Traditional research methods in software defect
                 prediction use part of the data in the same project to
                 train the defect prediction model and predict the
                 defect label of the remaining part of the data.
                 However, in the practical realm of software
                 development, the software project that needs to be
                 predicted is generally a brand new software project,
                 and there is not enough labeled data to build a defect
                 prediction model; therefore, traditional methods are no
                 longer applicable. Cross-project defect prediction uses
                 the labeled data of the same type of project similar to
                 the target project to build the defect prediction
                 model, so as to solve the problem of data loss in
                 traditional methods. However, the difference in data
                 distribution between the same type of project and the
                 target project reduces the performance of defect
                 prediction. To solve this problem, this paper proposes
                 a cross-project defect prediction method based on
                 manifold feature transformation. This method transforms
                 the original feature space of the project into a
                 manifold space, then reduces the difference in data
                 distribution of the transformed source project and the
                 transformed target project in the manifold space, and
                 finally uses the transformed source project to train a
                 naive Bayes prediction model with better performance. A
                 comparative experiment was carried out using the Relink
                 dataset and the AEEEM dataset. The experimental results
                 show that compared with the benchmark method and
                 several cross-project defect prediction methods, the
                 proposed method effectively reduces the difference in
                 data distribution between the source project and the
                 target project, and obtains a higher F1 value, which is
                 an indicator commonly used to measure the performance
                 of the two-class model.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chang:2021:TLR,
  author =       "Chin-Chen Chang and Jui-Feng Chang and Wei-Jiun Kao
                 and Ji-Hwei Horng",
  title =        "Two-Layer Reversible Data Hiding for {VQ}-Compressed
                 Images Based on De-Clustering and Indicator-Free
                 Search-Order Coding",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "215",
  day =          "20",
  month =        aug,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080215",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/215",
  abstract =     "During transmission of digital images, secret messages
                 can be embedded using data hiding techniques. Such
                 techniques can transfer private secrets without drawing
                 the attention of eavesdroppers. To reduce the amount of
                 transmitted data, image compression methods are widely
                 applied. Hiding secret data in compressed images is a
                 hot issue recently. In this paper, we apply the
                 de-clustering concept and the indicator-free
                 search-order coding (IFSOC) technique to hide
                 information into vector quantization (VQ) compressed
                 images. Experimental results show that the proposed
                 two-layer reversible data hiding scheme for
                 IFSOC-encoded VQ index table can hide a large amount of
                 secret data among state-of-the-art methods with a
                 relatively lower bit rate and high security.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ivanov:2021:IUM,
  author =       "Vladimir M. Ivanov and Anton M. Krivtsov and Sergey V.
                 Strelkov and Nikolay V. Kalakutskiy and Andrey I.
                 Yaremenko and Marina Yu. Petropavlovskaya and Maria N.
                 Portnova and Olga V. Lukina and Andrey P. Litvinov",
  title =        "Intraoperative Use of Mixed Reality Technology in
                 Median Neck and Branchial Cyst Excision",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "214",
  day =          "18",
  month =        aug,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080214",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/214",
  abstract =     "The paper considers the possibilities, prospects, and
                 drawbacks of the mixed reality (MR) technology
                 application using mixed reality smartglasses Microsoft
                 HoloLens 2. The main challenge was to find and develop
                 an approach that would allow surgeons to conduct
                 operations using mixed reality on a large scale,
                 reducing the preparation time required for the
                 procedure and without having to create custom solutions
                 for each patient. Research was conducted in three
                 clinical cases: two median neck and one branchial cyst
                 excisions. In each case, we applied a unique approach
                 of hologram positioning in space based on mixed reality
                 markers. As a result, we listed a series of positive
                 and negative aspects related to MR surgery, along with
                 proposed solutions for using MR in surgery on a daily
                 basis.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Euttamarajah:2021:EEJ,
  author =       "Shornalatha Euttamarajah and Yin Hoe Ng and Chee Keong
                 Tan",
  title =        "Energy-Efficient Joint Base Station Switching and
                 Power Allocation for Smart Grid Based Hybrid-Powered
                 {CoMP}-Enabled {HetNet}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "213",
  day =          "17",
  month =        aug,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080213",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/213",
  abstract =     "With the rapid proliferation of wireless traffic and
                 the surge of various data-intensive applications, the
                 energy consumption of wireless networks has
                 tremendously increased in the last decade, which not
                 only leads to more CO 2 emission, but also results in
                 higher operating expenditure. Consequently, energy
                 efficiency (EE) has been regarded as an essential
                 design criterion for future wireless networks. This
                 paper investigates the problem of EE maximisation for a
                 cooperative heterogeneous network (HetNet) powered by
                 hybrid energy sources via joint base station (BS)
                 switching (BS-Sw) and power allocation using
                 combinatorial optimisation. The cooperation among the
                 BSs is achieved through a coordinated multi-point
                 (CoMP) technique. Next, to overcome the complexity of
                 combinatorial optimisation, Lagrange dual decomposition
                 is applied to solve the power allocation problem and a
                 sub-optimal distance-based BS-Sw scheme is proposed.
                 The main advantage of the distance-based BS-Sw is that
                 the algorithm is tuning-free as it exploits two dynamic
                 thresholds, which can automatically adapt to various
                 user distributions and network deployment scenarios.
                 The optimal binomial and random BS-Sw schemes are also
                 studied to serve as benchmarks. Further, to solve the
                 non-fractional programming component of the EE
                 maximisation problem, a low-complexity and fast
                 converging Dinkelbach's method is proposed. Extensive
                 simulations under various scenarios reveal that in
                 terms of EE, the proposed joint distance-based BS-Sw
                 and power allocation technique applied to the
                 cooperative and harvesting BSs performs around 15-20\%
                 better than the non-cooperative and non-harvesting BSs
                 and can achieve near-optimal performance compared to
                 the optimal binomial method.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Casini:2021:BAI,
  author =       "Luca Casini and Marco Roccetti",
  title =        "A {Bayesian} Analysis of the Inversion of the
                 {SARS-COV-2} Case Rate in the Countries of the {2020
                 European Football Championship}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "212",
  day =          "17",
  month =        aug,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080212",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/212",
  abstract =     "While Europe was beginning to deal with the resurgence
                 of COVID-19 due to the Delta variant, the European
                 football championship took place from 11 June to 11
                 July 2021. We studied the inversion in the
                 decreased/increased rate of new SARS-COV-2 infections
                 in the countries of the tournament, investigating the
                 hypothesis of an association. Using a Bayesian
                 piecewise regression with a Poisson generalized linear
                 model, we looked for a changepoint in the timeseries of
                 the new SARS-COV-2 cases of each country, expecting it
                 to appear not later than two to three weeks after the
                 date of their first match. The two slopes, before and
                 after the changepoint, were used to discuss the
                 reversal from a decreasing to an increasing rate of the
                 infections. For 17 out of 22 countries (77\%) the
                 changepoint came on average 14.97 days after their
                 first match (95\% CI 12.29-17.47). For all those 17
                 countries, the changepoint coincides with an inversion
                 from a decreasing to an increasing rate of the
                 infections. Before the changepoint, the new cases were
                 decreasing, halving on average every 18.07 days (95\%
                 CI 11.81-29.42). After the changepoint, the cases begin
                 to increase, doubling every 29.10 days (95\% CI
                 14.12-9.78). This inversion in the SARS-COV-2 case
                 rate, which happened during the tournament, provides
                 evidence in favor of a relationship.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yoon:2021:RPP,
  author =       "Youngjoon Yoon and Hyogon Kim",
  title =        "Resolving Persistent Packet Collisions through
                 Broadcast Feedback in Cellular {V2X} Communication",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "211",
  day =          "16",
  month =        aug,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080211",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/211",
  abstract =     "The Third Generation Partnership Project (3GPP)
                 Release 16 defines the sensing-based semi-persistent
                 scheduling (SPS) as the resource allocation scheme for
                 Sidelink Mode 2 in New Radio (NR)-based
                 vehicle-to-everything (V2X) communication. A well-known
                 issue in Mode 2 is the persistent packet collision that
                 results from two or more vehicles repeatedly using the
                 same resource for transmission. It may create serious
                 safety problems when the vehicles are in a situation
                 where only the broadcast safety beacons can assist in
                 driving. To resolve this issue, a solution that relies
                 on the feedback from neighboring vehicles is proposed,
                 through which the vehicles suffering from persistent
                 packet collisions can quickly part and select other
                 resources. Extensive simulations show that the proposed
                 broadcast feedback scheme reduces persistent packet
                 collisions by an order of magnitude compared to SPS,
                 and it is achieved without sacrificing the average
                 packet reception ratio (PRR). Namely, it is the quality
                 aspect (i.e., burstiness) of the packet collisions that
                 the proposed scheme addresses rather than the quantity
                 (i.e., total number of collision losses). By preventing
                 extended packet loss events, the proposed scheme is
                 expected to serve NR V2X better, which requires
                 stringent QoS in terms of the information update delay
                 thereby helping to reduce the chances of vehicle
                 crashes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ghorpade:2021:SLI,
  author =       "Sheetal Ghorpade and Marco Zennaro and Bharat
                 Chaudhari",
  title =        "Survey of Localization for {Internet of Things} Nodes:
                 Approaches, Challenges and Open Issues",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "210",
  day =          "16",
  month =        aug,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080210",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/210",
  abstract =     "With exponential growth in the deployment of Internet
                 of Things (IoT) devices, many new innovative and
                 real-life applications are being developed. IoT
                 supports such applications with the help of
                 resource-constrained fixed as well as mobile nodes.
                 These nodes can be placed in anything from vehicles to
                 the human body to smart homes to smart factories.
                 Mobility of the nodes enhances the network coverage and
                 connectivity. One of the crucial requirements in IoT
                 systems is the accurate and fast localization of its
                 nodes with high energy efficiency and low cost. The
                 localization process has several challenges. These
                 challenges keep changing depending on the location and
                 movement of nodes such as outdoor, indoor, with or
                 without obstacles and so on. The performance of
                 localization techniques greatly depends on the
                 scenarios and conditions from which the nodes are
                 traversing. Precise localization of nodes is very much
                 required in many unique applications. Although several
                 localization techniques and algorithms are available,
                 there are still many challenges for the precise and
                 efficient localization of the nodes. This paper
                 classifies and discusses various state-of-the-art
                 techniques proposed for IoT node localization in
                 detail. It includes the different approaches such as
                 centralized, distributed, iterative, ranged based,
                 range free, device-based, device-free and their
                 subtypes. Furthermore, the different performance
                 metrics that can be used for localization, comparison
                 of the different techniques, some prominent
                 applications in smart cities and future directions are
                 also covered.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ellawindy:2021:CFQ,
  author =       "Ibtihal Ellawindy and Shahram Shah Heydari",
  title =        "Crowdsourcing Framework for {QoE}-Aware {SD-WAN}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "209",
  day =          "15",
  month =        aug,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080209",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/209",
  abstract =     "Quality of experience (QoE) is an important measure of
                 users' satisfaction regarding their network-based
                 services, and it is widely employed today to provide a
                 real assessment of the service quality as perceived by
                 the end users. QoE measures can be used to improve
                 application performance, as well as to optimize network
                 resources and reallocate them as needed when the
                 service quality degrades. While quantitative QoE
                 assessments based on network parameters may provide
                 insights into users' experience, subjective assessments
                 through direct feedback from the users have also
                 gathered interest recently due to their accuracy and
                 interactive nature. In this paper, we propose a
                 framework that can be used to collect real-time QoE
                 feedback through crowdsourcing and forward it to
                 network controllers to enhance streaming routes. We
                 analyze how QoE can be affected by different network
                 conditions, and how different streaming protocols
                 compare against each other when the network parameters
                 change dynamically. We also compare the real-time user
                 feedback to predefined network changes to measure if
                 participants will be able to identify all degradation
                 events, as well as to examine which combination of
                 degradation events are noticeable to the participants.
                 Our aim is to demonstrate that real-time QoE feedback
                 can enhance cloud-based services and can adjust service
                 quality on the basis of real-time, active participants'
                 interactions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kieseberg:2021:SID,
  author =       "Peter Kieseberg and Sebastian Schrittwieser and Edgar
                 Weippl",
  title =        "Secure Internal Data Markets",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "208",
  day =          "12",
  month =        aug,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080208",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/208",
  abstract =     "The data market concept has gained a lot of momentum
                 in recent years, fuelled by initiatives to set up such
                 markets, e.g., on the European level. Still, the
                 typical data market concept aims at providing a
                 centralised platform with all of its positive and
                 negative side effects. Internal data markets, also
                 called local or on-premise data markets, on the other
                 hand, are set up to allow data trade inside an
                 institution (e.g., between divisions of a large
                 company) or between members of a small, well-defined
                 consortium, thus allowing the remuneration of providing
                 data inside these structures. Still, while research on
                 securing global data markets has garnered some
                 attention throughout recent years, the internal data
                 markets have been treated as being more or less similar
                 in this respect. In this paper, we outline the major
                 differences between global and internal data markets
                 with respect to security and why further research is
                 required. Furthermore, we provide a fundamental model
                 for a secure internal data market that can be used as a
                 starting point for the generation of concrete internal
                 data market models. Finally, we provide an overview on
                 the research questions we deem most pressing in order
                 to make the internal data market concept work securely,
                 thus allowing for more widespread adoption.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alzahrani:2021:SSB,
  author =       "Bander Alzahrani and Nikos Fotiou",
  title =        "Securing {SDN}-Based {IoT} Group Communication",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "207",
  day =          "09",
  month =        aug,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080207",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/207",
  abstract =     "IoT group communication allows users to control
                 multiple IoT devices simultaneously. A convenient
                 method for implementing this communication paradigm is
                 by leveraging software-defined networking (SDN) and
                 allowing IoT endpoints to ``advertise'' the resources
                 that can be accessed through group communication. In
                 this paper, we propose a solution for securing this
                 process by preventing IoT endpoints from advertising
                 ``fake'' resources. We consider group communication
                 using the constrained application protocol (CoAP), and
                 we leverage Web of Things (WoT) Thing Description (TD)
                 to enable resources' advertisement. In order to achieve
                 our goal, we are using linked-data proofs.
                 Additionally, we evaluate the application of
                 zero-knowledge proofs (ZKPs) for hiding certain
                 properties of a WoT-TD file.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Vazquez-Lopez:2021:FAG,
  author =       "Alba V{\'a}zquez-L{\'o}pez and Manuel Marey-Perez",
  title =        "Factors Affecting e-Government Adoption by Dairy
                 Farmers: a Case Study in the {North-West} of {Spain}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "206",
  day =          "05",
  month =        aug,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080206",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/206",
  abstract =     "With the objective of assessing the farmers' situation
                 regarding the use of the ICT and their relations with
                 the electronic government, a case study consisting in
                 the realization of 34 face-to-face surveys was
                 conducted between February and March 2020 in dairy
                 farms in the region of Galicia (Spain). The sample was
                 selected according to one of the most important online
                 journals in the farming sector at a national level.
                 From the census, we chose those farms considered most
                 representative taking into account the main criteria:
                 the level of PAC (Common Agrarian Politics) subsidies
                 and milk production (litres/cow and year). The results
                 show that the majority of the farmers used the
                 internet, but on many an occasion, they were
                 discontented in relation to the poor connection quality
                 in their farms. In regard to the use of the electronic
                 government for procedures related to their farms, many
                 of them were able to perform them through the
                 government website; however, there were procedures
                 which the users defined as ``complex'' and which had to
                 be outsourced to authorised entities. The results also
                 show that the farmers do want to employ the
                 e-government, mainly because of the time and cost
                 saving; however, the current web pages do not meet the
                 users' expectations. Finally, this situation, applied
                 to a region placed among the 10 most productive regions
                 of milk, is comparable to what happens in other
                 regions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tashman:2021:CFC,
  author =       "Deemah Tashman and Walaa Hamouda",
  title =        "Cascaded $ \kappa $--$ \mu $ Fading Channels with
                 Colluding and Non-Colluding Eavesdroppers:
                 Physical-Layer Security Analysis",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "205",
  day =          "04",
  month =        aug,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080205",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/205",
  abstract =     "In this paper, the physical-layer security for a
                 three-node wiretap system model is studied. Under the
                 threat of multiple eavesdroppers, it is presumed that a
                 transmitter is communicating with a legitimate
                 receiver. The channels are assumed to be following
                 cascaded $ \kappa $--$ \mu $ fading distributions. In
                 addition, two scenarios for eavesdroppers' interception
                 and information-processing capabilities are
                 investigated: colluding and non-colluding
                 eavesdroppers. The positions of these eavesdroppers are
                 assumed to be random in the non-colluding eavesdropping
                 scenario, based on a homogeneous Poisson point process
                 (HPPP). The security is examined in terms of the
                 secrecy outage probability, the probability of non-zero
                 secrecy capacity, and the intercept probability. The
                 exact and asymptotic expressions for the secrecy outage
                 probability and the probability of non-zero secrecy
                 capacity are derived. The results demonstrate the
                 effect of the cascade level on security. Additionally,
                 the results indicate that as the number of
                 eavesdroppers rises, the privacy of signals exchanged
                 between legitimate ends deteriorates. Furthermore, in
                 this paper, regarding the capabilities of tapping and
                 processing the information, we provide a comparison
                 between colluding and non-colluding eavesdropping.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rojas:2021:DBR,
  author =       "Oscar Rojas and Veronica Gil-Costa and Mauricio
                 Marin",
  title =        "A {DFT}-Based Running Time Prediction Algorithm for
                 {Web} Queries",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "204",
  day =          "04",
  month =        aug,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080204",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/204",
  abstract =     "Web search engines are built from components capable
                 of processing large amounts of user queries per second
                 in a distributed way. Among them, the index service
                 computes the top- k documents that best match each
                 incoming query by means of a document ranking
                 operation. To achieve high performance, dynamic pruning
                 techniques such as the WAND and BM-WAND algorithms are
                 used to avoid fully processing all of the documents
                 related to a query during the ranking operation.
                 Additionally, the index service distributes the ranking
                 operations among clusters of processors wherein in each
                 processor multi-threading is applied to speed up query
                 solution. In this scenario, a query running time
                 prediction algorithm has practical applications in the
                 efficient assignment of processors and threads to
                 incoming queries. We propose a prediction algorithm for
                 the WAND and BM-WAND algorithms. We experimentally show
                 that our proposal is able to achieve accurate
                 prediction results while significantly reducing
                 execution time and memory consumption as compared
                 against an alternative prediction algorithm. Our
                 proposal applies the discrete Fourier transform (DFT)
                 to represent key features affecting query running time
                 whereas the resulting vectors are used to train a
                 feed-forward neural network with back-propagation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kammerer:2021:ASD,
  author =       "Klaus Kammerer and Manuel G{\"o}ster and Manfred
                 Reichert and R{\"u}diger Pryss",
  title =        "Ambalytics: a Scalable and Distributed System
                 Architecture Concept for Bibliometric Network
                 Analyses",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "203",
  day =          "04",
  month =        aug,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080203",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/203",
  abstract =     "A deep understanding about a field of research is
                 valuable for academic researchers. In addition to
                 technical knowledge, this includes knowledge about
                 subareas, open research questions, and social
                 communities (networks) of individuals and organizations
                 within a given field. With bibliometric analyses,
                 researchers can acquire quantitatively valuable
                 knowledge about a research area by using bibliographic
                 information on academic publications provided by
                 bibliographic data providers. Bibliometric analyses
                 include the calculation of bibliometric networks to
                 describe affiliations or similarities of bibliometric
                 entities (e.g., authors) and group them into clusters
                 representing subareas or communities. Calculating and
                 visualizing bibliometric networks is a nontrivial and
                 time-consuming data science task that requires highly
                 skilled individuals. In addition to domain knowledge,
                 researchers must often provide statistical knowledge
                 and programming skills or use software tools having
                 limited functionality and usability. In this paper, we
                 present the ambalytics bibliometric platform, which
                 reduces the complexity of bibliometric network analysis
                 and the visualization of results. It accompanies users
                 through the process of bibliometric analysis and
                 eliminates the need for individuals to have programming
                 skills and statistical knowledge, while preserving
                 advanced functionality, such as algorithm
                 parameterization, for experts. As a proof-of-concept,
                 and as an example of bibliometric analyses outcomes,
                 the calculation of research fronts networks based on a
                 hybrid similarity approach is shown. Being designed to
                 scale, ambalytics makes use of distributed systems
                 concepts and technologies. It is based on the
                 microservice architecture concept and uses the
                 Kubernetes framework for orchestration. This paper
                 presents the initial building block of a comprehensive
                 bibliometric analysis platform called ambalytics, which
                 aims at a high usability for users as well as
                 scalability.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Balderas:2021:ETB,
  author =       "David Balderas and Pedro Ponce and Diego Lopez-Bernal
                 and Arturo Molina",
  title =        "{Education 4.0}: Teaching the Basis of Motor Imagery
                 Classification Algorithms for Brain--Computer
                 Interfaces",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "202",
  day =          "03",
  month =        aug,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080202",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/202",
  abstract =     "Education 4.0 is looking to prepare future scientists
                 and engineers not only by granting them with knowledge
                 and skills but also by giving them the ability to apply
                 them to solve real life problems through the
                 implementation of disruptive technologies. As a
                 consequence, there is a growing demand for educational
                 material that introduces science and engineering
                 students to technologies, such as Artificial
                 Intelligence (AI) and Brain-Computer Interfaces (BCI).
                 Thus, our contribution towards the development of this
                 material is to create a test bench for BCI given the
                 basis and analysis on how they can be discriminated
                 against. This is shown using different AI methods:
                 Fisher Linear Discriminant Analysis (LDA), Support
                 Vector Machines (SVM), Artificial Neural Networks
                 (ANN), Restricted Boltzmann Machines (RBM) and
                 Self-Organizing Maps (SOM), allowing students to see
                 how input changes alter their performance. These tests
                 were done against a two-class Motor Image database.
                 First, using a large frequency band and no filtering
                 eye movement. Secondly, the band was reduced and the
                 eye movement was filtered. The accuracy was analyzed
                 obtaining values around 70--80\% for all methods,
                 excluding SVM and SOM mapping. Accuracy and mapping
                 differentiability increased for some subjects for the
                 second scenario 70--85\%, meaning either their band
                 with the most significant information is on that
                 limited space or the contamination because of eye
                 movement was better mitigated by the regression method.
                 This can be translated to saying that these methods
                 work better under limited spaces. The outcome of this
                 work is useful to show future scientists and engineers
                 how BCI experiments are conducted while teaching them
                 the basics of some AI techniques that can be used in
                 this and other several experiments that can be carried
                 on the framework of Education 4.0.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lim:2021:PMV,
  author =       "Seng Boon Lim and Jalaluddin Abdul Malek and Tan
                 Yigitcanlar",
  title =        "Post-Materialist Values of Smart City Societies:
                 International Comparison of Public Values for Good
                 Enough Governance",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "201",
  day =          "03",
  month =        aug,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080201",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/201",
  abstract =     "This study aims to analyze the application of good
                 enough governance in considering the citizens' value
                 propositions that shape smart city societies. This
                 paper applied a quantitative method with cross-country
                 comparisons. Survey data were derived from the World
                 Values Survey. Malaysia was chosen as the main study
                 area, and compared with Indonesia and other countries
                 worldwide. The findings revealed that politics is the
                 value of least concern across all samples. In terms of
                 qualities for children to develop, respondents in both
                 Malaysia and Indonesia were less concerned about
                 imagination and unselfishness. As for materialist
                 versus post-materialist, the ratios of Malaysia and
                 Indonesia were slightly higher than the average; the
                 post-materialist value of free speech was the lowest
                 value chosen. In the long term, all countries are
                 experiencing the trend of moving toward
                 post-materialist societies. To be sustained under the
                 Collective and Adaptive System of smart city societies,
                 good enough governance in Malaysia and Indonesia should
                 consider the cultural context of the Muslim majority,
                 prioritize governance content that allows more space
                 for political participation and free speech, and
                 cultivate the imagination and unselfishness of
                 children. The generated insights underline the critical
                 role that smart societies play in establishing smart
                 cities.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Moumgiakmas:2021:CVF,
  author =       "Seraphim S. Moumgiakmas and Gerasimos G. Samatas and
                 George A. Papakostas",
  title =        "Computer Vision for Fire Detection on {UAVs} --- From
                 Software to Hardware",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "200",
  day =          "31",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080200",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/200",
  abstract =     "Fire hazard is a condition that has potentially
                 catastrophic consequences. Artificial intelligence,
                 through Computer Vision, in combination with UAVs has
                 assisted dramatically to identify this risk and avoid
                 it in a timely manner. This work is a literature review
                 on UAVs using Computer Vision in order to detect fire.
                 The research was conducted for the last decade in order
                 to record the types of UAVs, the hardware and software
                 used and the proposed datasets. The scientific research
                 was executed through the Scopus database. The research
                 showed that multi-copters were the most common type of
                 vehicle and that the combination of RGB with a thermal
                 camera was part of most applications. In addition, the
                 trend in the use of Convolutional Neural Networks
                 (CNNs) is increasing. In the last decade, many
                 applications and a wide variety of hardware and methods
                 have been implemented and studied. Many efforts have
                 been made to effectively avoid the risk of fire. The
                 fact that state-of-the-art methodologies continue to be
                 researched, leads to the conclusion that the need for a
                 more effective solution continues to arouse interest.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liang:2021:END,
  author =       "Kun Liang and Jingjing Liu and Yiying Zhang",
  title =        "The Effects of Non-Directional Online Behavior on
                 Students' Learning Performance: a User Profile Based
                 Analysis Method",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "199",
  day =          "31",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080199",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/199",
  abstract =     "Network behavior analysis is an effective method to
                 outline user requirements, and can extract user
                 characteristics by constructing machine learning
                 models. To protect the privacy of data, the shared
                 information in the model is limited to non-directional
                 network behavior information, such as online duration,
                 traffic, etc., which also hides users' unconscious
                 needs and habits. However, the value density of this
                 type of information is low, and it is still unclear how
                 much student performance is affected by online
                 behavior; in addition there is a lack of methods for
                 analyzing the correlation between non-directed online
                 behavior and academic performance. In this article, we
                 propose a model for analyzing the correlation between
                 non-directed surfing behavior and academic performance
                 based on user portraits. Different from the existing
                 research, we mainly focus on the public student
                 behavior information in the campus network system and
                 conduct in-depth research on it. The experimental
                 results show that online time and online traffic are
                 negatively correlated with academic performance,
                 respectively, and student's academic performance can be
                 predicted through the study of non-directional online
                 behavior.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Vu:2021:SBI,
  author =       "Simon Nam Thanh Vu and Mads Stege and Peter Issam
                 El-Habr and Jesper Bang and Nicola Dragoni",
  title =        "A Survey on Botnets: Incentives, Evolution, Detection
                 and Current Trends",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "198",
  day =          "31",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080198",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/198",
  abstract =     "Botnets, groups of malware-infected hosts controlled
                 by malicious actors, have gained prominence in an era
                 of pervasive computing and the Internet of Things.
                 Botnets have shown a capacity to perform substantial
                 damage through distributed denial-of-service attacks,
                 information theft, spam and malware propagation. In
                 this paper, a systematic literature review on botnets
                 is presented to the reader in order to obtain an
                 understanding of the incentives, evolution, detection,
                 mitigation and current trends within the field of
                 botnet research in pervasive computing. The literature
                 review focuses particularly on the topic of botnet
                 detection and the proposed solutions to mitigate the
                 threat of botnets in system security. Botnet detection
                 and mitigation mechanisms are categorised and briefly
                 described to allow for an easy overview of the many
                 proposed solutions. The paper also summarises the
                 findings to identify current challenges and trends
                 within research to help identify improvements for
                 further botnet mitigation research.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fekete:2021:SLT,
  author =       "D{\'e}nes L{\'a}szl{\'o} Fekete and Attila Kiss",
  title =        "A Survey of Ledger Technology-Based Databases",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "197",
  day =          "31",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080197",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/197",
  abstract =     "The spread of crypto-currencies globally has led to
                 blockchain technology receiving greater attention in
                 recent times. This paper focuses more broadly on the
                 uses of ledger databases as a traditional database
                 manager. Ledger databases will be examined within the
                 parameters of two categories. The first of these are
                 Centralized Ledger Databases (CLD)-based Centralised
                 Ledger Technology (CLT), of which LedgerDB will be
                 discussed. The second of these are Permissioned
                 Blockchain Technology-based Decentralised Ledger
                 Technology (DLT) where Hyperledger Fabric, FalconDB,
                 BlockchainDB, ChainifyDB, BigchainDB, and Blockchain
                 Relational Database will be examined. The strengths and
                 weaknesses of the reviewed technologies will be
                 discussed, alongside a comparison of the mentioned
                 technologies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chiti:2021:TQI,
  author =       "Francesco Chiti and Romano Fantacci and Roberto Picchi
                 and Laura Pierucci",
  title =        "Towards the Quantum {Internet}: Satellite Control
                 Plane Architectures and Protocol Design",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "196",
  day =          "30",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080196",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/196",
  abstract =     "The creation of the future quantum Internet requires
                 the development of new systems, architectures, and
                 communications protocols. As a matter of fact, the
                 optical fiber technology is affected by extremely high
                 losses; thus, the deployment of a quantum satellite
                 network (QSN) composed of quantum satellite repeaters
                 (QSRs) in low Earth orbit would make it possible to
                 overcome these attenuation problems. For these reasons,
                 we consider the design of an ad hoc quantum satellite
                 backbone based on the Software-Defined Networking (SDN)
                 paradigm with a modular two-tier Control Plane (CP).
                 The first tier of the CP is embedded into a Master
                 Control Station (MCS) on the ground, which coordinates
                 the entire constellation and performs the management of
                 the CP integrated into the constellation itself. This
                 second tier is responsible for entanglement generation
                 and management on the selected path. In addition to
                 defining the SDN architecture in all its components, we
                 present a possible protocol to generate entanglement on
                 the end-to-end (E2E) path. Furthermore, we evaluate the
                 performance of the developed protocol in terms of the
                 latency required to establish entanglement between two
                 ground stations connected via the quantum satellite
                 backbone.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gupta:2021:IBP,
  author =       "Akash Gupta and Adnan Al-Anbuky",
  title =        "{IoT}-Based Patient Movement Monitoring: The
                 Post-Operative Hip Fracture Rehabilitation Model",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "195",
  day =          "29",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080195",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/195",
  abstract =     "Hip fracture incidence is life-threatening and has an
                 impact on the person's physical functionality and their
                 ability to live independently. Proper rehabilitation
                 with a set program can play a significant role in
                 recovering the person's physical mobility, boosting
                 their quality of life, reducing adverse clinical
                 outcomes, and shortening hospital stays. The Internet
                 of Things (IoT), with advancements in digital health,
                 could be leveraged to enhance the backup intelligence
                 used in the rehabilitation process and provide
                 transparent coordination and information about movement
                 during activities among relevant parties. This paper
                 presents a post-operative hip fracture rehabilitation
                 model that clarifies the involved rehabilitation
                 process, its associated events, and the main physical
                 movements of interest across all stages of care. To
                 support this model, the paper proposes an IoT-enabled
                 movement monitoring system architecture. The
                 architecture reflects the key operational
                 functionalities required to monitor patients in real
                 time and throughout the rehabilitation process. The
                 approach was tested incrementally on ten healthy
                 subjects, particularly for factors relevant to the
                 recognition and tracking of movements of interest. The
                 analysis reflects the significance of personalization
                 and the significance of a one-minute history of data in
                 monitoring the real-time behavior. This paper also
                 looks at the impact of edge computing at the gateway
                 and a wearable sensor edge on system performance. The
                 approach provides a solution for an architecture that
                 balances system performance with remote monitoring
                 functional requirements.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Jalata:2021:MAN,
  author =       "Ibsa K. Jalata and Thanh-Dat Truong and Jessica L.
                 Allen and Han-Seok Seo and Khoa Luu",
  title =        "Movement Analysis for Neurological and Musculoskeletal
                 Disorders Using Graph Convolutional Neural Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "194",
  day =          "28",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080194",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/194",
  abstract =     "Using optical motion capture and wearable sensors is a
                 common way to analyze impaired movement in individuals
                 with neurological and musculoskeletal disorders.
                 However, using optical motion sensors and wearable
                 sensors is expensive and often requires highly trained
                 professionals to identify specific impairments. In this
                 work, we proposed a graph convolutional neural network
                 that mimics the intuition of physical therapists to
                 identify patient-specific impairments based on video of
                 a patient. In addition, two modeling approaches are
                 compared: a graph convolutional network applied solely
                 on skeleton input data and a graph convolutional
                 network accompanied with a 1-dimensional convolutional
                 neural network (1D-CNN). Experiments on the dataset
                 showed that the proposed method not only improves the
                 correlation of the predicted gait measure with the
                 ground truth value (speed = 0.791, gait deviation index
                 (GDI) = 0.792) but also enables faster training with
                 fewer parameters. In conclusion, the proposed method
                 shows that the possibility of using video-based data to
                 treat neurological and musculoskeletal disorders with
                 acceptable accuracy instead of depending on the
                 expensive and labor-intensive optical motion capture
                 systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lopez-Bernal:2021:ETB,
  author =       "Diego Lopez-Bernal and David Balderas and Pedro Ponce
                 and Arturo Molina",
  title =        "{Education 4.0}: Teaching the Basics of {KNN}, {LDA}
                 and Simple Perceptron Algorithms for Binary
                 Classification Problems",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "193",
  day =          "27",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080193",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/193",
  abstract =     "One of the main focuses of Education 4.0 is to provide
                 students with knowledge on disruptive technologies,
                 such as Machine Learning (ML), as well as the skills to
                 implement this knowledge to solve real-life problems.
                 Therefore, both students and professors require
                 teaching and learning tools that facilitate the
                 introduction to such topics. Consequently, this study
                 looks forward to contributing to the development of
                 those tools by introducing the basic theory behind
                 three machine learning classifying algorithms:
                 K-Nearest-Neighbor (KNN), Linear Discriminant Analysis
                 (LDA), and Simple Perceptron; as well as discussing the
                 diverse advantages and disadvantages of each method.
                 Moreover, it is proposed to analyze how these methods
                 work on different conditions through their
                 implementation over a test bench. Thus, in addition to
                 the description of each algorithm, we discuss their
                 application to solving three different binary
                 classification problems using three different datasets,
                 as well as comparing their performances in these
                 specific case studies. The findings of this study can
                 be used by teachers to provide students the basic
                 knowledge of KNN, LDA, and perceptron algorithms, and,
                 at the same time, it can be used as a guide to learn
                 how to apply them to solve real-life problems that are
                 not limited to the presented datasets.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tihinen:2021:DMC,
  author =       "Maarit Tihinen and Ari Pikkarainen and Jukka
                 Joutsenvaara",
  title =        "Digital Manufacturing Challenges Education ---
                 {SmartLab} Concept as a Concrete Example in Tackling
                 These Challenges",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "192",
  day =          "26",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080192",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/192",
  abstract =     "Digitalization is boosting the manufacturing
                 industry's shift to smart manufacturing systems, which
                 will efficiently utilize the potential of new
                 technologies for their business outcomes and value.
                 However, the literature shows that manufacturing
                 companies have implemented very little digital
                 technology due to a lack of the required knowledge and
                 competences. Increasingly, interconnected, digitalized,
                 and complex processes lead to new skill requirements in
                 companies and thereafter also of their workforce's
                 training needs to respond to the smart manufacturing's
                 new great expectations. The article provides concrete
                 examples of tackling challenges in education arising
                 from digital manufacturing. The case study introduced
                 in this article concerns the additive manufacturing
                 (AM) method, which is expected to give rise to
                 significant changes in various industrial fields,
                 including digital manufacturing. Advances in digital
                 manufacturing requires skilled professionals who are
                 aware of the possibilities and potential of the latest
                 technology. Education therefore needs to be developed.
                 This article points out that the built learning and
                 development environment, SmartLab, supports
                 multidisciplinary approaches and close collaboration
                 between several stakeholders like companies,
                 engineering education courses, students, and RDI
                 actors. The SmartLab concept is thus also expected to
                 provide a remarkable competitive advantage for business
                 in the region.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Iqbal:2021:IPC,
  author =       "Umar Iqbal and Ashraf Abosekeen and Jacques Georgy and
                 Areejah Umar and Aboelmagd Noureldin and Michael J.
                 Korenberg",
  title =        "Implementation of Parallel Cascade Identification at
                 Various Phases for Integrated Navigation System",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "191",
  day =          "26",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080191",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/191",
  abstract =     "Global navigation satellite systems (GNSS) are widely
                 used for the navigation of land vehicles. However, the
                 positioning accuracy of GNSS, such as the global
                 positioning system (GPS), deteriorates in urban areas
                 due to signal blockage and multipath effects. GNSS can
                 be integrated with a micro-electro-mechanical system
                 (MEMS)-based inertial navigation system (INS), such as
                 a reduced inertial sensor system (RISS) using a Kalman
                 filter (KF) to enhance the performance of the
                 integrated navigation solution in GNSS challenging
                 environments. The linearized KF cannot model the
                 low-cost and small-size sensors due to relatively high
                 noise levels and compound error characteristics. This
                 paper reviews two approaches to employing parallel
                 cascade identification (PCI), a non-linear system
                 identification technique, augmented with KF to enhance
                 the navigational solution. First, PCI models azimuth
                 errors for a loosely coupled 2D RISS integrated system
                 with GNSS to obtain a navigation solution. The
                 experimental results demonstrated that PCI improved the
                 integrated 2D RISS/GNSS performance by modeling linear,
                 non-linear, and other residual azimuth errors. For the
                 second scenario, PCI is utilized for modeling residual
                 pseudorange correlated errors of a KF-based tightly
                 coupled RISS/GNSS navigation solution. Experimental
                 results have shown that PCI enhances the performance of
                 the tightly coupled KF by modeling the non-linear
                 pseudorange errors to provide an enhanced and more
                 reliable solution. For the first algorithm, the results
                 demonstrated that PCI can enhance the performance by
                 77\% as compared to the KF solution during the GNSS
                 outages. For the second algorithm, the performance
                 improvement for the proposed PCI technique during the
                 availability of three satellites was 39\% compared to
                 the KF solution.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Dowdeswell:2021:AAB,
  author =       "Barry Dowdeswell and Roopak Sinha and Stephen G.
                 MacDonell",
  title =        "Architecting an Agent-Based Fault Diagnosis Engine for
                 {IEC 61499} Industrial Cyber-Physical Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "8",
  pages =        "190",
  day =          "23",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13080190",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Aug 26 10:44:38 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/8/190",
  abstract =     "IEC 61499 is a reference architecture for constructing
                 Industrial Cyber-Physical Systems (ICPS). However,
                 current function block development environments only
                 provide limited fault-finding capabilities. There is a
                 need for comprehensive diagnostic tools that help
                 engineers identify faults, both during development and
                 after deployment. This article presents the software
                 architecture for an agent-based fault diagnostic engine
                 that equips agents with domain-knowledge of IEC 61499.
                 The engine encourages a Model-Driven Development with
                 Diagnostics methodology where agents work alongside
                 engineers during iterative cycles of design,
                 development, diagnosis and refinement. Attribute-Driven
                 Design (ADD) was used to propose the architecture to
                 capture fault telemetry directly from the ICPS. A Views
                 and Beyond Software Architecture Document presents the
                 architecture. The Architecturally-Significant
                 Requirement (ASRs) were used to design the views while
                 an Architectural Trade-off Analysis Method (ATAM)
                 evaluated critical parts of the architecture. The
                 agents locate faults during both early-stage
                 development and later provide long-term fault
                 management. The architecture introduces dynamic,
                 low-latency software-in-loop Diagnostic Points (DPs)
                 that operate under the control of an agent to capture
                 fault telemetry. Using sound architectural design
                 approaches and documentation methods, coupled with
                 rigorous evaluation and prototyping, the article
                 demonstrates how quality attributes, risks and
                 architectural trade-offs were identified and mitigated
                 early before the construction of the engine
                 commenced.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Saia:2021:WIM,
  author =       "Roberto Saia and Salvatore Carta and Olaf Bergmann",
  title =        "Wireless {Internet}, Multimedia, and Artificial
                 Intelligence: New Applications and Infrastructures",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "9",
  pages =        "240",
  day =          "21",
  month =        sep,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13090240",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Sep 28 10:43:54 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/9/240",
  abstract =     "The potential offered by the Internet, combined with
                 the enormous number of connectable devices, offers
                 benefits in many areas of our modern societies, both
                 public and private. The possibility of making
                 heterogeneous devices communicate with each other
                 through the Internet has given rise to a constantly
                 growing scenario, which was unthinkable not long ago.
                 This unstoppable growth takes place thanks to the
                 continuous availability of increasingly sophisticated
                 device features, an ever-increasing bandwidth and
                 reliability of the connections, and the ever-lower
                 consumption of the devices, which grants them long
                 autonomy. This scenario of exponential growth also
                 involves other sectors such as, for example, that of
                 Artificial Intelligence (AI), which offers us
                 increasingly sophisticated approaches that can be
                 synergistically combined with wireless devices and the
                 Internet in order to create powerful applications for
                 everyday life. Precisely for the aforementioned
                 reasons, the community of researchers, year by year,
                 dedicates more time and resources in this direction. It
                 should be observed that this happens in an atypical way
                 concerning the other research fields, and this is
                 because the achieved progress and the developed
                 applications have practical applications in numerous
                 and different domains.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rajpal:2021:FBH,
  author =       "Danveer Rajpal and Akhil Ranjan Garg and Om Prakash
                 Mahela and Hassan Haes Alhelou and Pierluigi Siano",
  title =        "A Fusion-Based Hybrid-Feature Approach for Recognition
                 of Unconstrained Offline Handwritten {Hindi}
                 Characters",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "9",
  pages =        "239",
  day =          "18",
  month =        sep,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13090239",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Sep 28 10:43:54 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/9/239",
  abstract =     "Hindi is the official language of India and used by a
                 large population for several public services like
                 postal, bank, judiciary, and public surveys. Efficient
                 management of these services needs language-based
                 automation. The proposed model addresses the problem of
                 handwritten Hindi character recognition using a machine
                 learning approach. The pre-trained DCNN models namely;
                 InceptionV3-Net, VGG19-Net, and ResNet50 were used for
                 the extraction of salient features from the characters'
                 images. A novel approach of fusion is adopted in the
                 proposed work; the DCNN-based features are fused with
                 the handcrafted features received from Bi-orthogonal
                 discrete wavelet transform. The feature size was
                 reduced by the Principal Component Analysis method. The
                 hybrid features were examined with popular classifiers
                 namely; Multi-Layer Perceptron (MLP) and Support Vector
                 Machine (SVM). The recognition cost was reduced by
                 84.37\%. The model achieved significant scores of
                 precision, recall, and F1-measure-98.78\%, 98.67\%, and
                 98.69\%-with overall recognition accuracy of 98.73\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fendji:2021:WST,
  author =       "Jean Louis Ebongue Kedieng Fendji and D{\'e}sir{\'e}
                 Manuel Taira and Marcellin Atemkeng and Adam Musa Ali",
  title =        "{WATS-SMS}: a {T5}-Based {French} {Wikipedia}
                 Abstractive Text Summarizer for {SMS}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "9",
  pages =        "238",
  day =          "18",
  month =        sep,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13090238",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Sep 28 10:43:54 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/9/238",
  abstract =     "Text summarization remains a challenging task in the
                 natural language processing field despite the plethora
                 of applications in enterprises and daily life. One of
                 the common use cases is the summarization of web pages
                 which has the potential to provide an overview of web
                 pages to devices with limited features. In fact,
                 despite the increasing penetration rate of mobile
                 devices in rural areas, the bulk of those devices offer
                 limited features in addition to the fact that these
                 areas are covered with limited connectivity such as the
                 GSM network. Summarizing web pages into SMS becomes,
                 therefore, an important task to provide information to
                 limited devices. This work introduces WATS-SMS, a
                 T5-based French Wikipedia Abstractive Text Summarizer
                 for SMS. It is built through a transfer learning
                 approach. The T5 English pre-trained model is used to
                 generate a French text summarization model by
                 retraining the model on 25,000 Wikipedia pages then
                 compared with different approaches in the literature.
                 The objective is twofold: (1) to check the assumption
                 made in the literature that abstractive models provide
                 better results compared to extractive ones; and (2) to
                 evaluate the performance of our model compared to other
                 existing abstractive models. A score based on ROUGE
                 metrics gave us a value of 52\% for articles with
                 length up to 500 characters against 34.2\% for
                 transformer-ED and 12.7\% for seq-2seq-attention; and a
                 value of 77\% for articles with larger size against
                 37\% for transformers-DMCA. Moreover, an architecture
                 including a software SMS-gateway has been developed to
                 allow owners of mobile devices with limited features to
                 send requests and to receive summaries through the GSM
                 network.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gutierrez:2021:RTP,
  author =       "Juan Roberto L{\'o}pez Guti{\'e}rrez and Pedro Ponce
                 and Arturo Molina",
  title =        "Real-Time Power Electronics Laboratory to Strengthen
                 Distance Learning Engineering Education on Smart Grids
                 and Microgrids",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "9",
  pages =        "237",
  day =          "17",
  month =        sep,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13090237",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Sep 28 10:43:54 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/9/237",
  abstract =     "In the science and engineering fields of study, a
                 hands-on learning experience is as crucial a part of
                 the learning process for the student as the theoretical
                 aspect of a given subject. With the COVID-19 pandemic
                 in 2020, educational institutions were forced to
                 migrate to digital platforms to ensure the continuity
                 of the imparted lectures. The online approach can be
                 challenging for engineering programs, especially in
                 courses that employ practical laboratory methods as the
                 primary teaching strategies. Laboratory courses that
                 include specialized hardware and software cannot
                 migrate to a virtual environment without compromising
                 the advantages that a hands-on method provides to the
                 engineering student. This work assesses different
                 approaches in the virtualization process of a
                 laboratory facility, diving these into key factors such
                 as required communication infrastructure and available
                 technologies; it opens a discussion on the trends and
                 possible obstacles in the virtualization of a Real-Time
                 (RT) laboratory intended for Microgrid education in a
                 power electronics laboratory course, exposing the main
                 simulation strategies that can be used in an RT
                 environment and how these have different effects on the
                 learning process of student, as well as addressing the
                 main competencies an engineering student can strengthen
                 through interaction with RT simulation technologies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Meng:2021:PNF,
  author =       "Fanhui Meng and Haoming Sun and Jiarong Xie and
                 Chengjun Wang and Jiajing Wu and Yanqing Hu",
  title =        "Preference for Number of Friends in Online Social
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "9",
  pages =        "236",
  day =          "16",
  month =        sep,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13090236",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Sep 28 10:43:54 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/9/236",
  abstract =     "Preferences or dislikes for specific numbers are
                 ubiquitous in human society. In traditional Chinese
                 culture, people show special preference for some
                 numbers, such as 6, 8, 10, 100, 200, etc. By analyzing
                 the data of 6.8 million users of Sina Weibo, one of the
                 largest online social media platforms in China, we
                 discover that users exhibit a distinct preference for
                 the number 200, i.e., a significant fraction of users
                 prefer to follow 200 friends. This number, which is
                 very close to the Dunbar number that predicts the
                 cognitive limit on the number of stable social
                 relationships, motivates us to investigate how the
                 preference for numbers in traditional Chinese culture
                 is reflected on social media. We systematically portray
                 users who prefer 200 friends and analyze their several
                 important social features, including activity,
                 popularity, attention tendency, regional distribution,
                 economic level, and education level. We find that the
                 activity and popularity of users with the preference
                 for the number 200 are relatively lower than others.
                 They are more inclined to follow popular users, and
                 their social portraits change relatively slowly.
                 Besides, users who have a stronger preference for the
                 number 200 are more likely to be located in regions
                 with underdeveloped economies and education. That
                 indicates users with the preference for the number 200
                 are likely to be vulnerable groups in society and are
                 easily affected by opinion leaders.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Almaaitah:2021:RTC,
  author =       "Abdallah Y. Alma'aitah and Mohammad A. Massad",
  title =        "Reader-Tag Commands via Modulation Cutoff Intervals in
                 {RFID} Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "9",
  pages =        "235",
  day =          "16",
  month =        sep,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13090235",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Sep 28 10:43:54 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/9/235",
  abstract =     "Radio frequency identification (RFID) technology
                 facilitates a myriad of applications. In such
                 applications, an efficient reader-tag interrogation
                 process is crucial. Nevertheless, throughout reader-tag
                 communication, significant amounts of time and power
                 are consumed on inescapable simultaneous tag replies
                 (i.e., collisions) due to the lack of carrier sensing
                 at the tags. This paper proposes the modulation cutoff
                 intervals (MCI) process as a novel reader-tag
                 interaction given the lack of carrier sensing
                 constraints in passive RFID tags. MCI is facilitated
                 through a simple digital baseband modulation
                 termination (DBMT) circuit at the tag. DBMT detects the
                 continuous-wave cutoff by the reader. In addition, DBMT
                 provides different flags based on the duration of the
                 continuous-wave cutoff. Given this capability at the
                 tag, the reader cuts off its continuous-wave
                 transmission for predefined intervals to indicate
                 different commands to the interrogated tag(s). The MCI
                 process is applied to tag interrogation (or
                 anti-collision) and tag-counting protocols. The MCI
                 process effect was evaluated by the two protocols under
                 high and low tag populations. The performance of such
                 protocols was significantly enhanced with precise
                 synchronization within time slots with more than 50\%
                 and more than 55.6\% enhancement on time and power
                 performance of anti-collision and counting protocols,
                 respectively. Through the MCI process, fast and
                 power-efficient tag identification is achieved in
                 inventory systems with low and high tag mobility;
                 alternatively, in addition to the rapid and power
                 efficient interaction with tags, anonymous tag counting
                 is conducted by the proposed process.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alshareef:2021:SGB,
  author =       "Norah Alshareef and Xiaohong Yuan and Kaushik Roy and
                 Mustafa Atay",
  title =        "A Study of Gender Bias in Face Presentation Attack and
                 Its Mitigation",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "9",
  pages =        "234",
  day =          "14",
  month =        sep,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13090234",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Sep 28 10:43:54 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/9/234",
  abstract =     "In biometric systems, the process of identifying or
                 verifying people using facial data must be highly
                 accurate to ensure a high level of security and
                 credibility. Many researchers investigated the fairness
                 of face recognition systems and reported demographic
                 bias. However, there was not much study on face
                 presentation attack detection technology (PAD) in terms
                 of bias. This research sheds light on bias in face
                 spoofing detection by implementing two phases. First,
                 two CNN (convolutional neural network)-based
                 presentation attack detection models, ResNet50 and
                 VGG16 were used to evaluate the fairness of detecting
                 imposer attacks on the basis of gender. In addition,
                 different sizes of Spoof in the Wild (SiW) testing and
                 training data were used in the first phase to study the
                 effect of gender distribution on the models'
                 performance. Second, the debiasing variational
                 autoencoder (DB-VAE) (Amini, A., et al., Uncovering and
                 Mitigating Algorithmic Bias through Learned Latent
                 Structure) was applied in combination with VGG16 to
                 assess its ability to mitigate bias in presentation
                 attack detection. Our experiments exposed minor gender
                 bias in CNN-based presentation attack detection
                 methods. In addition, it was proven that imbalance in
                 training and testing data does not necessarily lead to
                 gender bias in the model's performance. Results proved
                 that the DB-VAE approach (Amini, A., et al., Uncovering
                 and Mitigating Algorithmic Bias through Learned Latent
                 Structure) succeeded in mitigating bias in detecting
                 spoof faces.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lim:2021:RCT,
  author =       "Zhou-Yi Lim and Lee-Yeng Ong and Meng-Chew Leow",
  title =        "A Review on Clustering Techniques: Creating Better
                 User Experience for Online Roadshow",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "9",
  pages =        "233",
  day =          "13",
  month =        sep,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13090233",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Sep 28 10:43:54 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/9/233",
  abstract =     "Online roadshow is a relatively new concept that has
                 higher flexibility and scalability compared to the
                 physical roadshow. This is because online roadshow is
                 accessible through digital devices anywhere and
                 anytime. In a physical roadshow, organizations can
                 measure the effectiveness of the roadshow by
                 interacting with the customers. However, organizations
                 cannot monitor the effectiveness of the online roadshow
                 by using the same method. A good user experience is
                 important to increase the advertising effects on the
                 online roadshow website. In web usage mining,
                 clustering can discover user access patterns from the
                 weblog. By applying a clustering technique, the online
                 roadshow website can be further improved to provide a
                 better user experience. This paper presents a review of
                 clustering techniques used in web usage mining, namely
                 the partition-based, hierarchical, density-based, and
                 fuzzy clustering techniques. These clustering
                 techniques are analyzed from three perspectives: their
                 similarity measures, the evaluation metrics used to
                 determine the optimality of the clusters, and the
                 functional purpose of applying the techniques to
                 improve the user experience of the website. By applying
                 clustering techniques in different stages of the user
                 activities in the online roadshow website, the
                 advertising effectiveness of the website can be
                 enhanced in terms of its affordance, flow, and
                 interactivity.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Jaramillo-Ramirez:2021:SDF,
  author =       "Daniel Jaramillo-Ramirez and Manuel Perez",
  title =        "Spectrum Demand Forecasting for {IoT} Services",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "9",
  pages =        "232",
  day =          "08",
  month =        sep,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13090232",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Sep 28 10:43:54 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/9/232",
  abstract =     "The evolution of IoT has come with the challenge of
                 connecting not only a massive number of devices, but
                 also providing an always wider variety of services. In
                 the next few years, a big increase in the number of
                 connected devices is expected, together with an
                 important increase in the amount of traffic generated.
                 Never before have wireless communications permeated so
                 deeply in all industries and economic sectors.
                 Therefore, it is crucial to correctly forecast the
                 spectrum needs, which bands should be used for which
                 services, and the economic potential of its
                 utilization. This paper proposes a methodology for
                 spectrum forecasting consisting of two phases: a market
                 study and a spectrum forecasting model. The market
                 study determines the main drivers of the IoT industry
                 for any country: services, technologies, frequency
                 bands, and the number of devices that will require IoT
                 connectivity. The forecasting model takes the market
                 study as the input and calculates the spectrum demand
                 in 5 steps: Defining scenarios for spectrum contention,
                 calculating the offered traffic load, calculating a
                 capacity for some QoS requirements, finding the
                 spectrum required, and adjusting according to key
                 spectral efficiency determinants. This methodology is
                 applied for Colombia's IoT spectrum forecast. We
                 provide a complete step-by-step implementation in
                 fourteen independent spectrum contention scenarios,
                 calculating offered traffic, required capacity, and
                 spectrum for cellular licensed bands and non-cellular
                 unlicensed bands in a 10-year period. Detailed results
                 are presented specifying coverage area requirements per
                 economic sector, frequency band, and service. The need
                 for higher teledensity and higher spectral efficiency
                 turns out to be a determining factor for spectrum
                 savings.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Begum:2021:UAB,
  author =       "Nasima Begum and Md Azim Hossain Akash and Sayma
                 Rahman and Jungpil Shin and Md Rashedul Islam and Md
                 Ezharul Islam",
  title =        "User Authentication Based on Handwriting Analysis of
                 Pen-Tablet Sensor Data Using Optimal Feature Selection
                 Model",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "9",
  pages =        "231",
  day =          "06",
  month =        sep,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13090231",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Sep 28 10:43:54 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/9/231",
  abstract =     "Handwriting analysis is playing an important role in
                 user authentication or online writer identification for
                 more than a decade. It has a significant role in
                 different applications such as e-security, signature
                 biometrics, e-health, gesture analysis, diagnosis
                 system of Parkinson's disease,
                 Attention-deficit/hyperactivity disorders, analysis of
                 vulnerable people (stressed, elderly, or drugged),
                 prediction of gender, handedness and so on. Classical
                 authentication systems are image-based, text-dependent,
                 and password or fingerprint-based where the former one
                 has the risk of information leakage. Alternatively,
                 image processing and pattern-analysis-based systems are
                 vulnerable to camera attributes, camera frames, light
                 effect, and the quality of the image or pattern. Thus,
                 in this paper, we concentrate on real-time and
                 context-free handwriting data analysis for robust user
                 authentication systems using digital pen-tablet sensor
                 data. Most of the state-of-the-art authentication
                 models show suboptimal performance for improper
                 features. This research proposed a robust and efficient
                 user identification system using an optimal feature
                 selection technique based on the features from the
                 sensor's signal of pen and tablet devices. The proposed
                 system includes more genuine and accurate numerical
                 data which are used for features extraction model based
                 on both the kinematic and statistical features of
                 individual handwritings. Sensor data of digital
                 pen-tablet devices generate high dimensional feature
                 vectors for user identification. However, all the
                 features do not play equal contribution to identify a
                 user. Hence, to find out the optimal features, we
                 utilized a hybrid feature selection model. Extracted
                 features are then fed to the popular machine learning
                 (ML) algorithms to generate a nonlinear classifier
                 through training and testing phases. The experimental
                 result analysis shows that the proposed model achieves
                 more accurate and satisfactory results which ensure the
                 practicality of our system for user identification with
                 low computational cost.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kouhoue:2021:EVV,
  author =       "Austin Waffo Kouhou{\'e} and Yoann Bonavero and Thomas
                 Bou{\'e}tou Bou{\'e}tou and Marianne Huchard",
  title =        "Exploring Variability of Visual Accessibility Options
                 in Operating Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "9",
  pages =        "230",
  day =          "04",
  month =        sep,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13090230",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Sep 28 10:43:54 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/9/230",
  abstract =     "Digital technologies are an opportunity to overcome
                 disabilities, provided that accessibility is ensured.
                 In this paper, we focus on visual accessibility and the
                 way it is supported in Operating Systems (OS). The
                 significant variability in this support has practical
                 consequences, e.g., the difficulty to recommend or
                 select an OS, or migrate from one OS to another. This
                 suggests building a variability model for OS that would
                 classify them and would serve as a reference. We
                 propose a methodology to build such a variability model
                 with the help of the Formal Concept Analysis (FCA)
                 framework. In addition, as visual accessibility can be
                 divided into several concerns (e.g., zoom, or
                 contrast), we leverage an extension of FCA, namely
                 Relational Concept Analysis. We also build an ontology
                 to dispose of a standardized description of visual
                 accessibility options. We apply our proposal to the
                 analysis of the variability of a few representative
                 operating systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Anderson:2021:GSV,
  author =       "David P. Anderson",
  title =        "Globally Scheduling Volunteer Computing",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "9",
  pages =        "229",
  day =          "31",
  month =        aug,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13090229",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Sep 28 10:43:54 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/9/229",
  abstract =     "Volunteer computing uses millions of consumer
                 computing devices (desktop and laptop computers,
                 tablets, phones, appliances, and cars) to do
                 high-throughput scientific computing. It can provide
                 Exa-scale capacity, and it is a scalable and
                 sustainable alternative to data-center computing.
                 Currently, about 30 science projects use volunteer
                 computing in areas ranging from biomedicine to
                 cosmology. Each project has application programs with
                 particular hardware and software requirements (memory,
                 GPUs, VM support, and so on). Each volunteered device
                 has specific hardware and software capabilities, and
                 each device owner has preferences for which science
                 areas they want to support. This leads to a scheduling
                 problem: how to dynamically assign devices to projects
                 in a way that satisfies various constraints and that
                 balances various goals. We describe the scheduling
                 policy used in Science United, a global manager for
                 volunteer computing.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gronchi:2021:NTS,
  author =       "Giorgio Gronchi and Marco Raglianti and Fabio
                 Giovannelli",
  title =        "Network Theory and Switching Behaviors: a User Guide
                 for Analyzing Electronic Records Databases",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "9",
  pages =        "228",
  day =          "31",
  month =        aug,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13090228",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Sep 28 10:43:54 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/9/228",
  abstract =     "As part of studies that employ health electronic
                 records databases, this paper advocates the employment
                 of graph theory for investigating drug-switching
                 behaviors. Unlike the shared approach in this field
                 (comparing groups that have switched with control
                 groups), network theory can provide information about
                 actual switching behavior patterns. After a brief and
                 simple introduction to fundamental concepts of network
                 theory, here we present (i) a Python script to obtain
                 an adjacency matrix from a records database and (ii) an
                 illustrative example of the application of network
                 theory basic concepts to investigate drug-switching
                 behaviors. Further potentialities of network theory
                 (weighted matrices and the use of clustering
                 algorithms), along with the generalization of these
                 methods to other kinds of switching behaviors beyond
                 drug switching, are discussed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Scazzariello:2021:MSA,
  author =       "Mariano Scazzariello and Lorenzo Ariemma and Giuseppe
                 {Di Battista} and Maurizio Patrignani",
  title =        "{Megalos}: a Scalable Architecture for the
                 Virtualization of Large Network Scenarios",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "9",
  pages =        "227",
  day =          "30",
  month =        aug,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13090227",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Sep 28 10:43:54 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/9/227",
  abstract =     "We introduce an open-source, scalable, and distributed
                 architecture, called Megalos, that supports the
                 implementation of virtual network scenarios consisting
                 of virtual devices (VDs) where each VD may have several
                 Layer 2 interfaces assigned to virtual LANs. We rely on
                 Docker containers to realize vendor-independent VDs and
                 we leverage Kubernetes for the management of the nodes
                 of a distributed cluster. Our architecture does not
                 require platform-specific configurations and supports a
                 seamless interconnection between the virtual
                 environment and the physical one. Also, it guarantees
                 the segregation of each virtual LAN traffic from the
                 traffic of other LANs, from the cluster traffic, and
                 from Internet traffic. Further, a packet is only sent
                 to the cluster node containing the recipient VD. We
                 produce several example applications where we emulate
                 large network scenarios, with thousands of VDs and
                 LANs. Finally, we experimentally show the scalability
                 potential of Megalos by measuring the overhead of the
                 distributed environment and of its signaling
                 protocols.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tu:2021:IRS,
  author =       "Shu-Fen Tu and Ching-Sheng Hsu and Yu-Tzu Lu",
  title =        "Improving {RE-SWOT} Analysis with Sentiment
                 Classification: a Case Study of Travel Agencies",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "9",
  pages =        "226",
  day =          "30",
  month =        aug,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13090226",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Sep 28 10:43:54 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/9/226",
  abstract =     "Nowadays, many companies collect online user reviews
                 to determine how users evaluate their products. Dalpiaz
                 and Parente proposed the RE-SWOT method to
                 automatically generate a SWOT matrix based on online
                 user reviews. The SWOT matrix is an important basis for
                 a company to perform competitive analysis; therefore,
                 RE-SWOT is a very helpful tool for organizations.
                 Dalpiaz and Parente calculated feature performance
                 scores based on user reviews and ratings to generate
                 the SWOT matrix. However, the authors did not propose a
                 solution for situations when user ratings are not
                 available. Unfortunately, it is not uncommon for forums
                 to only have user reviews but no user ratings. In this
                 paper, sentiment analysis is used to deal with the
                 situation where user ratings are not available. We also
                 use KKday, a start-up online travel agency in Taiwan as
                 an example to demonstrate how to use the proposed
                 method to build a SWOT matrix.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alghamdi:2021:STP,
  author =       "Taghreed Alghamdi and Khalid Elgazzar and Taysseer
                 Sharaf",
  title =        "Spatiotemporal Traffic Prediction Using Hierarchical
                 {Bayesian} Modeling",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "9",
  pages =        "225",
  day =          "30",
  month =        aug,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13090225",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Sep 28 10:43:54 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/9/225",
  abstract =     "Hierarchical Bayesian models (HBM) are powerful tools
                 that can be used for spatiotemporal analysis. The
                 hierarchy feature associated with Bayesian modeling
                 enhances the accuracy and precision of spatiotemporal
                 predictions. This paper leverages the hierarchy of the
                 Bayesian approach using the three models; the Gaussian
                 process (GP), autoregressive (AR), and Gaussian
                 predictive processes (GPP) to predict long-term traffic
                 status in urban settings. These models are applied on
                 two different datasets with missing observation. In
                 terms of modeling sparse datasets, the GPP model
                 outperforms the other models. However, the GPP model is
                 not applicable for modeling data with spatial points
                 close to each other. The AR model outperforms the GP
                 models in terms of temporal forecasting. The GP model
                 is used with different covariance matrices:
                 exponential, Gaussian, spherical, and Mat{\'e}rn to
                 capture the spatial correlation. The exponential
                 covariance yields the best precision in spatial
                 analysis with the Gaussian process, while the Gaussian
                 covariance outperforms the others in temporal
                 forecasting.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Jimenez:2021:YVV,
  author =       "Mar{\'\i}a Artemisa Sangerm{\'a}n Jim{\'e}nez and
                 Pedro Ponce and Esteban V{\'a}zquez-Cano",
  title =        "{YouTube} Videos in the Virtual Flipped Classroom
                 Model Using Brain Signals and Facial Expressions",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "9",
  pages =        "224",
  day =          "30",
  month =        aug,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13090224",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Sep 28 10:43:54 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/9/224",
  abstract =     "As a result of the confinement due to the COVID-19
                 pandemic, various educational institutions migrated
                 their face-to-face teaching modality to a virtual
                 modality. This article presents the implementation of
                 the Flipped Classroom model in a completely virtual
                 format to develop grammatical competency in Spanish.
                 The model used videos from YouTube, one of the leading
                 global social network platforms, and the
                 videoconferencing system Zoom, the tool selected by the
                 studied educational institution to continue academic
                 operations during the health confinement. The model was
                 enriched with the Index for Learning Style test to
                 provide more differentiated teaching. This study showed
                 considerable improvement in the academic performance of
                 high school students taking a Spanish course at the
                 Mexico City campus of Tecnologico de Monterrey. Of the
                 total sample, 98\% increased their score by between 2
                 and 46 points, from a total of 100, in their
                 grammatical competency in Spanish. Additionally, the
                 student satisfaction survey showed that more than 90\%
                 considered the course methodology beneficial for
                 developing their grammatical competency in Spanish.
                 This study demonstrates the potential of the Flipped
                 Classroom model in a virtual format. This teaching
                 structure using the Flipped Classroom model could be
                 replicated in various educational settings and for
                 different areas of knowledge.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Eden:2021:RVA,
  author =       "Jen Eden and Anthony J. Roberto",
  title =        "The Role of Verbal Aggression in Cyberbullying
                 Perpetration and Victimization by Middle School
                 Students",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "9",
  pages =        "223",
  day =          "30",
  month =        aug,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13090223",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Sep 28 10:43:54 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/9/223",
  abstract =     "This manuscript examined the role trait verbal
                 aggression plays in cyberbullying victimization and
                 perpetration in adolescence. More than 400 middle
                 school students (46.8\% males and 52.2\% females)
                 completed a questionnaire on trait verbal aggression
                 and their history of cyberbullying perpetration and
                 victimization. Linear regression analyses revealed that
                 trait verbal aggression was a statistically significant
                 predictor of both cyberbullying perpetration and
                 victimization, that cyberbullying perpetration and
                 cyberbullying victimization are related, and that
                 cyberbullying perpetration appears to increase with
                 age, while cyberbullying victimization does not. Ideas
                 and implications for future applications of verbal
                 aggression and cyberbullying are discussed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{DAmbrosio:2021:SAP,
  author =       "Raffaele D'Ambrosio and Giuseppe Giordano and Serena
                 Mottola and Beatrice Paternoster",
  title =        "Stiffness Analysis to Predict the Spread Out of Fake
                 Information",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "9",
  pages =        "222",
  day =          "28",
  month =        aug,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13090222",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Sep 28 10:43:54 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/9/222",
  abstract =     "This work highlights how the stiffness index, which is
                 often used as a measure of stiffness for differential
                 problems, can be employed to model the spread of fake
                 news. In particular, we show that the higher the
                 stiffness index is, the more rapid the transit of fake
                 news in a given population. The illustration of our
                 idea is presented through the stiffness analysis of the
                 classical SIR model, commonly used to model the spread
                 of epidemics in a given population. Numerical
                 experiments, performed on real data, support the
                 effectiveness of the approach.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wehbe:2021:BBS,
  author =       "Rania Wehbe and Isam Shahrour",
  title =        "A {BIM}-Based Smart System for Fire Evacuation",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "9",
  pages =        "221",
  day =          "25",
  month =        aug,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13090221",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Sep 28 10:43:54 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/9/221",
  abstract =     "Building fires constitute a significant threat that
                 affects property, the environment, and human health.
                 The management of this risk requires an efficient fire
                 evacuation system for buildings' occupants. Therefore,
                 a smart fire evacuation system that combines building
                 information modeling (BIM) and smart technologies is
                 proposed. The system provides the following capacities:
                 (i) early fire detection; (ii) the evaluation of
                 environmental data; (iii) the identification of the
                 best evacuation path; and (iv) information for
                 occupants about the best evacuation routes. The system
                 was implemented in a research building at Lille
                 University in France. The results show the system's
                 capacities and benefits, particularly for the
                 identification of the best evacuation paths.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhao:2021:TPE,
  author =       "Xujian Zhao and Wei Li",
  title =        "Trend Prediction of Event Popularity from Microblogs",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "9",
  pages =        "220",
  day =          "24",
  month =        aug,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13090220",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Sep 28 10:43:54 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/9/220",
  abstract =     "Owing to rapid development of the Internet and the
                 rise of the big data era, microblog has become the main
                 means for people to spread and obtain information. If
                 people can accurately predict the development trend of
                 a microblog event, it will be of great significance for
                 the government to carry out public relations activities
                 on network event supervision and guide the development
                 of microblog event reasonably for network crisis. This
                 paper presents effective solutions to deal with trend
                 prediction of microblog events' popularity. Firstly, by
                 selecting the influence factors and quantifying the
                 weight of each factor with an information entropy
                 algorithm, the microblog event popularity is modeled.
                 Secondly, the singular spectrum analysis is carried out
                 to decompose and reconstruct the time series of the
                 popularity of microblog event. Then, the box chart
                 method is used to divide the popularity of microblog
                 event into various trend spaces. In addition, this
                 paper exploits the Bi-LSTM model to deal with trend
                 prediction with a sequence to label model. Finally, the
                 comparative experimental analysis is carried out on two
                 real data sets crawled from Sina Weibo platform.
                 Compared to three comparative methods, the experimental
                 results show that our proposal improves F1-score by up
                 to 39\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Nozari:2021:ISG,
  author =       "Hamed Nozari and Agnieszka Szmelter-Jarosz and Javid
                 Ghahremani-Nahr",
  title =        "The Ideas of Sustainable and Green Marketing Based on
                 the {Internet of Everything} --- The Case of the Dairy
                 Industry",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "10",
  pages =        "266",
  day =          "19",
  month =        oct,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13100266",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Oct 22 11:19:02 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/10/266",
  abstract =     "The use of advanced computer technologies has
                 dramatically changed marketing. Concepts such as smart,
                 sustainable, and green marketing have emerged in the
                 last 20 years. One of these new technologies is the
                 Internet of Things (IoT), which has led to the
                 development of the activities and performances of
                 industries in various dimensions. For the various
                 objects, such as people, processes, and data, involved
                 in marketing activities, the Internet of Everything
                 (IoE) as an evolved IoT is a possible future scenario.
                 Some sectors pretend to be the first to implement this,
                 and the more they rely on dynamic, unstable customer
                 needs, the better a solution the IoE is for them.
                 Therefore, this paper presents a clear vision of smart,
                 sustainable marketing based on the IoE in one of the
                 fast-moving consumer goods (FMCG) industries, the dairy
                 industry. Key factors are identified to help readers
                 understand this concept better. The expert interview
                 makes it possible to draw a picture of the factors that
                 have helped successfully implement the IoE in the dairy
                 sector.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chen:2021:UTR,
  author =       "Jie Chen and Bing Han and Xufeng Ma and Jian Zhang",
  title =        "Underwater Target Recognition Based on Multi-Decision
                 {LOFAR} Spectrum Enhancement: a Deep-Learning
                 Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "10",
  pages =        "265",
  day =          "13",
  month =        oct,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13100265",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Oct 22 11:19:02 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/10/265",
  abstract =     "Underwater target recognition is an important
                 supporting technology for the development of marine
                 resources, which is mainly limited by the purity of
                 feature extraction and the universality of recognition
                 schemes. The low-frequency analysis and recording
                 (LOFAR) spectrum is one of the key features of the
                 underwater target, which can be used for feature
                 extraction. However, the complex underwater environment
                 noise and the extremely low signal-to-noise ratio of
                 the target signal lead to breakpoints in the LOFAR
                 spectrum, which seriously hinders the underwater target
                 recognition. To overcome this issue and to further
                 improve the recognition performance, we adopted a
                 deep-learning approach for underwater target
                 recognition, and a novel LOFAR spectrum enhancement
                 (LSE)-based underwater target-recognition scheme was
                 proposed, which consists of preprocessing, offline
                 training, and online testing. In preprocessing, we
                 specifically design a LOFAR spectrum enhancement based
                 on multi-step decision algorithm to recover the
                 breakpoints in LOFAR spectrum. In offline training, the
                 enhanced LOFAR spectrum is adopted as the input of
                 convolutional neural network (CNN) and a LOFAR-based
                 CNN (LOFAR-CNN) for online recognition is developed.
                 Taking advantage of the powerful capability of CNN in
                 feature extraction, the recognition accuracy can be
                 further improved by the proposed LOFAR-CNN. Finally,
                 extensive simulation results demonstrate that the
                 LOFAR-CNN network can achieve a recognition accuracy of
                 95.22\%, which outperforms the state-of-the-art
                 methods.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lepasepp:2021:SLR,
  author =       "Tuuli Katarina Lepasepp and William Hurst",
  title =        "A Systematic Literature Review of {Industry 4.0}
                 Technologies within Medical Device Manufacturing",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "10",
  pages =        "264",
  day =          "13",
  month =        oct,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13100264",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Oct 22 11:19:02 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/10/264",
  abstract =     "Ever since the emergence of Industry 4.0 as the
                 synonymous term for the fourth industrial revolution,
                 its applications have been widely discussed and used in
                 many business scenarios. This concept is derived from
                 the advantages of internet and technology, and it
                 describes the efficient synchronicity of humans and
                 computers in smart factories. By leveraging big data
                 analysis, machine learning and robotics, the end-to-end
                 supply chain is optimized in many ways. However, these
                 implementations are more challenging in heavily
                 regulated fields, such as medical device manufacturing,
                 as incorporating new technologies into factories is
                 restricted by the regulations in place. Moreover, the
                 production of medical devices requires an elaborate
                 quality analysis process to assure the best possible
                 outcome to the patient. Therefore, this article
                 reflects on the benefits (features) and limitations
                 (obstacles), in addition to the various smart
                 manufacturing trends that could be implemented within
                 the medical device manufacturing field by conducting a
                 systematic literature review of 104 articles sourced
                 from four digital libraries. Out of the 7 main themes
                 and 270 unique applied technologies, 317 features and
                 117 unique obstacles were identified. Furthermore, the
                 main findings include an overview of ways in which
                 manufacturing could be improved and optimized within a
                 regulated setting, such as medical device
                 manufacturing.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hilda:2021:CTE,
  author =       "Jabanjalin Hilda and Srimathi Chandrasekaran",
  title =        "Cost and Time Economical Planning Algorithm for
                 Scientific Workflows in Cloud Computing",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "10",
  pages =        "263",
  day =          "13",
  month =        oct,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13100263",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Oct 22 11:19:02 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/10/263",
  abstract =     "A heterogeneous system can be portrayed as a variety
                 of unlike resources that can be locally or geologically
                 spread, which is exploited to implement data-intensive
                 and computationally intensive applications. The
                 competence of implementing the scientific workflow
                 applications on heterogeneous systems is determined by
                 the approaches utilized to allocate the tasks to the
                 proper resources. Cost and time necessity are evolving
                 as different vital concerns of cloud computing
                 environments such as data centers. In the area of
                 scientific workflows, the difficulties of increased
                 cost and time are highly challenging, as they elicit
                 rigorous computational tasks over the communication
                 network. For example, it was discovered that the time
                 to execute a task in an unsuited resource consumes more
                 cost and time in the cloud data centers. In this paper,
                 a new cost- and time-efficient planning algorithm for
                 scientific workflow scheduling has been proposed for
                 heterogeneous systems in the cloud based upon the
                 Predict Optimistic Time and Cost (POTC). The proposed
                 algorithm computes the rank based not only on the
                 completion time of the current task but also on the
                 successor node in the critical path. Under a tight
                 deadline, the running time of the workflow and the
                 transfer cost are reduced by using this technique. The
                 proposed approach is evaluated using true cases of
                 data-exhaustive workflows compared with other
                 algorithms from written works. The test result shows
                 that our proposed method can remarkably decrease the
                 cost and time of the experimented workflows while
                 ensuring a better mapping of the task to the resource.
                 In terms of makespan, speedup, and efficiency, the
                 proposed algorithm surpasses the current existing
                 algorithms-such as Endpoint communication
                 contention-aware List Scheduling Heuristic (ELSH),
                 Predict Earliest Finish Time (PEFT), Budget-and
                 Deadline-constrained heuristic-based upon HEFT
                 (BDHEFT), Minimal Optimistic Processing Time (MOPT) and
                 Predict Earlier Finish Time (PEFT)-while holding the
                 same time complexity.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Shi:2021:RAC,
  author =       "Jia Shi and Xuewen Zeng and Yang Li",
  title =        "A Register Access Control Scheme for {SNR} System to
                 Counter {CPA} Attack Based on Malicious User
                 Blacklist",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "10",
  pages =        "262",
  day =          "13",
  month =        oct,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13100262",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Oct 22 11:19:02 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/10/262",
  abstract =     "Standalone Name Resolution (SNR) is an essential
                 component of many Information-Centric Networking (ICN)
                 infrastructures that maps and stores the mappings of
                 IDs and locators. The delivery of data can be realized
                 only when the name resolution process is completed
                 correctly. It also makes the SNR become the key target
                 of network attackers. In this paper, our research
                 focuses on the more covert and complex Content
                 Pollution Attack (CPA). By continuously sending invalid
                 content to the network at a low speed, attackers will
                 consume a lot of the resources and time of the SNR
                 system, resulting in a serious increase in the
                 resolution delay of normal users and further cache
                 pollution in ICN. It is difficult to be quickly
                 detected because the characteristics of attack are
                 inconspicuous. To address the challenge, a register
                 access control scheme for an SNR system based on a
                 malicious user blacklist query is proposed. A neighbor
                 voting algorithm is designed to discover possible
                 attacks in the network quickly and build a blacklist of
                 malicious users reasonably. Users on the blacklist will
                 be restricted from accessing the ICN network during the
                 registration phase with the resolution system.
                 Incentives and punishments for network users are
                 introduced to automate responses about the potential
                 malicious behavior reports. Our scheme is more
                 efficient as users do not have to wait for an
                 additional system component to perform operations. In
                 addition, our algorithm can better solve the collusion
                 problem in the voting process when compared with the
                 others. We experimentally evaluate our protocol to
                 demonstrate that the probability of successful
                 collusion attack can be reduced to less than 0.1 when
                 the attacker ratio is 0.5.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2021:ITC,
  author =       "Yinfeng Wang and Longxiang Wang and Xiaoshe Dong",
  title =        "An Intelligent {TCP} Congestion Control Method Based
                 on Deep {Q} Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "10",
  pages =        "261",
  day =          "09",
  month =        oct,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13100261",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Oct 22 11:19:02 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/10/261",
  abstract =     "To optimize the data migration performance between
                 different supercomputing centers in China, we present
                 TCP-DQN, which is an intelligent TCP congestion control
                 method based on DQN (Deep Q network). The TCP
                 congestion control process is abstracted as a partially
                 observed Markov decision process. In this process, an
                 agent is constructed to interact with the network
                 environment. The agent adjusts the size of the
                 congestion window by observing the characteristics of
                 the network state. The network environment feeds back
                 the reward to the agent, and the agent tries to
                 maximize the expected reward in an episode. We designed
                 a weighted reward function to balance the throughput
                 and delay. Compared with traditional Q-learning, DQN
                 uses double-layer neural networks and experience replay
                 to reduce the oscillation problem that may occur in
                 gradient descent. We implemented the TCP-DQN method and
                 compared it with mainstream congestion control
                 algorithms such as cubic, Highspeed and NewReno. The
                 results show that the throughput of TCP-DQN can reach
                 more than 2 times of the comparison method while the
                 latency is close to the three compared methods.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Qiao:2021:DSR,
  author =       "Wenxin Qiao and Hao Lu and Yu Lu and Lijie Meng and
                 Yicen Liu",
  title =        "A Dynamic Service Reconfiguration Method for
                 Satellite-Terrestrial Integrated Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "10",
  pages =        "260",
  day =          "09",
  month =        oct,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13100260",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Oct 22 11:19:02 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/10/260",
  abstract =     "Satellite-terrestrial integrated networks (STINs) are
                 regarded as a promising solution to meeting the demands
                 of global high-speed seamless network access in the
                 future. Software-defined networking and network
                 function virtualization (SDN/NFV) are two complementary
                 technologies that can be used to ensure that the
                 heterogeneous resources in STINs can be easily managed
                 and deployed. Considering the dual mobility of
                 satellites and ubiquitous users, along with the dynamic
                 requirements of user requests and network resource
                 states, it is challenging to maintain service
                 continuity and high QoE performance in STINs. Thus, we
                 investigate the service migration and reconfiguration
                 scheme, which are of great significance to the
                 guarantee of continuous service provisioning.
                 Specifically, this paper proposes a dynamic service
                 reconfiguration method that can support flexible
                 service configurations on integrated networks,
                 including LEO satellites and ground nodes. We first
                 model the migration cost as an extra delay incurred by
                 service migration and reconfiguration and then
                 formulate the selection processes of the location and
                 migration paths of virtual network functions (VNFs) as
                 an integer linear programming (ILP) optimization
                 problem. Then, we propose a fuzzy logic and quantum
                 genetic algorithm (FQGA) to obtain an approximate
                 optimal solution that can accelerate the solving
                 process efficiently with the benefits of the
                 high-performance computing capacity of QGA. The
                 simulation results validate the effectiveness and
                 improved performance of the scheme proposed in this
                 paper.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Celsi:2021:PTR,
  author =       "Lorenzo Ricciardi Celsi and Andrea Caliciotti and
                 Matteo D'Onorio and Eugenio Scocchi and Nour Alhuda
                 Sulieman and Massimo Villari",
  title =        "On Predicting Ticket Reopening for Improving Customer
                 Service in {5G} Fiber Optic Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "10",
  pages =        "259",
  day =          "09",
  month =        oct,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13100259",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Oct 22 11:19:02 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/10/259",
  abstract =     "The paper proposes a data-driven strategy for
                 predicting technical ticket reopening in the context of
                 customer service for telecommunications companies
                 providing 5G fiber optic networks. Namely, the main aim
                 is to ensure that, between end user and service
                 provider, the Service Level Agreement in terms of
                 perceived Quality of Service is satisfied. The activity
                 has been carried out within the framework of an
                 extensive joint research initiative focused on Next
                 Generation Networks between ELIS Innovation Hub and a
                 major network service provider in Italy over the years
                 2018-2021. The authors make a detailed comparison among
                 the performance of different approaches to
                 classification-ranging from decision trees to
                 Artificial Neural Networks and Support Vector
                 Machines-and claim that a Bayesian network classifier
                 is the most accurate at predicting whether a monitored
                 ticket will be reopened or not. Moreover, the authors
                 propose an approach to dimensionality reduction that
                 proves to be successful at increasing the computational
                 efficiency, namely by reducing the size of the relevant
                 training dataset by two orders of magnitude with
                 respect to the original dataset. Numerical simulations
                 end the paper, proving that the proposed approach can
                 be a very useful tool for service providers in order to
                 identify the customers that are most at risk of
                 reopening a ticket due to an unsolved technical
                 issue.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Foschini:2021:SEA,
  author =       "Luca Foschini and Valentina Mignardi and Rebecca
                 Montanari and Domenico Scotece",
  title =        "An {SDN}-Enabled Architecture for {IT\slash OT}
                 Converged Networks: a Proposal and Qualitative Analysis
                 under {DDoS} Attacks",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "10",
  pages =        "258",
  day =          "08",
  month =        oct,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13100258",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Oct 22 11:19:02 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/10/258",
  abstract =     "Real-time business practices require huge amounts of
                 data directly from the production assets. This new
                 thirst for accurate and timely data has forced the
                 convergence of the traditionally business-focused
                 information technology (IT) environment with the
                 production-focused operational technology (OT).
                 Recently, software-defined network (SDN) methodologies
                 have benefitted OT networks with enhanced situational
                 awareness, centralized configuration, deny-by-default
                 forwarding rules, and increased performance. What makes
                 SDNs so innovative is the separation between the
                 control plane and the data plane, centralizing the
                 command in the controllers. However, due to their young
                 age, the use of SDNs in the industry context has not
                 yet matured comprehensive SDN-based architectures for
                 IT/OT networks, which are also resistant to security
                 attacks such as denial-of-service ones, which may occur
                 in SDN-based industrial IoT (IIoT) networks. One main
                 motivation is that the lack of comprehensive SDN-based
                 architectures for IT/OT networks making it difficult to
                 effectively simulate, analyze, and identify proper
                 detection and mitigation strategies for DoS attacks in
                 IT/OT networks. No consolidated security solutions are
                 available that provide DoS detection and mitigation
                 strategies in IT/OT networks. Along this direction,
                 this paper's contributions are twofold. On the one
                 hand, this paper proposes a convergent IT/OT SDN-based
                 architecture applied in a real implementation of an
                 IT/OT support infrastructure called SIRDAM4.0 within
                 the context of the SBDIOI40 project. On the other hand,
                 this paper proposes a qualitative analysis on how this
                 architecture works under DoS attacks, focusing on what
                 the specific problems and vulnerabilities are. In
                 particular, we simulated several distributed
                 denial-of-service (DDoS) attack scenarios within the
                 context of the proposed architecture to show the
                 minimum effort needed by the attacker to hack the
                 network, and our obtained experimental results show how
                 it is possible to compromise the network, thus
                 considerably worsening the performance and, in general,
                 the functioning of the network. Finally, we conclude
                 our analysis with a brief description on the importance
                 of employing machine learning approaches for attack
                 detection and for mitigation techniques.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{ElGhanam:2021:ABD,
  author =       "Eiman ElGhanam and Ibtihal Ahmed and Mohamed Hassan
                 and Ahmed Osman",
  title =        "Authentication and Billing for Dynamic Wireless {EV}
                 Charging in an {Internet of Electric Vehicles}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "10",
  pages =        "257",
  day =          "08",
  month =        oct,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13100257",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Oct 22 11:19:02 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/10/257",
  abstract =     "Dynamic wireless charging (DWC) is a promising
                 technology to charge Electric Vehicles (EV) using
                 on-road charging segments (CS), also known as DWC pads.
                 In order to ensure effective utilization of this
                 on-the-road charging service, communication and
                 coordination need to be established between the EVs and
                 the different network entities, thereby forming an
                 Internet of Electric Vehicles (IoEV). In an IoEV, EVs
                 can utilize different V2X communication modes to enable
                 charging scheduling, load management, and reliable
                 authentication and billing services. Yet, designing an
                 authentication scheme for dynamic EV charging presents
                 significant challenges given the mobility of the EVs
                 and the short contact time between the EVs and the
                 charging segments. Accordingly, this work proposes a
                 fast, secure and lightweight authentication scheme that
                 allows only authentic EVs with valid credentials to
                 charge their batteries while ensuring secure and fair
                 payments. The presented scheme starts with a key
                 pre-distribution phase between the charging service
                 company (CSC) and the charging pad owner (PO), followed
                 by a hash chain and digital signature-based
                 registration and authentication phase between the EV
                 and the CSC, before the EV reaches the beginning of the
                 charging lane. These preliminary authentication phases
                 allow the authentication between the EVs and the
                 charging segments to be performed using simple hash key
                 verification operations prior to charging activation,
                 which reduces the computational cost of the EVs and the
                 CS. Symmetric and asymmetric key cryptography are
                 utilized to secure the communication between the
                 different network entities. Analysis of the
                 computational and transmission time requirements of the
                 proposed authentication scheme shows that, for an EV
                 traveling at 60 km/h to start charging at the beginning
                 of the charging lane, the authentication process must
                 be initiated at least 1.35 m ahead of the starting
                 point of the lane as it requires $ \approx 81 $ ms to
                 be completed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2021:MAS,
  author =       "Shaoyong Li and Liang Lv and Xiaoya Li and Zhaoyun
                 Ding",
  title =        "Mobile App Start-Up Prediction Based on Federated
                 Learning and Attributed Heterogeneous Network
                 Embedding",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "10",
  pages =        "256",
  day =          "07",
  month =        oct,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13100256",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Oct 22 11:19:02 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/10/256",
  abstract =     "At present, most mobile App start-up prediction
                 algorithms are only trained and predicted based on
                 single-user data. They cannot integrate the data of all
                 users to mine the correlation between users, and cannot
                 alleviate the cold start problem of new users or newly
                 installed Apps. There are some existing works related
                 to mobile App start-up prediction using multi-user
                 data, which require the integration of multi-party
                 data. In this case, a typical solution is distributed
                 learning of centralized computing. However, this
                 solution can easily lead to the leakage of user privacy
                 data. In this paper, we propose a mobile App start-up
                 prediction method based on federated learning and
                 attributed heterogeneous network embedding, which
                 alleviates the cold start problem of new users or new
                 Apps while guaranteeing users' privacy.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Noguez:2021:VHM,
  author =       "Julieta Noguez and Luis Neri and V{\'\i}ctor
                 Robledo-Rella and Rosa Mar{\'\i}a Guadalupe
                 Garc{\'\i}a-Castel{\'a}n and Andres Gonzalez-Nucamendi
                 and David Escobar-Castillejos and Arturo Molina",
  title =        "{VIS-HAPT}: a Methodology Proposal to Develop
                 Visuo-Haptic Environments in {Education 4.0}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "10",
  pages =        "255",
  day =          "05",
  month =        oct,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13100255",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Oct 22 11:19:02 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/10/255",
  abstract =     "Education 4.0 demands a flexible combination of
                 digital literacy, critical thinking, and
                 problem-solving in educational settings linked to
                 real-world scenarios. Haptic technology incorporates
                 the sense of touch into a visual simulator to enrich
                 the user's sensory experience, thus supporting a
                 meaningful learning process. After developing several
                 visuo-haptic simulators, our team identified serious
                 difficulties and important challenges to achieve
                 successful learning environments within the framework
                 of Education 4.0. This paper presents the VIS-HAPT
                 methodology for developing realistic visuo-haptic
                 scenarios to promote the learning of science and
                 physics concepts for engineering students. This
                 methodology consists of four stages that integrate
                 different aspects and processes leading to meaningful
                 learning experiences for students. The different
                 processes that must be carried out through the
                 different stages, the difficulties to overcome and
                 recommendations on how to face them are all described
                 herein. The results are encouraging since a significant
                 decrease (of approximately 40\%) in the development and
                 implementation times was obtained as compared with
                 previous efforts. The quality of the visuo-haptic
                 environments was also enhanced. Student perceptions of
                 the benefits of using visuo-haptic simulators to
                 enhance their understanding of physics concepts also
                 improved after using the proposed methodology. The
                 incorporation of haptic technologies in higher
                 education settings will certainly foster better student
                 performance in subsequent real environments related to
                 Industry 4.0.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alasmari:2021:RAC,
  author =       "Ashwag Alasmari and Aseel Addawood and Mariam Nouh and
                 Wajanat Rayes and Areej Al-Wabil",
  title =        "A Retrospective Analysis of the {COVID-19} Infodemic
                 in {Saudi Arabia}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "10",
  pages =        "254",
  day =          "30",
  month =        sep,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13100254",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Oct 22 11:19:02 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/10/254",
  abstract =     "COVID-19 has had broad disruptive effects on
                 economies, healthcare systems, governments, societies,
                 and individuals. Uncertainty concerning the scale of
                 this crisis has given rise to countless rumors, hoaxes,
                 and misinformation. Much of this type of conversation
                 and misinformation about the pandemic now occurs online
                 and in particular on social media platforms like
                 Twitter. This study analysis incorporated a data-driven
                 approach to map the contours of misinformation and
                 contextualize the COVID-19 pandemic with regards to
                 socio-religious-political information. This work
                 consists of a combined system bridging quantitative and
                 qualitative methodologies to assess how
                 information-exchanging behaviors can be used to
                 minimize the effects of emergent misinformation. The
                 study revealed that the social media platforms detected
                 the most significant source of rumors in transmitting
                 information rapidly in the community. It showed that
                 WhatsApp users made up about 46\% of the source of
                 rumors in online platforms, while, through Twitter, it
                 demonstrated a declining trend of rumors by 41\%.
                 Moreover, the results indicate the second-most common
                 type of misinformation was provided by pharmaceutical
                 companies; however, a prevalent type of misinformation
                 spreading in the world during this pandemic has to do
                 with the biological war. In this combined retrospective
                 analysis of the study, social media with varying
                 approaches in public discourse contributes to efficient
                 public health responses.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ming:2021:DCV,
  author =       "Teo Rhun Ming and Noris Mohd Norowi and Rahmita Wirza
                 and Azrina Kamaruddin",
  title =        "Designing a Collaborative Virtual Conference
                 Application: Challenges, Requirements and Guidelines",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "10",
  pages =        "253",
  day =          "29",
  month =        sep,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13100253",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Oct 22 11:19:02 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/10/253",
  abstract =     "Due to the recent COVID-19 pandemic that has swept the
                 globe, more people are working from home. People use
                 synchronous applications to communicate remotely
                 because they are not able to meet face-to-face.
                 However, few research studies on the issues surrounding
                 the virtual conference application, particularly those
                 that include collaborative activities, have been
                 conducted. The usability study recruited 16
                 participants (in four groups of four) to communicate
                 synchronously while performing collaborative
                 activities, such as drawing together on a shared
                 screen. According to the findings of the usability
                 study, users do not often use the collaborative tools
                 provided by the current virtual conference application.
                 This is due to low exposure and unfamiliarity with the
                 use of collaborative tools. The findings also show that
                 users frequently do not turn on the web camera due to
                 several reasons, including privacy, connectivity
                 issues, the environment, and background distraction.
                 Turning on the web camera can also cause anxiety due to
                 shyness in front of the camera. However, some
                 participants prefer to turn on the web camera so that
                 they can see each other's reactions when performing
                 collaborative activities. The article provides several
                 guidelines to assist in the design of virtual
                 conference applications, including a simple familiar
                 intuitive interface to encourage the use of
                 collaborative tools and also introduces the use of
                 virtual avatars as a way to represent oneself during
                 online meetings to allow affective sharing while
                 respecting the privacy of its users.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yuloskov:2021:SCR,
  author =       "Artem Yuloskov and Mohammad Reza Bahrami and Manuel
                 Mazzara and Iouri Kotorov",
  title =        "Smart Cities in {Russia}: Current Situation and
                 Insights for Future Development",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "10",
  pages =        "252",
  day =          "28",
  month =        sep,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13100252",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Oct 22 11:19:02 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/10/252",
  abstract =     "The development of smart cities is a clear growing
                 trend all around the world. The convergence of
                 different technological, social, political, economical,
                 and ecological trends has allowed the concepts to rise
                 up quickly in governmental agendas. In this paper, we
                 analyze the situation of Russia regarding smart cities.
                 Moscow, Saint Petersburg, and Kazan are considered at
                 the ``Smart City 3.0'' stage of development, meaning
                 that the citizens are participating in their
                 advancement. Our reasons to focus on Russia are
                 two-fold: (1) we know the situation well, as we live
                 and work in a new city, Innopolis, founded in 2015 and
                 meant to be a blueprint for smart cities; (2) large
                 Russian cities are actively developing projects in this
                 sphere and are highly regarded worldwide in these
                 endeavors. It is therefore worth analyzing the context
                 and the trends. By studying the scientific literature
                 and categorizing the features of smart cities the world
                 over, we found that large Russian cities are developing
                 most of the components necessary in order to be called
                 smart. Herein we also discuss areas of possible growth
                 for Russian cities, such as green technologies and a
                 smart environment.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2021:FSP,
  author =       "Shunli Wang and Rui Li and Jie Jiang and Yao Meng",
  title =        "Fine-Scale Population Estimation Based on Building
                 Classifications: a Case Study in {Wuhan}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "10",
  pages =        "251",
  day =          "28",
  month =        sep,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13100251",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Oct 22 11:19:02 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/10/251",
  abstract =     "In the context of rapid urbanization, the refined
                 management of cities is facing higher requirements. In
                 improving urban population management levels and the
                 scientific allocation of resources, fine-scale
                 population data plays an increasingly important role.
                 The current population estimation studies mainly focus
                 on low spatial resolution, such as city-scale and
                 county scale, without considering differences in
                 population distributions within cities. This paper
                 mines and defines the spatial correlations of
                 multi-source data, including urban building data, point
                 of interest ( POI ) data, census data, and
                 administrative division data. With populations mainly
                 distributed in residential buildings, a population
                 estimation model at a subdistrict scale is established
                 based on building classifications. Composed of spatial
                 information and attribute information, POI data are
                 spaced irregularly. Based on this characteristic, the
                 text classification method, frequency-inverse document
                 frequency ( TF-IDF ), is applied to obtain functional
                 classifications of buildings. Then we screen out
                 residential buildings, and quantify characteristic
                 variables in subdistricts, including perimeter, area,
                 and total number of floors in residential buildings. To
                 assess the validity of the variables, the random forest
                 method is selected for variable screening and
                 correlation analysis, because this method has clear
                 advantages when dealing with unbalanced data. Under the
                 assumption of linearity, multiple regression analysis
                 is conducted, to obtain a linear model of the number of
                 buildings, their geometric characteristics, and the
                 population in each administrative division. Experiments
                 showed that the urban fine-scale population estimation
                 model established in this study can estimate the
                 population at a subdistrict scale with high accuracy.
                 This method improves the precision and automation of
                 urban population estimation. It allows the accurate
                 estimation of the population at a subdistrict scale,
                 thereby providing important data to support the overall
                 planning of regional energy resource allocation,
                 economic development, social governance, and
                 environmental protection.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Corujo:2021:ERH,
  author =       "Luis A. Corujo and Emily Kieson and Timo Schloesser
                 and Peter A. Gloor",
  title =        "Emotion Recognition in Horses with Convolutional
                 Neural Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "10",
  pages =        "250",
  day =          "28",
  month =        sep,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13100250",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Oct 22 11:19:02 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/10/250",
  abstract =     "Creating intelligent systems capable of recognizing
                 emotions is a difficult task, especially when looking
                 at emotions in animals. This paper describes the
                 process of designing a ``proof of concept'' system to
                 recognize emotions in horses. This system is formed by
                 two elements, a detector and a model. The detector is a
                 fast region-based convolutional neural network that
                 detects horses in an image. The model is a
                 convolutional neural network that predicts the emotions
                 of those horses. These two elements were trained with
                 multiple images of horses until they achieved high
                 accuracy in their tasks. In total, 400 images of horses
                 were collected and labeled to train both the detector
                 and the model while 40 were used to test the system.
                 Once the two components were validated, they were
                 combined into a testable system that would detect
                 equine emotions based on established behavioral
                 ethograms indicating emotional affect through the head,
                 neck, ear, muzzle, and eye position. The system showed
                 an accuracy of 80\% on the validation set and 65\% on
                 the test set, demonstrating that it is possible to
                 predict emotions in animals using autonomous
                 intelligent systems. Such a system has multiple
                 applications including further studies in the growing
                 field of animal emotions as well as in the veterinary
                 field to determine the physical welfare of horses or
                 other livestock.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{daCruz:2021:ORO,
  author =       "Mauro A. A. da Cruz and Heitor T. L. de Paula and
                 Bruno P. G. Caputo and Samuel B. Mafra and Pascal
                 Lorenz and Joel J. P. C. Rodrigues",
  title =        "{OLP} --- a {RESTful} Open Low-Code Platform",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "10",
  pages =        "249",
  day =          "25",
  month =        sep,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13100249",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Oct 22 11:19:02 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/10/249",
  abstract =     "Low-code is an emerging concept that transforms visual
                 representations into functional software, allowing
                 anyone to be a developer. However, building a low-code
                 platform from scratch can be challenging concerning the
                 scarce available literature about the topic. In this
                 sense, this paper proposes an Open Low-Code Platform
                 (OLP), a low-code solution that enables regular users
                 to create applications. Furthermore, it presents
                 low-code's functional and nonfunctional requirements,
                 as well as its similarities and its differences with
                 the no-code concept. The experience obtained while
                 developing OLP was translated into a pipeline that
                 details how code was transformed from the visual
                 representations into a fully fledged application. The
                 paper demonstrates the solution's viability and is
                 especially useful for building a low-code platform from
                 scratch or improving an existing one.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Xu:2021:EPE,
  author =       "Ronghua Xu and Deeraj Nagothu and Yu Chen",
  title =        "{EconLedger}: a Proof-of-{ENF} Consensus Based
                 Lightweight Distributed Ledger for {IoVT} Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "10",
  pages =        "248",
  day =          "24",
  month =        sep,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13100248",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Oct 22 11:19:02 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/10/248",
  abstract =     "The rapid advancement in artificial intelligence (AI)
                 and wide deployment of Internet of Video Things (IoVT)
                 enable situation awareness (SAW). The robustness and
                 security of IoVT systems are essential for a
                 sustainable urban environment. While blockchain
                 technology has shown great potential in enabling
                 trust-free and decentralized security mechanisms,
                 directly embedding cryptocurrency oriented blockchain
                 schemes into resource-constrained Internet of Video
                 Things (IoVT) networks at the edge is not feasible. By
                 leveraging Electrical Network Frequency (ENF) signals
                 extracted from multimedia recordings as
                 region-of-recording proofs, this paper proposes
                 EconLedger, an ENF-based consensus mechanism that
                 enables secure and lightweight distributed ledgers for
                 small-scale IoVT edge networks. The proposed consensus
                 mechanism relies on a novel Proof-of-ENF (PoENF)
                 algorithm where a validator is qualified to generate a
                 new block if and only if a proper ENF-containing
                 multimedia signal proof is produced within the current
                 round. The decentralized database (DDB) is adopted in
                 order to guarantee efficiency and resilience of raw ENF
                 proofs on the off-chain storage. A proof-of-concept
                 prototype is developed and tested in a physical IoVT
                 network environment. The experimental results validated
                 the feasibility of the proposed EconLedger to provide a
                 trust-free and partially decentralized security
                 infrastructure for IoVT edge networks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2021:HPP,
  author =       "Baocheng Wang and Zetao Li",
  title =        "{Healthchain}: a Privacy Protection System for Medical
                 Data Based on Blockchain",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "10",
  pages =        "247",
  day =          "24",
  month =        sep,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13100247",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Oct 22 11:19:02 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/10/247",
  abstract =     "Recently, with the great development of e-health, more
                 and more countries have made certain achievements in
                 the field of electronic medical treatment. The
                 digitization of medical equipment and the
                 structuralization of electronic medical records are the
                 general trends. While bringing convenience to people,
                 the explosive growth of medical data will further
                 promote the value of mining medical data. Obviously,
                 finding out how to safely store such a large amount of
                 data is a problem that urgently needs to be solved.
                 Additionally, the particularity of medical data makes
                 it necessarily subject to great privacy protection
                 needs. This reinforces the importance of designing a
                 safe solution to ensure data privacy. Many existing
                 schemes are based on single-server architecture, which
                 have some natural defects (such as single-point
                 faults). Although blockchain can help solve such
                 problems, there are still some deficiencies in privacy
                 protection. To solve these problems, this paper designs
                 a medical data privacy protection system, which
                 integrates blockchain, group signature, and asymmetric
                 encryption to realize reliable medical data sharing
                 between medical institutions and protect the data
                 privacy of patients. This paper proves theoretically
                 that it meets our security and privacy requirements,
                 and proves its practicability through system
                 implementation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gonzalez-Nieto:2021:SCD,
  author =       "No{\'e} Abraham Gonz{\'a}lez-Nieto and Caridad
                 Garc{\'\i}a-Hern{\'a}ndez and Margarita
                 Espinosa-Meneses",
  title =        "School Culture and Digital Technologies: Educational
                 Practices at Universities within the Context of the
                 {COVID-19} Pandemic",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "10",
  pages =        "246",
  day =          "24",
  month =        sep,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13100246",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Oct 22 11:19:02 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/10/246",
  abstract =     "The pandemic caused by COVID-19 led schools to
                 continue their work by relying on digital technologies.
                 Changes in this matter are observed within three
                 dimensions in the theoretical and conceptual
                 background: (a) the influence of ITC in education, (b)
                 the macrosocial changes in the educational systems and
                 public policy derived from the COVID-19 pandemic, and
                 (c) the impact of the COVID-19 pandemic in higher
                 education and its role for the future. The general
                 objective of this research was to characterize the
                 educational practices executed by the university
                 community (students, professors, and managers) during
                 the emerging remote classes derived from the pandemic
                 at the Universidad Autonoma Metropolitana, Cuajimalpa
                 Campus, a public educational institution in Mexico
                 (through an explanation for each educational actor
                 profile). As specific research objectives, this paper:
                 (a) examines whether the professors and students had
                 enough digital technology to continue with the classes,
                 (b) defines the obstacles they had in the use of said
                 digital technology, and (c) recognizes the existence of
                 innovative educational practices and determines whether
                 stated learning was achieved in educational programs.
                 For this purpose, a mixed methodology was chosen,
                 comprising the application of surveys to students and
                 professors and semi-structured interviews with
                 managers, professors, and students. It was found that
                 there was innovation in the area of resources
                 (material-economic dimension) and in the area of
                 relationships (socio-political dimension), while the
                 discursive dimension (cultural-discursive dimension)
                 was negatively impacted. Based on the above, we
                 conclude that the school culture of the UAM-C is solid
                 and that it has the necessary technological resources
                 to continue with the teaching-learning process. The
                 educational practice was transformed, which resulted in
                 advantages and disadvantages, but despite these
                 situations, most students developed their learning.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Nikulchev:2021:ISE,
  author =       "Evgeny Nikulchev and Dmitry Ilin and Pavel Kolyasnikov
                 and Shamil Magomedov and Anna Alexeenko and Alexander
                 N. Kosenkov and Andrey Sokolov and Artem Malykh and
                 Victoria Ismatullina and Sergey Malykh",
  title =        "Isolated Sandbox Environment Architecture for Running
                 Cognitive Psychological Experiments in {Web}
                 Platforms",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "10",
  pages =        "245",
  day =          "24",
  month =        sep,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13100245",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Oct 22 11:19:02 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/10/245",
  abstract =     "Web surveys are an integral part of the feedback of
                 Internet services, a research tool for respondents,
                 including in the field of health and psychology. Web
                 technologies allow conducting research on large
                 samples. For mental health, an important metric is
                 reaction time in cognitive tests and in answering
                 questions. The use of mobile devices such as
                 smartphones and tablets has increased markedly in web
                 surveys, so the impact of device types and operating
                 systems needs to be investigated. This article proposes
                 an architectural solution aimed at reducing the effect
                 of device variability on the results of cognitive
                 psychological experiments. An experiment was carried
                 out to formulate the requirements for software and
                 hardware. Three groups of 1000 respondents were
                 considered, corresponding to three types of computers
                 and operating systems: Mobile Device, Legacy PC, and
                 Modern PC. The results obtained showed a slight bias in
                 the estimates for each group. It is noticed that the
                 error for a group of devices differs both upward and
                 downward for various tasks in a psychological
                 experiment. Thus, for cognitive tests, in which the
                 reaction time is critical, an architectural solution
                 was synthesized for conducting psychological research
                 in a web browser. The proposed architectural solution
                 considers the characteristics of the device used by
                 participants to undergo research in the web platform
                 and allows to restrict access from devices that do not
                 meet the specified criteria.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alenezi:2021:MLD,
  author =       "Mohammed N. Alenezi and Zainab M. Alqenaei",
  title =        "Machine Learning in Detecting {COVID-19}
                 Misinformation on {Twitter}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "10",
  pages =        "244",
  day =          "23",
  month =        sep,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13100244",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Oct 22 11:19:02 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/10/244",
  abstract =     "Social media platforms such as Facebook, Instagram,
                 and Twitter are an inevitable part of our daily lives.
                 These social media platforms are effective tools for
                 disseminating news, photos, and other types of
                 information. In addition to the positives of the
                 convenience of these platforms, they are often used for
                 propagating malicious data or information. This
                 misinformation may misguide users and even have
                 dangerous impact on society's culture, economics, and
                 healthcare. The propagation of this enormous amount of
                 misinformation is difficult to counter. Hence, the
                 spread of misinformation related to the COVID-19
                 pandemic, and its treatment and vaccination may lead to
                 severe challenges for each country's frontline workers.
                 Therefore, it is essential to build an effective
                 machine-learning (ML) misinformation-detection model
                 for identifying the misinformation regarding COVID-19.
                 In this paper, we propose three effective
                 misinformation detection models. The proposed models
                 are long short-term memory (LSTM) networks, which is a
                 special type of RNN; a multichannel convolutional
                 neural network (MC-CNN); and k-nearest neighbors (KNN).
                 Simulations were conducted to evaluate the performance
                 of the proposed models in terms of various evaluation
                 metrics. The proposed models obtained superior results
                 to those from the literature.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Spruit:2021:ABG,
  author =       "Marco Spruit and Marcin Kais and Vincent Menger",
  title =        "Automated Business Goal Extraction from E-mail
                 Repositories to Bootstrap Business Understanding",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "10",
  pages =        "243",
  day =          "23",
  month =        sep,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13100243",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Oct 22 11:19:02 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/10/243",
  abstract =     "The Cross-Industry Standard Process for Data Mining
                 (CRISP-DM), despite being the most popular data mining
                 process for more than two decades, is known to leave
                 those organizations lacking operational data mining
                 experience puzzled and unable to start their data
                 mining projects. This is especially apparent in the
                 first phase of Business Understanding, at the
                 conclusion of which, the data mining goals of the
                 project at hand should be specified, which arguably
                 requires at least a conceptual understanding of the
                 knowledge discovery process. We propose to bridge this
                 knowledge gap from a Data Science perspective by
                 applying Natural Language Processing techniques (NLP)
                 to the organizations' e-mail exchange repositories to
                 extract explicitly stated business goals from the
                 conversations, thus bootstrapping the Business
                 Understanding phase of CRISP-DM. Our NLP-Automated
                 Method for Business Understanding (NAMBU) generates a
                 list of business goals which can subsequently be used
                 for further specification of data mining goals. The
                 validation of the results on the basis of comparison to
                 the results of manual business goal extraction from the
                 Enron corpus demonstrates the usefulness of our NAMBU
                 method when applied to large datasets.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ramadan:2021:UML,
  author =       "Lara Ramadan and Isam Shahrour and Hussein Mroueh and
                 Fadi Hage Chehade",
  title =        "Use of Machine Learning Methods for Indoor Temperature
                 Forecasting",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "10",
  pages =        "242",
  day =          "23",
  month =        sep,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13100242",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Oct 22 11:19:02 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/10/242",
  abstract =     "Improving the energy efficiency of the building sector
                 has become an increasing concern in the world, given
                 the alarming reports of greenhouse gas emissions. The
                 management of building energy systems is considered an
                 essential means for achieving this goal. Predicting
                 indoor temperature constitutes a critical task for the
                 management strategies of these systems. Several
                 approaches have been developed for predicting indoor
                 temperature. Determining the most effective has thus
                 become a necessity. This paper contributes to this
                 objective by comparing the ability of seven machine
                 learning algorithms (ML) and the thermal gray box model
                 to predict the indoor temperature of a closed room. The
                 comparison was conducted on a set of data recorded in a
                 room of the Laboratory of Civil Engineering and
                 geo-Environment (LGCgE) at Lille University. The
                 results showed that the best prediction was obtained
                 with the artificial neural network (ANN) and extra
                 trees regressor (ET) methods, which outperformed the
                 thermal gray box model.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tan:2021:ETS,
  author =       "Yee-Fan Tan and Lee-Yeng Ong and Meng-Chew Leow and
                 Yee-Xian Goh",
  title =        "Exploring Time-Series Forecasting Models for Dynamic
                 Pricing in Digital Signage Advertising",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "10",
  pages =        "241",
  day =          "22",
  month =        sep,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13100241",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Oct 22 11:19:02 MDT 2021",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/10/241",
  abstract =     "Audience attention is vital in Digital Signage
                 Advertising (DSA), as it has a significant impact on
                 the pricing decision to advertise on those media.
                 Various environmental factors affect the audience
                 attention level toward advertising signage. Fixed-price
                 strategies, which have been applied in DSA for pricing
                 decisions, are generally inefficient at maximizing the
                 potential profit of the service provider, as the
                 environmental factors that could affect the audience
                 attention are changing fast and are generally not
                 considered in the current pricing solutions in a timely
                 manner. Therefore, the time-series forecasting method
                 is a suitable pricing solution for DSA, as it improves
                 the pricing decision by modeling the changes in the
                 environmental factors and audience attention level
                 toward signage for optimal pricing. However, it is
                 difficult to determine an optimal price forecasting
                 model for DSA with the increasing number of available
                 time-series forecasting models in recent years. Based
                 on the 84 research articles reviewed, the data
                 characteristics analysis in terms of linearity,
                 stationarity, volatility, and dataset size is helpful
                 in determining the optimal model for time-series price
                 forecasting. This paper has reviewed the widely used
                 time-series forecasting models and identified the
                 related data characteristics of each model. A framework
                 is proposed to demonstrate the model selection process
                 for dynamic pricing in DSA based on its data
                 characteristics analysis, paving the way for future
                 research of pricing solutions for DSA.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liu:2021:FSC,
  author =       "Kunlin Liu and Ping Wang and Wenbo Zhou and Zhenyu
                 Zhang and Yanhao Ge and Honggu Liu and Weiming Zhang
                 and Nenghai Yu",
  title =        "Face Swapping Consistency Transfer with Neural
                 Identity Carrier",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "298",
  day =          "22",
  month =        nov,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110298",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/298",
  abstract =     "Deepfake aims to swap a face of an image with someone
                 else's likeness in a reasonable manner. Existing
                 methods usually perform deepfake frame by frame, thus
                 ignoring video consistency and producing incoherent
                 results. To address such a problem, we propose a novel
                 framework Neural Identity Carrier (NICe), which learns
                 identity transformation from an arbitrary face-swapping
                 proxy via a U-Net. By modeling the incoherence between
                 frames as noise, NICe naturally suppresses its
                 disturbance and preserves primary identity information.
                 Concretely, NICe inputs the original frame and learns
                 transformation supervised by swapped pseudo labels. As
                 the temporal incoherence has an uncertain or stochastic
                 pattern, NICe can filter out such outliers and well
                 maintain the target content by uncertainty prediction.
                 With the predicted temporally stable appearance, NICe
                 enhances its details by constraining 3D geometry
                 consistency, making NICe learn fine-grained facial
                 structure across the poses. In this way, NICe
                 guarantees the temporal stableness of deepfake
                 approaches and predicts detailed results against
                 over-smoothness. Extensive experiments on benchmarks
                 demonstrate that NICe significantly improves the
                 quality of existing deepfake methods on video-level.
                 Besides, data generated by our methods can benefit
                 video-level deepfake detection methods.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gavra:2021:DIA,
  author =       "Dmitrii Gavra and Ksenia Namyatova and Lidia Vitkova",
  title =        "Detection of Induced Activity in Social Networks:
                 Model and Methodology",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "297",
  day =          "22",
  month =        nov,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110297",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/297",
  abstract =     "This paper examines the problem of social media
                 special operations and especially induced support in
                 social media during political election campaigns. The
                 theoretical background of the paper is based on the
                 study fake activity in social networks during
                 pre-election processes and the existing models and
                 methods of detection of such activity. The article
                 proposes a methodology for identifying and diagnosing
                 induced support for a political project. The
                 methodology includes a model of induced activity, an
                 algorithm for segmenting the audience of a political
                 project, and a technique for detecting and diagnosing
                 induced support. The proposed methodology provides
                 identification of network combatants, participants of
                 social media special operations, influencing public
                 opinion in the interests of a political project. The
                 methodology can be used to raise awareness of the
                 electorate, the public, and civil society in general
                 about the presence of artificial activity on the page
                 of a political project.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bagnoli:2021:CFB,
  author =       "Franco Bagnoli and Guido de Bonfioli Cavalcabo' and
                 Banedetto Casu and Andrea Guazzini",
  title =        "Community Formation as a Byproduct of a Recommendation
                 System: a Simulation Model for Bubble Formation in
                 Social Media",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "296",
  day =          "22",
  month =        nov,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110296",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/296",
  abstract =     "We investigate the problem of the formation of
                 communities of users that selectively exchange messages
                 among them in a simulated environment. This closed
                 community can be seen as the prototype of the bubble
                 effect, i.e., the isolation of individuals from other
                 communities. We develop a computational model of a
                 society, where each individual is represented as a
                 simple neural network (a perceptron), under the
                 influence of a recommendation system that honestly
                 forward messages (posts) to other individuals that in
                 the past appreciated previous messages from the sender,
                 i.e., that showed a certain degree of affinity. This
                 dynamical affinity database determines the interaction
                 network. We start from a set of individuals with random
                 preferences (factors), so that at the beginning, there
                 is no community structure at all. We show that the
                 simple effect of the recommendation system is not
                 sufficient to induce the isolation of communities, even
                 when the database of user-user affinity is based on a
                 small sample of initial messages, subject to
                 small-sampling fluctuations. On the contrary, when the
                 simulated individuals evolve their internal factors
                 accordingly with the received messages, communities can
                 emerge. This emergence is stronger the slower the
                 evolution of individuals, while immediate convergence
                 favors to the breakdown of the system in smaller
                 communities. In any case, the final communities are
                 strongly dependent on the sequence of messages, since
                 one can get different final communities starting from
                 the same initial distribution of users' factors,
                 changing only the order of users emitting messages. In
                 other words, the main outcome of our investigation is
                 that the bubble formation depends on users' evolution
                 and is strongly dependent on early interactions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Blekanov:2021:DHC,
  author =       "Ivan Blekanov and Svetlana S. Bodrunova and Askar
                 Akhmetov",
  title =        "Detection of Hidden Communities in {Twitter}
                 Discussions of Varying Volumes",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "295",
  day =          "20",
  month =        nov,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110295",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/295",
  abstract =     "The community-based structure of communication on
                 social networking sites has long been a focus of
                 scholarly attention. However, the problem of discovery
                 and description of hidden communities, including
                 defining the proper level of user aggregation, remains
                 an important problem not yet resolved. Studies of
                 online communities have clear social implications, as
                 they allow for assessment of preference-based user
                 grouping and the detection of socially hazardous
                 groups. The aim of this study is to comparatively
                 assess the algorithms that effectively analyze large
                 user networks and extract hidden user communities from
                 them. The results we have obtained show the most
                 suitable algorithms for Twitter datasets of different
                 volumes (dozen thousands, hundred thousands, and
                 millions of tweets). We show that the Infomap and
                 Leiden algorithms provide for the best results overall,
                 and we advise testing a combination of these algorithms
                 for detecting discursive communities based on user
                 traits or views. We also show that the generalized K
                 -means algorithm does not apply to big datasets, while
                 a range of other algorithms tend to prioritize the
                 detection of just one big community instead of many
                 that would mirror the reality better. For isolating
                 overlapping communities, the GANXiS algorithm should be
                 used, while OSLOM is not advised.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liu:2021:PPE,
  author =       "Jianhua Liu and Zibo Wu",
  title =        "{PECSA}: Practical Edge Computing Service Architecture
                 Applicable to Adaptive {IoT}-Based Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "294",
  day =          "19",
  month =        nov,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110294",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/294",
  abstract =     "The cloud-based Internet of Things (IoT-Cloud)
                 combines the advantages of the IoT and cloud computing,
                 which not only expands the scope of cloud computing but
                 also enhances the data processing capability of the
                 IoT. Users always seek affordable and efficient
                 services, which can be completed by the cooperation of
                 all available network resources, such as edge computing
                 nodes. However, current solutions exhibit significant
                 security and efficiency problems that must be solved.
                 Insider attacks could degrade the performance of the
                 IoT-Cloud due to its natural environment and inherent
                 open construction. Unfortunately, traditional security
                 approaches cannot defend against these attacks
                 effectively. In this paper, a novel practical edge
                 computing service architecture (PECSA), which
                 integrates a trust management methodology with dynamic
                 cost evaluation schemes, is proposed to address these
                 problems. In the architecture, the edge network devices
                 and edge platform cooperate to achieve a shorter
                 response time and/or less economic costs, as well as to
                 enhance the effectiveness of the trust management
                 methodology, respectively. To achieve faster responses
                 for IoT-based requirements, all the edge computing
                 devices and cloud resources cooperate in a reasonable
                 way by evaluating computational cost and runtime
                 resource capacity in the edge networks. Moreover, when
                 cooperated with the edge platform, the edge networks
                 compute trust values of linked nodes and find the best
                 collaborative approach for each user to meet various
                 service requirements. Experimental results demonstrate
                 the efficiency and the security of the proposed
                 architecture.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Vogel:2021:RCD,
  author =       "Elisabeth Vogel and Zoya Dyka and Dan Klann and Peter
                 Langend{\"o}rfer",
  title =        "Resilience in the Cyberworld: Definitions, Features
                 and Models",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "293",
  day =          "19",
  month =        nov,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110293",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/293",
  abstract =     "Resilience is a feature that is gaining more and more
                 attention in computer science and computer engineering.
                 However, the definition of resilience for the cyber
                 landscape, especially embedded systems, is not yet
                 clear. This paper discusses definitions provided by
                 different authors, on different years and with
                 different application areas the field of computer
                 science/computer engineering. We identify the core
                 statements that are more or less common to the majority
                 of the definitions, and based on this we give a
                 holistic definition using attributes for (cyber-)
                 resilience. In order to pave a way towards resilience
                 engineering, we discuss a theoretical model of the life
                 cycle of a (cyber-) resilient system that consists of
                 key actions presented in the literature. We adapt this
                 model for embedded (cyber-) resilient systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Matsumoto-Royo:2021:ODL,
  author =       "Kiomi Matsumoto-Royo and Maria Soledad
                 Ram{\'\i}rez-Montoya and Paulette Conget",
  title =        "Opportunities to Develop Lifelong Learning Tendencies
                 in Practice-Based Teacher Education: Getting Ready for
                 {Education 4.0}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "292",
  day =          "19",
  month =        nov,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110292",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/292",
  abstract =     "Education 4.0 prepares new generations to develop the
                 skills required to perform in a technological, dynamic,
                 and unpredictable world. The main barrier to
                 implementing Education 4.0 in schools is that teachers
                 have not been trained for it. Given the advances and
                 new resources of the technological field, teacher
                 preparation will be insufficient if it focuses on
                 technological skills but does not incorporate the
                 necessary dispositions for lifelong learning.
                 Universities have the ethical imperative to update
                 teacher education so teachers can become lifelong
                 learners. The objective of this study was to understand
                 whether practice-based curricula offer opportunities to
                 promote lifelong learning tendencies. We used a
                 sequential explanatory method. Quantitative and
                 qualitative instruments were applied to pre-service
                 teachers (survey: n = 231, semi-structured interviews:
                 n = 8), and causal and descriptive approaches were
                 supported by a structural equation model and constant
                 comparative method, respectively. Data triangulation
                 confirmed and added depth to the relationship found.
                 Practice opportunities provided by teacher educators in
                 learning activities and assessment tasks promote
                 curiosity, motivation, perseverance, and self-learning
                 regulation, when they are (i) systematic; (ii) relevant
                 to the classroom work; (iii) presented with clear
                 instructions and effective rubrics; (iv) accompanied
                 with feedback focused on the task, soliciting
                 reflection, and performed by peers and teacher
                 educators in a trustworthy environment. This research
                 may be of value to universities looking to renew their
                 Education 4.0 programs because it shows that
                 practice-based curricula not only transform pre-service
                 teachers into teaching experts but also into lifelong
                 learners.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Qu:2021:EFP,
  author =       "Qian Qu and Ronghua Xu and Yu Chen and Erik Blasch and
                 Alexander Aved",
  title =        "Enable Fair Proof-of-Work ({PoW}) Consensus for
                 Blockchains in {IoT} by {Miner Twins (MinT)}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "291",
  day =          "19",
  month =        nov,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110291",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/291",
  abstract =     "Blockchain technology has been recognized as a
                 promising solution to enhance the security and privacy
                 of Internet of Things (IoT) and Edge Computing
                 scenarios. Taking advantage of the Proof-of-Work (PoW)
                 consensus protocol, which solves a computation
                 intensive hashing puzzle, Blockchain ensures the
                 security of the system by establishing a digital
                 ledger. However, the computation intensive PoW favors
                 members possessing more computing power. In the IoT
                 paradigm, fairness in the highly heterogeneous network
                 edge environments must consider devices with various
                 constraints on computation power. Inspired by the
                 advanced features of Digital Twins (DT), an emerging
                 concept that mirrors the lifespan and operational
                 characteristics of physical objects, we propose a novel
                 Miner Twins (MinT) architecture to enable a fair PoW
                 consensus mechanism for blockchains in IoT
                 environments. MinT adopts an edge-fog-cloud hierarchy.
                 All physical miners of the blockchain are deployed as
                 microservices on distributed edge devices, while
                 fog/cloud servers maintain digital twins that
                 periodically update miners' running status. By timely
                 monitoring of a miner's footprint that is mirrored by
                 twins, a lightweight Singular Spectrum Analysis
                 (SSA)-based detection achieves the identification of
                 individual misbehaved miners that violate fair mining.
                 Moreover, we also design a novel Proof-of-Behavior
                 (PoB) consensus algorithm to detect dishonest miners
                 that collude to control a fair mining network. A
                 preliminary study is conducted on a proof-of-concept
                 prototype implementation, and experimental evaluation
                 shows the feasibility and effectiveness of the proposed
                 MinT scheme under a distributed byzantine network
                 environment.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mei:2021:MMF,
  author =       "Jing Mei and Huahu Xu and Yang Li and Minjie Bian and
                 Yuzhe Huang",
  title =        "{MFCNet}: Mining Features Context Network for {RGB-IR}
                 Person Re-Identification",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "290",
  day =          "18",
  month =        nov,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110290",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/290",
  abstract =     "RGB-IR cross modality person re-identification (RGB-IR
                 Re-ID) is an important task for video surveillance in
                 poorly illuminated or dark environments. In addition to
                 the common challenge of Re-ID, the large cross-modality
                 variations between RGB and IR images must be
                 considered. The existing RGB-IR Re-ID methods use
                 different network structures to learn the global shared
                 features associated with multi-modalities. However,
                 most global shared feature learning methods are
                 sensitive to background clutter, and contextual feature
                 relationships are not considered among the mined
                 features. To solve these problems, this paper proposes
                 a dual-path attention network architecture MFCNet. SGA
                 (Spatial-Global Attention) module embedded in MFCNet
                 includes spatial attention and global attention
                 branches to mine discriminative features. First, the
                 SGA module proposed in this paper focuses on the key
                 parts of the input image to obtain robust features.
                 Next, the module mines the contextual relationships
                 among features to obtain discriminative features and
                 improve network performance. Finally, extensive
                 experiments demonstrate that the performance of the
                 network architecture proposed in this paper is better
                 than that of state-of-the-art methods under various
                 settings. In the all-search mode of the SYSU and RegDB
                 data sets, the rank-1 accuracy reaches 51.64\% and
                 69.76\%, respectively.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chen:2021:PRIb,
  author =       "Xingyuan Chen and Huahu Xu and Yang Li and Minjie
                 Bian",
  title =        "Person Re-Identification by Low-Dimensional Features
                 and Metric Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "289",
  day =          "18",
  month =        nov,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110289",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/289",
  abstract =     "Person re-identification (Re-ID) has attracted
                 attention due to its wide range of applications. Most
                 recent studies have focused on the extraction of deep
                 features, while ignoring color features that can remain
                 stable, even for illumination variations and the
                 variation in person pose. There are also few studies
                 that combine the powerful learning capabilities of deep
                 learning with color features. Therefore, we hope to use
                 the advantages of both to design a model with low
                 computational resource consumption and excellent
                 performance to solve the task of person
                 re-identification. In this paper, we designed a color
                 feature containing relative spatial information, namely
                 the color feature with spatial information. Then,
                 bidirectional long short-term memory (BLSTM) networks
                 with an attention mechanism are used to obtain the
                 contextual relationship contained in the hand-crafted
                 color features. Finally, experiments demonstrate that
                 the proposed model can improve the recognition
                 performance compared with traditional methods. At the
                 same time, hand-crafted features based on human prior
                 knowledge not only reduce computational consumption
                 compared with deep learning methods but also make the
                 model more interpretable.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fan:2021:DIA,
  author =       "Li Fan and Wei Li and Xiaohui Cui",
  title =        "Deepfake-Image Anti-Forensics with Adversarial
                 Examples Attacks",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "288",
  day =          "17",
  month =        nov,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110288",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/288",
  abstract =     "Many deepfake-image forensic detectors have been
                 proposed and improved due to the development of
                 synthetic techniques. However, recent studies show that
                 most of these detectors are not immune to adversarial
                 example attacks. Therefore, understanding the impact of
                 adversarial examples on their performance is an
                 important step towards improving deepfake-image
                 detectors. This study developed an anti-forensics case
                 study of two popular general deepfake detectors based
                 on their accuracy and generalization. Herein, we
                 propose the Poisson noise DeepFool (PNDF), an improved
                 iterative adversarial examples generation method. This
                 method can simply and effectively attack forensics
                 detectors by adding perturbations to images in
                 different directions. Our attacks can reduce its AUC
                 from 0.9999 to 0.0331, and the detection accuracy of
                 deepfake images from 0.9997 to 0.0731. Compared with
                 state-of-the-art studies, our work provides an
                 important defense direction for future research on
                 deepfake-image detectors, by focusing on the
                 generalization performance of detectors and their
                 resistance to adversarial example attacks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hota:2021:ACM,
  author =       "Lopamudra Hota and Biraja Prasad Nayak and Arun Kumar
                 and G. G. Md. Nawaz Ali and Peter Han Joo Chong",
  title =        "An Analysis on Contemporary {MAC} Layer Protocols in
                 Vehicular Networks: State-of-the-Art and Future
                 Directions",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "287",
  day =          "17",
  month =        nov,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110287",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/287",
  abstract =     "Traffic density around the globe is increasing on a
                 day-to-day basis, resulting in more accidents,
                 congestion, and pollution. The dynamic vehicular
                 environment induces challenges in designing an
                 efficient and reliable protocol for communication.
                 Timely delivery of safety and non-safety messages is
                 necessary for traffic congestion control and for
                 avoiding road mishaps. For efficient resource sharing
                 and optimized channel utilization, the media access
                 control (MAC) protocol plays a vital role. An efficient
                 MAC protocol design can provide fair channel access and
                 can delay constraint safety message dissemination,
                 improving road safety. This paper reviews the
                 applications, characteristics, and challenges faced in
                 the design of MAC protocols. A classification of the
                 MAC protocol is presented based on contention
                 mechanisms and channel access. The classification based
                 on contention is oriented as contention-based,
                 contention-free, and hybrid, whereas the classification
                 based on channel access is categorized as distributed,
                 centralized, cluster-based, cooperative, token-based,
                 and random access. These are further sub-classified as
                 single-channel and multi-channel, based on the type of
                 channel resources they utilize. This paper gives an
                 analysis of the objectives, mechanisms,
                 advantages/disadvantages, and simulators used in
                 specified protocols. Finally, the paper concludes with
                 a discussion on the future scope and open challenges
                 for improving the MAC protocol design.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Guazzini:2021:WWW,
  author =       "Andrea Guazzini and Maria Fiorenza and Gabriele
                 Panerai and Mirko Duradoni",
  title =        "What Went Wrong? {Predictors} of Contact Tracing
                 Adoption in {Italy} during {COVID-19} Pandemic",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "286",
  day =          "15",
  month =        nov,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110286",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/286",
  abstract =     "Together with vaccines, contact tracing systems (CTS)
                 have proved to be one of the best strategies to deal
                 with the current COVID-19 pandemic. However, the
                 adoption of such systems has been quite limited in EU
                 countries, and Italy was no exception. The present
                 research aimed to investigate the factors drawn from
                 the most relevant psychological models in the
                 literature, most associated with the adoption of CTS.
                 The data analysis of the 501 surveyed answers (329 from
                 CTS adopters) showed that knowing important others who
                 have downloaded the CTS, CTS attitudes, CTS perceived
                 efficacy, COVID-19 risk perception, and trust in the
                 government and its actions influenced the adoption of
                 the Italian CTS (52\% of explained variance). These
                 factors defined a new specific model that can be used
                 to more effectively promote CTS adoption and thus
                 increase the protective potential of these
                 technologies, whose effectiveness is inevitably linked
                 to adoption.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Akbar:2021:DHD,
  author =       "Nur Arifin Akbar and Amgad Muneer and Narmine ElHakim
                 and Suliman Mohamed Fati",
  title =        "Distributed Hybrid Double-Spending Attack Prevention
                 Mechanism for Proof-of-Work and Proof-of-Stake
                 Blockchain Consensuses",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "285",
  day =          "12",
  month =        nov,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110285",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/285",
  abstract =     "Blockchain technology is a sustainable technology that
                 offers a high level of security for many industrial
                 applications. Blockchain has numerous benefits, such as
                 decentralisation, immutability and tamper-proofing.
                 Blockchain is composed of two processes, namely, mining
                 (the process of adding a new block or transaction to
                 the global public ledger created by the previous block)
                 and validation (the process of validating the new block
                 added). Several consensus protocols have been
                 introduced to validate blockchain transactions,
                 Proof-of-Work (PoW) and Proof-of-Stake (PoS), which are
                 crucial to cryptocurrencies, such as Bitcoin. However,
                 these consensus protocols are vulnerable to
                 double-spending attacks. Amongst these attacks, the
                 51\% attack is the most prominent because it involves
                 forking a blockchain to conduct double spending. Many
                 attempts have been made to solve this issue, and
                 examples include delayed proof-of-work (PoW) and
                 several Byzantine fault tolerance mechanisms. These
                 attempts, however, suffer from delay issues and
                 unsorted block sequences. This study proposes a hybrid
                 algorithm that combines PoS and PoW mechanisms to
                 provide a fair mining reward to the miner/validator by
                 conducting forking to combine PoW and PoS consensuses.
                 As demonstrated by the experimental results, the
                 proposed algorithm can reduce the possibility of
                 intruders performing double mining because it requires
                 achieving 100\% dominance in the network, which is
                 impossible.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhu:2021:IPR,
  author =       "Qigang Zhu and Yifan Liu and Ming Liu and Shuaishuai
                 Zhang and Guangyang Chen and Hao Meng",
  title =        "Intelligent Planning and Research on Urban Traffic
                 Congestion",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "284",
  day =          "08",
  month =        nov,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110284",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/284",
  abstract =     "For large and medium-sized cities, the planning and
                 development of urban road networks may not keep pace
                 with the growth of urban vehicles, resulting in traffic
                 congestion on urban roads during peak hours. Take
                 Jinan, a mid-sized city in China's Shandong Province,
                 for example. In view of the daily traffic jam of the
                 city's road traffic, through investigation and
                 analysis, the existing problems of the road traffic are
                 found out. Based on real-time, daily road traffic data,
                 combined with the existing road network and the planned
                 road network, the application of a road intelligent
                 transportation system is proposed. Combined with the
                 application of a road intelligent transportation
                 system, this paper discusses the future development of
                 urban road traffic and puts forward improvement
                 suggestions for road traffic planning. This paper has
                 reference value for city development, road network
                 construction, the application of intelligent
                 transportation systems, and road traffic planning.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alicea:2021:MFN,
  author =       "Michael Alicea and Izzat Alsmadi",
  title =        "Misconfiguration in Firewalls and Network Access
                 Controls: Literature Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "283",
  day =          "08",
  month =        nov,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110283",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/283",
  abstract =     "Firewalls and network access controls play important
                 roles in security control and protection. Those
                 firewalls may create an incorrect sense or state of
                 protection if they are improperly configured. One of
                 the major configuration problems in firewalls is
                 related to misconfiguration in the access control roles
                 added to the firewall that will control network
                 traffic. In this paper, we evaluated recent research
                 trends and open challenges related to firewalls and
                 access controls in general and misconfiguration
                 problems in particular. With the recent advances in
                 next-generation (NG) firewalls, firewall roles can be
                 auto-generated based on networks and threats.
                 Nonetheless, and due to the large number of roles in
                 any medium to large networks, roles' misconfiguration
                 may occur for several reasons and will impact the
                 performance of the firewall and overall network and
                 protection efficiency.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gonzalez-Perez:2021:IIR,
  author =       "Laura Icela Gonz{\'a}lez-P{\'e}rez and Mar{\'\i}a
                 Soledad Ram{\'\i}rez-Montoya and Francisco Jos{\'e}
                 Garc{\'\i}a-Pe{\~n}alvo",
  title =        "Improving Institutional Repositories through
                 User-Centered Design: Indicators from a Focus Group",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "282",
  day =          "02",
  month =        nov,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110282",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/282",
  abstract =     "User experience with intuitive and flexible digital
                 platforms can be enjoyable and satisfying. A strategy
                 to deliver such an experience is to place the users at
                 the center of the design process and analyze their
                 beliefs and perceptions to add appropriate platform
                 features. This study conducted with focus groups as a
                 qualitative method of data collection to investigate
                 users' preferences and develop a new landing page for
                 institutional repositories with attractive
                 functionalities based on their information-structural
                 rules. The research question was: What are the
                 motivations and experiences of users in an academic
                 community when publishing scientific information in an
                 institutional repository? The focus group technique
                 used in this study had three sessions. Results showed
                 that 50\% of the participants did not know the
                 functionalities of the institutional repository nor its
                 benefits. Users' perceptions of platforms such as
                 ResearchGate or Google Scholar that provide academic
                 production were also identified. The findings showed
                 that motivating an academic community to use an
                 institutional repository requires technological
                 functions, user guidelines that identify what can or
                 cannot be published in open access, and training
                 programs for open access publication practices and
                 institutional repository use. These measures align with
                 global strategies to strengthen the digital identities
                 of scientific communities and thus benefit open
                 science.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Suttle:2021:UCM,
  author =       "Ryan Suttle and Scott Hogan and Rachel Aumaugher and
                 Matthew Spradling and Zak Merrigan and Jeremy Straub",
  title =        "University Community Members' Perceptions of Labels
                 for Online Media",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "281",
  day =          "31",
  month =        oct,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110281",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/281",
  abstract =     "Fake news is prevalent in society. A variety of
                 methods have been used in an attempt to mitigate the
                 spread of misinformation and fake news ranging from
                 using machine learning to detect fake news to paying
                 fact checkers to manually fact check media to ensure
                 its accuracy. In this paper, three studies were
                 conducted at two universities with different regional
                 demographic characteristics to gain a better
                 understanding of respondents' perception of online
                 media labeling techniques. The first study deals with
                 what fields should appear on a media label. The second
                 study looks into what types of informative labels
                 respondents would use. The third focuses on blocking
                 type labels. Participants' perceptions, preferences,
                 and results are analyzed by their demographic
                 characteristics.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Miranda:2021:CHC,
  author =       "Pedro R. Miranda and Daniel Pestana and Jo{\~a}o D.
                 Lopes and Rui Policarpo Duarte and M{\'a}rio P.
                 V{\'e}stias and Hor{\'a}cio C. Neto and Jos{\'e} T. de
                 Sousa",
  title =        "Configurable Hardware Core for {IoT} Object
                 Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "280",
  day =          "30",
  month =        oct,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110280",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/280",
  abstract =     "Object detection is an important task for many
                 applications, like transportation, security, and
                 medical applications. Many of these applications are
                 needed on edge devices to make local decisions.
                 Therefore, it is necessary to provide low-cost, fast
                 solutions for object detection. This work proposes a
                 configurable hardware core on a field-programmable gate
                 array (FPGA) for object detection. The configurability
                 of the core allows its deployment on target devices
                 with diverse hardware resources. The object detection
                 accelerator is based on YOLO, for its good accuracy at
                 moderate computational complexity. The solution was
                 applied to the design of a core to accelerate the
                 Tiny-YOLOv3, based on a CNN developed for constrained
                 environments. However, it can be applied to other YOLO
                 versions. The core was integrated into a full
                 system-on-chip solution and tested with the COCO
                 dataset. It achieved a performance from 7 to 14 FPS in
                 a low-cost ZYNQ7020 FPGA, depending on the
                 quantization, with an accuracy reduction from 2.1 to
                 1.4 points of mAP50 mAP50 mAP50.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Satar:2021:TVC,
  author =       "Siti Dhalila Mohd Satar and Masnida Hussin and Zurina
                 Mohd Hanapi and Mohamad Afendee Mohamed",
  title =        "Towards Virtuous Cloud Data Storage Using Access
                 Policy Hiding in Ciphertext Policy Attribute-Based
                 Encryption",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "279",
  day =          "30",
  month =        oct,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110279",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/279",
  abstract =     "Managing and controlling access to the tremendous data
                 in Cloud storage is very challenging. Due to various
                 entities engaged in the Cloud environment, there is a
                 high possibility of data tampering. Cloud encryption is
                 being employed to control data access while securing
                 Cloud data. The encrypted data are sent to Cloud
                 storage with an access policy defined by the data
                 owner. Only authorized users can decrypt the encrypted
                 data. However, the access policy of the encrypted data
                 is in readable form, which results in privacy leakage.
                 To address this issue, we proposed a reinforcement
                 hiding in access policy over Cloud storage by enhancing
                 the Ciphertext Policy Attribute-based Encryption
                 (CP-ABE) algorithm. Besides the encryption process, the
                 reinforced CP-ABE used logical connective operations to
                 hide the attribute value of data in the access policy.
                 These attributes were converted into scrambled data
                 along with a ciphertext form that provides a better
                 unreadability feature. It means that a two-level
                 concealed tactic is employed to secure data from any
                 unauthorized access during a data transaction.
                 Experimental results revealed that our reinforced
                 CP-ABE had a low computational overhead and consumed
                 low storage costs. Furthermore, a case study on
                 security analysis shows that our approach is secure
                 against a passive attack such as traffic analysis.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Moreno:2021:OSF,
  author =       "Jes{\'u}s Fernando Cevallos Moreno and Rebecca Sattler
                 and Ra{\'u}l P. Caulier Cisterna and Lorenzo Ricciardi
                 Celsi and Aminael S{\'a}nchez Rodr{\'\i}guez and
                 Massimo Mecella",
  title =        "Online Service Function Chain Deployment for
                 Live-Streaming in Virtualized Content Delivery
                 Networks: a Deep Reinforcement Learning Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "278",
  day =          "29",
  month =        oct,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110278",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/278",
  abstract =     "Video delivery is exploiting 5G networks to enable
                 higher server consolidation and deployment flexibility.
                 Performance optimization is also a key target in such
                 network systems. We present a multi-objective
                 optimization framework for service function chain
                 deployment in the particular context of Live-Streaming
                 in virtualized content delivery networks using deep
                 reinforcement learning. We use an Enhanced Exploration,
                 Dense-reward mechanism over a Dueling Double Deep Q
                 Network (E2-D4QN). Our model assumes to use network
                 function virtualization at the container level. We
                 carefully model processing times as a function of
                 current resource utilization in data ingestion and
                 streaming processes. We assess the performance of our
                 algorithm under bounded network resource conditions to
                 build a safe exploration strategy that enables the
                 market entry of new bounded-budget vCDN players.
                 Trace-driven simulations with real-world data reveal
                 that our approach is the only one to adapt to the
                 complexity of the particular context of Live-Video
                 delivery concerning the state-of-art algorithms
                 designed for general-case service function chain
                 deployment. In particular, our simulation test revealed
                 a substantial QoS/QoE performance improvement in terms
                 of session acceptance ratio against the compared
                 algorithms while keeping operational costs within
                 proper bounds.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Faraj:2021:RVC,
  author =       "Ghazal Faraj and Andr{\'a}s Micsik",
  title =        "Representing and Validating Cultural Heritage
                 Knowledge Graphs in {CIDOC-CRM} Ontology",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "277",
  day =          "29",
  month =        oct,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110277",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/277",
  abstract =     "In order to unify access to multiple heterogeneous
                 sources of cultural heritage data, many datasets were
                 mapped to the CIDOC-CRM ontology. CIDOC-CRM provides a
                 formal structure and definitions for most cultural
                 heritage concepts and their relationships. The COURAGE
                 project includes historic data concerning people,
                 organizations, cultural heritage collections, and
                 collection items covering the period between 1950 and
                 1990. Therefore, CIDOC-CRM seemed the optimal choice
                 for describing COURAGE entities, improving knowledge
                 sharing, and facilitating the COURAGE dataset
                 unification with other datasets. This paper introduces
                 the results of translating the COURAGE dataset to
                 CIDOC-CRM semantically. This mapping was implemented
                 automatically according to predefined mapping rules.
                 Several SPARQL queries were applied to validate the
                 migration process manually. In addition, multiple SHACL
                 shapes were conducted to validate the data and mapping
                 models.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hamada:2021:SCL,
  author =       "Louiza Hamada and Pascal Lorenz and Marc Gilg",
  title =        "Security Challenges for Light Emitting Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "276",
  day =          "28",
  month =        oct,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110276",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/276",
  abstract =     "Although visible light communication (VLC) channels
                 are more secure than radio frequency channels, the
                 broadcast nature of VLC links renders them open to
                 eavesdropping. As a result, VLC networks must provide
                 security in order to safeguard the user's data from
                 eavesdroppers. In the literature, keyless security
                 techniques have been developed to offer security for
                 VLC. Even though these techniques provide strong
                 security against eavesdroppers, they are difficult to
                 deploy. Key generation algorithms are critical for
                 securing wireless connections. Nonetheless, in many
                 situations, the typical key generation methods may be
                 quite complicated and costly. They consume scarce
                 resources, such as bandwidth. In this paper, we propose
                 a novel key extraction procedure that uses
                 error-correcting coding and one time pad (OTP) to
                 improve the security of VLC networks and the validity
                 of data. This system will not have any interference
                 problems with other devices. We also explain error
                 correction while sending a message across a network,
                 and suggest a change to the Berlekamp--Massey (BM)
                 algorithm for error identification and assessment.
                 Because each OOK signal frame is encrypted by a
                 different key, the proposed protocol provides high
                 physical layer security; it allows for key extraction
                 based on the messages sent, so an intruder can never
                 break the encryption system, even if the latter knows
                 the protocol with which we encrypted the message; our
                 protocol also enables for error transmission rate
                 correction and bit mismatch rates with on-the-fly key
                 fetch. The results presented in this paper were
                 performed using MATLAB.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Arca:2021:AAP,
  author =       "Sevgi Arca and Rattikorn Hewett",
  title =        "Analytics on Anonymity for Privacy Retention in Smart
                 Health Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "274",
  day =          "28",
  month =        oct,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110274",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/274",
  abstract =     "Advancements in smart technology, wearable and mobile
                 devices, and Internet of Things, have made smart health
                 an integral part of modern living to better individual
                 healthcare and well-being. By enhancing
                 self-monitoring, data collection and sharing among
                 users and service providers, smart health can increase
                 healthy lifestyles, timely treatments, and save lives.
                 However, as health data become larger and more
                 accessible to multiple parties, they become vulnerable
                 to privacy attacks. One way to safeguard privacy is to
                 increase users' anonymity as anonymity increases
                 indistinguishability making it harder for
                 re-identification. Still the challenge is not only to
                 preserve data privacy but also to ensure that the
                 shared data are sufficiently informative to be useful.
                 Our research studies health data analytics focusing on
                 anonymity for privacy protection. This paper presents a
                 multi-faceted analytical approach to (1) identifying
                 attributes susceptible to information leakages by using
                 entropy-based measure to analyze information loss, (2)
                 anonymizing the data by generalization using attribute
                 hierarchies, and (3) balancing between anonymity and
                 informativeness by our anonymization technique that
                 produces anonymized data satisfying a given anonymity
                 requirement while optimizing data retention. Our
                 anonymization technique is an automated Artificial
                 Intelligent search based on two simple heuristics. The
                 paper describes and illustrates the detailed approach
                 and analytics including pre and post anonymization
                 analytics. Experiments on published data are performed
                 on the anonymization technique. Results, compared with
                 other similar techniques, show that our anonymization
                 technique gives the most effective data sharing
                 solution, with respect to computational cost and
                 balancing between anonymity and data retention.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yimam:2021:IVS,
  author =       "Seid Muhie Yimam and Abinew Ali Ayele and
                 Gopalakrishnan Venkatesh and Ibrahim Gashaw and Chris
                 Biemann",
  title =        "Introducing Various Semantic Models for {Amharic}:
                 Experimentation and Evaluation with Multiple Tasks and
                 Datasets",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "275",
  day =          "27",
  month =        oct,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110275",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/275",
  abstract =     "The availability of different pre-trained semantic
                 models has enabled the quick development of machine
                 learning components for downstream applications.
                 However, even if texts are abundant for low-resource
                 languages, there are very few semantic models publicly
                 available. Most of the publicly available pre-trained
                 models are usually built as a multilingual version of
                 semantic models that will not fit well with the need
                 for low-resource languages. We introduce different
                 semantic models for Amharic, a morphologically complex
                 Ethio-Semitic language. After we investigate the
                 publicly available pre-trained semantic models, we
                 fine-tune two pre-trained models and train seven new
                 different models. The models include Word2Vec
                 embeddings, distributional thesaurus (DT), BERT-like
                 contextual embeddings, and DT embeddings obtained via
                 network embedding algorithms. Moreover, we employ these
                 models for different NLP tasks and study their impact.
                 We find that newly-trained models perform better than
                 pre-trained multilingual models. Furthermore, models
                 based on contextual embeddings from FLAIR and RoBERTa
                 perform better than word2Vec models for the NER and POS
                 tagging tasks. DT-based network embeddings are suitable
                 for the sentiment classification task. We publicly
                 release all the semantic models, machine learning
                 components, and several benchmark datasets such as NER,
                 POS tagging, sentiment classification, as well as
                 Amharic versions of WordSim353 and SimLex999.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Qasaimeh:2021:SDE,
  author =       "Malik Qasaimeh and Raad S. Al-Qassas and Mohammad
                 Ababneh",
  title =        "Software Design and Experimental Evaluation of a
                 Reduced {AES} for {IoT} Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "273",
  day =          "27",
  month =        oct,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110273",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/273",
  abstract =     "IoT devices include RFID tags, microprocessors,
                 sensors, readers, and actuators. Their main
                 characteristics are their limited resources and
                 computing capabilities, which pose critical challenges
                 to the reliability and security of their applications.
                 Encryption is necessary for security when using these
                 limited-resource devices, but conventional
                 cryptographic algorithms are too heavyweight and
                 resource-demanding to run on IoT infrastructures. This
                 paper presents a lightweight version of AES (called
                 LAES), which provides competitive results in terms of
                 randomness levels and processing time, operating on
                 GF(2 4 ). Detailed mathematical operations and proofs
                 are presented concerning LAES rounds design
                 fundamentals. The proposed LAES algorithm is evaluated
                 based on its randomness, performance, and power
                 consumption; it is then compared to other cryptographic
                 algorithm variants, namely Present, Clefia, and AES.
                 The design of the randomness and performance analysis
                 is based on six measures developed with the help of the
                 NIST test statistical suite of cryptographic
                 applications. The performance and power consumption of
                 LAES on a low-power, 8-bit microcontroller unit were
                 evaluated using an Arduino Uno board. LAES was found to
                 have competitive randomness levels, processing times,
                 and power consumption compared to Present, Clefia, and
                 AES.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Shalaginov:2021:SRC,
  author =       "Andrii Shalaginov and Muhammad Ajmal Azad",
  title =        "Securing Resource-Constrained {IoT} Nodes: Towards
                 Intelligent Microcontroller-Based Attack Detection in
                 Distributed Smart Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "272",
  day =          "27",
  month =        oct,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110272",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/272",
  abstract =     "In recent years, the Internet of Things (IoT) devices
                 have become an inseparable part of our lives. With the
                 growing demand for Smart Applications, it becomes clear
                 that IoT will bring regular automation and intelligent
                 sensing to a new level thus improving quality of life.
                 The core component of the IoT ecosystem is data which
                 exists in various forms and formats. The collected data
                 is then later used to create context awareness and make
                 meaningful decisions. Besides an undoubtedly large
                 number of advantages from the usage of IoT, there exist
                 numerous challenges attributed to the security of
                 objects that cannot be neglected for uninterrupted
                 services. The Mirai botnet attack demonstrated that the
                 IoT system is susceptible to different forms of
                 cyberattacks. While advanced data analytics and Machine
                 Learning have proved efficiency in various applications
                 of cybersecurity, those still have not been explored
                 enough in the literature from the applicability
                 perspective in the domain of resource-constrained IoT.
                 Several architectures and frameworks have been proposed
                 for defining the ways for analyzing the data, yet
                 mostly investigating off-chip analysis. In this
                 contribution, we show how an Artificial Neural Network
                 model can be trained and deployed on trivial IoT nodes
                 for detecting intelligent similarity-based network
                 attacks. This article proposes a concept of the
                 resource-constrained intelligent system as a part of
                 the IoT infrastructure to be able to harden the
                 cybersecurity on microcontrollers. This work will serve
                 as a stepping stone for the application of Artificial
                 Intelligence on devices with limited computing
                 capabilities such as end-point IoT nodes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Veloso:2021:HHC,
  author =       "Artur Felipe da Silva Veloso and Jos{\'e} Valdemir
                 Reis J{\'u}nior and Ricardo de Andrade Lira Rabelo and
                 Jocines Dela-flora Silveira",
  title =        "{HyDSMaaS}: a Hybrid Communication Infrastructure with
                 {LoRaWAN} and {LoraMesh} for the Demand Side Management
                 as a Service",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "271",
  day =          "26",
  month =        oct,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110271",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/271",
  abstract =     "Seeking to solve problems in the power electric system
                 (PES) related to exacerbated and uncontrolled energy
                 consumption by final consumers such as residences,
                 condominiums, public buildings and industries, electric
                 power companies (EPC) are increasingly seeking new
                 information and communication technologies (ICTs) to
                 transform traditional electric power distribution
                 networks into smart grids (SG). With this
                 implementation, PES will be able to remotely control
                 electric power consumption as well as monitor data
                 generated by smart meters (SM). However,
                 Internet-of-Things (IoT) technologies will enable all
                 this to happen quickly and at low cost, since they are
                 low-cost devices that can be deployed quickly and at
                 scale in these scenarios. With this in mind, this work
                 aimed to study, propose, and implement a hybrid
                 communication infrastructure with LoRaWAN and LoraMesh
                 for the demand-side management as a service (HyDSMaaS)
                 using IoT devices such as long range (LoRa) to provide
                 an advanced metering infrastructure (AMI) capable of
                 performing all these applications as a service offered
                 by EPC to end consumers. Additionally, services such as
                 demand-side management (DSMaaS) can be used in this
                 infrastructure. From the preliminary results it was
                 found that the LoRaWAN network achieved a range of up
                 to 2.35 km distance and the LoRaMESH one of 600 m;
                 thus, the latter is more suitable for scenarios where
                 there is little interference and the SMs are at long
                 distances, while the other is used for scenarios with
                 greater agglomeration of nearby SMs. Considering the
                 hybridized scenario between LoraWAN and LoRaMESH, it
                 can be seen that the implementation possibilities
                 increase, since its range was approximately 3 km
                 considering only one hop, and it can reach 1023 devices
                 present in a mesh network. Thus, it was possible to
                 propose the actual implementation of LoRaWAN and
                 LoRaMESH protocols as well as the hybridization of the
                 two protocols for HyDSMaaS. Additionally, the results
                 obtained are exclusively from Radioenge's LoRa
                 technology, which can be further improved in the case
                 of using more powerful equipment.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Simoes:2021:DAS,
  author =       "Rhodney Sim{\~o}es and Kelvin Dias and Ricardo
                 Martins",
  title =        "Dynamic Allocation of {SDN} Controllers in {NFV}-Based
                 {MEC} for the {Internet of Vehicles}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "270",
  day =          "26",
  month =        oct,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110270",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/270",
  abstract =     "The expected huge amount of connected cars and
                 applications with varying Quality of Service (QoS)
                 demands still depend on agile/flexible networking
                 infrastructure to deal with dynamic service requests to
                 the control plane, which may become a bottleneck for 5G
                 and Beyond Software-Defined Network (SDN) based
                 Internet of Vehicles (IoV). At the heart of this issue
                 is the need for an architecture and optimization
                 mechanisms that benefit from cutting edge technologies
                 while granting latency bounds in order to control and
                 manage the dynamic nature of IoV. To this end, this
                 article proposes an autonomic software-defined
                 vehicular architecture grounded on the synergy of
                 Multi-access Edge Computing (MEC) and Network Functions
                 Virtualization (NFV) along with a heuristic approach
                 and an exact model based on linear programming to
                 efficiently optimize the dynamic resource allocation of
                 SDN controllers, ensuring load balancing between
                 controllers and employing reserve resources for
                 tolerance in case of demand variation. The analyses
                 carried out in this article consider: (a) to avoid
                 waste of limited MEC resources, (b) to devise load
                 balancing among controllers, (c) management complexity,
                 and (d) to support scalability in dense IoV scenarios.
                 The results show that the heuristic efficiently manages
                 the environment even in highly dynamic and dense
                 scenarios.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Murugappan:2021:CIP,
  author =       "Manickam Murugappan and John Victor Joshua Thomas and
                 Ugo Fiore and Yesudas Bevish Jinila and Subhashini
                 Radhakrishnan",
  title =        "{COVIDNet}: Implementing Parallel Architecture on
                 Sound and Image for High Efficacy",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "269",
  day =          "26",
  month =        oct,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110269",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/269",
  abstract =     "The present work relates to the implementation of core
                 parallel architecture in a deep learning algorithm. At
                 present, deep learning technology forms the main
                 interdisciplinary basis of healthcare, hospital
                 hygiene, biological and medicine. This work establishes
                 a baseline range by training hyperparameter space,
                 which could be support images, and sound with further
                 develop a parallel architectural model using multiple
                 inputs with and without the patient's involvement. The
                 chest X-ray images input could form the model
                 architecture include variables for the number of nodes
                 in each layer and dropout rate. Fourier transformation
                 Mel-spectrogram images with the correct pixel range use
                 to covert sound acceptance at the convolutional neural
                 network in embarrassingly parallel sequences. COVIDNet
                 the end user tool has to input a chest X-ray image and
                 a cough audio file which could be a natural cough or a
                 forced cough. Three binary classification models
                 (COVID-19 CXR, non-COVID-19 CXR, COVID-19 cough) were
                 trained. The COVID-19 CXR model classifies between
                 healthy lungs and the COVID-19 model meanwhile the
                 non-COVID-19 CXR model classifies between non-COVID-19
                 pneumonia and healthy lungs. The COVID-19 CXR model has
                 an accuracy of 95\% which was trained using 1681
                 COVID-19 positive images and 10,895 healthy lungs
                 images, meanwhile, the non-COVID-19 CXR model has an
                 accuracy of 91\% which was trained using 7478
                 non-COVID-19 pneumonia positive images and 10,895
                 healthy lungs. The reason why all the models are binary
                 classification is due to the lack of available data
                 since medical image datasets are usually highly
                 imbalanced and the cost of obtaining them are very
                 pricey and time-consuming. Therefore, data augmentation
                 was performed on the medical images datasets that were
                 used. Effects of parallel architecture and optimization
                 to improve on design were investigated.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Oikonomidis:2021:MAR,
  author =       "Theodoros Oikonomidis and Konstantinos Fouskas and
                 Maro Vlachopoulou",
  title =        "A Multidimensional Analysis of Released {COVID-19}
                 Location-Based Mobile Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "268",
  day =          "25",
  month =        oct,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110268",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/268",
  abstract =     "The spread of coronavirus disease (COVID-19) has
                 triggered a series of responses worldwide ranging from
                 traveling restrictions and shelter-in-place orders to
                 lockdowns, contact tracing, social distancing, and
                 other mitigation measures. To assist with contact
                 tracing and ensure the safety of citizens, a
                 significant number of mobile applications has been
                 developed, utilizing geospatial information and
                 proximity sensing. We perform a thorough research on
                 seven digital databases (Appbrain, e-Health Hub,
                 GDPRhub, ``fs0c131y'', News Sites, Appstore, and Google
                 Play), identifying a total of 160 apps regarding
                 COVID-19 related to our research questions. The aim of
                 this research is to identify the main categories of
                 apps and analyze their functions based on a proposed
                 framework of by mapping aspects that affect their
                 functionalities regarding Services, Technology,
                 Societal \& Business, and Legal aspects. As the world
                 comes to the new normal, the utilization of these apps
                 might become more essential for more mobile users and
                 developers. The new encryption protocols that are
                 established are also in favor of this argument. Future
                 work can utilize our framework to further examine the
                 development, design, and adoption of such mobile
                 applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Peng:2021:RDB,
  author =       "Yun Peng and Jianmei Wang",
  title =        "Rumor Detection Based on Attention {CNN} and Time
                 Series of Context Information",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "11",
  pages =        "267",
  day =          "25",
  month =        oct,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13110267",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:13 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/11/267",
  abstract =     "This study aims to explore the time series context and
                 sentiment polarity features of rumors' life cycles, and
                 how to use them to optimize the CNN model parameters
                 and improve the classification effect. The proposed
                 model is a convolutional neural network embedded with
                 an attention mechanism of sentiment polarity and time
                 series information. Firstly, the whole life cycle of
                 rumors is divided into 20 groups by the time series
                 algorithm and each group of texts is trained by Doc2Vec
                 to obtain the text vector. Secondly, the SVM algorithm
                 is used to obtain the sentiment polarity features of
                 each group. Lastly, the CNN model with the spatial
                 attention mechanism is used to obtain the rumors'
                 classification. The experiment results show that the
                 proposed model introduced with features of time series
                 and sentiment polarity is very effective for rumor
                 detection, and can greatly reduce the number of
                 iterations for model training as well. The accuracy,
                 precision, recall and F1 of the attention CNN are
                 better than the latest benchmark model.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Baranov:2021:IEN,
  author =       "Dmitry Baranov and Alexandr Terekhin and Dmitry Bragin
                 and Anton Konev",
  title =        "Implementation and Evaluation of Nodal Distribution
                 and Movement in a {5G} Mobile Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "12",
  pages =        "321",
  day =          "20",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13120321",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:14 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/12/321",
  abstract =     "The determining factor in the accelerated pace of
                 informatization is the increase in the speed and
                 reliability of data transmission networks. In this
                 regard, new and existing standards are developed and
                 modernized. A lot of organizations are constantly
                 working on the development and implementation of new
                 generation communication networks. This article
                 provides an overview of available software solutions
                 that allow us to investigate and evaluate the behavior
                 of data networks. In particular, tools suitable for
                 mobile communication systems were determined, having
                 sufficient built-in functionality and allowing us to
                 add our own implementations. NS3 has been chosen as a
                 suitable network simulator. Apart from the review, a
                 solution for this tool was developed. It allows
                 estimating the reliability of data transmission from
                 the start movement of a network node at all times
                 during its removal from a base station.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Leiding:2021:MEM,
  author =       "Benjamin Leiding and Priyanka Sharma and Alexander
                 Norta",
  title =        "The Machine-to-Everything ({M2X}) Economy: Business
                 Enactments, Collaborations, and e-Governance",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "12",
  pages =        "319",
  day =          "19",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13120319",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:14 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/12/319",
  abstract =     "Nowadays, business enactments almost exclusively focus
                 on human-to-human business transactions. However, the
                 ubiquitousness of smart devices enables business
                 enactments among autonomously acting machines, thereby
                 providing the foundation for the machine-driven
                 Machine-to-Everything (M2X) Economy. Human-to-human
                 business is governed by enforceable contracts either in
                 the form of oral, or written agreements. Still, a
                 machine-driven ecosystem requires a digital equivalent
                 that is accessible to all stakeholders. Additionally,
                 an electronic contract platform enables fact-tracking,
                 non-repudiation, auditability and tamper-resistant
                 storage of information in a distributed
                 multi-stakeholder setting. A suitable approach for M2X
                 enactments are electronic smart contracts that allow to
                 govern business transactions using a computerized
                 transaction protocol such as a blockchain. In this
                 position paper, we argue in favor of an open,
                 decentralized and distributed smart contract-based M2X
                 Economy that supports the corresponding
                 multi-stakeholder ecosystem and facilitates M2X value
                 exchange, collaborations, and business enactments.
                 Finally, it allows for a distributed e-governance model
                 that fosters open platforms and interoperability. Thus,
                 serving as a foundation for the ubiquitous M2X Economy
                 and its ecosystem.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ibrahim:2021:FBC,
  author =       "Ahmed H. Ibrahim and Zaki T. Fayed and Hossam M.
                 Faheem",
  title =        "Fog-Based {CDN} Framework for Minimizing Latency of
                 {Web} Services Using Fog-Based {HTTP} Browser",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "12",
  pages =        "320",
  day =          "17",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13120320",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:14 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/12/320",
  abstract =     "Cloud computing has been a dominant computing paradigm
                 for many years. It provides applications with
                 computing, storage, and networking capabilities.
                 Furthermore, it enhances the scalability and quality of
                 service (QoS) of applications and offers the better
                 utilization of resources. Recently, these advantages of
                 cloud computing have deteriorated in quality. Cloud
                 services have been affected in terms of latency and QoS
                 due to the high streams of data produced by many
                 Internet of Things (IoT) devices, smart machines, and
                 other computing devices joining the network, which in
                 turn affects network capabilities. Content delivery
                 networks (CDNs) previously provided a partial solution
                 for content retrieval, availability, and resource
                 download time. CDNs rely on the geographic distribution
                 of cloud servers to provide better content
                 reachability. CDNs are perceived as a network layer
                 near cloud data centers. Recently, CDNs began to
                 perceive the same degradations of QoS due to the same
                 factors. Fog computing fills the gap between cloud
                 services and consumers by bringing cloud capabilities
                 close to end devices. Fog computing is perceived as
                 another network layer near end devices. The adoption of
                 the CDN model in fog computing is a promising approach
                 to providing better QoS and latency for cloud services.
                 Therefore, a fog-based CDN framework capable of
                 reducing the load time of web services was proposed in
                 this paper. To evaluate our proposed framework and
                 provide a complete set of tools for its use, a
                 fog-based browser was developed. We showed that our
                 proposed fog-based CDN framework improved the load time
                 of web pages compared to the results attained through
                 the use of the traditional CDN. Different experiments
                 were conducted with a simple network topology against
                 six websites with different content sizes along with a
                 different number of fog nodes at different network
                 distances. The results of these experiments show that
                 with a fog-based CDN framework offloading autonomy,
                 latency can be reduced by 85\% and enhance the user
                 experience of websites.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ahmad:2021:MVD,
  author =       "Rasheed Ahmad and Izzat Alsmadi and Wasim Alhamdani
                 and Lo'ai Tawalbeh",
  title =        "Models versus Datasets: Reducing Bias through Building
                 a Comprehensive {IDS} Benchmark",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "12",
  pages =        "318",
  day =          "17",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13120318",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:14 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/12/318",
  abstract =     "Today, deep learning approaches are widely used to
                 build Intrusion Detection Systems for securing IoT
                 environments. However, the models' hidden and complex
                 nature raises various concerns, such as trusting the
                 model output and understanding why the model made
                 certain decisions. Researchers generally publish their
                 proposed model's settings and performance results based
                 on a specific dataset and a classification model but do
                 not report the proposed model's output and findings.
                 Similarly, many researchers suggest an IDS solution by
                 focusing only on a single benchmark dataset and
                 classifier. Such solutions are prone to generating
                 inaccurate and biased results. This paper overcomes
                 these limitations in previous work by analyzing various
                 benchmark datasets and various individual and hybrid
                 deep learning classifiers towards finding the best IDS
                 solution for IoT that is efficient, lightweight, and
                 comprehensive in detecting network anomalies. We also
                 showed the model's localized predictions and analyzed
                 the top contributing features impacting the global
                 performance of deep learning models. This paper aims to
                 extract the aggregate knowledge from various datasets
                 and classifiers and analyze the commonalities to avoid
                 any possible bias in results and increase the trust and
                 transparency of deep learning models. We believe this
                 paper's findings will help future researchers build a
                 comprehensive IDS based on well-performing classifiers
                 and utilize the aggregated knowledge and the minimum
                 set of significantly contributing features.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Trihinas:2021:FTS,
  author =       "Demetris Trihinas and Michalis Agathocleous and Karlen
                 Avogian and Ioannis Katakis",
  title =        "{FlockAI}: a Testing Suite for {ML}-Driven Drone
                 Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "12",
  pages =        "317",
  day =          "16",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13120317",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:14 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/12/317",
  abstract =     "Machine Learning (ML) is now becoming a key driver
                 empowering the next generation of drone technology and
                 extending its reach to applications never envisioned
                 before. Examples include precision agriculture, crowd
                 detection, and even aerial supply transportation.
                 Testing drone projects before actual deployment is
                 usually performed via robotic simulators. However,
                 extending testing to include the assessment of on-board
                 ML algorithms is a daunting task. ML practitioners are
                 now required to dedicate vast amounts of time for the
                 development and configuration of the benchmarking
                 infrastructure through a mixture of use-cases coded
                 over the simulator to evaluate various key performance
                 indicators. These indicators extend well beyond the
                 accuracy of the ML algorithm and must capture
                 drone-relevant data including flight performance,
                 resource utilization, communication overhead and energy
                 consumption. As most ML practitioners are not
                 accustomed with all these demanding requirements, the
                 evaluation of ML-driven drone applications can lead to
                 sub-optimal, costly, and error-prone deployments. In
                 this article we introduce FlockAI, an open and modular
                 by design framework supporting ML practitioners with
                 the rapid deployment and repeatable testing of
                 ML-driven drone applications over the Webots simulator.
                 To show the wide applicability of rapid testing with
                 FlockAI, we introduce a proof-of-concept use-case
                 encompassing different scenarios, ML algorithms and
                 KPIs for pinpointing crowded areas in an urban
                 environment.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Eramo:2021:PIC,
  author =       "Vincenzo Eramo and Francesco Valente and Tiziana
                 Catena and Francesco Giacinto Lavacca",
  title =        "Proposal and Investigation of a Convolutional and
                 {LSTM} Neural Network for the Cost-Aware Resource
                 Prediction in Softwarized Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "12",
  pages =        "316",
  day =          "16",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13120316",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:14 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/12/316",
  abstract =     "Resource prediction algorithms have been recently
                 proposed in Network Function Virtualization
                 architectures. A prediction-based resource allocation
                 is characterized by higher operation costs due to: (i)
                 Resource underestimate that leads to quality of service
                 degradation; (ii) used cloud resource over allocation
                 when a resource overestimate occurs. To reduce such a
                 cost, we propose a cost-aware prediction algorithm able
                 to minimize the sum of the two cost components. The
                 proposed prediction solution is based on a
                 convolutional and Long Short Term Memory neural network
                 to handle the spatial and temporal correlations of the
                 need processing capacities. We compare in a real
                 network and traffic scenario the proposed technique to
                 a traditional one in which the aim is to exactly
                 predict the needed processing capacity. We show how the
                 proposed solution allows for cost advantages in the
                 order of 20\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Shilov:2021:RHF,
  author =       "Lev Shilov and Semen Shanshin and Aleksandr Romanov
                 and Anastasia Fedotova and Anna Kurtukova and Evgeny
                 Kostyuchenko and Ivan Sidorov",
  title =        "Reconstruction of a {3D} Human Foot Shape Model Based
                 on a Video Stream Using Photogrammetry and Deep Neural
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "12",
  pages =        "315",
  day =          "14",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13120315",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:14 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/12/315",
  abstract =     "Reconstructed 3D foot models can be used for 3D
                 printing and further manufacturing of individual
                 orthopedic shoes, as well as in medical research and
                 for online shoe shopping. This study presents a
                 technique based on the approach and algorithms of
                 photogrammetry. The presented technique was used to
                 reconstruct a 3D model of the foot shape, including the
                 lower arch, using smartphone images. The technique is
                 based on modern computer vision and artificial
                 intelligence algorithms designed for image processing,
                 obtaining sparse and dense point clouds, depth maps,
                 and a final 3D model. For the segmentation of foot
                 images, the Mask R-CNN neural network was used, which
                 was trained on foot data from a set of 40 people. The
                 obtained accuracy was 97.88\%. The result of the study
                 was a high-quality reconstructed 3D model. The standard
                 deviation of linear indicators in length and width was
                 0.95 mm, with an average creation time of 1 min 35 s
                 recorded. Integration of this technique into the
                 business models of orthopedic enterprises, Internet
                 stores, and medical organizations will allow basic
                 manufacturing and shoe-fitting services to be carried
                 out and will help medical research to be performed via
                 the Internet.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Abuzrieq:2021:EPE,
  author =       "Yara Abuzrieq and Amro Al-Said Ahmad and Maram Bani
                 Younes",
  title =        "An Experimental Performance Evaluation of
                 Cloud-{API}-Based Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "12",
  pages =        "314",
  day =          "13",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13120314",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:14 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/12/314",
  abstract =     "Cloud Application Programming Interfaces (APIs) have
                 been developed to link several cloud computing
                 applications together. API-based applications are
                 widely used to provide flexible and reliable services
                 over cloud platforms. Recently, a huge number of
                 services have been attached to cloud platforms and
                 widely utilized during a very short period of time.
                 This is due to the COVID-19 lockdowns, which forced
                 several businesses to switch to online services
                 instantly. Several cloud platforms have failed to
                 support adequate services, especially for extended and
                 real-time-based applications. Early testing of the
                 available platforms guarantees a level of suitability
                 and reliability for the uploaded services. In this
                 work, we first selected two different API-based
                 applications from education and professional
                 taxonomies, the two most recently used applications
                 that have switched to the cloud environment. Then, we
                 aimed to evaluate the performance of different
                 API-based applications under different cloud platforms,
                 in order to measure and validate the ability of these
                 platforms to support these services. The advantages and
                 drawbacks of each platform were experimentally
                 investigated for each application.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kapassa:2021:BAI,
  author =       "Evgenia Kapassa and Marinos Themistocleous and Klitos
                 Christodoulou and Elias Iosif",
  title =        "Blockchain Application in {Internet of Vehicles}:
                 Challenges, Contributions and Current Limitations",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "12",
  pages =        "313",
  day =          "10",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13120313",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:14 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/12/313",
  abstract =     "Blockchain technology is highly coupled with
                 cryptocurrencies; however, it provides several other
                 potential use cases, related to energy and
                 sustainability, Internet of Things (IoT), smart cities,
                 smart mobility and more. Blockchain can offer security
                 for Electric Vehicle (EV) transactions in the Internet
                 of Vehicles (IoV) concept, allowing electricity trading
                 to be performed in a decentralized, transparent and
                 secure way. Additionally, blockchain provides the
                 necessary functionalities for IoV decentralized
                 application development, such as data exchange,
                 personal digital identity, sharing economy and
                 optimized charging pattern. Moreover, blockchain
                 technology has the potential to significantly increase
                 energy efficiency, decrease management costs and
                 guarantee the effective use of the energy recourses.
                 Therefore, its application in the IoV concept provides
                 secure, autonomous and automated energy trading between
                 EVs. While several studies on blockchain technology in
                 smart grids have been conducted, insufficient attention
                 has been given to conducting a detailed review and
                 state-of-the-art analysis of blockchain application in
                 the IoV domain. To this end, this work provides a
                 systematic literature review of blockchain-based
                 applications in the IoV domain. The aim is to
                 investigate the current challenges of IoV and to
                 highlight how blockchain characteristics can contribute
                 to this emerging paradigm. In addition, limitations and
                 future research directions related to the integration
                 of blockchain technology within the IoV are discussed.
                 To this end, this study incorporates the theoretical
                 foundations of several research articles published in
                 scientific publications over the previous five years,
                 as a method of simplifying our assessment and capturing
                 the ever-expanding blockchain area. We present a
                 comprehensive taxonomy of blockchain-enabled
                 applications in the IoV domain, such as privacy and
                 security, data protection and management, vehicle
                 management, charging optimization and P2P energy
                 trading, based on a structured, systematic review and
                 content analysis of the discovered literature, and we
                 identify key trends and emerging areas for research.
                 The contribution of this article is two-fold: (a) we
                 highlight the limitations presented in the relevant
                 literature, particularly the barriers of blockchain
                 technology and how they influence its integration into
                 the IoV and (b) we present a number of research gaps
                 and suggest future exploratory areas.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gangwani:2021:SEI,
  author =       "Pranav Gangwani and Alexander Perez-Pons and Tushar
                 Bhardwaj and Himanshu Upadhyay and Santosh Joshi and
                 Leonel Lagos",
  title =        "Securing Environmental {IoT} Data Using Masked
                 Authentication Messaging Protocol in a {DAG}-Based
                 Blockchain: {IOTA} Tangle",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "12",
  pages =        "312",
  day =          "06",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13120312",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:14 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/12/312",
  abstract =     "The demand for the digital monitoring of environmental
                 ecosystems is high and growing rapidly as a means of
                 protecting the public and managing the environment.
                 However, before data, algorithms, and models can be
                 mobilized at scale, there are considerable concerns
                 associated with privacy and security that can
                 negatively affect the adoption of technology within
                 this domain. In this paper, we propose the advancement
                 of electronic environmental monitoring through the
                 capability provided by the blockchain. The blockchain's
                 use of a distributed ledger as its underlying
                 infrastructure is an attractive approach to counter
                 these privacy and security issues, although its
                 performance and ability to manage sensor data must be
                 assessed. We focus on a new distributed ledger
                 technology for the IoT, called IOTA, that is based on a
                 directed acyclic graph. IOTA overcomes the current
                 limitations of the blockchain and offers a data
                 communication protocol called masked authenticated
                 messaging for secure data sharing among Internet of
                 Things (IoT) devices. We show how the application layer
                 employing the data communication protocol, MAM, can
                 support the secure transmission, storage, and retrieval
                 of encrypted environmental sensor data by using an
                 immutable distributed ledger such as that shown in
                 IOTA. Finally, we evaluate, compare, and analyze the
                 performance of the MAM protocol against a non-protocol
                 approach.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Guazzini:2021:PEA,
  author =       "Andrea Guazzini and Tommaso Raimondi and Benedetta
                 Biagini and Franco Bagnoli and Mirko Duradoni",
  title =        "Phubber's Emotional Activations: The Association
                 between {PANAS} and Phubbing Behavior",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "12",
  pages =        "311",
  day =          "04",
  month =        dec,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13120311",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:14 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/12/311",
  abstract =     "Currently, mobile phones are widely used worldwide.
                 Thus, phubbing rapidly became a common phenomenon in
                 our social life. Phubbing is considered by the
                 literature as a new form of technology-related
                 addiction that may undermine interpersonal
                 relationships and mental health. Our study contributed
                 to exploring phubbers' emotional activation as no other
                 work has investigated it so far. Indeed, researchers
                 have only explored phubbees' but not phubbers'
                 emotional correlates. A sample of 419 Italian
                 individuals (143 males) participated in our data
                 collection on a voluntary basis. The results showed
                 that phubbing is related to negative affects, but not
                 to positive affects. Moreover, phubbing in both its
                 components (i.e., communication disturbance, phone
                 obsession) appeared to elicit an emotional activation
                 similar to that of social media addiction. These
                 findings may help in strengthening the discussion
                 around the emotional consequences of virtual
                 environment design, as well as the awareness about what
                 happens at a relational level during phubbing.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sun:2021:SSA,
  author =       "Haoli Sun and Bingfeng Pi and Jun Sun and Takeshi
                 Miyamae and Masanobu Morinaga",
  title =        "{SASLedger}: a Secured, Accelerated Scalable Storage
                 Solution for Distributed Ledger Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "12",
  pages =        "310",
  day =          "30",
  month =        nov,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13120310",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:14 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/12/310",
  abstract =     "Blockchain technology provides a ``tamper-proof
                 distributed ledger'' for its users. Typically, to
                 ensure the integrity and immutability of the
                 transaction data, each node in a blockchain network
                 retains a full copy of the ledger; however, this
                 characteristic imposes an increasing storage burden
                 upon each node with the accumulation of data. In this
                 paper, an off-chain solution is introduced to relieve
                 the storage burden of blockchain nodes while ensuring
                 the integrity of the off-chain data. In our solution,
                 an off-chain remote DB server stores the fully
                 replicated data while the nodes only store the
                 commitments of the data to verify whether the off-chain
                 data are tampered with. To minimize the influence on
                 performance, the nodes will store data locally at first
                 and transfer it to the remote DB server when otherwise
                 idle. Our solution also supports accessing all
                 historical data for newly joined nodes through a
                 snapshot mechanism. The solution is implemented based
                 on the Hyperledger Fabric (HLF). Experiments show that
                 our solution reduces the block data for blockchain
                 nodes by 93.3\% compared to the original HLF and that
                 our advanced solution enhances the TPS by 9.6\%
                 compared to our primary solution.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Marques:2021:DFB,
  author =       "Claudio Marques and Silvestre Malta and Jo{\~a}o
                 Magalh{\~a}es",
  title =        "{DNS} Firewall Based on Machine Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "12",
  pages =        "309",
  day =          "30",
  month =        nov,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13120309",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:14 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/12/309",
  abstract =     "Nowadays there are many DNS firewall solutions to
                 prevent users accessing malicious domains. These can
                 provide real-time protection and block illegitimate
                 communications, contributing to the cybersecurity
                 posture of the organizations. Most of these solutions
                 are based on known malicious domain lists that are
                 being constantly updated. However, in this way, it is
                 only possible to block malicious communications for
                 known malicious domains, leaving out many others that
                 are malicious but have not yet been updated in the
                 blocklists. This work provides a study to implement a
                 DNS firewall solution based on ML and so improve the
                 detection of malicious domain requests on the fly. For
                 this purpose, a dataset with 34 features and 90 k
                 records was created based on real DNS logs. The data
                 were enriched using OSINT sources. Exploratory analysis
                 and data preparation steps were carried out, and the
                 final dataset submitted to different Supervised ML
                 algorithms to accurately and quickly classify if a
                 domain request is malicious or not. The results show
                 that the ML algorithms were able to classify the benign
                 and malicious domains with accuracy rates between 89\%
                 and 96\%, and with a classification time between 0.01
                 and 3.37 s. The contributions of this study are
                 twofold. In terms of research, a dataset was made
                 public and the methodology can be used by other
                 researchers. In terms of solution, the work provides
                 the baseline to implement an in band DNS firewall.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Dirir:2021:ADL,
  author =       "Ahmed Dirir and Henry Ignatious and Hesham Elsayed and
                 Manzoor Khan and Mohammed Adib and Anas Mahmoud and
                 Moatasem Al-Gunaid",
  title =        "An Advanced Deep Learning Approach for Multi-Object
                 Counting in Urban Vehicular Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "12",
  pages =        "306",
  day =          "30",
  month =        nov,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13120306",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:14 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/12/306",
  abstract =     "Object counting is an active research area that gained
                 more attention in the past few years. In smart cities,
                 vehicle counting plays a crucial role in urban planning
                 and management of the Intelligent Transportation
                 Systems (ITS). Several approaches have been proposed in
                 the literature to address this problem. However, the
                 resulting detection accuracy is still not adequate.
                 This paper proposes an efficient approach that uses
                 deep learning concepts and correlation filters for
                 multi-object counting and tracking. The performance of
                 the proposed system is evaluated using a dataset
                 consisting of 16 videos with different features to
                 examine the impact of object density, image quality,
                 angle of view, and speed of motion towards system
                 accuracy. Performance evaluation exhibits promising
                 results in normal traffic scenarios and adverse weather
                 conditions. Moreover, the proposed approach outperforms
                 the performance of two recent approaches from the
                 literature.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Md:2021:TOU,
  author =       "Abdul Quadir Md and Divyank Agrawal and Monark Mehta
                 and Arun Kumar Sivaraman and Kong Fah Tee",
  title =        "Time Optimization of Unmanned Aerial Vehicles Using an
                 Augmented Path",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "12",
  pages =        "308",
  day =          "29",
  month =        nov,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13120308",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:14 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/12/308",
  abstract =     "With the pandemic gripping the entire humanity and
                 with uncertainty hovering like a black cloud over all
                 our future sustainability and growth, it became almost
                 apparent that though the development and advancement
                 are at their peak, we are still not ready for the
                 worst. New and better solutions need to be applied so
                 that we will be capable of fighting these conditions.
                 One such prospect is delivery, where everything has to
                 be changed, and each parcel, which was passed people to
                 people, department to department, has to be made
                 contactless throughout with as little error as
                 possible. Thus, the prospect of drone delivery and its
                 importance came around with optimization of the
                 existing system for making it useful in the prospects
                 of delivery of important items like medicines,
                 vaccines, etc. These modular AI-guided drones are
                 faster, efficient, less expensive, and less
                 power-consuming than the actual delivery.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Varadarajan:2021:EDC,
  author =       "Vijayakumar Varadarajan and Dweepna Garg and Ketan
                 Kotecha",
  title =        "An Efficient Deep Convolutional Neural Network
                 Approach for Object Detection and Recognition Using a
                 Multi-Scale Anchor Box in Real-Time",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "12",
  pages =        "307",
  day =          "29",
  month =        nov,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13120307",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:14 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/12/307",
  abstract =     "Deep learning is a relatively new branch of machine
                 learning in which computers are taught to recognize
                 patterns in massive volumes of data. It primarily
                 describes learning at various levels of representation,
                 which aids in understanding data that includes text,
                 voice, and visuals. Convolutional neural networks have
                 been used to solve challenges in computer vision,
                 including object identification, image classification,
                 semantic segmentation and a lot more. Object detection
                 in videos involves confirming the presence of the
                 object in the image or video and then locating it
                 accurately for recognition. In the video, modelling
                 techniques suffer from high computation and memory
                 costs, which may decrease performance measures such as
                 accuracy and efficiency to identify the object
                 accurately in real-time. The current object detection
                 technique based on a deep convolution neural network
                 requires executing multilevel convolution and pooling
                 operations on the entire image to extract deep semantic
                 properties from it. For large objects, detection models
                 can provide superior results; however, those models
                 fail to detect the varying size of the objects that
                 have low resolution and are greatly influenced by noise
                 because the features after the repeated convolution
                 operations of existing models do not fully represent
                 the essential characteristics of the objects in
                 real-time. With the help of a multi-scale anchor box,
                 the proposed approach reported in this paper enhances
                 the detection accuracy by extracting features at
                 multiple convolution levels of the object. The major
                 contribution of this paper is to design a model to
                 understand better the parameters and the
                 hyper-parameters which affect the detection and the
                 recognition of objects of varying sizes and shapes, and
                 to achieve real-time object detection and recognition
                 speeds by improving accuracy. The proposed model has
                 achieved 84.49 mAP on the test set of the Pascal
                 VOC-2007 dataset at 11 FPS, which is comparatively
                 better than other real-time object detection models.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Altulyan:2021:CIA,
  author =       "May Altulyan and Lina Yao and Chaoran Huang and
                 Xianzhi Wang and Salil S. Kanhere",
  title =        "Context-Induced Activity Monitoring for On-Demand
                 Things-of-Interest Recommendation in an Ambient
                 Intelligent Environment",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "12",
  pages =        "305",
  day =          "28",
  month =        nov,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13120305",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:14 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/12/305",
  abstract =     "Recommendation systems are crucial in the provision of
                 services to the elderly with Alzheimer's disease in
                 IoT-based smart home environments. In this work, a
                 Reminder Care System (RCS) is presented to help
                 Alzheimer patients live in and operate their homes
                 safely and independently. A contextual bandit approach
                 is utilized in the formulation of the proposed
                 recommendation system to tackle dynamicity in human
                 activities and to construct accurate recommendations
                 that meet user needs without their feedback. The system
                 was evaluated based on three public datasets using a
                 cumulative reward as a metric. Our experimental results
                 demonstrate the feasibility and effectiveness of the
                 proposed Reminder Care System for real-world IoT-based
                 smart home applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Abdellah:2021:MLA,
  author =       "Ali R. Abdellah and Omar Abdulkareem Mahmood and
                 Ruslan Kirichek and Alexander Paramonov and Andrey
                 Koucheryavy",
  title =        "Machine Learning Algorithm for Delay Prediction in
                 {IoT} and Tactile {Internet}",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "12",
  pages =        "304",
  day =          "26",
  month =        nov,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13120304",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:14 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/12/304",
  abstract =     "The next-generation cellular systems, including
                 fifth-generation cellular systems (5G), are empowered
                 with the recent advances in artificial intelligence
                 (AI) and other recent paradigms. The internet of things
                 (IoT) and the tactile internet are paradigms that can
                 be empowered with AI solutions and integrated with 5G
                 systems to deliver novel services that impact the
                 future. Machine learning technologies (ML) can
                 understand examples of nonlinearity from the
                 environment and are suitable for network traffic
                 prediction. Network traffic prediction is one of the
                 most active research areas that integrates AI with
                 information networks. Traffic prediction is an integral
                 approach to ensure security, reliability, and quality
                 of service (QoS) requirements. Nowadays, it can be used
                 in various applications, such as network monitoring,
                 resource management, congestion control, network
                 bandwidth allocation, network intrusion detection, etc.
                 This paper performs time series prediction for IoT and
                 tactile internet delays, using the k -step-ahead
                 prediction approach with nonlinear autoregressive with
                 external input (NARX)-enabled recurrent neural network
                 (RNN). The ML was trained with four different training
                 functions: Bayesian regularization backpropagation
                 (Trainbr), Levenberg--Marquardt backpropagation
                 (Trainlm), conjugate gradient backpropagation with
                 Fletcher--Reeves updates (Traincgf), and the resilient
                 backpropagation algorithm (Trainrp). The accuracy of
                 the predicted delay was measured using three functions
                 based on ML: mean square error (MSE), root mean square
                 error (RMSE), and mean absolute percentage error
                 (MAPE).",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2021:AMG,
  author =       "Xiaoliang Wang and Peiquan Jin",
  title =        "Adaptive Multi-Grained Buffer Management for Database
                 Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "12",
  pages =        "303",
  day =          "26",
  month =        nov,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13120303",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:14 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/12/303",
  abstract =     "The traditional page-grained buffer manager in
                 database systems has a low hit ratio when only a few
                 tuples within a page are frequently accessed. To handle
                 this issue, this paper proposes a new buffering scheme
                 called the AMG-Buffer (Adaptive Multi-Grained Buffer).
                 AMG-Buffer proposes to use two page buffers and a tuple
                 buffer to organize the whole buffer. In this way, the
                 AMG-Buffer can hold more hot tuples than a single
                 page-grained buffer. Further, we notice that the tuple
                 buffer may cause additional read I/Os when writing
                 dirty tuples into disks. Thus, we introduce a new
                 metric named clustering rate to quantify the hot-tuple
                 rate in a page. The use of the tuple buffer is
                 determined by the clustering rate, allowing the
                 AMG-Buffer to adapt to different workloads. We conduct
                 experiments on various workloads to compare the
                 AMG-Buffer with several existing schemes, including
                 LRU, LIRS, CFLRU, CFDC, and MG-Buffer. The results show
                 that AMG-Buffer can significantly improve the hit ratio
                 and reduce I/Os compared to its competitors. Moreover,
                 the AMG-Buffer achieves the best performance on a
                 dynamic workload as well as on a large data set,
                 suggesting its adaptivity and scalability to changing
                 workloads.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Agbaegbu:2021:OCC,
  author =       "JohnBosco Agbaegbu and Oluwasefunmi Tale Arogundade
                 and Sanjay Misra and Robertas Damasevicius",
  title =        "Ontologies in Cloud Computing --- Review and Future
                 Directions",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "12",
  pages =        "302",
  day =          "26",
  month =        nov,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13120302",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:14 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/12/302",
  abstract =     "Cloud computing as a technology has the capacity to
                 enhance cooperation, scalability, accessibility, and
                 offers discount prospects using improved and effective
                 computing, and this capability helps organizations to
                 stay focused. Ontologies are used to model knowledge.
                 Once knowledge is modeled, knowledge management systems
                 can be used to search, match, visualize knowledge, and
                 also infer new knowledge. Ontologies use semantic
                 analysis to define information within an environment
                 with interconnecting relationships between
                 heterogeneous sets. This paper aims to provide a
                 comprehensive review of the existing literature on
                 ontology in cloud computing and defines the state of
                 the art. We applied the systematic literature review
                 (SLR) approach and identified 400 articles; 58 of the
                 articles were selected after further selection based on
                 set selection criteria, and 35 articles were considered
                 relevant to the study. The study shows that four
                 predominant areas of cloud computing-cloud security,
                 cloud interoperability, cloud resources and service
                 description, and cloud services discovery and
                 selection-have attracted the attention of researchers
                 as dominant areas where cloud ontologies have made
                 great impact. The proposed methods in the literature
                 applied 30 ontologies in the cloud domain, and five of
                 the methods are still practiced in the legacy computing
                 environment. From the analysis, it was found that
                 several challenges exist, including those related to
                 the application of ontologies to enhance business
                 operations in the cloud and multi-cloud. Based on this
                 review, the study summarizes some unresolved challenges
                 and possible future directions for cloud ontology
                 researchers.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Cocco:2021:BSS,
  author =       "Luisanna Cocco and Roberto Tonelli and Michele
                 Marchesi",
  title =        "Blockchain and Self Sovereign Identity to Support
                 Quality in the Food Supply Chain",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "12",
  pages =        "301",
  day =          "26",
  month =        nov,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13120301",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:14 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/12/301",
  abstract =     "This work presents how a digital identity management
                 system can support food supply chains in guaranteeing
                 the quality of the products marketed and the compliance
                 of the several supply-chain's nodes to standards and
                 technical regulations. Specific goal of this work is to
                 present a system that provides full visibility of
                 process/food certifications, which nowadays are issued
                 by accredited and approved certification bodies
                 (issuers) and delivered and stored in paper version by
                 the several participants (holders) of the supply chain.
                 The system is designed and implemented by combining the
                 latest most innovative and disruptive technologies in
                 the market-Self Sovereign Identity system, Blockchain,
                 and Inter Planetary File System. The crucial aspects
                 that it aims to hit are the storage and access of
                 food/process certifications, and the proper eligibility
                 verification of these certifications exploiting the
                 concepts of the Self Sovereign Identity-based models.
                 The proposed system, realized by using standards that
                 are WWW Consortium-compatible and the Ethereum
                 Blockchain, ensures eligibility, transparency, and
                 traceability of the certifications along a food supply
                 chain, and could be an innovation model/idea that the
                 companies that adopt the Open Innovation paradigm might
                 want to pursue.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kwon:2021:IRM,
  author =       "Junhyung Kwon and Sangkyun Lee",
  title =        "Improving the Robustness of Model Compression by
                 On-Manifold Adversarial Training",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "12",
  pages =        "300",
  day =          "25",
  month =        nov,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13120300",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:14 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/12/300",
  abstract =     "Despite the advance in deep learning technology,
                 assuring the robustness of deep neural networks (DNNs)
                 is challenging and necessary in safety-critical
                 environments, including automobiles, IoT devices in
                 smart factories, and medical devices, to name a few.
                 Furthermore, recent developments allow us to compress
                 DNNs to reduce the size and computational requirements
                 of DNNs to fit them into small embedded devices.
                 However, how robust a compressed DNN can be has not
                 been well studied in addressing its relationship to
                 other critical factors, such as prediction performance
                 and model sizes. In particular, existing studies on
                 robust model compression have been focused on the
                 robustness against off-manifold adversarial
                 perturbation, which does not explain how a DNN will
                 behave against perturbations that follow the same
                 probability distribution as the training data. This
                 aspect is relevant for on-device AI models, which are
                 more likely to experience perturbations due to noise
                 from the regular data observation environment compared
                 with off-manifold perturbations provided by an external
                 attacker. Therefore, this paper investigates the
                 robustness of compressed deep neural networks, focusing
                 on the relationship between the model sizes and the
                 prediction performance on noisy perturbations. Our
                 experiment shows that on-manifold adversarial training
                 can be effective in building robust classifiers,
                 especially when the model compression rate is high.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ali:2021:SEM,
  author =       "Guma Ali and Mussa Ally Dida and Anael Elikana Sam",
  title =        "A Secure and Efficient Multi-Factor Authentication
                 Algorithm for Mobile Money Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "13",
  number =       "12",
  pages =        "299",
  day =          "25",
  month =        nov,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi13120299",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:14 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/13/12/299",
  abstract =     "With the expansion of smartphone and financial
                 technologies (FinTech), mobile money emerged to improve
                 financial inclusion in many developing nations. The
                 majority of the mobile money schemes used in these
                 nations implement two-factor authentication (2FA) as
                 the only means of verifying mobile money users. These
                 2FA schemes are vulnerable to numerous security attacks
                 because they only use a personal identification number
                 (PIN) and subscriber identity module (SIM). This study
                 aims to develop a secure and efficient multi-factor
                 authentication algorithm for mobile money applications.
                 It uses a novel approach combining PIN, a one-time
                 password (OTP), and a biometric fingerprint to enforce
                 extra security during mobile money authentication. It
                 also uses a biometric fingerprint and quick response
                 (QR) code to confirm mobile money withdrawal. The
                 security of the PIN and OTP is enforced by using secure
                 hashing algorithm-256 (SHA-256), a biometric
                 fingerprint by Fast IDentity Online (FIDO) that uses a
                 standard public key cryptography technique (RSA), and
                 Fernet encryption to secure a QR code and the records
                 in the databases. The evolutionary prototyping model
                 was adopted when developing the native mobile money
                 application prototypes to prove that the algorithm is
                 feasible and provides a higher degree of security. The
                 developed applications were tested, and a detailed
                 security analysis was conducted. The results show that
                 the proposed algorithm is secure, efficient, and highly
                 effective against the various threat models. It also
                 offers secure and efficient authentication and ensures
                 data confidentiality, integrity, non-repudiation, user
                 anonymity, and privacy. The performance analysis
                 indicates that it achieves better overall performance
                 compared with the existing mobile money systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alberro:2022:EED,
  author =       "Leonardo Alberro and Alberto Castro and Eduardo
                 Grampin",
  title =        "Experimentation Environments for Data Center Routing
                 Protocols: a Comprehensive Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "1",
  pages =        "29",
  day =          "17",
  month =        jan,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14010029",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/1/29",
  abstract =     "The Internet architecture has been undergoing a
                 significant refactoring, where the past preeminence of
                 transit providers has been replaced by content
                 providers, which have a ubiquitous presence throughout
                 the world, seeking to improve the user experience,
                 bringing content closer to its final recipients. This
                 restructuring is materialized in the emergence of
                 Massive Scale Data Centers (MSDC) worldwide, which
                 allows the implementation of the Cloud Computing
                 concept. MSDC usually deploy Fat-Tree topologies, with
                 constant bisection bandwidth among servers and
                 multi-path routing. To take full advantage of such
                 characteristics, specific routing protocols are needed.
                 Multi-path routing also calls for revision of transport
                 protocols and forwarding policies, also affected by
                 specific MSDC applications' traffic characteristics.
                 Experimenting over these infrastructures is
                 prohibitively expensive, and therefore, scalable and
                 realistic experimentation environments are needed to
                 research and test solutions for MSDC. In this paper, we
                 review several environments, both single-host and
                 distributed, which permit analyzing the pros and cons
                 of different solutions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Trofimova:2022:ERA,
  author =       "Yelena Trofimova and Pavel Tvrd{\'\i}k",
  title =        "Enhancing Reactive Ad Hoc Routing Protocols with
                 Trust",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "1",
  pages =        "28",
  day =          "15",
  month =        jan,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14010028",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/1/28",
  abstract =     "In wireless ad hoc networks, security and
                 communication challenges are frequently addressed by
                 deploying a trust mechanism. A number of approaches for
                 evaluating trust of ad hoc network nodes have been
                 proposed, including the one that uses neural networks.
                 We proposed to use packet delivery ratios as input to
                 the neural network. In this article, we present a new
                 method, called TARA (Trust-Aware Reactive Ad Hoc
                 routing), to incorporate node trusts into reactive ad
                 hoc routing protocols. The novelty of the TARA method
                 is that it does not require changes to the routing
                 protocol itself. Instead, it influences the routing
                 choice from outside by delaying the route request
                 messages of untrusted nodes. The performance of the
                 method was evaluated on the use case of sensor nodes
                 sending data to a sink node. The experiments showed
                 that the method improves the packet delivery ratio in
                 the network by about 70\%. Performance analysis of the
                 TARA method provided recommendations for its
                 application in a particular ad hoc network.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2022:GCD,
  author =       "Junda Li and Chunxu Zhang and Bo Yang",
  title =        "Global Contextual Dependency Network for Object
                 Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "1",
  pages =        "27",
  day =          "13",
  month =        jan,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14010027",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/1/27",
  abstract =     "Current two-stage object detectors extract the local
                 visual features of Regions of Interest (RoIs) for
                 object recognition and bounding-box regression.
                 However, only using local visual features will lose
                 global contextual dependencies, which are helpful to
                 recognize objects with featureless appearances and
                 restrain false detections. To tackle the problem, a
                 simple framework, named Global Contextual Dependency
                 Network (GCDN), is presented to enhance the
                 classification ability of two-stage detectors. Our GCDN
                 mainly consists of two components, Context
                 Representation Module (CRM) and Context Dependency
                 Module (CDM). Specifically, a CRM is proposed to
                 construct multi-scale context representations. With
                 CRM, contextual information can be fully explored at
                 different scales. Moreover, the CDM is designed to
                 capture global contextual dependencies. Our GCDN
                 includes multiple CDMs. Each CDM utilizes local Region
                 of Interest (RoI) features and single-scale context
                 representation to generate single-scale contextual RoI
                 features via the attention mechanism. Finally, the
                 contextual RoI features generated by parallel CDMs
                 independently are combined with the original RoI
                 features to help classification. Experiments on MS-COCO
                 2017 benchmark dataset show that our approach brings
                 continuous improvements for two-stage detectors.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Niarchos:2022:SPF,
  author =       "Michail Niarchos and Marina Eirini Stamatiadou and
                 Charalampos Dimoulas and Andreas Veglis and Andreas
                 Symeonidis",
  title =        "A Semantic Preprocessing Framework for Breaking News
                 Detection to Support Future Drone Journalism Services",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "1",
  pages =        "26",
  day =          "10",
  month =        jan,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14010026",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/1/26",
  abstract =     "Nowadays, news coverage implies the existence of video
                 footage and sound, from which arises the need for fast
                 reflexes by media organizations. Social media and
                 mobile journalists assist in fulfilling this
                 requirement, but quick on-site presence is not always
                 feasible. In the past few years, Unmanned Aerial
                 Vehicles (UAVs), and specifically drones, have evolved
                 to accessible recreational and business tools. Drones
                 could help journalists and news organizations capture
                 and share breaking news stories. Media corporations and
                 individual professionals are waiting for the
                 appropriate flight regulation and data handling
                 framework to enable their usage to become widespread.
                 Drone journalism services upgrade the usage of drones
                 in day-to-day news reporting operations, offering
                 multiple benefits. This paper proposes a system for
                 operating an individual drone or a set of drones,
                 aiming to mediate real-time breaking news coverage.
                 Apart from the definition of the system requirements
                 and the architecture design of the whole system, the
                 current work focuses on data retrieval and the
                 semantics preprocessing framework that will be the
                 basis of the final implementation. The ultimate goal of
                 this project is to implement a whole system that will
                 utilize data retrieved from news media organizations,
                 social media, and mobile journalists to provide alerts,
                 geolocation inference, and flight planning.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lombardo:2022:MUW,
  author =       "Gianfranco Lombardo and Michele Tomaiuolo and Monica
                 Mordonini and Gaia Codeluppi and Agostino Poggi",
  title =        "Mobility in Unsupervised Word Embeddings for Knowledge
                 Extraction --- The Scholars' Trajectories across
                 Research Topics",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "1",
  pages =        "25",
  day =          "09",
  month =        jan,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14010025",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/1/25",
  abstract =     "In the knowledge discovery field of the Big Data
                 domain the analysis of geographic positioning and
                 mobility information plays a key role. At the same
                 time, in the Natural Language Processing (NLP) domain
                 pre-trained models such as BERT and word embedding
                 algorithms such as Word2Vec enabled a rich encoding of
                 words that allows mapping textual data into points of
                 an arbitrary multi-dimensional space, in which the
                 notion of proximity reflects an association among terms
                 or topics. The main contribution of this paper is to
                 show how analytical tools, traditionally adopted to
                 deal with geographic data to measure the mobility of an
                 agent in a time interval, can also be effectively
                 applied to extract knowledge in a semantic realm, such
                 as a semantic space of words and topics, looking for
                 latent trajectories that can benefit the properties of
                 neural network latent representations. As a case study,
                 the Scopus database was queried about works of highly
                 cited researchers in recent years. On this basis, we
                 performed a dynamic analysis, for measuring the Radius
                 of Gyration as an index of the mobility of researchers
                 across scientific topics. The semantic space is built
                 from the automatic analysis of the paper abstracts of
                 each author. In particular, we evaluated two different
                 methodologies to build the semantic space and we found
                 that Word2Vec embeddings perform better than the BERT
                 ones for this task. Finally, The scholars' trajectories
                 show some latent properties of this model, which also
                 represent new scientific contributions of this work.
                 These properties include ( i ) the correlation between
                 the scientific mobility and the achievement of
                 scientific results, measured through the H-index; ( ii
                 ) differences in the behavior of researchers working in
                 different countries and subjects; and ( iii ) some
                 interesting similarities between mobility patterns in
                 this semantic realm and those typically observed in the
                 case of human mobility.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yan:2022:CDC,
  author =       "Hui Yan and Chaoyuan Cui",
  title =        "{CacheHawkeye}: Detecting Cache Side Channel Attacks
                 Based on Memory Events",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "1",
  pages =        "24",
  day =          "08",
  month =        jan,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14010024",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/1/24",
  abstract =     "Cache side channel attacks, as a type of
                 cryptanalysis, seriously threaten the security of the
                 cryptosystem. These attacks continuously monitor the
                 memory addresses associated with the victim's secret
                 information, which cause frequent memory access on
                 these addresses. This paper proposes CacheHawkeye,
                 which uses the frequent memory access characteristic of
                 the attacker to detect attacks. CacheHawkeye monitors
                 memory events by CPU hardware performance counters. We
                 proved the effectiveness of CacheHawkeye on
                 Flush+Reload and Flush+Flush attacks. In addition, we
                 evaluated the accuracy of CacheHawkeye under different
                 system loads. Experiments demonstrate that CacheHawkeye
                 not only has good accuracy but can also adapt to
                 various system loads.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rodrigues:2022:QBM,
  author =       "La{\'e}cio Rodrigues and Joel J. P. C. Rodrigues and
                 Antonio de Barros Serra and Francisco Airton Silva",
  title =        "A Queueing-Based Model Performance Evaluation for
                 {Internet} of People Supported by Fog Computing",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "1",
  pages =        "23",
  day =          "08",
  month =        jan,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14010023",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/1/23",
  abstract =     "Following the Internet of Things (IoT) and the
                 Internet of Space (IoS), we are now approaching IoP
                 (Internet of People), or the Internet of Individuals,
                 with the integration of chips inside people that link
                 to other chips and the Internet. Low latency is
                 required in order to achieve great service quality in
                 these ambient assisted living facilities. Failures, on
                 the other hand, are not tolerated, and assessing the
                 performance of such systems in a real-world setting is
                 difficult. Analytical models may be used to examine
                 these types of systems even in the early phases of
                 design. The performance of aged care monitoring systems
                 is evaluated using an M/M/c/K queuing network. The
                 model enables resource capacity, communication, and
                 service delays to be calibrated. The proposed model was
                 shown to be capable of predicting the system's MRT
                 (mean response time) and calculating the quantity of
                 resources required to satisfy certain user
                 requirements. To analyze data from IoT solutions, the
                 examined architecture incorporates cloud and fog
                 resources. Different circumstances were analyzed as
                 case studies, with four main characteristics taken into
                 consideration. These case studies look into how cloud
                 and fog resources differ. Simulations were also run to
                 test various routing algorithms with the goal of
                 improving performance metrics. As a result, our study
                 can assist in the development of more sophisticated
                 health monitoring systems without incurring additional
                 costs.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ponce:2022:SFA,
  author =       "Pedro Ponce and Omar Mata and Esteban Perez and Juan
                 Roberto Lopez and Arturo Molina and Troy McDaniel",
  title =        "{S4} Features and Artificial Intelligence for
                 Designing a Robot against {COVID}-19-Robocov",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "1",
  pages =        "22",
  day =          "06",
  month =        jan,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14010022",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/1/22",
  abstract =     "Since the COVID-19 Pandemic began, there have been
                 several efforts to create new technology to mitigate
                 the impact of the COVID-19 Pandemic around the world.
                 One of those efforts is to design a new task force,
                 robots, to deal with fundamental goals such as public
                 safety, clinical care, and continuity of work. However,
                 those characteristics need new products based on
                 features that create them more innovatively and
                 creatively. Those products could be designed using the
                 S4 concept (sensing, smart, sustainable, and social
                 features) presented as a concept able to create a new
                 generation of products. This paper presents a low-cost
                 robot, Robocov, designed as a rapid response against
                 the COVID-19 Pandemic at Tecnologico de Monterrey,
                 Mexico, with implementations of artificial intelligence
                 and the S4 concept for the design. Robocov can achieve
                 numerous tasks using the S4 concept that provides
                 flexibility in hardware and software. Thus, Robocov can
                 impact positivity public safety, clinical care,
                 continuity of work, quality of life, laboratory and
                 supply chain automation, and non-hospital care. The
                 mechanical structure and software development allow
                 Robocov to complete support tasks effectively so
                 Robocov can be integrated as a technological tool for
                 achieving the new normality's required conditions
                 according to government regulations. Besides, the
                 reconfiguration of the robot for moving from one task
                 (robot for disinfecting) to another one (robot for
                 detecting face masks) is an easy endeavor that only one
                 operator could do. Robocov is a teleoperated system
                 that transmits information by cameras and an ultrasonic
                 sensor to the operator. In addition, pre-recorded paths
                 can be executed autonomously. In terms of communication
                 channels, Robocov includes a speaker and microphone.
                 Moreover, a machine learning algorithm for detecting
                 face masks and social distance is incorporated using a
                 pre-trained model for the classification process. One
                 of the most important contributions of this paper is to
                 show how a reconfigurable robot can be designed under
                 the S3 concept and integrate AI methodologies. Besides,
                 it is important that this paper does not show specific
                 details about each subsystem in the robot.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhang:2022:SLP,
  author =       "Weiwei Zhang and Xin Ma and Yuzhao Zhang and Ming Ji
                 and Chenghui Zhen",
  title =        "{SMYOLO}: Lightweight Pedestrian Target Detection
                 Algorithm in Low-Altitude Scenarios",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "1",
  pages =        "21",
  day =          "04",
  month =        jan,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14010021",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/1/21",
  abstract =     "Due to the arbitrariness of the drone's shooting angle
                 of view and camera movement and the limited computing
                 power of the drone platform, pedestrian detection in
                 the drone scene poses a greater challenge. This paper
                 proposes a new convolutional neural network structure,
                 SMYOLO, which achieves the balance of accuracy and
                 speed from three aspects: (1) By combining deep
                 separable convolution and point convolution and
                 replacing the activation function, the calculation
                 amount and parameters of the original network are
                 reduced; (2) by adding a batch normalization (BN)
                 layer, SMYOLO accelerates the convergence and improves
                 the generalization ability; and (3) through scale
                 matching, reduces the feature loss of the original
                 network. Compared with the original network model,
                 SMYOLO reduces the accuracy of the model by only
                 4.36\%, the model size is reduced by 76.90\%, the
                 inference speed is increased by 43.29\%, and the
                 detection target is accelerated by 33.33\%, achieving
                 minimization of the network model volume while ensuring
                 the detection accuracy of the model.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Duong:2022:UHC,
  author =       "Tan Nghia Duong and Nguyen Nam Doan and Truong Giang
                 Do and Manh Hoang Tran and Duc Minh Nguyen and Quang
                 Hieu Dang",
  title =        "Utilizing Half Convolutional Autoencoder to Generate
                 User and Item Vectors for Initialization in Matrix
                 Factorization",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "1",
  pages =        "20",
  day =          "04",
  month =        jan,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14010020",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/1/20",
  abstract =     "Recommendation systems based on convolutional neural
                 network (CNN) have attracted great attention due to
                 their effectiveness in processing unstructured data
                 such as images or audio. However, a huge amount of raw
                 data produced by data crawling and digital
                 transformation is structured, which makes it difficult
                 to utilize the advantages of CNN. This paper introduces
                 a novel autoencoder, named Half Convolutional
                 Autoencoder, which adopts convolutional layers to
                 discover the high-order correlation between structured
                 features in the form of Tag Genome, the side
                 information associated with each movie in the MovieLens
                 20 M dataset, in order to generate a robust feature
                 vector. Subsequently, these new movie representations,
                 along with the introduction of users' characteristics
                 generated via Tag Genome and their past transactions,
                 are applied into well-known matrix factorization models
                 to resolve the initialization problem and enhance the
                 predicting results. This method not only outperforms
                 traditional matrix factorization techniques by at least
                 5.35\% in terms of accuracy but also stabilizes the
                 training process and guarantees faster convergence.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kouahla:2022:SBI,
  author =       "Zineddine Kouahla and Ala-Eddine Benrazek and Mohamed
                 Amine Ferrag and Brahim Farou and Hamid Seridi and
                 Muhammet Kurulay and Adeel Anjum and Alia Asheralieva",
  title =        "A Survey on Big {IoT} Data Indexing: Potential
                 Solutions, Recent Advancements, and Open Issues",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "1",
  pages =        "19",
  day =          "31",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14010019",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/1/19",
  abstract =     "The past decade has been characterized by the growing
                 volumes of data due to the widespread use of the
                 Internet of Things (IoT) applications, which introduced
                 many challenges for efficient data storage and
                 management. Thus, the efficient indexing and searching
                 of large data collections is a very topical and urgent
                 issue. Such solutions can provide users with valuable
                 information about IoT data. However, efficient
                 retrieval and management of such information in terms
                 of index size and search time require optimization of
                 indexing schemes which is rather difficult to
                 implement. The purpose of this paper is to examine and
                 review existing indexing techniques for large-scale
                 data. A taxonomy of indexing techniques is proposed to
                 enable researchers to understand and select the
                 techniques that will serve as a basis for designing a
                 new indexing scheme. The real-world applications of the
                 existing indexing techniques in different areas, such
                 as health, business, scientific experiments, and social
                 networks, are presented. Open problems and research
                 challenges, e.g., privacy and large-scale data mining,
                 are also discussed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Dang:2022:NCS,
  author =       "Shoujiang Dang and Rui Han",
  title =        "An In-Network Cooperative Storage Schema Based on
                 Neighbor Offloading in a Programmable Data Plane",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "1",
  pages =        "18",
  day =          "30",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14010018",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/1/18",
  abstract =     "In scientific domains such as high-energy particle
                 physics and genomics, the quantity of high-speed data
                 traffic generated may far exceed the storage throughput
                 and be unable to be in time stored in the current node.
                 Cooperating and utilizing multiple storage nodes on the
                 forwarding path provides an opportunity for high-speed
                 data storage. This paper proposes the use of flow
                 entries to dynamically split traffic among selected
                 neighbor nodes to sequentially amortize excess traffic.
                 We propose a neighbor selection mechanism based on the
                 Local Name Mapping and Resolution System, in which the
                 node weights are computed by combing the link bandwidth
                 and node storage capability, and determining whether to
                 split traffic by comparing normalized weight values
                 with thresholds. To dynamically offload traffic among
                 multiple targets, the cooperative storage strategy
                 implemented in a programmable data plane is presented
                 using the relative weights and ID suffix matching.
                 Evaluation shows that our proposed schema is more
                 efficient compared with end-to-end transmission and
                 ECMP in terms of bandwidth usage and transfer time, and
                 is beneficial in big science.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2022:IRG,
  author =       "Shuailong Li and Wei Zhang and Yuquan Leng and Xiaohui
                 Wang",
  title =        "The Important Role of Global State for Multi-Agent
                 Reinforcement Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "1",
  pages =        "17",
  day =          "30",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14010017",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/1/17",
  abstract =     "Environmental information plays an important role in
                 deep reinforcement learning (DRL). However, many
                 algorithms do not pay much attention to environmental
                 information. In multi-agent reinforcement learning
                 decision-making, because agents need to make decisions
                 combined with the information of other agents in the
                 environment, this makes the environmental information
                 more important. To prove the importance of
                 environmental information, we added environmental
                 information to the algorithm. We evaluated many
                 algorithms on a challenging set of StarCraft II
                 micromanagement tasks. Compared with the original
                 algorithm, the standard deviation (except for the VDN
                 algorithm) was smaller than that of the original
                 algorithm, which shows that our algorithm has better
                 stability. The average score of our algorithm was
                 higher than that of the original algorithm (except for
                 VDN and COMA), which shows that our work significantly
                 outperforms existing multi-agent RL methods.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Jatoth:2022:ICB,
  author =       "Chandrashekar Jatoth and Rishabh Jain and Ugo Fiore
                 and Subrahmanyam Chatharasupalli",
  title =        "Improved Classification of Blockchain Transactions
                 Using Feature Engineering and Ensemble Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "1",
  pages =        "16",
  day =          "28",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14010016",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/1/16",
  abstract =     "Although the blockchain technology is gaining a
                 widespread adoption across multiple sectors, its most
                 popular application is in cryptocurrency. The
                 decentralized and anonymous nature of transactions in a
                 cryptocurrency blockchain has attracted a multitude of
                 participants, and now significant amounts of money are
                 being exchanged by the day. This raises the need of
                 analyzing the blockchain to discover information
                 related to the nature of participants in transactions.
                 This study focuses on the identification for risky and
                 non-risky blocks in a blockchain. In this paper, the
                 proposed approach is to use ensemble learning with or
                 without feature selection using correlation-based
                 feature selection. Ensemble learning yielded good
                 results in the experiments, but class-wise analysis
                 reveals that ensemble learning with feature selection
                 improves even further. After training Machine Learning
                 classifiers on the dataset, we observe an improvement
                 in accuracy of 2-3\% and in F-score of 7-8\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ge:2022:KPL,
  author =       "Shengguo Ge and Siti Nurulain Mohd Rum",
  title =        "Key Points' Location in Infrared Images of the Human
                 Body Based on {Mscf-ResNet}",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "1",
  pages =        "15",
  day =          "27",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14010015",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/1/15",
  abstract =     "The human body generates infrared radiation through
                 the thermal movement of molecules. Based on this
                 phenomenon, infrared images of the human body are often
                 used for monitoring and tracking. Among them, key point
                 location on infrared images of the human body is an
                 important technology in medical infrared image
                 processing. However, the fuzzy edges, poor detail
                 resolution, and uneven brightness distribution of the
                 infrared image of the human body cause great
                 difficulties in positioning. Therefore, how to improve
                 the positioning accuracy of key points in human
                 infrared images has become the main research direction.
                 In this study, a multi-scale convolution fusion deep
                 residual network (Mscf-ResNet) model is proposed for
                 human body infrared image positioning. This model is
                 based on the traditional ResNet, changing the
                 single-scale convolution to multi-scale and fusing the
                 information of different receptive fields, so that the
                 extracted features are more abundant and the
                 degradation problem, caused by the excessively deep
                 network, is avoided. The experiments show that our
                 proposed method has higher key point positioning
                 accuracy than other methods. At the same time, because
                 the network structure of this paper is too deep, there
                 are too many parameters and a large volume of
                 calculations. Therefore, a more lightweight network
                 model is the direction of future research.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Han:2022:CFM,
  author =       "Junyan Han and Huili Shi and Longfei Chen and Hao Li
                 and Xiaoyuan Wang",
  title =        "The Car-Following Model and Its Applications in the
                 {V2X} Environment: a Historical Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "1",
  pages =        "14",
  day =          "27",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14010014",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/1/14",
  abstract =     "The application of vehicle-to-everything (V2X)
                 technology has resulted in the traffic environment
                 being different from how it was in the past. In the V2X
                 environment, the information perception ability of the
                 driver-vehicle unit is greatly enhanced. With V2X
                 technology, the driver-vehicle unit can obtain a
                 massive amount of traffic information and is able to
                 form a connection and interaction relationship between
                 multiple vehicles and themselves. In the traditional
                 car-following models, only the dual-vehicle interaction
                 relationship between the object vehicle and its
                 preceding vehicle was considered, making these models
                 unable to be employed to describe the car-following
                 behavior in the V2X environment. As one of the core
                 components of traffic flow theory, research on
                 car-following behavior needs to be further developed.
                 First, the development process of the traditional
                 car-following models is briefly reviewed. Second,
                 previous research on the impacts of V2X technology,
                 car-following models in the V2X environment, and the
                 applications of these models, such as the calibration
                 of the model parameters, the analysis of traffic flow
                 characteristics, and the methods that are used to
                 estimate a vehicle's energy consumption and emissions,
                 are comprehensively reviewed. Finally, the achievements
                 and shortcomings of these studies along with trends
                 that require further exploration are discussed. The
                 results that were determined here can provide a
                 reference for the further development of traffic flow
                 theory, personalized advanced driving assistance
                 systems, and anthropopathic autonomous-driving
                 vehicles.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Artem:2022:DFI,
  author =       "Volkov Artem and Kovalenko Vadim and Ibrahim A.
                 Elgendy and Ammar Muthanna and Andrey Koucheryavy",
  title =        "{DD-FoG}: Intelligent Distributed Dynamic {FoG}
                 Computing Framework",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "1",
  pages =        "13",
  day =          "27",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14010013",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/1/13",
  abstract =     "Nowadays, 5G networks are emerged and designed to
                 integrate all the achievements of mobile and fixed
                 communication networks, in which it can provide
                 ultra-high data speeds and enable a broad range of new
                 services with new cloud computing structures such as
                 fog and edge. In spite of this, the complex nature of
                 the system, especially with the varying network
                 conditions, variety of possible mechanisms, hardware,
                 and protocols, makes communication between these
                 technologies challenging. To this end, in this paper,
                 we proposed a new distributed and fog (DD-fog)
                 framework for software development, in which fog and
                 mobile edge computing (MEC) technologies and
                 microservices approach are jointly considered. More
                 specifically, based on the computational and network
                 capabilities, this framework provides a microservices
                 migration between fog structures and elements, in which
                 user query statistics in each of the fog structures are
                 considered. In addition, a new modern solution was
                 proposed for IoT-based application development and
                 deployment, which provides new time constraint services
                 like a tactile internet, autonomous vehicles, etc.
                 Moreover, to maintain quality service delivery
                 services, two different algorithms have been developed
                 to pick load points in the search mechanism for
                 congestion of users and find the fog migration node.
                 Finally, simulation results proved that the proposed
                 framework could reduce the execution time of the
                 microservice function by up to 70\% by deploying the
                 rational allocation of resources reasonably.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alowish:2022:TLA,
  author =       "Mazen Alowish and Yoshiaki Shiraishi and Masami Mohri
                 and Masakatu Morii",
  title =        "Three Layered Architecture for Driver Behavior
                 Analysis and Personalized Assistance with Alert Message
                 Dissemination in {5G} Envisioned Fog-{IoCV}",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "1",
  pages =        "12",
  day =          "27",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14010012",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/1/12",
  abstract =     "The Internet of connected vehicles (IoCV) has made
                 people more comfortable and safer while driving
                 vehicles. This technology has made it possible to
                 reduce road casualties; however, increased traffic and
                 uncertainties in environments seem to be limitations to
                 improving the safety of environments. In this paper,
                 driver behavior is analyzed to provide personalized
                 assistance and to alert surrounding vehicles in case of
                 emergencies. The processes involved in this research
                 are as follows. (i) Initially, the vehicles in an
                 environment are clustered to reduce the complexity in
                 analyzing a large number of vehicles.
                 Multi-criterion-based hierarchical correlation
                 clustering (MCB-HCC) is performed to dynamically
                 cluster vehicles. Vehicular motion is detected by
                 edge-assisted road side units (E-RSUs) by using an
                 attention-based residual neural network (AttResNet).
                 (ii) Driver behavior is analyzed based on the
                 physiological parameters of drivers, vehicle on-board
                 parameters, and environmental parameters, and driver
                 behavior is classified into different classes by
                 implementing a refined asynchronous advantage actor
                 critic (RA3C) algorithm for assistance generation.
                 (iii) If the driver's current state is found to be an
                 emergency state, an alert message is disseminated to
                 the surrounding vehicles in that area and to the
                 neighboring areas based on traffic flow by using jelly
                 fish search optimization (JSO). If a neighboring area
                 does not have a fog node, a virtual fog node is
                 deployed by executing a constraint-based quantum
                 entropy function to disseminate alert messages at
                 ultra-low latency. (iv) Personalized assistance is
                 provided to the driver based on behavior analysis to
                 assist the driver by using a multi-attribute utility
                 model, thereby preventing road accidents. The proposed
                 driver behavior analysis and personalized assistance
                 model are experimented on with the Network Simulator
                 3.26 tool, and performance was evaluated in terms of
                 prediction error, number of alerts, number of risk
                 maneuvers, accuracy, latency, energy consumption, false
                 alarm rate, safety score, and alert-message
                 dissemination efficiency.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Abdulsalam:2022:SPC,
  author =       "Yunusa Simpa Abdulsalam and Mustapha Hedabou",
  title =        "Security and Privacy in Cloud Computing: Technical
                 Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "1",
  pages =        "11",
  day =          "27",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14010011",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/1/11",
  abstract =     "Advances in the usage of information and communication
                 technologies (ICT) has given rise to the popularity and
                 success of cloud computing. Cloud computing offers
                 advantages and opportunities for business users to
                 migrate and leverage the scalability of the
                 pay-as-you-go price model. However, outsourcing
                 information and business applications to the cloud or a
                 third party raises security and privacy concerns, which
                 have become critical in adopting cloud implementation
                 and services. Researchers and affected organisations
                 have proposed different security approaches in the
                 literature to tackle the present security flaws. The
                 literature also provides an extensive review of
                 security and privacy issues in cloud computing.
                 Unfortunately, the works provided in the literature
                 lack the flexibility in mitigating multiple threats
                 without conflicting with cloud security objectives. The
                 literature has further focused on only highlighting
                 security and privacy issues without providing adequate
                 technical approaches to mitigate such security and
                 privacy threats. Conversely, studies that offer
                 technical solutions to security threats have failed to
                 explain how such security threats exist. This paper
                 aims to introduce security and privacy issues that
                 demand an adaptive solution approach without
                 conflicting with existing or future cloud security.
                 This paper reviews different works in the literature,
                 taking into account its adaptiveness in mitigating
                 against future reoccurring threats and showing how
                 cloud security conflicts have invalidated their
                 proposed models. The article further presents the
                 security threats surrounding cloud computing from a
                 user perspective using the STRIDE approach.
                 Additionally, it provides an analysis of different
                 inefficient solutions in the literature and offers
                 recommendations in terms of implementing a secure,
                 adaptive cloud environment.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Malik:2022:RTN,
  author =       "Faheem Ahmed Malik and Laurent Dala and Krishna
                 Busawon",
  title =        "Real-Time Nanoscopic Rider Safety System for Smart and
                 Green Mobility Based upon Varied Infrastructure
                 Parameters",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "1",
  pages =        "9",
  day =          "25",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14010009",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/1/9",
  abstract =     "To create a safe bicycle infrastructure system, this
                 article develops an intelligent embedded learning
                 system using a combination of deep neural networks. The
                 learning system is used as a case study in the
                 Northumbria region in England's northeast. It is made
                 up of three components: (a) input data unit, (b)
                 knowledge processing unit, and (c) output unit. It is
                 demonstrated that various infrastructure
                 characteristics influence bikers' safe interactions,
                 which is used to estimate the riskiest age and gender
                 rider groups. Two accurate prediction models are built,
                 with a male accuracy of 88 per cent and a female
                 accuracy of 95 per cent. The findings concluded that
                 different infrastructures pose varying levels of risk
                 to users of different ages and genders. Certain aspects
                 of the infrastructure are hazardous to all bikers.
                 However, the cyclist's characteristics determine the
                 level of risk that any infrastructure feature presents.
                 Following validation, the built learning system is
                 interoperable under various scenarios, including
                 current heterogeneous and future semi-autonomous and
                 autonomous transportation systems. The results
                 contribute towards understanding the risk variation of
                 various infrastructure types. The study's findings will
                 help to improve safety and lead to the construction of
                 a sustainable integrated cycling transportation
                 system.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ranaldi:2022:DCA,
  author =       "Leonardo Ranaldi and Francesca Fallucchi and Fabio
                 Massimo Zanzotto",
  title =        "Dis-Cover {AI} Minds to Preserve Human Knowledge",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "1",
  pages =        "10",
  day =          "24",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14010010",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/1/10",
  abstract =     "Modern AI technologies make use of statistical
                 learners that lead to self-empiricist logic, which,
                 unlike human minds, use learned non-symbolic
                 representations. Nevertheless, it seems that it is not
                 the right way to progress in AI. The structure of
                 symbols-the operations by which the intellectual
                 solution is realized-and the search for strategic
                 reference points evoke important issues in the analysis
                 of AI. Studying how knowledge can be represented
                 through methods of theoretical generalization and
                 empirical observation is only the latest step in a long
                 process of evolution. For many years, humans, seeing
                 language as innate, have carried out symbolic theories.
                 Everything seems to have skipped ahead with the advent
                 of Machine Learning. In this paper, after a long
                 analysis of history, the rule-based and the
                 learning-based vision, we would investigate the syntax
                 as possible meeting point between the different
                 learning theories. Finally, we propose a new vision of
                 knowledge in AI models based on a combination of rules,
                 learning, and human knowledge.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Volkau:2022:INS,
  author =       "Ihar Volkau and Abdul Mujeeb and Wenting Dai and
                 Marius Erdt and Alexei Sourin",
  title =        "The Impact of a Number of Samples on Unsupervised
                 Feature Extraction, Based on Deep Learning for
                 Detection Defects in Printed Circuit Boards",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "1",
  pages =        "8",
  day =          "23",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14010008",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/1/8",
  abstract =     "Deep learning provides new ways for defect detection
                 in automatic optical inspections (AOI). However, the
                 existing deep learning methods require thousands of
                 images of defects to be used for training the
                 algorithms. It limits the usability of these approaches
                 in manufacturing, due to lack of images of defects
                 before the actual manufacturing starts. In contrast, we
                 propose to train a defect detection unsupervised deep
                 learning model, using a much smaller number of images
                 without defects. We propose an unsupervised deep
                 learning model, based on transfer learning, that
                 extracts typical semantic patterns from defect-free
                 samples (one-class training). The model is built upon a
                 pre-trained VGG16 model. It is further trained on
                 custom datasets with different sizes of possible
                 defects (printed circuit boards and soldered joints)
                 using only small number of normal samples. We have
                 found that the defect detection can be performed very
                 well on a smooth background; however, in cases where
                 the defect manifests as a change of texture, the
                 detection can be less accurate. The proposed study uses
                 deep learning self-supervised approach to identify if
                 the sample under analysis contains any deviations (with
                 types not defined in advance) from normal design. The
                 method would improve the robustness of the AOI process
                 to detect defects.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2022:NPO,
  author =       "Jin Wang and Jun Luo",
  title =        "No Perfect Outdoors: Towards a Deep Profiling of
                 {GNSS}-Based Location Contexts",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "1",
  pages =        "7",
  day =          "23",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14010007",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/1/7",
  abstract =     "While both outdoor and indoor localization methods are
                 flourishing, how to properly marry them to offer
                 pervasive localizability in urban areas remains open.
                 Recently, proposals on indoor-outdoor detection have
                 made the first step towards such an integration, yet
                 complicated urban environments render such a binary
                 classification incompetent. Fortunately, the latest
                 developments in Android have granted us access to raw
                 GNSS measurements, which contain far more information
                 than commonly derived GPS location indicators. In this
                 paper, we explore these newly available measurements in
                 order to better characterize diversified urban
                 environments. Essentially, we tackle the challenges
                 introduced by the complex GNSS data and apply a deep
                 learning model to identify representations for
                 respective location contexts. We further develop two
                 preliminary applications of our deep profiling: one, we
                 offer a more fine-grained semantic classification than
                 binary indoor-outdoor detection; and two, we derive a
                 GPS error indicator that is more meaningful than that
                 provided by Google Maps. These results are all
                 corroborated by our extensive data collection and
                 trace-driven evaluations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Trajanovski:2022:ABB,
  author =       "Tolijan Trajanovski and Ning Zhang",
  title =        "An Automated Behaviour-Based Clustering of {IoT}
                 Botnets",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "1",
  pages =        "6",
  day =          "23",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14010006",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/1/6",
  abstract =     "The leaked IoT botnet source-codes have facilitated
                 the proliferation of different IoT botnet variants,
                 some of which are equipped with new capabilities and
                 may be difficult to detect. Despite the availability of
                 solutions for automated analysis of IoT botnet samples,
                 the identification of new variants is still very
                 challenging because the analysis results must be
                 manually interpreted by malware analysts. To overcome
                 this challenge, we propose an approach for automated
                 behaviour-based clustering of IoT botnet samples, aimed
                 to enable automatic identification of IoT botnet
                 variants equipped with new capabilities. In the
                 proposed approach, the behaviour of the IoT botnet
                 samples is captured using a sandbox and represented as
                 behaviour profiles describing the actions performed by
                 the samples. The behaviour profiles are vectorised
                 using TF-IDF and clustered using the DBSCAN algorithm.
                 The proposed approach was evaluated using a collection
                 of samples captured from IoT botnets propagating on the
                 Internet. The evaluation shows that the proposed
                 approach enables accurate automatic identification of
                 IoT botnet variants equipped with new capabilities,
                 which will help security researchers to investigate the
                 new capabilities, and to apply the investigation
                 findings for improving the solutions for detecting and
                 preventing IoT botnet infections.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gloor:2022:YFM,
  author =       "Peter A. Gloor and Andrea Fronzetti Colladon and Erkin
                 Altuntas and Cengiz Cetinkaya and Maximilian F. Kaiser
                 and Lukas Ripperger and Tim Schaefer",
  title =        "Your Face Mirrors Your Deepest Beliefs-Predicting
                 Personality and Morals through Facial Emotion
                 Recognition",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "1",
  pages =        "5",
  day =          "22",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14010005",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/1/5",
  abstract =     "Can we really ``read the mind in the eyes''? Moreover,
                 can AI assist us in this task? This paper answers these
                 two questions by introducing a machine learning system
                 that predicts personality characteristics of
                 individuals on the basis of their face. It does so by
                 tracking the emotional response of the individual's
                 face through facial emotion recognition (FER) while
                 watching a series of 15 short videos of different
                 genres. To calibrate the system, we invited 85 people
                 to watch the videos, while their emotional responses
                 were analyzed through their facial expression. At the
                 same time, these individuals also took four
                 well-validated surveys of personality characteristics
                 and moral values: the revised NEO FFI personality
                 inventory, the Haidt moral foundations test, the
                 Schwartz personal value system, and the domain-specific
                 risk-taking scale (DOSPERT). We found that personality
                 characteristics and moral values of an individual can
                 be predicted through their emotional response to the
                 videos as shown in their face, with an accuracy of up
                 to 86\% using gradient-boosted trees. We also found
                 that different personality characteristics are better
                 predicted by different videos, in other words, there is
                 no single video that will provide accurate predictions
                 for all personality characteristics, but it is the
                 response to the mix of different videos that allows for
                 accurate prediction.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fedotova:2022:AAS,
  author =       "Anastasia Fedotova and Aleksandr Romanov and Anna
                 Kurtukova and Alexander Shelupanov",
  title =        "Authorship Attribution of Social Media and Literary
                 {Russian}-Language Texts Using Machine Learning Methods
                 and Feature Selection",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "1",
  pages =        "4",
  day =          "22",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14010004",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/1/4",
  abstract =     "Authorship attribution is one of the important fields
                 of natural language processing (NLP). Its popularity is
                 due to the relevance of implementing solutions for
                 information security, as well as copyright protection,
                 various linguistic studies, in particular, researches
                 of social networks. The article is a continuation of
                 the series of studies aimed at the identification of
                 the Russian-language text's author and reducing the
                 required text volume. The focus of the study was aimed
                 at the attribution of textual data created as a product
                 of human online activity. The effectiveness of the
                 models was evaluated on the two Russian-language
                 datasets: literary texts and short comments from users
                 of social networks. Classical machine learning (ML)
                 algorithms, popular neural networks (NN) architectures,
                 and their hybrids, including convolutional neural
                 network (CNN), networks with long short-term memory
                 (LSTM), Bidirectional Encoder Representations from
                 Transformers (BERT), and fastText, that have not been
                 used in previous studies, were applied to solve the
                 problem. A particular experiment was devoted to the
                 selection of informative features using genetic
                 algorithms (GA) and evaluation of the classifier
                 trained on the optimal feature space. Using fastText or
                 a combination of support vector machine (SVM) with GA
                 reduced the time costs by half in comparison with deep
                 NNs with comparable accuracy. The average accuracy for
                 literary texts was 80.4\% using SVM combined with GA,
                 82.3\% using deep NNs, and 82.1\% using fastText. For
                 social media comments, results were 66.3\%, 73.2\%, and
                 68.1\%, respectively.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Salazar:2022:AML,
  author =       "Luiz Henrique A. Salazar and Valderi R. Q. Leithardt
                 and Wemerson Delcio Parreira and Anita M. da Rocha
                 Fernandes and Jorge Luis Vict{\'o}ria Barbosa and
                 S{\'e}rgio Duarte Correia",
  title =        "Application of Machine Learning Techniques to Predict
                 a {Patient}'s No-Show in the Healthcare Sector",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "1",
  pages =        "3",
  day =          "22",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14010003",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/1/3",
  abstract =     "The health sector faces a series of problems generated
                 by patients who miss their scheduled appointments. The
                 main challenge to this problem is to understand the
                 patient's profile and predict potential absences. The
                 goal of this work is to explore the main causes that
                 contribute to a patient's no-show and develop a
                 prediction model able to identify whether the patient
                 will attend their scheduled appointment or not. The
                 study was based on data from clinics that serve the
                 Unified Health System (SUS) at the University of Vale
                 do Itaja{\'\i} in southern Brazil. The model obtained
                 was tested on a real collected dataset with about 5000
                 samples. The best model result was performed by the
                 Random Forest classifier. It had the best Recall Rate
                 (0.91) and achieved an ROC curve rate of 0.969. This
                 research was approved and authorized by the Ethics
                 Committee of the University of Vale do Itaja{\'\i},
                 under opinion 4270,234, contemplating the General Data
                 Protection Law.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rodriguez-Diaz:2022:MLB,
  author =       "Nuria Rodriguez-Diaz and Decky Aspandi and Federico M.
                 Sukno and Xavier Binefa",
  title =        "Machine Learning-Based {Lie} Detector Applied to a
                 Novel Annotated Game Dataset",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "1",
  pages =        "2",
  day =          "21",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14010002",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/1/2",
  abstract =     "Lie detection is considered a concern for everyone in
                 their day-to-day life, given its impact on human
                 interactions. Thus, people normally pay attention to
                 both what their interlocutors are saying and to their
                 visual appearance, including the face, to find any
                 signs that indicate whether or not the person is
                 telling the truth. While automatic lie detection may
                 help us to understand these lying characteristics,
                 current systems are still fairly limited, partly due to
                 lack of adequate datasets to evaluate their performance
                 in realistic scenarios. In this work, we collect an
                 annotated dataset of facial images, comprising both 2D
                 and 3D information of several participants during a
                 card game that encourages players to lie. Using our
                 collected dataset, we evaluate several types of machine
                 learning-based lie detectors in terms of their
                 generalization, in person-specific and
                 cross-application experiments. We first extract both
                 handcrafted and deep learning-based features as
                 relevant visual inputs, then pass them into multiple
                 types of classifier to predict respective lie/non-lie
                 labels. Subsequently, we use several metrics to judge
                 the models' accuracy based on the models predictions
                 and ground truth. In our experiment, we show that
                 models based on deep learning achieve the highest
                 accuracy, reaching up to 57\% for the generalization
                 task and 63\% when applied to detect the lie to a
                 single participant. We further highlight the limitation
                 of the deep learning-based lie detector when dealing
                 with cross-application lie detection tasks. Finally,
                 this analysis along the proposed datasets would
                 potentially be useful not only from the perspective of
                 computational systems perspective (e.g., improving
                 current automatic lie prediction accuracy), but also
                 for other relevant application fields, such as health
                 practitioners in general medical counselings, education
                 in academic settings or finance in the banking sector,
                 where close inspections and understandings of the
                 actual intentions of individuals can be very
                 important.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Przytarski:2022:QPB,
  author =       "Dennis Przytarski and Christoph Stach and
                 Cl{\'e}mentine Gritti and Bernhard Mitschang",
  title =        "Query Processing in Blockchain Systems: Current State
                 and Future Challenges",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "1",
  pages =        "1",
  day =          "21",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14010001",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/1/1",
  abstract =     "When, in 2008, Satoshi Nakamoto envisioned the first
                 distributed database management system that relied on
                 cryptographically secured chain of blocks to store data
                 in an immutable and tamper-resistant manner, his
                 primary use case was the introduction of a digital
                 currency. Owing to this use case, the blockchain system
                 was geared towards efficient storage of data, whereas
                 the processing of complex queries, such as provenance
                 analyses of data history, is out of focus. The
                 increasing use of Internet of Things technologies and
                 the resulting digitization in many domains, however,
                 have led to a plethora of novel use cases for a secure
                 digital ledger. For instance, in the healthcare sector,
                 blockchain systems are used for the secure storage and
                 sharing of electronic health records, while the food
                 industry applies such systems to enable a reliable
                 food-chain traceability, e.g., to prove compliance with
                 cold chains. In these application domains, however,
                 querying the current state is not
                 sufficient-comprehensive history queries are required
                 instead. Due to these altered usage modes involving
                 more complex query types, it is questionable whether
                 today's blockchain systems are prepared for this type
                 of usage and whether such queries can be processed
                 efficiently by them. In our paper, we therefore
                 investigate novel use cases for blockchain systems and
                 elicit their requirements towards a data store in terms
                 of query capabilities. We reflect the state of the art
                 in terms of query support in blockchain systems and
                 assess whether it is capable of meeting the
                 requirements of such more sophisticated use cases. As a
                 result, we identify future research challenges with
                 regard to query processing in blockchain systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kianersi:2022:ERM,
  author =       "Darius Kianersi and Suraj Uppalapati and Anirudh
                 Bansal and Jeremy Straub",
  title =        "Evaluation of a Reputation Management Technique for
                 Autonomous Vehicles",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "31",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/31",
  abstract =     "Future autonomous vehicles will rely heavily on
                 sharing and communicating information with other
                 vehicles to maximize their efficiency. These
                 interactions, which will likely include details about
                 the positions of surrounding vehicles and obstacles on
                 the road, are essential to their decision-making and
                 the prevention of accidents. However, malicious
                 vehicles-those that intentionally communicate false
                 information-have the capacity to adversely influence
                 other vehicles in the network. This paper presents and
                 evaluates a reputation management system, capable of
                 identifying malicious actors, to mitigate their effects
                 on the vehicle network. The viability of multiple
                 report weighting schemes to calculate reputation is
                 evaluated through a simulation, and a blockchain-based
                 backend for the reputation management system to
                 securely maintain and communicate reputation data is
                 proposed. Storage and computational challenges are
                 considered. This paper shows that weighting schemas,
                 related to the number and reputation of witnesses,
                 positively affect the accuracy of the model and are
                 able to identify malicious vehicles in a network with
                 consistent accuracy and scalability.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tu:2022:TOB,
  author =       "Youpeng Tu and Haiming Chen and Linjie Yan and Xinyan
                 Zhou",
  title =        "Task Offloading Based on {LSTM} Prediction and Deep
                 Reinforcement Learning for Efficient Edge Computing in
                 {IoT}",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "30",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Jan 19 05:45:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/30",
  abstract =     "In IoT (Internet of Things) edge computing, task
                 offloading can lead to additional transmission delays
                 and transmission energy consumption. To reduce the cost
                 of resources required for task offloading and improve
                 the utilization of server resources, in this paper, we
                 model the task offloading problem as a joint decision
                 making problem for cost minimization, which integrates
                 the processing latency, processing energy consumption,
                 and the task throw rate of latency-sensitive tasks. The
                 Online Predictive Offloading (OPO) algorithm based on
                 Deep Reinforcement Learning (DRL) and Long Short-Term
                 Memory (LSTM) networks is proposed to solve the above
                 task offloading decision problem. In the training phase
                 of the model, this algorithm predicts the load of the
                 edge server in real-time with the LSTM algorithm, which
                 effectively improves the convergence accuracy and
                 convergence speed of the DRL algorithm in the
                 offloading process. In the testing phase, the LSTM
                 network is used to predict the characteristics of the
                 next task, and then the computational resources are
                 allocated for the task in advance by the DRL decision
                 model, thus further reducing the response delay of the
                 task and enhancing the offloading performance of the
                 system. The experimental evaluation shows that this
                 algorithm can effectively reduce the average latency by
                 6.25\%, the offloading cost by 25.6\%, and the task
                 throw rate by 31.7\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Pathmaperuma:2022:CUA,
  author =       "Madushi H. Pathmaperuma and Yogachandran
                 Rahulamathavan and Safak Dogan and Ahmet Kondoz",
  title =        "{CNN} for User Activity Detection Using Encrypted
                 In-App Mobile Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "67",
  day =          "21",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020067",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/67",
  abstract =     "In this study, a simple yet effective framework is
                 proposed to characterize fine-grained in-app user
                 activities performed on mobile applications using a
                 convolutional neural network (CNN). The proposed
                 framework uses a time window-based approach to split
                 the activity's encrypted traffic flow into segments, so
                 that in-app activities can be identified just by
                 observing only a part of the activity-related encrypted
                 traffic. In this study, matrices were constructed for
                 each encrypted traffic flow segment. These matrices
                 acted as input into the CNN model, allowing it to learn
                 to differentiate previously trained (known) and
                 previously untrained (unknown) in-app activities as
                 well as the known in-app activity type. The proposed
                 method extracts and selects salient features for
                 encrypted traffic classification. This is the
                 first-known approach proposing to filter unknown
                 traffic with an average accuracy of 88\%. Once the
                 unknown traffic is filtered, the classification
                 accuracy of our model would be 92\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Krouska:2022:PEA,
  author =       "Akrivi Krouska and Katerina Kabassi and Christos
                 Troussas and Cleo Sgouropoulou",
  title =        "Personalizing Environmental Awareness through
                 Smartphones Using {AHP} and {PROMETHEE II}",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "66",
  day =          "21",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020066",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/66",
  abstract =     "Environmental awareness refers to the understanding of
                 the importance of protecting the natural environment.
                 Digital technologies can play an important role in
                 raising awareness of environmental issues. In view of
                 this compelling need, this paper presents a novel way
                 to promote environmental awareness with the use of
                 smartphones. To achieve this, it employs
                 personalization techniques, and specifically the
                 Analytic Hierarchy Process (AHP) and PROMETHEE II. In
                 more detail, the mobile application incorporates a user
                 model that holds information, such as location (city,
                 mountain, sea, etc.), age, interests, needs and
                 indicators of waste management, economy of natural
                 resources, general environmental protection, and
                 biodiversity. At the first interaction of the user with
                 the application, the user model is initialized; then,
                 the system uses AHP and PROMETHEE II to provide
                 personalized advice to users in order to help them
                 raise their environmental awareness. The criteria, used
                 to evaluate environmental advice, include the current
                 location, living environment, habits, interests, needs,
                 age, and seasonal suitability of the user. The novelty
                 of this paper is the combination of AHP and PROMETHEE
                 II for personalizing the environmental awareness using
                 mobile technologies, taking into consideration the user
                 profile as well as the surrounding area where the user
                 is at the time that the advice is provided. The
                 presented application has been evaluated regarding the
                 system usefulness and environmental awareness. The
                 findings indicate the high acceptance of this approach
                 and its positive impact on users' attitude and behavior
                 with regard to reducing their environmental
                 footprint.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fraga:2022:FSD,
  author =       "Martin Fraga and Mat{\'\i}as Micheletto and Andr{\'e}s
                 Llin{\'a}s and Rodrigo Santos and Paula Zabala",
  title =        "Flow Scheduling in Data Center Networks with Time and
                 Energy Constraints: a Software-Defined Network
                 Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "65",
  day =          "21",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020065",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/65",
  abstract =     "Flow scheduling in Data Center Networks (DCN) is a hot
                 topic as cloud computing and virtualization are
                 becoming the dominant paradigm in the increasing demand
                 of digital services. Within the cost of the DCN, the
                 energy demands associated with the network
                 infrastructure represent an important portion. When
                 flows have temporal restrictions, the scheduling with
                 path selection to reduce the number of active switching
                 devices is a NP-hard problem as proven in the
                 literature. In this paper, an heuristic approach to
                 schedule real-time flows in data-centers is proposed,
                 optimizing the temporal requirements while reducing the
                 energy consumption in the network infrastructure via a
                 proper selection of the paths. The experiments show
                 good performance of the solutions found in relation to
                 exact solution approximations based on an integer
                 linear programming model. The possibility of
                 programming the network switches allows the dynamic
                 schedule of paths of flows under the software-defined
                 network management.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Qian:2022:DTC,
  author =       "Cheng Qian and Xing Liu and Colin Ripley and Mian Qian
                 and Fan Liang and Wei Yu",
  title =        "Digital Twin --- Cyber Replica of Physical Things:
                 Architecture, Applications and Future Research
                 Directions",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "64",
  day =          "21",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020064",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/64",
  abstract =     "The Internet of Things (IoT) connects massive smart
                 devices to collect big data and carry out the
                 monitoring and control of numerous things in
                 cyber-physical systems (CPS). By leveraging machine
                 learning (ML) and deep learning (DL) techniques to
                 analyze the collected data, physical systems can be
                 monitored and controlled effectively. Along with the
                 development of IoT and data analysis technologies, a
                 number of CPS (smart grid, smart transportation, smart
                 manufacturing, smart cities, etc.) adopt IoT and data
                 analysis technologies to improve their performance and
                 operations. Nonetheless, directly manipulating or
                 updating the real system has inherent risks. Thus,
                 creating a digital clone of a real physical system,
                 denoted as a Digital Twin (DT), is a viable strategy.
                 Generally speaking, a DT is a data-driven software and
                 hardware emulation platform, which is a cyber replica
                 of physical systems. Meanwhile, a DT describes a
                 specific physical system and tends to achieve the
                 functions and use cases of physical systems. Since DT
                 is a complex digital system, finding a way to
                 effectively represent a variety of things in timely and
                 efficient manner poses numerous challenges to the
                 networking, computing, and data analytics for IoT.
                 Furthermore, the design of a DT for IoT systems must
                 consider numerous exceptional requirements (e.g.,
                 latency, reliability, safety, scalability, security,
                 and privacy). To address such challenges, the
                 thoughtful design of DTs offers opportunities for novel
                 and interdisciplinary research efforts. To address the
                 aforementioned problems and issues, in this paper, we
                 first review the architectures of DTs, data
                 representation, and communication protocols. We then
                 review existing efforts on applying DT into IoT
                 data-driven smart systems, including the smart grid,
                 smart transportation, smart manufacturing, and smart
                 cities. Further, we summarize the existing challenges
                 from CPS, data science, optimization, and security and
                 privacy perspectives. Finally, we outline possible
                 future research directions from the perspectives of
                 performance, new DT-driven services, model and
                 learning, and security and privacy.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Almeida:2022:EBC,
  author =       "Fernando Almeida and Jorge Sim{\~o}es and S{\'e}rgio
                 Lopes",
  title =        "Exploring the Benefits of Combining {DevOps} and
                 {Agile}",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "63",
  day =          "19",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020063",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/63",
  abstract =     "The combined adoption of Agile and DevOps enables
                 organizations to cope with the increasing complexity of
                 managing customer requirements and requests. It fosters
                 the emergence of a more collaborative and Agile
                 framework to replace the waterfall models applied to
                 software development flow and the separation of
                 development teams from operations. This study aims to
                 explore the benefits of the combined adoption of both
                 models. A qualitative methodology is adopted by
                 including twelve case studies from international
                 software engineering companies. Thematic analysis is
                 employed in identifying the benefits of the combined
                 adoption of both paradigms. The findings reveal the
                 existence of twelve benefits, highlighting the
                 automation of processes, improved communication between
                 teams, and reduction in time to market through process
                 integration and shorter software delivery cycles.
                 Although they address different goals and challenges,
                 the Agile and DevOps paradigms when properly combined
                 and aligned can offer relevant benefits to
                 organizations. The novelty of this study lies in the
                 systematization of the benefits of the combined
                 adoption of Agile and DevOps considering multiple
                 perspectives of the software engineering business
                 environment.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zubani:2022:PCD,
  author =       "Matteo Zubani and Luca Sigalini and Ivan Serina and
                 Luca Putelli and Alfonso E. Gerevini and Mattia
                 Chiari",
  title =        "A Performance Comparison of Different Cloud-Based
                 Natural Language Understanding Services for an
                 {Italian} e-Learning Platform",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "62",
  day =          "18",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020062",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/62",
  abstract =     "During the COVID-19 pandemic, the corporate online
                 training sector has increased exponentially and online
                 course providers had to implement innovative solutions
                 to be more efficient and provide a satisfactory
                 service. This paper considers a real case study in
                 implementing a chatbot, which answers frequently asked
                 questions from learners on an Italian e-learning
                 platform that provides workplace safety courses to
                 several business customers. Having to respond quickly
                 to the increase in the courses activated, the company
                 decided to develop a chatbot using a cloud-based
                 service currently available on the market. These
                 services are based on Natural Language Understanding
                 (NLU) engines, which deal with identifying information
                 such as entities and intentions from the sentences
                 provided as input. To integrate a chatbot in an
                 e-learning platform, we studied the performance of the
                 intent recognition task of the major NLU platforms
                 available on the market with an in-depth comparison,
                 using an Italian dataset provided by the owner of the
                 e-learning platform. We focused on intent recognition,
                 carried out several experiments and evaluated
                 performance in terms of F-score, error rate, response
                 time, and robustness of all the services selected. The
                 chatbot is currently in production, therefore we
                 present a description of the system implemented and its
                 results on the original users' requests.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Marabissi:2022:INA,
  author =       "Dania Marabissi and Lorenzo Mucchi and Andrea
                 Stomaci",
  title =        "{IoT} Nodes Authentication and {ID} Spoofing Detection
                 Based on Joint Use of Physical Layer Security and
                 Machine Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "61",
  day =          "17",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020061",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/61",
  abstract =     "The wide variety of services and applications that
                 shall be supported by future wireless systems will lead
                 to a high amount of sensitive data exchanged via radio,
                 thus introducing a significant challenge for security.
                 Moreover, in new networking paradigms, such as the
                 Internet of Things, traditional methods of security may
                 be difficult to implement due to the radical change of
                 requirements and constraints. In such contexts,
                 physical layer security is a promising additional means
                 to realize communication security with low complexity.
                 In particular, this paper focuses on node
                 authentication and spoofing detection in an actual
                 wireless sensor network (WSN), where multiple nodes
                 communicate with a sink node. Nodes are in fixed
                 positions, but the communication channels varies due to
                 the scatterers' movement. In the proposed security
                 framework, the sink node is able to perform a
                 continuous authentication of nodes during communication
                 based on wireless fingerprinting. In particular, a
                 machine learning approach is used for authorized nodes
                 classification by means of the identification of
                 specific attributes of their wireless channel. Then
                 classification results are compared with the node ID in
                 order to detect if the message has been generated by a
                 node other than its claimed source. Finally, in order
                 to increase the spoofing detection performance in small
                 networks, the use of low-complexity sentinel nodes is
                 proposed here. Results show the good performance of the
                 proposed method that is suitable for actual
                 implementation in a WSN.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hu:2022:SVD,
  author =       "Zhixi Hu and Yi Zhu and Xiaoying Chen and Yu Zhao",
  title =        "Safety Verification of Driving Resource Occupancy
                 Rules Based on Functional Language",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "60",
  day =          "17",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020060",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/60",
  abstract =     "Autonomous driving is a safety-critical system, and
                 the occupancy of its environmental resources affects
                 the safety of autonomous driving. In view of the lack
                 of safety verification of environmental resource
                 occupation rules in autonomous driving, this paper
                 proposes a verification method of automatic driving
                 model based on functional language through CSP M.
                 Firstly, the modeling and verification framework of an
                 autopilot model based on CSP M is given. Secondly, the
                 process algebra definition of CSP M is given. Thirdly,
                 the typical single loop environment model in automatic
                 driving is abstracted, and the mapping method from
                 automatic driving model to CSP is described in detail
                 for the automatic driving environment and the typical
                 collision, overtaking, lane change and other scenes
                 involved. Finally, the autopilot model of the single
                 loop is mapped to CSP M, and the application effect of
                 this method is discussed by using FDR tool. Experiments
                 show that this method can verify the safety of
                 autonomous driving resources, thereby improving the
                 reliability of the autonomous driving model.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Adoga:2022:NFV,
  author =       "Haruna Umar Adoga and Dimitrios P. Pezaros",
  title =        "Network Function Virtualization and Service Function
                 Chaining Frameworks: a Comprehensive Review of
                 Requirements, Objectives, Implementations, and Open
                 Research Challenges",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "59",
  day =          "15",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020059",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/59",
  abstract =     "Network slicing has become a fundamental property for
                 next-generation networks, especially because an
                 inherent part of 5G standardisation is the ability for
                 service providers to migrate some or all of their
                 network services to a virtual network infrastructure,
                 thereby reducing both capital and operational costs.
                 With network function virtualisation (NFV), network
                 functions (NFs) such as firewalls, traffic load
                 balancers, content filters, and intrusion detection
                 systems (IDS) are either instantiated on virtual
                 machines (VMs) or lightweight containers, often chained
                 together to create a service function chain (SFC). In
                 this work, we review the state-of-the-art NFV and SFC
                 implementation frameworks and present a taxonomy of the
                 current proposals. Our taxonomy comprises three major
                 categories based on the primary objectives of each of
                 the surveyed frameworks: (1) resource allocation and
                 service orchestration, (2) performance tuning, and (3)
                 resilience and fault recovery. We also identify some
                 key open research challenges that require further
                 exploration by the research community to achieve
                 scalable, resilient, and high-performance NFV/SFC
                 deployments in next-generation networks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mahapatra:2022:FBP,
  author =       "Tanmaya Mahapatra and Syeeda Nilofer Banoo",
  title =        "Flow-Based Programming for Machine Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "58",
  day =          "15",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020058",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/58",
  abstract =     "Machine Learning (ML) has gained prominence and has
                 tremendous applications in fields like medicine,
                 biology, geography and astrophysics, to name a few.
                 Arguably, in such areas, it is used by domain experts,
                 who are not necessarily skilled-programmers. Thus, it
                 presents a steep learning curve for such domain experts
                 in programming ML applications. To overcome this and
                 foster widespread adoption of ML techniques, we propose
                 to equip them with domain-specific graphical tools.
                 Such tools, based on the principles of flow-based
                 programming paradigm, would support the graphical
                 composition of ML applications at a higher level of
                 abstraction and auto-generation of target code.
                 Accordingly, (i) we have modelled ML algorithms as
                 composable components; (ii) described an approach to
                 parse a flow created by connecting several such
                 composable components and use an API-based code
                 generation technique to generate the ML application. To
                 demonstrate the feasibility of our conceptual approach,
                 we have modelled the APIs of Apache Spark ML as
                 composable components and validated it in three
                 use-cases. The use-cases are designed to capture the
                 ease of program specification at a higher abstraction
                 level, easy parametrisation of ML APIs, auto-generation
                 of the ML application and auto-validation of the
                 generated model for better prediction accuracy.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{DOrtona:2022:OSM,
  author =       "Cristian D'Ortona and Daniele Tarchi and Carla
                 Raffaelli",
  title =        "Open-Source {MQTT}-Based End-to-End {IoT} System for
                 Smart City Scenarios",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "57",
  day =          "15",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020057",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/57",
  abstract =     "Many innovative services are emerging based on the
                 Internet of Things (IoT) technology, aiming at
                 fostering better sustainability of our cities. New
                 solutions integrating Information and Communications
                 Technologies (ICTs) with sustainable transport media
                 are encouraged by several public administrations in the
                 so-called Smart City scenario, where heterogeneous
                 users in city roads call for safer mobility. Among
                 several possible applications, recently, there has been
                 a lot of attention on the so-called Vulnerable Road
                 Users (VRUs), such as pedestrians or bikers. They can
                 be equipped with wearable sensors that are able to
                 communicate their data through a chain of devices
                 towards the cloud for agile and effective control of
                 their mobility. This work describes a complete
                 end-to-end IoT system implemented through the
                 integration of different complementary technologies,
                 whose main purpose is to monitor the information
                 related to road users generated by wearable sensors.
                 The system has been implemented using an ESP32
                 micro-controller connected to the sensors and
                 communicating through a Bluetooth Low Energy (BLE)
                 interface with an Android device, which is assumed to
                 always be carried by any road user. Based on this, we
                 use it as a gateway node, acting as a real-time
                 asynchronous publisher of a Message Queue Telemetry
                 Transport (MQTT) protocol chain. The MQTT broker is
                 configured on a Raspberry PI device and collects sensor
                 data to be sent to a web-based control panel that
                 performs data monitoring and processing. All the
                 architecture modules have been implemented through
                 open-source technologies. The analysis of the BLE
                 packet exchange has been carried out by resorting to
                 the Wireshark packet analyzer. In addition, a
                 feasibility analysis has been carried out by showing
                 the capability of the proposed solution to show the
                 values gathered through the sensors on a remote
                 dashboard. The developed system is publicly available
                 to allow the possible integration of other modules for
                 additional Smart City services or extension to further
                 ICT applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rajendran:2022:IES,
  author =       "Venushini Rajendran and R Kanesaraj Ramasamy and
                 Wan-Noorshahida Mohd-Isa",
  title =        "Improved Eagle Strategy Algorithm for Dynamic {Web}
                 Service Composition in the {IoT}: a Conceptual
                 Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "56",
  day =          "15",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020056",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/56",
  abstract =     "The Internet of Things (IoT) is now expanding and
                 becoming more popular in most industries, which leads
                 to vast growth in cloud computing. The architecture of
                 IoT is integrated with cloud computing through web
                 services. Recently, Dynamic Web Service Composition
                 (DWSC) has been implemented to fulfill the IoT and
                 business processes. In recent years, the number of
                 cloud services has multiplied, resulting in cloud
                 services providing similar services with similar
                 functionality but varying in Quality of Services (QoS),
                 for instance, on the response time of web services;
                 however, existing methods are insufficient in solving
                 large-scale repository issues. Bio-inspired algorithm
                 methods have shown better performance in solving the
                 large-scale service composition problems, unlike
                 deterministic algorithms, which are restricted. Thus,
                 an improved eagle strategy algorithm method is proposed
                 to increase the performance that directly indicates an
                 improvement in computation time in large-scale DWSC in
                 a cloud-based platform and on both functional and
                 non-functional attributes of services. By proposing the
                 improved bio-inspired method, the computation time can
                 be improved, especially in a large-scale repository of
                 IoT.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Muthavhine:2022:SID,
  author =       "Khumbelo Muthavhine and Mbuyu Sumbwanyambe",
  title =        "Securing {IoT} Devices against Differential-Linear
                 ({DL}) Attack Used on {Serpent} Algorithm",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "55",
  day =          "13",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020055",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/55",
  abstract =     "Cryptographic algorithms installed on Internet of
                 Things (IoT) devices suffer many attacks. Some of these
                 attacks include the differential linear attack (DL).
                 The DL attack depends on the computation of the
                 probability of differential-linear characteristics,
                 which yields a Differential-Linear Connectivity Table (
                 DLCT ). The DLCT is a probability table that provides
                 an attacker many possibilities of guessing the
                 cryptographic keys of any algorithm such as Serpent. In
                 essence, the attacker firstly constructs a DLCT by
                 using building blocks such as Substitution Boxes
                 (S-Boxes) found in many algorithms' architectures. In
                 depth, this study focuses on securing IoT devices
                 against DL attacks used on Serpent algorithms by using
                 three magic numbers mapped on a newly developed
                 mathematical function called Blocker, which will be
                 added on Serpent's infrastructure before being
                 installed in IoT devices. The new S-Boxes with 32-bit
                 output were generated to replace the original Serpent's
                 S-Boxes with 4-bit output. The new S-Boxes were also
                 inserted in Serpent's architecture. This novel approach
                 of using magic numbers and the Blocker Function worked
                 successfully in this study. The results demonstrated an
                 algorithm for which its S-Box is composed of a
                 4-bit-output that is more vulnerable to being attacked
                 than an algorithm in which its S-Box comprises 32-bit
                 outputs. The novel approach of using a Blocker,
                 developed by three magic numbers and 32-bits output
                 S-Boxes, successfully blocked the construction of DLCT
                 and DL attacks. This approach managed to secure the
                 Serpent algorithm installed on IoT devices against DL
                 attacks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chen:2022:AVR,
  author =       "Ning Chen and Yu Chen",
  title =        "Anomalous Vehicle Recognition in Smart Urban Traffic
                 Monitoring as an Edge Service",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "54",
  day =          "10",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020054",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/54",
  abstract =     "The past decades witnessed an unprecedented
                 urbanization and the proliferation of modern
                 information and communication technologies (ICT), which
                 makes the concept of Smart City feasible. Among various
                 intelligent components, smart urban transportation
                 monitoring is an essential part of smoothly operational
                 smart cities. Although there is fast development of
                 Smart Cities and the growth of Internet of Things
                 (IoT), real-time anomalous behavior detection in
                 Intelligent Transportation Systems (ITS) is still
                 challenging. Because of multiple advanced features
                 including flexibility, safety, and ease of
                 manipulation, quadcopter drones have been widely
                 adopted in many areas, from service improvement to
                 urban surveillance, and data collection for scientific
                 research. In this paper, a Smart Urban traffic
                 Monitoring (SurMon) scheme is proposed employing drones
                 following an edge computing paradigm. A dynamic video
                 stream processing scheme is proposed to meet the
                 requirements of real-time information processing and
                 decision-making at the edge. Specifically, we propose
                 to identify anomalous vehicle behaviors in real time by
                 creatively applying the multidimensional Singular
                 Spectrum Analysis (mSSA) technique in space to detect
                 the different vehicle behaviors on roads. Multiple
                 features of vehicle behaviors are fed into channels of
                 the mSSA procedure. Instead of trying to create and
                 define a database of normal activity patterns of
                 vehicles on the road, the anomaly detection is
                 reformatted as an outlier identifying problem. Then, a
                 cascaded Capsules Network is designed to predict
                 whether the behavior is a violation. An extensive
                 experimental study has been conducted and the results
                 have validated the feasibility and effectiveness of the
                 SurMon scheme.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Office:2022:ARF,
  author =       "Future Internet Editorial Office",
  title =        "Acknowledgment to Reviewers of {{\booktitle{Future
                 Internet}}} in 2021",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "53",
  day =          "10",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020053",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/53",
  abstract =     "The past decades witnessed an unprecedented
                 urbanization and the proliferation of modern
                 information and communication technologies (ICT), which
                 makes the concept of Smart City feasible. Among various
                 intelligent components, smart urban transportation
                 monitoring is an essential part of smoothly operational
                 smart cities. Although there is fast development of
                 Smart Cities and the growth of Internet of Things
                 (IoT), real-time anomalous behavior detection in
                 Intelligent Transportation Systems (ITS) is still
                 challenging. Because of multiple advanced features
                 including flexibility, safety, and ease of
                 manipulation, quadcopter drones have been widely
                 adopted in many areas, from service improvement to
                 urban surveillance, and data collection for scientific
                 research. In this paper, a Smart Urban traffic
                 Monitoring (SurMon) scheme is proposed employing drones
                 following an edge computing paradigm. A dynamic video
                 stream processing scheme is proposed to meet the
                 requirements of real-time information processing and
                 decision-making at the edge. Specifically, we propose
                 to identify anomalous vehicle behaviors in real time by
                 creatively applying the multidimensional Singular
                 Spectrum Analysis (mSSA) technique in space to detect
                 the different vehicle behaviors on roads. Multiple
                 features of vehicle behaviors are fed into channels of
                 the mSSA procedure. Instead of trying to create and
                 define a database of normal activity patterns of
                 vehicles on the road, the anomaly detection is
                 reformatted as an outlier identifying problem. Then, a
                 cascaded Capsules Network is designed to predict
                 whether the behavior is a violation. An extensive
                 experimental study has been conducted and the results
                 have validated the feasibility and effectiveness of the
                 SurMon scheme.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Marir:2022:SBF,
  author =       "Souad Marir and Faiza Belala and Nabil Hameurlain",
  title =        "A Strategy-Based Formal Approach for Fog Systems
                 Analysis",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "52",
  day =          "09",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020052",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/52",
  abstract =     "Fog systems are a new emergent technology having a
                 wide range of architectures and pronounced needs making
                 their design complex. Consequently, the design of fog
                 systems is crucial, including service portability and
                 interoperability between the various elements of a
                 system being the most essential aspects of fog
                 computing. This article presents a fog system
                 cross-layer architecture as a first step of such a
                 design to provide a graphical and conceptual
                 description. Then, a BiAgents* (Bigraphical Agents)
                 formal model is defined to provide a rigorous
                 description of physical, virtual, and behavioural
                 aspects of Fog systems. Besides, this formalisation is
                 implemented and executed under a Maude strategy system.
                 The proposed approach is illustrated through a case
                 study: an airport terminal Luggage Inspection System
                 (LIS) while checking the correctness of its relevant
                 properties: the portability of data and their
                 interoperability. The integration of the Maude
                 strategies in the rewriting of Fog system states made
                 it possible to guide the execution of the model and its
                 analysis.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mourao:2022:ILS,
  author =       "Helmer Augusto de Souza Mour{\~a}o and Hor{\'a}cio
                 Antonio Braga Fernandes de Oliveira",
  title =        "Indoor Localization System Using Fingerprinting and
                 Novelty Detection for Evaluation of Confidence",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "51",
  day =          "07",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020051",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/51",
  abstract =     "Indoor localization systems are used to locate mobile
                 devices inside buildings where traditional solutions,
                 such as the Global Navigation Satellite Systems (GNSS),
                 do not work well due to the lack of direct visibility
                 to the satellites. Fingerprinting is one of the most
                 known solutions for indoor localization. It is based on
                 the Received Signal Strength (RSS) of packets
                 transmitted among mobile devices and anchor nodes.
                 However, RSS values are known to be unstable and noisy
                 due to obstacles and the dynamicity of the scenarios,
                 causing inaccuracies in the position estimations. This
                 instability and noise often cause the system to
                 indicate a location that it is not quite sure is
                 correct, although it is the most likely based on the
                 calculations. This property of RSS can cause algorithms
                 to return a localization with a low confidence level.
                 If we could choose more reliable results, we would have
                 an overall result with better quality. Thus, in our
                 solution, we created a checking phase of the confidence
                 level of the localization result. For this, we use the
                 prediction probability provided by KNN and the novelty
                 detection to discard classifications that are not very
                 reliable and often wrong. In this work, we propose
                 LocFiND (Localization using Fingerprinting and Novelty
                 Detection), a fingerprint-based solution that uses
                 prediction probability and novelty detection to
                 evaluate the confidence of the estimated positions and
                 mitigate inaccuracies caused by RSS in the localization
                 phase. We implemented our solution in a real-world,
                 large-scale school area using Bluetooth-based devices.
                 Our performance evaluation shows considerable
                 improvement in the localization accuracy and stability
                 while discarding only a few, low confidence
                 estimations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhang:2022:JCN,
  author =       "Yaojie Zhang and Huahu Xu and Junsheng Xiao and Minjie
                 Bian",
  title =        "{JoSDW}: Combating Noisy Labels by Dynamic Weight",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "50",
  day =          "02",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020050",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/50",
  abstract =     "The real world is full of noisy labels that lead
                 neural networks to perform poorly because deep neural
                 networks (DNNs) are prone to overfitting label noise.
                 Noise label training is a challenging problem relating
                 to weakly supervised learning. The most advanced
                 existing methods mainly adopt a small loss sample
                 selection strategy, such as selecting the small loss
                 part of the sample for network model training. However,
                 the previous literature stopped here, neglecting the
                 performance of the small loss sample selection strategy
                 while training the DNNs, as well as the performance of
                 different stages, and the performance of the
                 collaborative learning of the two networks from
                 disagreement to an agreement, and making a second
                 classification based on this. We train the network
                 using a comparative learning method. Specifically, a
                 small loss sample selection strategy with dynamic
                 weight is designed. This strategy increases the
                 proportion of agreement based on network predictions,
                 gradually reduces the weight of the complex sample, and
                 increases the weight of the pure sample at the same
                 time. A large number of experiments verify the
                 superiority of our method.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ang:2022:TCI,
  author =       "Kenneth Li Minn Ang and Jasmine Kah Phooi Seng and
                 Ericmoore Ngharamike",
  title =        "Towards Crowdsourcing {Internet of Things}
                 ({Crowd-IoT}): Architectures, Security and
                 Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "49",
  day =          "31",
  month =        jan,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020049",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/49",
  abstract =     "Crowdsourcing can play an important role in the
                 Internet of Things (IoT) applications for information
                 sensing and gathering where the participants are
                 equipped with geolocated devices. Mobile crowdsourcing
                 can be seen as a new paradigm contributing to the
                 development of the IoT. They can be merged to form a
                 new and essential platform in crowdsourcing IoT
                 paradigm for data collection from different sources and
                 communication mediums. This paper presents a
                 comprehensive survey for this new Crowdsourcing IoT
                 paradigm from four different perspectives: (1)
                 Architectures for Crowd-IoT; (2) Trustworthy, Privacy
                 and Security for Crowd-IoT; (3) Resources, Sharing,
                 Storage and Energy Considerations for Crowd-IoT; and
                 (4) Applications for Crowd-IoT. This survey paper aims
                 to increase awareness and encourage continuing
                 developments and innovations from the research
                 community and industry towards the Crowdsourcing IoT
                 paradigm.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Herouala:2022:CTB,
  author =       "Abdelkader Tayeb Herouala and Chaker Abdelaziz
                 Kerrache and Benameur Ziani and Carlos T. Calafate and
                 Nasreddine Lagraa and Abdou el Karim Tahari",
  title =        "Controlling the Trade-Off between Resource Efficiency
                 and User Satisfaction in {NDNs} Based on Na{\"\i}ve
                 {Bayes} Data Classification and {Lagrange} Method",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "48",
  day =          "31",
  month =        jan,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020048",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/48",
  abstract =     "This paper addresses the fundamental problem of the
                 trade-off between resource efficiency and user
                 satisfaction in the limited environments of Named Data
                 Networks (NDNs). The proposed strategy is named RADC
                 (Resource Allocation based Data Classification), which
                 aims at managing such trade-off by controlling the
                 system's fairness index. To this end, a machine
                 learning technique based on Multinomial Na{\"\i}ve
                 Bayes is used to classify the received contents. Then,
                 an adaptive resource allocation strategy based on the
                 Lagrange utility function is proposed. To cache the
                 received content, an adequate content placement and a
                 replacement mechanism are enforced. Simulation at the
                 system level shows that this strategy could be a
                 powerful tool for administrators to manage the
                 trade-off between efficiency and user satisfaction.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Xiong:2022:RPB,
  author =       "Huanliang Xiong and Muxi Chen and Canghai Wu and
                 Yingding Zhao and Wenlong Yi",
  title =        "Research on Progress of Blockchain Consensus
                 Algorithm: a Review on Recent Progress of Blockchain
                 Consensus Algorithms",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "47",
  day =          "30",
  month =        jan,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020047",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/47",
  abstract =     "Blockchain technology can solve the problem of trust
                 in the open network in a decentralized way. It has
                 broad application prospects and has attracted extensive
                 attention from academia and industry. The blockchain
                 consensus algorithm ensures that the nodes in the chain
                 reach consensus in the complex network environment, and
                 the node status ultimately remains the same. The
                 consensus algorithm is one of the core technologies of
                 blockchain and plays a pivotal role in the research of
                 blockchain technology. This article gives the basic
                 concepts of the blockchain, summarizes the key
                 technologies of the blockchain, especially focuses on
                 the research of the blockchain consensus algorithm,
                 expounds the general principles of the consensus
                 process, and classifies the mainstream consensus
                 algorithms. Then, focusing on the improvement of
                 consensus algorithm performance, it reviews the
                 research progress of consensus algorithms in detail,
                 analyzes and compares the characteristics, suitable
                 scenarios, and possible shortcomings of different
                 consensus algorithms, and based on this, studies the
                 future development trend of consensus algorithms for
                 reference.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Qiu:2022:FCD,
  author =       "Haoxuan Qiu and Yanhui Du and Tianliang Lu",
  title =        "The Framework of Cross-Domain and Model Adversarial
                 Attack against Deepfake",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "46",
  day =          "29",
  month =        jan,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020046",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/46",
  abstract =     "To protect images from the tampering of deepfake,
                 adversarial examples can be made to replace the
                 original images by distorting the output of the
                 deepfake model and disrupting its work. Current studies
                 lack generalizability in that they simply focus on the
                 adversarial examples generated by a model in a domain.
                 To improve the generalization of adversarial examples
                 and produce better attack effects on each domain of
                 multiple deepfake models, this paper proposes a
                 framework of Cross-Domain and Model Adversarial Attack
                 (CDMAA). Firstly, CDMAA uniformly weights the loss
                 function of each domain and calculates the cross-domain
                 gradient. Then, inspired by the multiple gradient
                 descent algorithm (MGDA), CDMAA integrates the
                 cross-domain gradients of each model to obtain the
                 cross-domain perturbation vector, which is used to
                 optimize the adversarial example. Finally, we propose a
                 penalty-based gradient regularization method to
                 pre-process the cross-domain gradients to improve the
                 success rate of attacks. CDMAA experiments on four
                 mainstream deepfake models showed that the adversarial
                 examples generated from CDMAA have the generalizability
                 of attacking multiple models and multiple domains
                 simultaneously. Ablation experiments were conducted to
                 compare the CDMAA components with the methods used in
                 existing studies and verify the superiority of CDMAA.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kakkavas:2022:TIL,
  author =       "Grigorios Kakkavas and Vasileios Karyotis and Symeon
                 Papavassiliou",
  title =        "Topology Inference and Link Parameter Estimation Based
                 on End-to-End Measurements",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "45",
  day =          "28",
  month =        jan,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020045",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/45",
  abstract =     "This paper focuses on the design, implementation,
                 experimental validation, and evaluation of a network
                 tomography approach for performing inferential
                 monitoring based on indirect measurements. In
                 particular, we address the problems of inferring the
                 routing tree topology (both logical and physical) and
                 estimating the links' loss rate and jitter based on
                 multicast end-to-end measurements from a source node to
                 a set of destination nodes using an agglomerative
                 clustering algorithm. The experimentally-driven
                 evaluation of the proposed algorithm, particularly the
                 impact of the employed reduction update scheme, takes
                 place in real topologies constructed in an open
                 large-scale testbed. Finally, we implement and present
                 a motivating practical application of the proposed
                 algorithm that combines monitoring with change point
                 analysis to realize performance anomaly detection.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Aouedi:2022:ITM,
  author =       "Ons Aouedi and Kandaraj Piamrat and Beno{\^\i}t
                 Parrein",
  title =        "Intelligent Traffic Management in Next-Generation
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "44",
  day =          "28",
  month =        jan,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020044",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/44",
  abstract =     "The recent development of smart devices has lead to an
                 explosion in data generation and heterogeneity. Hence,
                 current networks should evolve to become more
                 intelligent, efficient, and most importantly, scalable
                 in order to deal with the evolution of network traffic.
                 In recent years, network softwarization has drawn
                 significant attention from both industry and academia,
                 as it is essential for the flexible control of
                 networks. At the same time, machine learning (ML) and
                 especially deep learning (DL) methods have also been
                 deployed to solve complex problems without explicit
                 programming. These methods can model and learn network
                 traffic behavior using training data/environments. The
                 research community has advocated the application of
                 ML/DL in softwarized environments for network traffic
                 management, including traffic classification,
                 prediction, and anomaly detection. In this paper, we
                 survey the state of the art on these topics. We start
                 by presenting a comprehensive background beginning from
                 conventional ML algorithms and DL and follow this with
                 a focus on different dimensionality reduction
                 techniques. Afterward, we present the study of ML/DL
                 applications in softwarized environments. Finally, we
                 highlight the issues and challenges that should be
                 considered.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Cai:2022:GDA,
  author =       "Liewu Cai and Lei Zhu and Hongyan Zhang and Xinghui
                 Zhu",
  title =        "{DA-GAN}: Dual Attention Generative Adversarial
                 Network for Cross-Modal Retrieval",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "43",
  day =          "27",
  month =        jan,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020043",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/43",
  abstract =     "Cross-modal retrieval aims to search samples of one
                 modality via queries of other modalities, which is a
                 hot issue in the community of multimedia. However, two
                 main challenges, i.e., heterogeneity gap and semantic
                 interaction across different modalities, have not been
                 solved efficaciously. Reducing the heterogeneous gap
                 can improve the cross-modal similarity measurement.
                 Meanwhile, modeling cross-modal semantic interaction
                 can capture the semantic correlations more accurately.
                 To this end, this paper presents a novel end-to-end
                 framework, called Dual Attention Generative Adversarial
                 Network (DA-GAN). This technique is an adversarial
                 semantic representation model with a dual attention
                 mechanism, i.e., intra-modal attention and inter-modal
                 attention. Intra-modal attention is used to focus on
                 the important semantic feature within a modality, while
                 inter-modal attention is to explore the semantic
                 interaction between different modalities and then
                 represent the high-level semantic correlation more
                 precisely. A dual adversarial learning strategy is
                 designed to generate modality-invariant
                 representations, which can reduce the cross-modal
                 heterogeneity efficiently. The experiments on three
                 commonly used benchmarks show the better performance of
                 DA-GAN than these competitors.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Munjal:2022:MAD,
  author =       "Rashmi Munjal and William Liu and Xuejun Li and Jairo
                 Gutierrez and Peter Han Joo Chong",
  title =        "Multi-Attribute Decision Making for Energy-Efficient
                 Public Transport Network Selection in Smart Cities",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "42",
  day =          "26",
  month =        jan,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020042",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/42",
  abstract =     "Smart cities use many smart devices to facilitate the
                 well-being of society by different means. However,
                 these smart devices create great challenges, such as
                 energy consumption and carbon emissions. The proposed
                 research lies in communication technologies to deal
                 with big data-driven applications. Aiming at multiple
                 sources of big data in a smart city, we propose a
                 public transport-assisted data-dissemination system to
                 utilize public transport as another communication
                 medium, along with other networks, with the help of
                 software-defined technology. Our main objective is to
                 minimize energy consumption with the maximum delivery
                 of data. A multi-attribute decision-making strategy is
                 adopted for the selection of the best network among
                 wired, wireless, and public transport networks, based
                 upon users' requirements and different services. Once
                 public transport is selected as the best network, the
                 Capacitated Vehicle Routing Problem (CVRP) will be
                 implemented to offload data onto buses as per the
                 maximum capacity of buses. For validation, the case of
                 Auckland Transport is used to offload data onto buses
                 for energy-efficient delay-tolerant data transmission.
                 Experimental results show that buses can be utilized
                 efficiently to deliver data as per their demands and
                 consume 33\% less energy in comparison to other
                 networks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Shi:2022:HRL,
  author =       "Jialin Shi and Chenyi Guo and Ji Wu",
  title =        "A Hybrid Robust-Learning Architecture for Medical
                 Image Segmentation with Noisy Labels",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "41",
  day =          "26",
  month =        jan,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020041",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/41",
  abstract =     "Deep-learning models require large amounts of
                 accurately labeled data. However, for medical image
                 segmentation, high-quality labels rely on expert
                 experience, and less-experienced operators provide
                 noisy labels. How one might mitigate the negative
                 effects caused by noisy labels for 3D medical image
                 segmentation has not been fully investigated. In this
                 paper, our purpose is to propose a novel hybrid
                 robust-learning architecture to combat noisy labels for
                 3D medical image segmentation. Our method consists of
                 three components. First, we focus on the noisy
                 annotations of slices and propose a slice-level
                 label-quality awareness method, which automatically
                 generates label-quality scores for slices in a set.
                 Second, we propose a shape-awareness regularization
                 loss based on distance transform maps to introduce
                 prior shape information and provide extra performance
                 gains. Third, based on a re-weighting strategy, we
                 propose an end-to-end hybrid robust-learning
                 architecture to weaken the negative effects caused by
                 noisy labels. Extensive experiments are performed on
                 two representative datasets (i.e., liver segmentation
                 and multi-organ segmentation). Our hybrid noise-robust
                 architecture has shown competitive performance,
                 compared to other methods. Ablation studies also
                 demonstrate the effectiveness of slice-level
                 label-quality awareness and a shape-awareness
                 regularization loss for combating noisy labels.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yang:2022:IBC,
  author =       "Cunwei Yang and Weiqing Wang and Fengying Li and
                 Degang Yang",
  title =        "An {IoT}-Based {COVID-19} Prevention and Control
                 System for Enclosed Spaces",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "40",
  day =          "26",
  month =        jan,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020040",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/40",
  abstract =     "To date, the protracted pandemic caused by the severe
                 acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
                 has had widespread ramifications for the economy,
                 politics, public health, etc. Based on the current
                 situation, definitively stopping the spread of the
                 virus is infeasible in many countries. This does not
                 mean that populations should ignore the pandemic;
                 instead, normal life needs to be balanced with disease
                 prevention and control. This paper highlights the use
                 of Internet of Things (IoT) for the prevention and
                 control of coronavirus disease (COVID-19) in enclosed
                 spaces. The proposed booking algorithm is able to
                 control the gathering of crowds in specific regions.
                 K-nearest neighbors (KNN) is utilized for the
                 implementation of a navigation system with a congestion
                 control strategy and global path planning capabilities.
                 Furthermore, a risk assessment model is designed based
                 on a ``Sliding Window-Timer'' algorithm, providing an
                 infection risk assessment for individuals in potential
                 contact with patients.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wu:2022:CFE,
  author =       "Meng Wu and Tingting Jiang and Chenyang Bu and Bin
                 Zhu",
  title =        "Coarse-to-Fine Entity Alignment for {Chinese}
                 Heterogeneous Encyclopedia Knowledge Base",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "39",
  day =          "25",
  month =        jan,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020039",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/39",
  abstract =     "Entity alignment (EA) aims to automatically determine
                 whether an entity pair in different knowledge bases or
                 knowledge graphs refer to the same entity in reality.
                 Inspired by human cognitive mechanisms, we propose a
                 coarse-to-fine entity alignment model (called CFEA)
                 consisting of three stages: coarse-grained,
                 middle-grained, and fine-grained. In the coarse-grained
                 stage, a pruning strategy based on the restriction of
                 entity types is adopted to reduce the number of
                 candidate matching entities. The goal of this stage is
                 to filter out pairs of entities that are clearly not
                 the same entity. In the middle-grained stage, we
                 calculate the similarity of entity pairs through some
                 key attribute values and matched attribute values, the
                 goal of which is to identify the entity pairs that are
                 obviously not the same entity or are obviously the same
                 entity. After this step, the number of candidate entity
                 pairs is further reduced. In the fine-grained stage,
                 contextual information, such as abstract and
                 description text, is considered, and topic modeling is
                 carried out to achieve more accurate matching. The
                 basic idea of this stage is to use more information to
                 help judge entity pairs that are difficult to
                 distinguish using basic information from the first two
                 stages. The experimental results on real-world datasets
                 verify the effectiveness of our model compared with
                 baselines.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Duan:2022:SRM,
  author =       "Yingjie Duan and Hong Ni and Xiaoyong Zhu and Xu
                 Wang",
  title =        "A Single-Rate Multicast Congestion Control ({SRMCC})
                 Mechanism in Information-Centric Networking",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "2",
  pages =        "38",
  day =          "25",
  month =        jan,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14020038",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Feb 25 07:09:39 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/2/38",
  abstract =     "Information-centric networking (ICN) is expected to be
                 a candidate for future internet architecture, and it
                 supports features such as multicast that improves
                 bandwidth utilization and transmission efficiency.
                 However, multicast itself does not provide congestion
                 control. When multiple multicast groups coexist,
                 multicast traffic may exhaust all network resources,
                 and cause network congestion and packet loss.
                 Additionally, traditional IP multicast congestion
                 control mechanisms cannot be directly applied to ICN
                 architecture. Therefore, it is necessary to consider an
                 effective congestion control mechanism for ICN
                 multicast. This paper proposes a single-rate multicast
                 congestion control mechanism, called SRMCC. It supports
                 router-assisted awareness of the network congestion
                 state and congestion control message aggregation.
                 Moreover, the fair shared rate estimation method is
                 innovatively proposed to achieve protocol fairness.
                 Most importantly, it adjusts the rate according to
                 different congestion states indicated by the queue
                 occupancy ratio. By introducing a rate selection
                 factor, it can achieve a balance between packet loss
                 rate and throughput. Experimental results show that our
                 proposal outperforms other mechanisms in throughput,
                 packet loss rate, total bandwidth utilization, and
                 overhead, and achieves protocol fairness and better TCP
                 friendliness.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lembo:2022:GGL,
  author =       "Domenico Lembo and Valerio Santarelli and Domenico
                 Fabio Savo and Giuseppe {De Giacomo}",
  title =        "\pkg{Graphol}: A Graphical Language for Ontology
                 Modeling Equivalent to \pkg{OWL 2}",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "3",
  pages =        "78",
  day =          "28",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14030078",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 4 08:59:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/3/78",
  abstract =     "In this paper we study Graphol, a fully graphical
                 language inspired by standard formalisms for conceptual
                 modeling, similar to the UML class diagram and the ER
                 model, but equipped with formal semantics. We formally
                 prove that Graphol is equivalent to OWL 2, i.e., it can
                 capture every OWL 2 ontology and vice versa. We also
                 present some usability studies indicating that Graphol
                 is suitable for quick adoption by conceptual modelers
                 that are familiar with UML and ER. This is further
                 testified by the adoption of Graphol for ontology
                 representation in several industrial projects.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Khanal:2022:UBI,
  author =       "Yurika Pant Khanal and Abeer Alsadoon and Khurram
                 Shahzad and Ahmad B. Al-Khalil and Penatiyana W. C.
                 Prasad and Sabih Ur Rehman and Rafiqul Islam",
  title =        "Utilizing Blockchain for {IoT} Privacy through
                 Enhanced {ECIES} with Secure Hash Function",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "3",
  pages =        "77",
  day =          "28",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14030077",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 4 08:59:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/hash.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/3/77",
  abstract =     "Blockchain technology has been widely advocated for
                 security and privacy in IoT systems. However, a major
                 impediment to its successful implementation is the lack
                 of privacy protection regarding user access policy
                 while accessing personal data in the IoT system. This
                 work aims to preserve the privacy of user access policy
                 by protecting the confidentiality and authenticity of
                 the transmitted message while obtaining the necessary
                 consents for data access. We consider a Modified
                 Elliptic Curve Integrated Encryption Scheme (ECIES) to
                 improve the security strength of the transmitted
                 message. A secure hash function is used in conjunction
                 with a key derivation function to modify the encryption
                 procedure, which enhances the efficiency of the
                 encryption and decryption by generating multiple secure
                 keys through one master key. The proposed solution
                 eliminates user-dependent variables by including
                 transaction generation and verification in the
                 calculation of computation time, resulting in increased
                 system reliability. In comparison to previously
                 established work, the security of the transmitted
                 message is improved through a reduction of more than
                 12\% in the correlation coefficient between the
                 constructed request transaction and encrypted
                 transaction, coupled with a decrease of up to 7\% in
                 computation time.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{daSilva:2022:FSD,
  author =       "Diogo E. Moreira da Silva and Eduardo J. Solteiro
                 Pires and Ars{\'e}nio Reis and Paulo B. de Moura
                 Oliveira and Jo{\~a}o Barroso",
  title =        "Forecasting Students Dropout: A {UTAD} University
                 Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "3",
  pages =        "76",
  day =          "28",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14030076",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 4 08:59:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/3/76",
  abstract =     "In Portugal, the dropout rate of university courses is
                 around 29\%. Understanding the reasons behind such a
                 high desertion rate can drastically improve the success
                 of students and universities. This work applies
                 existing data mining techniques to predict the academic
                 dropout mainly using the academic grades. Four
                 different machine learning techniques are presented and
                 analyzed. The dataset consists of 331 students who were
                 previously enrolled in the Computer Engineering degree
                 at the Universidade de Tr{\'a}s-os-Montes e Alto Douro
                 (UTAD). The study aims to detect students who may
                 prematurely drop out using existing methods. The most
                 relevant data features were identified using the
                 Permutation Feature Importance technique. In the second
                 phase, several methods to predict the dropouts were
                 applied. Then, each machine learning technique's
                 results were displayed and compared to select the best
                 approach to predict academic dropout. The methods used
                 achieved good results, reaching an F1-Score of 81\% in
                 the final test set, concluding that students' marks
                 somehow incorporate their living conditions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Vryzas:2022:PWA,
  author =       "Nikolaos Vryzas and Anastasia Katsaounidou and Lazaros
                 Vrysis and Rigas Kotsakis and Charalampos Dimoulas",
  title =        "A Prototype {Web} Application to Support
                 Human-Centered Audiovisual Content Authentication and
                 Crowdsourcing",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "3",
  pages =        "75",
  day =          "27",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14030075",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 4 08:59:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/3/75",
  abstract =     "Media authentication relies on the detection of
                 inconsistencies that may indicate malicious editing in
                 audio and video files. Traditionally, authentication
                 processes are performed by forensics professionals
                 using dedicated tools. There is rich research on the
                 automation of this procedure, but the results do not
                 yet guarantee the feasibility of providing automated
                 tools. In the current approach, a computer-supported
                 toolbox is presented, providing online functionality
                 for assisting technically inexperienced users
                 (journalists or the public) to investigate visually the
                 consistency of audio streams. Several algorithms based
                 on previous research have been incorporated on the
                 backend of the proposed system, including a novel CNN
                 model that performs a Signal-to-Reverberation-Ratio
                 (SRR) estimation with a mean square error of 2.9\%. The
                 user can access the web application online through a
                 web browser. After providing an audio/video file or a
                 YouTube link, the application returns as output a set
                 of interactive visualizations that can allow the user
                 to investigate the authenticity of the file. The
                 visualizations are generated based on the outcomes of
                 Digital Signal Processing and Machine Learning models.
                 The files are stored in a database, along with their
                 analysis results and annotation. Following a
                 crowdsourcing methodology, users are allowed to
                 contribute by annotating files from the dataset
                 concerning their authenticity. The evaluation version
                 of the web application is publicly available online.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Reis:2022:BMI,
  author =       "Jacqueline Zonichenn Reis and Rodrigo Franco
                 Gon{\c{c}}alves and Marcia Terra da Silva and Nikolai
                 Kazantsev",
  title =        "Business Models for the {Internet of Services}: State
                 of the Art and Research Agenda",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "3",
  pages =        "74",
  day =          "25",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14030074",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 4 08:59:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/3/74",
  abstract =     "The relevance of the Internet of Services (IoS) comes
                 from the global reach of the Internet into everyone's
                 home and daily activities and from the move from a
                 manufacturing-based economy to a service-based economy.
                 The IoS is seen as a new ecosystem where service
                 providers and consumers explore their business networks
                 for service provision and consumption. The scientific
                 literature refers to IoS as an important cornerstone
                 for Industry 4.0 and Future Internet; thus, it becomes
                 relevant to study how IoS interacts with business
                 models. Nevertheless, there is a lack of clarity on
                 such an intersection. Moreover, a systematic review of
                 IoS-based business models is still missing. This paper
                 aims to make a systematic review of IoS-based business
                 models and their application fields. We included
                 studies from Scopus and Web of Science databases, we
                 excluded duplicated papers and short conference
                 versions of the later full paper journal publications.
                 Twenty-three different studies are presented,
                 categorized in the sub-areas of IoS, and then by the
                 fields of applications. The main finding highlights the
                 opportunities of IoS applications in different fields,
                 offering directions for future research on this new
                 arena.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Adnan:2022:QKD,
  author =       "Mohd Hirzi Adnan and Zuriati Ahmad Zukarnain and Nur
                 Ziadah Harun",
  title =        "Quantum Key Distribution for {5G} Networks: A Review,
                 State of Art and Future Directions",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "3",
  pages =        "73",
  day =          "25",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14030073",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 4 08:59:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/3/73",
  abstract =     "In recent years, 5G networks and services become
                 progressively popular among telecommunication
                 providers. Simultaneously, the growth in the usage and
                 deployment of smartphone platforms and mobile
                 applications have been seen as phenomenal. Therefore,
                 this paper discusses the current state of the art of 5G
                 technology in the merger of unconditional security
                 requirements referred to as Quantum Cryptography. The
                 various domain of Quantum Cryptography is illustrated
                 including the protocols available, their functionality
                 and previous implementation in real networks. This
                 paper further identifies research gaps covering
                 critical aspects of how Quantum Cryptography can be
                 realized and effectively utilized in 5G networks. These
                 include improving the current technique in Quantum
                 Cryptography through efficient key distribution and
                 message sharing between users in 5G networks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Teixeira:2022:VBA,
  author =       "Diogo Teixeira and Silvestre Malta and Pedro Pinto",
  title =        "A Vote-Based Architecture to Generate Classified
                 Datasets and Improve Performance of Intrusion Detection
                 Systems Based on Supervised Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "3",
  pages =        "72",
  day =          "25",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14030072",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 4 08:59:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/3/72",
  abstract =     "An intrusion detection system (IDS) is an important
                 tool to prevent potential threats to systems and data.
                 Anomaly-based IDSs may deploy machine learning
                 algorithms to classify events either as normal or
                 anomalous and trigger the adequate response. When using
                 supervised learning, these algorithms require
                 classified, rich, and recent datasets. Thus, to foster
                 the performance of these machine learning models,
                 datasets can be generated from different sources in a
                 collaborative approach, and trained with multiple
                 algorithms. This paper proposes a vote-based
                 architecture to generate classified datasets and
                 improve the performance of supervised learning-based
                 IDSs. On a regular basis, multiple IDSs in different
                 locations send their logs to a central system that
                 combines and classifies them using different machine
                 learning models and a majority vote system. Then, it
                 generates a new and classified dataset, which is
                 trained to obtain the best updated model to be
                 integrated into the IDS of the companies involved. The
                 proposed architecture trains multiple times with
                 several algorithms. To shorten the overall runtimes,
                 the proposed architecture was deployed in Fed4FIRE+
                 with Ray to distribute the tasks by the available
                 resources. A set of machine learning algorithms and the
                 proposed architecture were assessed. When compared with
                 a baseline scenario, the proposed architecture enabled
                 to increase the accuracy by 11.5\% and the precision by
                 11.2\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tran:2022:DRS,
  author =       "Thanh-Nam Tran and Van-Cuu Ho and Thoai Phu Vo and
                 Khanh Ngo Nhu Tran and Miroslav Voznak",
  title =        "Design of Relay Switching to Combat an Eavesdropper in
                 {IoT-NOMA} Wireless Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "3",
  pages =        "71",
  day =          "24",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14030071",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 4 08:59:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/3/71",
  abstract =     "The requirements of low latency, low cost, less energy
                 consumption, high flexibility, high network capacity,
                 and high data safety are crucial challenges for future
                 Internet of Things (IoT) wireless networks. Motivated
                 by these challenges, this study deals with a novel
                 design of green-cooperative IoT network, which employed
                 coupled relays consisting of one IoT relay selected for
                 forwarding signals to multiple IoT devices while
                 another IoT relay transmitted jamming signals to an
                 eavesdropper. For flexibility, all IoT nodes were
                 powered by solar energy enough to sustain themselves,
                 in order to consume less energy. To reach low latency,
                 the study adopted the emerging non-orthogonal multiple
                 access technique to serve multiple IoT devices
                 simultaneously. Furthermore, the study adopted the
                 simultaneous wireless information and power transfer
                 technique which transmits wireless data for information
                 processing and energy for energy harvesting. The study
                 sketched a novel transmission block time period
                 framework which plotted how a signal could travel via
                 an individual IoT model. Maximizing the achievable
                 bit-rate of IoT devices was considered to improve
                 network capacity and data safety as well. Aiming at
                 enhancing secrecy performance, a rest IoT relay played
                 a role as a friendly jammer to transmit a jamming
                 signal to an eavesdropper using energy harvested from
                 the power splitting protocol. The results achieved in
                 this study showed that the proposed model satisfied the
                 requirements of future green IoT wireless networks.
                 Derivatives leading to closed-form expressions are
                 presented and verified by simulation results. The
                 investigated results demonstrated that a friendly
                 jammer based on radio frequency and energy harvesting
                 strongly forces the intercept probability performance
                 of the eavesdropper towards one, while outage
                 probability performance of IoT devices towards zero
                 showed that the signal to noise ratio tends to
                 infinity.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Varlamis:2022:SUG,
  author =       "Iraklis Varlamis and Dimitrios Michail and Foteini
                 Glykou and Panagiotis Tsantilas",
  title =        "A Survey on the Use of Graph Convolutional Networks
                 for Combating Fake News",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "3",
  pages =        "70",
  day =          "24",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14030070",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 4 08:59:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/3/70",
  abstract =     "The combat against fake news and disinformation is an
                 ongoing, multi-faceted task for researchers in social
                 media and social networks domains, which comprises not
                 only the detection of false facts in published content
                 but also the detection of accountability mechanisms
                 that keep a record of the trustfulness of sources that
                 generate news and, lately, of the networks that
                 deliberately distribute fake information. In the
                 direction of detecting and handling organized
                 disinformation networks, major social media and social
                 networking sites are currently developing strategies
                 and mechanisms to block such attempts. The role of
                 machine learning techniques, especially neural
                 networks, is crucial in this task. The current work
                 focuses on the popular and promising graph
                 representation techniques and performs a survey of the
                 works that employ Graph Convolutional Networks (GCNs)
                 to the task of detecting fake news, fake accounts and
                 rumors that spread in social networks. It also
                 highlights the available benchmark datasets employed in
                 current research for validating the performance of the
                 proposed methods. This work is a comprehensive survey
                 of the use of GCNs in the combat against fake news and
                 aims to be an ideal starting point for future
                 researchers in the field.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Blekanov:2022:TBA,
  author =       "Ivan S. Blekanov and Nikita Tarasov and Svetlana S.
                 Bodrunova",
  title =        "Transformer-Based Abstractive Summarization for
                 {Reddit} and {Twitter}: Single Posts vs. Comment Pools
                 in Three Languages",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "3",
  pages =        "69",
  day =          "23",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14030069",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 4 08:59:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/3/69",
  abstract =     "Abstractive summarization is a technique that allows
                 for extracting condensed meanings from long texts, with
                 a variety of potential practical applications.
                 Nonetheless, today's abstractive summarization research
                 is limited to testing the models on various types of
                 data, which brings only marginal improvements and does
                 not lead to massive practical employment of the method.
                 In particular, abstractive summarization is not used
                 for social media research, where it would be very
                 useful for opinion and topic mining due to the
                 complications that social media data create for other
                 methods of textual analysis. Of all social media,
                 Reddit is most frequently used for testing new neural
                 models of text summarization on large-scale datasets in
                 English, without further testing on real-world
                 smaller-size data in various languages or from various
                 other platforms. Moreover, for social media,
                 summarizing pools of texts (one-author posts, comment
                 threads, discussion cascades, etc.) may bring crucial
                 results relevant for social studies, which have not yet
                 been tested. However, the existing methods of
                 abstractive summarization are not fine-tuned for social
                 media data and have next-to-never been applied to data
                 from platforms beyond Reddit, nor for comments or
                 non-English user texts. We address these research gaps
                 by fine-tuning the newest Transformer-based neural
                 network models LongFormer and T5 and testing them
                 against BART, and on real-world data from Reddit, with
                 improvements of up to 2\%. Then, we apply the best
                 model (fine-tuned T5) to pools of comments from Reddit
                 and assess the similarity of post and comment
                 summarizations. Further, to overcome the 500-token
                 limitation of T5 for analyzing social media pools that
                 are usually bigger, we apply LongFormer Large and T5
                 Large to pools of tweets from a large-scale discussion
                 on the Charlie Hebdo massacre in three languages and
                 prove that pool summarizations may be used for
                 detecting micro-shifts in agendas of networked
                 discussions. Our results show, however, that additional
                 learning is definitely needed for German and French, as
                 the results for these languages are non-satisfactory,
                 and more fine-tuning is needed even in English for
                 Twitter data. Thus, we show that a `one-for-all'
                 neural-network summarization model is still impossible
                 to reach, while fine-tuning for platform affordances
                 works well. We also show that fine-tuned T5 works best
                 for small-scale social media data, but LongFormer is
                 helpful for larger-scale pool summarizations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2022:AIE,
  author =       "Jiaqi Li and Jiali You and Haojiang Deng",
  title =        "Adjacency-Information-Entropy-Based Cooperative Name
                 Resolution Approach in {ICN}",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "3",
  pages =        "68--??",
  day =          "23",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14030068",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Mar 4 08:59:15 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/3/68",
  abstract =     "Information-centric networking (ICN) is an emerging
                 network architecture that has the potential to address
                 low-transmission latency and high-reliability
                 requirements in the fifth generation and beyond
                 communication networks (5G/B5G). In the ICN
                 architectures that use the identifier--locator
                 separation mode, a name resolution system (NRS) is an
                 important infrastructure for managing and maintaining
                 the mappings between identifiers and locators. To meet
                 the demands of time-sensitive applications, researchers
                 have developed a distributed local NRS that can provide
                 name resolution service within deterministic latency,
                 which means it can respond to a name resolution request
                 within a latency upper bound. However, processing name
                 resolution requests only locally cannot take full
                 advantage of the potential of the distributed local
                 NRS. In this paper, we propose a name resolution
                 approach, called adjacency-information-entropy-based
                 cooperative name resolution (ACNR). In ACNR, when a
                 name resolution node receives a name resolution request
                 from a user, it can use neighboring name resolution
                 nodes to respond to this request in a parallel
                 processing manner. For this purpose, ACNR uses the
                 information entropy that takes into account the
                 adjacency and latency between name resolution nodes to
                 describe the local structure of nodes efficiently. The
                 proposed approach is extensively validated on simulated
                 networks. Compared with several other approaches, the
                 experiment results show that ACNR can discover more
                 cooperative neighbors in a reasonable communication
                 overhead, and achieve a higher name resolution success
                 rate.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Scanlan:2022:CHP,
  author =       "Joel Scanlan and Paul A. Watters and Jeremy Prichard
                 and Charlotte Hunn and Caroline Spiranovic and Richard
                 Wortley",
  title =        "Creating Honeypots to Prevent Online Child
                 Exploitation",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "4",
  pages =        "121--??",
  day =          "14",
  month =        apr,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14040121",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 22 09:50:26 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/4/121",
  abstract =     "Honeypots have been a key tool in controlling and
                 understanding digital crime for several decades. The
                 tool has traditionally been deployed against actors who
                 are attempting to hack into systems or as a discovery
                 mechanism for new forms of malware. This paper presents
                 a novel approach to using a honeypot architecture in
                 conjunction with social networks to respond to
                 non-technical digital crimes. The tool is presented
                 within the context of Child Exploitation Material
                 (CEM), and to support the goal of taking an educative
                 approach to Internet users who are developing an
                 interest in this material. The architecture that is
                 presented in the paper includes multiple layers,
                 including recruitment, obfuscation, and education. The
                 approach does not aim to collect data to support
                 punitive action, but to educate users, increasing their
                 knowledge and awareness of the negative impacts of such
                 material.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sharma:2022:FWN,
  author =       "Sachin Sharma and Saish Urumkar and Gianluca Fontanesi
                 and Byrav Ramamurthy and Avishek Nag",
  title =        "Future Wireless Networking Experiments Escaping
                 Simulations",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "4",
  pages =        "120--??",
  day =          "14",
  month =        apr,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14040120",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 22 09:50:26 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/4/120",
  abstract =     "In computer networking, simulations are widely used to
                 test and analyse new protocols and ideas. Currently,
                 there are a number of open real testbeds available to
                 test the new protocols. In the EU, for example, there
                 are Fed4Fire testbeds, while in the US, there are
                 POWDER and COSMOS testbeds. Several other countries,
                 including Japan, Brazil, India, and China, have also
                 developed next-generation testbeds. Compared to
                 simulations, these testbeds offer a more realistic way
                 to test protocols and prototypes. In this paper, we
                 examine some available wireless testbeds from the EU
                 and the US, which are part of an open-call EU project
                 under the NGIAtlantic H2020 initiative to conduct
                 Software-Defined Networking (SDN) experiments on
                 intelligent Internet of Things (IoT) networks.
                 Furthermore, the paper presents benchmarking results
                 and failure recovery results from each of the
                 considered testbeds using a variety of wireless network
                 topologies. The paper compares the testbeds based on
                 throughput, latency, jitter, resources available, and
                 failure recovery time, by sending different types of
                 traffic. The results demonstrate the feasibility of
                 performing wireless experiments on different testbeds
                 in the US and the EU. Further, issues faced during
                 experimentation on EU and US testbeds are also
                 reported.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2022:LCG,
  author =       "Zhihao Wang and Ru Huo and Shuo Wang",
  title =        "A Lightweight Certificateless Group Key Agreement
                 Method without Pairing Based on Blockchain for Smart
                 Grid",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "4",
  pages =        "119--??",
  day =          "14",
  month =        apr,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14040119",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 22 09:50:26 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/4/119",
  abstract =     "In smart grids, the access verification of a large
                 number of intelligent gateways and terminal devices has
                 become one of the main concerns to ensure system
                 security. This means that smart grids need a new key
                 management method that is safe and efficient and has a
                 low computational cost. Although a large number of
                 scholars have conducted relevant research, most of
                 these schemes cannot balance the computational overhead
                 and security. Therefore, we propose a lightweight and
                 secure key management method, having a low
                 computational overhead, based on blockchain for smart
                 grids. Firstly, we redesigned the architecture of the
                 smart grid based on blockchain and completed the
                 division of various entities. Furthermore, we designed
                 a pairing-free certification authenticated group key
                 agreement method based on blockchain under the
                 architecture. Finally, we achieved higher security
                 attributes, and lower authentication delay and
                 computational overhead, compared to the traditional
                 schemes, as shown in performance analysis and
                 comparison.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alaoui:2022:DLV,
  author =       "Rokia Lamrani Alaoui and El Habib Nfaoui",
  title =        "Deep Learning for Vulnerability and Attack Detection
                 on {Web} Applications: a Systematic Literature Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "4",
  pages =        "118--??",
  day =          "13",
  month =        apr,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14040118",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 22 09:50:26 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/4/118",
  abstract =     "Web applications are the best Internet-based solution
                 to provide online web services, but they also bring
                 serious security challenges. Thus, enhancing web
                 applications security against hacking attempts is of
                 paramount importance. Traditional Web Application
                 Firewalls based on manual rules and traditional Machine
                 Learning need a lot of domain expertise and human
                 intervention and have limited detection results faced
                 with the increasing number of unknown web attacks. To
                 this end, more research work has recently been devoted
                 to employing Deep Learning (DL) approaches for web
                 attacks detection. We performed a Systematic Literature
                 Review (SLR) and quality analysis of 63 Primary Studies
                 (PS) on DL-based web applications security published
                 between 2010 and September 2021. We investigated the PS
                 from different perspectives and synthesized the results
                 of the analyses. To the best of our knowledge, this
                 study is the first of its kind on SLR in this field.
                 The key findings of our study include the following.
                 (i) It is fundamental to generate standard real-world
                 web attacks datasets to encourage effective
                 contribution in this field and to reduce the gap
                 between research and industry. (ii) It is interesting
                 to explore some advanced DL models, such as Generative
                 Adversarial Networks and variants of
                 Encoders--Decoders, in the context of web attacks
                 detection as they have been successful in similar
                 domains such as networks intrusion detection. (iii) It
                 is fundamental to bridge expertise in web applications
                 security and expertise in Machine Learning to build
                 theoretical Machine Learning models tailored for web
                 attacks detection. (iv) It is important to create a
                 corpus for web attacks detection in order to take full
                 advantage of text mining in DL-based web attacks
                 detection models construction. (v) It is essential to
                 define a common framework for developing and comparing
                 DL-based web attacks detection models. This SLR is
                 intended to improve research work in the domain of
                 DL-based web attacks detection, as it covers a
                 significant number of research papers and identifies
                 the key points that need to be addressed in this
                 research field. Such a contribution is helpful as it
                 allows researchers to compare existing approaches and
                 to exploit the proposed future work opportunities.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Salameh:2022:CTA,
  author =       "Ahmed I. Salameh and Mohamed El Tarhuni",
  title =        "From {5G} to {6G}---Challenges, Technologies, and
                 Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "4",
  pages =        "117--??",
  day =          "12",
  month =        apr,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14040117",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 22 09:50:26 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/4/117",
  abstract =     "As the deployment of 5G mobile radio networks gains
                 momentum across the globe, the wireless research
                 community is already planning the successor of 5G. In
                 this paper, we highlight the shortcomings of 5G in
                 meeting the needs of more data-intensive, low-latency,
                 and ultra-high-reliability applications. We then
                 discuss the salient characteristics of the 6G network
                 following a hierarchical approach including the social,
                 economic, and technological aspects. We also discuss
                 some of the key technologies expected to support the
                 move towards 6G. Finally, we quantify and summarize the
                 research work related to beyond 5G and 6G networks
                 through an extensive search of publications and
                 research groups and present a possible timeline for 6G
                 activities.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Dangi:2022:MBN,
  author =       "Ramraj Dangi and Akshay Jadhav and Gaurav Choudhary
                 and Nicola Dragoni and Manas Kumar Mishra and Praveen
                 Lalwani",
  title =        "{ML}-Based {5G} Network Slicing Security: a
                 Comprehensive Survey",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "4",
  pages =        "116--??",
  day =          "08",
  month =        apr,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14040116",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 22 09:50:26 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/4/116",
  abstract =     "Fifth-generation networks efficiently support and
                 fulfill the demands of mobile broadband and
                 communication services. There has been a continuing
                 advancement from 4G to 5G networks, with 5G mainly
                 providing the three services of enhanced mobile
                 broadband (eMBB), massive machine type communication
                 (eMTC), and ultra-reliable low-latency services
                 (URLLC). Since it is difficult to provide all of these
                 services on a physical network, the 5G network is
                 partitioned into multiple virtual networks called
                 ``slices''. These slices customize these unique
                 services and enable the network to be reliable and
                 fulfill the needs of its users. This phenomenon is
                 called network slicing. Security is a critical concern
                 in network slicing as adversaries have evolved to
                 become more competent and often employ new attack
                 strategies. This study focused on the security issues
                 that arise during the network slice lifecycle. Machine
                 learning and deep learning algorithm solutions were
                 applied in the planning and design, construction and
                 deployment, monitoring, fault detection, and security
                 phases of the slices. This paper outlines the 5G
                 network slicing concept, its layers and architectural
                 framework, and the prevention of attacks, threats, and
                 issues that represent how network slicing influences
                 the 5G network. This paper also provides a comparison
                 of existing surveys and maps out taxonomies to
                 illustrate various machine learning solutions for
                 different application parameters and network functions,
                 along with significant contributions to the field.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Al-Dwairi:2022:RRS,
  author =       "Mahmoud Al-Dwairi and Ahmed S. Shatnawi and Osama
                 Al-Khaleel and Basheer Al-Duwairi",
  title =        "Ransomware-Resilient Self-Healing {XML} Documents",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "4",
  pages =        "115--??",
  day =          "07",
  month =        apr,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14040115",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 22 09:50:26 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/4/115",
  abstract =     "In recent years, various platforms have witnessed an
                 unprecedented increase in the number of ransomware
                 attacks targeting hospitals, governments, enterprises,
                 and end-users. The purpose of this is to maliciously
                 encrypt documents and files on infected machines,
                 depriving victims of access to their data, whereupon
                 attackers would seek some sort of a ransom in return
                 for restoring access to the legitimate owners; hence
                 the name. This cybersecurity threat would inherently
                 cause substantial financial losses and time wastage for
                 affected organizations and users. A great deal of
                 research has taken place across academia and around the
                 industry to combat this threat and mitigate its danger.
                 These ongoing endeavors have resulted in several
                 detection and prevention schemas. Nonetheless, these
                 approaches do not cover all possible risks of losing
                 data. In this paper, we address this facet and provide
                 an efficient solution that would ensure an efficient
                 recovery of XML documents from ransomware attacks. This
                 paper proposes a self-healing version-aware ransomware
                 recovery (SH-VARR) framework for XML documents. The
                 proposed framework is based on the novel idea of using
                 the link concept to maintain file versions in a
                 distributed manner while applying access-control
                 mechanisms to protect these versions from being
                 encrypted or deleted. The proposed SH-VARR framework is
                 experimentally evaluated in terms of storage overhead,
                 time requirement, CPU utilization, and memory usage.
                 Results show that the snapshot size increases
                 proportionately with the original size; the time
                 required is less than 120 ms for files that are less
                 than 1 MB in size; and the highest CPU utilization
                 occurs when using the bzip2. Moreover, when the zip and
                 gzip are used, the memory usage is almost fixed (around
                 6.8 KBs). In contrast, it increases to around 28 KBs
                 when the bzip2 is used.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Marosi:2022:IDA,
  author =       "Attila Csaba Marosi and M{\'a}rk Emodi and {\'A}kos
                 Hajnal and R{\'o}bert Lovas and Tam{\'a}s Kiss and
                 Valerie Poser and Jibinraj Antony and Simon Bergweiler
                 and Hamed Hamzeh and James Deslauriers and J{\'o}zsef
                 Kov{\'a}cs",
  title =        "Interoperable Data Analytics Reference Architectures
                 Empowering Digital-Twin-Aided Manufacturing",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "4",
  pages =        "114--??",
  day =          "06",
  month =        apr,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14040114",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 22 09:50:26 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/4/114",
  abstract =     "The use of mature, reliable, and validated solutions
                 can save significant time and cost when introducing new
                 technologies to companies. Reference Architectures
                 represent such best-practice techniques and have the
                 potential to increase the speed and reliability of the
                 development process in many application domains. One
                 area where Reference Architectures are increasingly
                 utilized is cloud-based systems. Exploiting the
                 high-performance computing capability offered by
                 clouds, while keeping sovereignty and governance of
                 proprietary information assets can be challenging. This
                 paper explores how Reference Architectures can be
                 applied to overcome this challenge when developing
                 cloud-based applications. The presented approach was
                 developed within the DIGITbrain European project, which
                 aims at supporting small and medium-sized enterprises
                 (SMEs) and mid-caps in realizing smart business models
                 called Manufacturing as a Service, via the efficient
                 utilization of Digital Twins. In this paper, an
                 overview of Reference Architecture concepts, as well as
                 their classification, specialization, and particular
                 application possibilities are presented. Various data
                 management and potentially spatially detached data
                 processing configurations are discussed, with special
                 attention to machine learning techniques, which are of
                 high interest within various sectors, including
                 manufacturing. A framework that enables the deployment
                 and orchestration of such overall data analytics
                 Reference Architectures in clouds resources is also
                 presented, followed by a demonstrative application
                 example where the applicability of the introduced
                 techniques and solutions are showcased in practice.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2022:MLF,
  author =       "Zhao Wang and Qingguo Xu and Weimin Li",
  title =        "Multi-Layer Feature Fusion-Based Community Evolution
                 Prediction",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "4",
  pages =        "113--??",
  day =          "06",
  month =        apr,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14040113",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 22 09:50:26 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/4/113",
  abstract =     "Analyzing and predicting community evolution has many
                 important applications in criminology, sociology, and
                 other fields. In community evolution prediction, most
                 of the existing research is simply calculating the
                 features of the community, and then predicting the
                 evolution event through the classifier. However, these
                 methods do not consider the complex characteristics of
                 community evolution, and only predict the community's
                 evolution from a single level. To solve these problems,
                 this paper proposes an algorithm called multi-layer
                 feature fusion-based community evolution prediction,
                 which obtains features from the community layer and
                 node layer. The final community feature is the fusion
                 of the two layer features. At the node layer, this
                 paper proposes a global and local-based role-extraction
                 algorithm. This algorithm can effectively discover
                 different roles in the community. In this way, we can
                 distinguish the influence of nodes with different
                 characteristics on the community evolution. At the
                 community layer, this paper proposes to use the
                 community hypergraph to obtain the inter-community
                 interaction relationship. After all the features are
                 obtained, this paper trains a classifier through these
                 features and uses them in community evolution
                 prediction. The experimental results show that the
                 algorithm proposed in this paper is better than other
                 algorithms in terms of prediction effect.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Symvoulidis:2022:HIB,
  author =       "Chrysostomos Symvoulidis and George Marinos and
                 Athanasios Kiourtis and Argyro Mavrogiorgou and
                 Dimosthenis Kyriazis",
  title =        "{HealthFetch}: an Influence-Based, Context-Aware
                 Prefetch Scheme in Citizen-Centered Health Storage
                 Clouds",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "4",
  pages =        "112--??",
  day =          "01",
  month =        apr,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14040112",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 22 09:50:26 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/4/112",
  abstract =     "Over the past few years, increasing attention has been
                 given to the health sector and the integration of new
                 technologies into it. Cloud computing and storage
                 clouds have become essentially state of the art
                 solutions for other major areas and have started to
                 rapidly make their presence powerful in the health
                 sector as well. More and more companies are working
                 toward a future that will allow healthcare
                 professionals to engage more with such infrastructures,
                 enabling them a vast number of possibilities. While
                 this is a very important step, less attention has been
                 given to the citizens. For this reason, in this paper,
                 a citizen-centered storage cloud solution is proposed
                 that will allow citizens to hold their health data in
                 their own hands while also enabling the exchange of
                 these data with healthcare professionals during
                 emergency situations. Not only that, in order to reduce
                 the health data transmission delay, a novel
                 context-aware prefetch engine enriched with deep
                 learning capabilities is proposed. The proposed
                 prefetch scheme, along with the proposed storage cloud,
                 is put under a two-fold evaluation in several
                 deployment and usage scenarios in order to examine its
                 performance with respect to the data transmission
                 times, while also evaluating its outcomes compared to
                 other state of the art solutions. The results show that
                 the proposed solution shows significant improvement of
                 the download speed when compared with the storage
                 cloud, especially when large data are exchanged. In
                 addition, the results of the proposed scheme evaluation
                 depict that the proposed scheme improves the overall
                 predictions, considering the coefficient of
                 determination ( R2 {$>$} 0.94) and the mean of errors
                 (RMSE {$<$} 1), while also reducing the training data
                 by 12\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Khalil:2022:LTC,
  author =       "Haytham Khalil and Khalid Elgazzar",
  title =        "Location Transparency Call ({LTC}) System: an
                 Intelligent Phone Dialing System Based on the {Phone of
                 Things (PoT)} Architecture",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "4",
  pages =        "111--??",
  day =          "31",
  month =        mar,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14040111",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 22 09:50:26 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/4/111",
  abstract =     "Phone of Things (PoT) extends the connectivity options
                 for IoT systems by leveraging the ubiquitous phone
                 network infrastructure, making it part of the IoT
                 architecture. PoT enriches the connectivity options of
                 IoT while promoting its affordability, accessibility,
                 security, and scalability. PoT enables incentive IoT
                 applications that can result in more innovative homes,
                 office environments, and telephony solutions. This
                 paper presents the Location Transparency Call (LTC)
                 system, an intelligent phone dialing system for
                 businesses based on the PoT architecture. The LTC
                 system intelligently mitigates the impact of missed
                 calls on companies and provides high availability and
                 dynamic reachability to employees within the premises.
                 LTC automatically forwards calls to the intended
                 employees to the closest phone extensions at their
                 current locations. Location transparency is achieved by
                 actively maintaining and dynamically updating a
                 real-time database that maps the persons' locations
                 using the RFID tags they carry. We demonstrate the
                 system's feasibility and usability and evaluate its
                 performance through a fully-fledged prototype
                 representing its hardware and software components that
                 can be applied in real situations at large scale.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Patil:2022:DBD,
  author =       "Pranita Patil and Kevin Purcell",
  title =        "Decorrelation-Based Deep Learning for Bias
                 Mitigation",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "4",
  pages =        "110--??",
  day =          "29",
  month =        mar,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14040110",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 22 09:50:26 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/4/110",
  abstract =     "Although deep learning has proven to be tremendously
                 successful, the main issue is the dependency of its
                 performance on the quality and quantity of training
                 datasets. Since the quality of data can be affected by
                 biases, a novel deep learning method based on
                 decorrelation is presented in this study. The
                 decorrelation specifically learns bias invariant
                 features by reducing the non-linear statistical
                 dependency between features and bias itself. This makes
                 the deep learning models less prone to biased decisions
                 by addressing data bias issues. We introduce
                 Decorrelated Deep Neural Networks (DcDNN) or
                 Decorrelated Convolutional Neural Networks (DcCNN) and
                 Decorrelated Artificial Neural Networks (DcANN) by
                 applying decorrelation-based optimization to Deep
                 Neural Networks (DNN) and Artificial Neural Networks
                 (ANN), respectively. Previous bias mitigation methods
                 result in a drastic loss in accuracy at the cost of
                 bias reduction. Our study aims to resolve this by
                 controlling how strongly the decorrelation function for
                 bias reduction and loss function for accuracy affect
                 the network objective function. The detailed analysis
                 of the hyperparameter shows that for the optimal value
                 of hyperparameter, our model is capable of maintaining
                 accuracy while being bias invariant. The proposed
                 method is evaluated on several benchmark datasets with
                 different types of biases such as age, gender, and
                 color. Additionally, we test our approach along with
                 traditional approaches to analyze the bias mitigation
                 in deep learning. Using simulated datasets, the results
                 of t-distributed stochastic neighbor embedding (t-SNE)
                 of the proposed model validated the effective removal
                 of bias. An analysis of fairness metrics and accuracy
                 comparisons shows that using our proposed models
                 reduces the biases without compromising accuracy
                 significantly. Furthermore, the comparison of our
                 method with existing methods shows the superior
                 performance of our model in terms of bias mitigation,
                 as well as simplicity of training.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ayaida:2022:TMR,
  author =       "Marwane Ayaida and Nadhir Messai and Frederic Valentin
                 and Dimitri Marcheras",
  title =        "{TalkRoBots}: a Middleware for Robotic Systems in
                 {Industry 4.0}",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "4",
  pages =        "109--??",
  day =          "29",
  month =        mar,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14040109",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 22 09:50:26 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/4/109",
  abstract =     "This paper proposes a middleware called TalkRoBots
                 that handles interoperability issues, which could be
                 encountered in Industry 4.0. The latter proposes a
                 unified communication approach facilitating the
                 collaboration between heterogeneous equipment without
                 needing to change neither the already used software nor
                 the existing hardware. It allows heterogeneous robots,
                 using both open and proprietary robotic frameworks
                 (i.e., ROS, ABB, Universal Robots, etc.), to
                 communicate and to share information in a transparent
                 manner. It allows robots and Industrial Internet of
                 Things (IIoT) devices to communicate together.
                 Furthermore, a resilience mechanism based on an
                 Artificial Intelligence (AI) approach was designed in
                 order to allow automatically replacing a defective
                 robot with an optimal alternatively available robot.
                 Finally, a remote interface, which could be run through
                 the Cloud, allows users to manipulate fleets of robots
                 from anywhere and to obtain access to sensors' data. A
                 practical scenario using five different robots has been
                 realized to demonstrate the different possibilities.
                 This demonstrates the cost effectiveness of our
                 middleware in terms of its impacts on the communication
                 network. Finally, a simulation study that evaluates the
                 scalability of our middleware clearly shows that
                 TalkRoBots can be used efficiently in industrial
                 scenarios involving a huge number of heterogeneous
                 robots and IIoT devices.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Vitorino:2022:APP,
  author =       "Jo{\~a}o Vitorino and Nuno Oliveira and Isabel
                 Pra{\c{c}}a",
  title =        "Adaptative Perturbation Patterns: Realistic
                 Adversarial Learning for Robust Intrusion Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "4",
  pages =        "108--??",
  day =          "29",
  month =        mar,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14040108",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 22 09:50:26 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/4/108",
  abstract =     "Adversarial attacks pose a major threat to machine
                 learning and to the systems that rely on it. In the
                 cybersecurity domain, adversarial cyber-attack examples
                 capable of evading detection are especially concerning.
                 Nonetheless, an example generated for a domain with
                 tabular data must be realistic within that domain. This
                 work establishes the fundamental constraint levels
                 required to achieve realism and introduces the
                 adaptative perturbation pattern method (A2PM) to
                 fulfill these constraints in a gray-box setting. A2PM
                 relies on pattern sequences that are independently
                 adapted to the characteristics of each class to create
                 valid and coherent data perturbations. The proposed
                 method was evaluated in a cybersecurity case study with
                 two scenarios: Enterprise and Internet of Things (IoT)
                 networks. Multilayer perceptron (MLP) and random forest
                 (RF) classifiers were created with regular and
                 adversarial training, using the CIC-IDS2017 and IoT-23
                 datasets. In each scenario, targeted and untargeted
                 attacks were performed against the classifiers, and the
                 generated examples were compared with the original
                 network traffic flows to assess their realism. The
                 obtained results demonstrate that A2PM provides a
                 scalable generation of realistic adversarial examples,
                 which can be advantageous for both adversarial training
                 and attacks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Afrin:2022:MSA,
  author =       "Nusrat Afrin and Jason Brown and Jamil Y. Khan",
  title =        "A Multi-Service Adaptive Semi-Persistent {LTE} Uplink
                 Scheduler for Low Power {M2M} Devices",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "4",
  pages =        "107--??",
  day =          "27",
  month =        mar,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14040107",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 22 09:50:26 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/4/107",
  abstract =     "The prominence of Machine-to-Machine (M2M)
                 communications in the future wide area communication
                 networks place various challenges to the cellular
                 technologies such as the Long Term Evolution (LTE)
                 standard, owing to the large number of M2M devices
                 generating small bursts of infrequent data packets with
                 a wide range of delay requirements. The channel
                 structure and Quality of Service (QoS) framework of LTE
                 networks fail to support M2M traffic with multiple
                 burst sizes and QoS requirements while a bottleneck
                 often arises from the limited control resources to
                 communicate future uplink resource allocations to the
                 M2M devices. Moreover, many of the M2M devices are
                 battery-powered and require a low-power consuming wide
                 area technology for wide-spread deployments. To
                 alleviate these issues, in this article we propose an
                 adaptive semi-persistent scheduling (SPS) scheme for
                 the LTE uplink which caters for multi-service M2M
                 traffic classes with variable burst sizes and delay
                 tolerances. Instead of adhering to the rigid LTE QoS
                 framework, the proposed algorithm supports variation of
                 uplink allocation sizes based on queued data length yet
                 does not require control signaling to inform those
                 allocations to the respective devices. Both the eNodeB
                 and the M2M devices can determine the precise uplink
                 resource allocation related parameters based on their
                 mutual knowledge, thus omitting the burden of regular
                 control signaling exchanges. Based on a control
                 parameter, the algorithm can offer different capacities
                 and levels of QoS satisfaction to different traffic
                 classes. We also introduce a pre-emptive feature by
                 which the algorithm can prioritize new traffic with low
                 delay tolerance over ongoing delay-tolerant traffic. We
                 also build a model for incorporating the Discontinuous
                 Reception (DRX) mechanism in synchronization with the
                 adaptive SPS transmissions so that the UE power
                 consumption can be significantly lowered, thereby
                 extending their battery lives. The simulation and
                 performance analysis of the proposed scheme shows
                 significant improvement over the traditional LTE
                 scheduler in terms of QoS satisfaction, channel
                 utilization and low power requirements of multi-service
                 M2M traffic.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Esposito:2022:SIN,
  author =       "Massimo Esposito and Giovanni Luca Masala and Aniello
                 Minutolo and Marco Pota",
  title =        "Special Issue {``Natural Language Engineering:
                 Methods, Tasks and Applications''}",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "4",
  pages =        "106--??",
  day =          "26",
  month =        mar,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14040106",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 22 09:50:26 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/4/106",
  abstract =     "The prominence of Machine-to-Machine (M2M)
                 communications in the future wide area communication
                 networks place various challenges to the cellular
                 technologies such as the Long Term Evolution (LTE)
                 standard, owing to the large number of M2M devices
                 generating small bursts of infrequent data packets with
                 a wide range of delay requirements. The channel
                 structure and Quality of Service (QoS) framework of LTE
                 networks fail to support M2M traffic with multiple
                 burst sizes and QoS requirements while a bottleneck
                 often arises from the limited control resources to
                 communicate future uplink resource allocations to the
                 M2M devices. Moreover, many of the M2M devices are
                 battery-powered and require a low-power consuming wide
                 area technology for wide-spread deployments. To
                 alleviate these issues, in this article we propose an
                 adaptive semi-persistent scheduling (SPS) scheme for
                 the LTE uplink which caters for multi-service M2M
                 traffic classes with variable burst sizes and delay
                 tolerances. Instead of adhering to the rigid LTE QoS
                 framework, the proposed algorithm supports variation of
                 uplink allocation sizes based on queued data length yet
                 does not require control signaling to inform those
                 allocations to the respective devices. Both the eNodeB
                 and the M2M devices can determine the precise uplink
                 resource allocation related parameters based on their
                 mutual knowledge, thus omitting the burden of regular
                 control signaling exchanges. Based on a control
                 parameter, the algorithm can offer different capacities
                 and levels of QoS satisfaction to different traffic
                 classes. We also introduce a pre-emptive feature by
                 which the algorithm can prioritize new traffic with low
                 delay tolerance over ongoing delay-tolerant traffic. We
                 also build a model for incorporating the Discontinuous
                 Reception (DRX) mechanism in synchronization with the
                 adaptive SPS transmissions so that the UE power
                 consumption can be significantly lowered, thereby
                 extending their battery lives. The simulation and
                 performance analysis of the proposed scheme shows
                 significant improvement over the traditional LTE
                 scheduler in terms of QoS satisfaction, channel
                 utilization and low power requirements of multi-service
                 M2M traffic.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Duan:2022:DCA,
  author =       "Yingjie Duan and Hong Ni and Xiaoyong Zhu",
  title =        "A Dynamic Cache Allocation Mechanism ({DCAM}) for
                 Reliable Multicast in Information-Centric Networking",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "4",
  pages =        "105--??",
  day =          "25",
  month =        mar,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14040105",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 22 09:50:26 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/4/105",
  abstract =     "As a new network architecture, information-centric
                 networking (ICN) decouples the identifiers and locators
                 of network entities and makes full use of in-network
                 cache technology to improve the content distribution
                 efficiency. For reliable multicast, ICN in-network
                 cache can help reduce the loss recovery delay. However,
                 with the development of applications and services, a
                 multicast tree node often serves multiple reliable
                 multicast groups. How to reasonably allocate cache
                 resources for each multicast group will greatly affect
                 the performance of reliable multicast. In order to
                 improve the overall loss recovery performance of
                 reliable multicast, this paper designs a dynamic cache
                 allocation mechanism (DCAM). DCAM considers the packet
                 loss probability, the node depth of the multicast tree,
                 and the multicast transmission rate of multicast group,
                 and then allocates cache space for multicast group
                 based on the normalized cache quota weight. We also
                 explore the performance of three cache allocation
                 mechanisms (DCAM, AARM, and Equal) combined with four
                 cache strategies (LCE, CAPC, Prob, and ProbCache),
                 respectively. Experimental results show that DCAM can
                 adjust cache allocation results in time according to
                 network changes, and its combinations with various
                 cache strategies outperform other combinations.
                 Moreover, the combination of DCAM and CAPC can achieve
                 optimal performance in loss recovery delay, cache hit
                 ratio, transmission completion time, and overhead.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kavrestad:2022:ECG,
  author =       "Joakim K{\"a}vrestad and Allex Hagberg and Marcus
                 Nohlberg and Jana Rambusch and Robert Roos and Steven
                 Furnell",
  title =        "Evaluation of Contextual and Game-Based Training for
                 Phishing Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "4",
  pages =        "104--??",
  day =          "25",
  month =        mar,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14040104",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 22 09:50:26 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/4/104",
  abstract =     "Cybersecurity is a pressing matter, and a lot of the
                 responsibility for cybersecurity is put on the
                 individual user. The individual user is expected to
                 engage in secure behavior by selecting good passwords,
                 identifying malicious emails, and more. Typical support
                 for users comes from Information Security Awareness
                 Training (ISAT), which makes the effectiveness of ISAT
                 a key cybersecurity issue. This paper presents an
                 evaluation of how two promising methods for ISAT
                 support users in acheiving secure behavior using a
                 simulated experiment with 41 participants. The methods
                 were game-based training, where users learn by playing
                 a game, and Context-Based Micro-Training (CBMT), where
                 users are presented with short information in a
                 situation where the information is of direct relevance.
                 Participants were asked to identify phishing emails
                 while their behavior was monitored using eye-tracking
                 technique. The research shows that both training
                 methods can support users towards secure behavior and
                 that CBMT does so to a higher degree than game-based
                 training. The research further shows that most
                 participants were susceptible to phishing, even after
                 training, which suggests that training alone is
                 insufficient to make users behave securely.
                 Consequently, future research ideas, where training is
                 combined with other support systems, are proposed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chen:2022:CDT,
  author =       "Xiaolin Chen and Qixing Qu and Chengxi Wei and Shudong
                 Chen",
  title =        "Cross-Domain Transfer Learning Prediction of
                 {COVID-19} Popular Topics Based on Knowledge Graph",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "4",
  pages =        "103--??",
  day =          "24",
  month =        mar,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14040103",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 22 09:50:26 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/4/103",
  abstract =     "The significance of research on public opinion
                 monitoring of social network emergencies is becoming
                 increasingly important. As a platform for users to
                 communicate and share information online, social
                 networks are often the source of public opinion about
                 emergencies. Considering the relevance and
                 transmissibility of the same event in different social
                 networks, this paper takes the COVID-19 outbreak as the
                 background and selects the platforms Weibo and TikTok
                 as the research objects. In this paper, first, we use
                 the transfer learning model to apply the knowledge
                 obtained in the source domain of Weibo to the target
                 domain of TikTok. From the perspective of text
                 information, we propose an improved TC-LDA model to
                 measure the similarity between the two domains,
                 including temporal similarity and conceptual
                 similarity, which effectively improves the learning
                 effect of instance transfer and makes up for the
                 problem of insufficient sample data in the target
                 domain. Then, based on the results of transfer
                 learning, we use the improved single-pass incremental
                 clustering algorithm to discover and filter popular
                 topics in streaming data of social networks. Finally,
                 we build a topic knowledge graph using the Neo4j graph
                 database and conduct experiments to predict the
                 evolution of popular topics in new emergencies. Our
                 research results can provide a reference for public
                 opinion monitoring and early warning of emergencies in
                 government departments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tomer:2022:DIA,
  author =       "Vikas Tomer and Sachin Sharma",
  title =        "Detecting {IoT} Attacks Using an Ensemble Machine
                 Learning Model",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "4",
  pages =        "102--??",
  day =          "24",
  month =        mar,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14040102",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 22 09:50:26 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/4/102",
  abstract =     "Malicious attacks are becoming more prevalent due to
                 the growing use of Internet of Things (IoT) devices in
                 homes, offices, transportation, healthcare, and other
                 locations. By incorporating fog computing into IoT,
                 attacks can be detected in a short amount of time, as
                 the distance between IoT devices and fog devices is
                 smaller than the distance between IoT devices and the
                 cloud. Machine learning is frequently used for the
                 detection of attacks due to the huge amount of data
                 available from IoT devices. However, the problem is
                 that fog devices may not have enough resources, such as
                 processing power and memory, to detect attacks in a
                 timely manner. This paper proposes an approach to
                 offload the machine learning model selection task to
                 the cloud and the real-time prediction task to the fog
                 nodes. Using the proposed method, based on historical
                 data, an ensemble machine learning model is built in
                 the cloud, followed by the real-time detection of
                 attacks on fog nodes. The proposed approach is tested
                 using the NSL-KDD dataset. The results show the
                 effectiveness of the proposed approach in terms of
                 several performance measures, such as execution time,
                 precision, recall, accuracy, and ROC (receiver
                 operating characteristic) curve.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sarma:2022:PAD,
  author =       "Subhra Sankha Sarma and Ranjay Hazra and Peter Han Joo
                 Chong",
  title =        "Performance Analysis of {DF} Relay-Assisted {D2D}
                 Communication in a {5G} {mmWave} Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "4",
  pages =        "101--??",
  day =          "24",
  month =        mar,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14040101",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 22 09:50:26 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/4/101",
  abstract =     "Enabling D2D communication in the mmWave band has many
                 obstacles that must be mitigated. The primary concern
                 is the introduction of interference from various
                 sources. Thus, we focused our work on the performance
                 of decode-and-forward (DF) relay-assisted D2D
                 communication in the mmWave band to increase the
                 coverage probability and energy efficiency (EE). Three
                 modes are proposed for D2D communication to prevail.
                 The bitwise binary XOR operation was executed at the
                 relay node, which increased the security feature. The
                 radius of coverage was derived, which indicated the
                 switching of the modes. The diffused incoherent
                 scattering power was also considered as part of the
                 power consumption. Furthermore, a unique relay
                 selection scheme, the dynamic relay selection (DRS)
                 method, is proposed to select the optimal relay for
                 information exchange. A comparison of the proposed DF
                 relay scheme with the amplify-and-forward (AF) scheme
                 was also made. Finally, the simulation results proved
                 the efficacy of the proposed work.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Krammer:2022:USI,
  author =       "Peter Krammer and Marcel Kvassay and J{\'a}n Mojzis
                 and Martin Kenyeres and Milos Ockay and Ladislav
                 Hluch{\'y} and Lubos Pavlov and Lubos Skurc{\'a}k",
  title =        "Using Satellite Imagery to Improve Local Pollution
                 Models for High-Voltage Transmission Lines and
                 Insulators",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "4",
  pages =        "99--??",
  day =          "23",
  month =        mar,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14040099",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 22 09:50:26 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/4/99",
  abstract =     "This paper addresses the regression modeling of local
                 environmental pollution levels for electric power
                 industry needs, which is fundamental for the proper
                 design and maintenance of high-voltage transmission
                 lines and insulators in order to prevent various
                 hazards, such as accidental flashovers due to pollution
                 and the resultant power outages. The primary goal of
                 our study was to increase the precision of regression
                 models for this application area by exploiting
                 additional input attributes extracted from satellite
                 imagery and adjusting the modeling methodology. Given
                 that thousands of different attributes can be extracted
                 from satellite images, of which only a few are likely
                 to contain useful information, we also explored
                 suitable feature selection procedures. We show that a
                 suitable combination of attribute selection methods
                 (relief, FSRF-Test, and forward selection), regression
                 models (random forest models and M5P regression trees),
                 and modeling methodology (estimating field-measured
                 values of target variables rather than their upper
                 bounds) can significantly increase the total modeling
                 accuracy, measured by the correlation between the
                 estimated and the true values of target variables.
                 Specifically, the accuracies of our regression models
                 dramatically rose from 0.12--0.23 to 0.40--0.64, while
                 their relative absolute errors were conversely reduced
                 (e.g., from 1.04 to 0.764 for the best model).",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Milicevic:2022:DRN,
  author =       "Mario Milicevic and Vedran Batos and Adriana Lipovac
                 and Zeljka Car",
  title =        "Deep Regression Neural Networks for Proportion
                 Judgment",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "4",
  pages =        "100--??",
  day =          "23",
  month =        mar,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14040100",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 22 09:50:26 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/4/100",
  abstract =     "Deep regression models are widely employed to solve
                 computer vision tasks, such as human age or pose
                 estimation, crowd counting, object detection, etc.
                 Another possible area of application, which to our
                 knowledge has not been systematically explored so far,
                 is proportion judgment. As a prerequisite for
                 successful decision making, individuals often have to
                 use proportion judgment strategies, with which they
                 estimate the magnitude of one stimulus relative to
                 another (larger) stimulus. This makes this estimation
                 problem interesting for the application of machine
                 learning techniques. In regard to this, we proposed
                 various deep regression architectures, which we tested
                 on three original datasets of very different origin and
                 composition. This is a novel approach, as the
                 assumption is that the model can learn the concept of
                 proportion without explicitly counting individual
                 objects. With comprehensive experiments, we have
                 demonstrated the effectiveness of the proposed models
                 which can predict proportions on real-life datasets
                 more reliably than human experts, considering the
                 coefficient of determination ({$>$0}.95) and the amount
                 of errors ( MAE {$<$} 2, RMSE {$<$} 3). If there is no
                 significant number of errors in determining the ground
                 truth, with an appropriate size of the learning
                 dataset, an additional reduction of MAE to 0.14 can be
                 achieved. The used datasets will be publicly available
                 to serve as reference data sources in similar
                 projects.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Cocco:2022:BSH,
  author =       "Luisanna Cocco and Roberto Tonelli and Michele
                 Marchesi",
  title =        "Bitcoin as a Safe Haven during {COVID-19} Disease",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "4",
  pages =        "98--??",
  day =          "22",
  month =        mar,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14040098",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 22 09:50:26 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/4/98",
  abstract =     "In this paper, we investigate the role of Bitcoin as a
                 safe haven against the stock market losses during the
                 spread of COVID-19. The performed analysis was based on
                 a regression model with dummy variables defined around
                 some crucial dates of the pandemic and on the dynamic
                 conditional correlations. To try to model the real
                 dynamics of the markets, we studied the safe-haven
                 properties of Bitcoin against thirteen of the major
                 stock market indexes losses using daily data spanning
                 from 1 July 2019 until 20 February 2021. A similar
                 analysis was also performed for Ether. Results show
                 that this pandemic impacts on the Bitcoin status as
                 safe haven, but we are still far from being able to
                 define Bitcoin as a safe haven.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ferres:2022:PDE,
  author =       "Kim Ferres and Timo Schloesser and Peter A. Gloor",
  title =        "Predicting Dog Emotions Based on Posture Analysis
                 Using {DeepLabCut}",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "4",
  pages =        "97--??",
  day =          "22",
  month =        mar,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14040097",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 22 09:50:26 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/4/97",
  abstract =     "This paper describes an emotion recognition system for
                 dogs automatically identifying the emotions anger,
                 fear, happiness, and relaxation. It is based on a
                 previously trained machine learning model, which uses
                 automatic pose estimation to differentiate emotional
                 states of canines. Towards that goal, we have compiled
                 a picture library with full body dog pictures featuring
                 400 images with 100 samples each for the states
                 ``Anger'', ``Fear'', ``Happiness'' and ``Relaxation''.
                 A new dog keypoint detection model was built using the
                 framework DeepLabCut for animal keypoint detector
                 training. The newly trained detector learned from a
                 total of 13,809 annotated dog images and possesses the
                 capability to estimate the coordinates of 24 different
                 dog body part keypoints. Our application is able to
                 determine a dog's emotional state visually with an
                 accuracy between 60\% and 70\%, exceeding human
                 capability to recognize dog emotions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhang:2022:LCG,
  author =       "Xinhe Zhang and Wenbo Lv and Haoran Tan",
  title =        "Low-Complexity {GSM} Detection Based on Maximum Ratio
                 Combining",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "159",
  day =          "23",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050159",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/159",
  abstract =     "Generalized spatial modulation (GSM) technology is an
                 extension of spatial modulation (SM) technology, and
                 one of its main advantages is to further improve band
                 efficiency. However, the multiple active antennas for
                 transmission also brings the demodulation difficulties
                 at the receiver. To solve the problem of high
                 computational complexity of the optimal maximum
                 likelihood (ML) detection, two sub-optimal detection
                 algorithms are proposed through reducing the number of
                 transmit antenna combinations (TACs) detected at the
                 receiver. One is the maximum ratio combining detection
                 algorithm based on repetitive sorting strategy, termed
                 as (MRC-RS), which uses MRC repetitive sorting strategy
                 to select the most likely TACs in detection. The other
                 is the maximum ratio combining detection algorithm,
                 which is based on the iterative idea of the orthogonal
                 matching pursuit, termed the MRC-MP algorithm. The
                 MRC-MP algorithm reduces the number of TACs through
                 finite iterations to reduce the computational
                 complexity. For M-QAM constellation, a hard-limited
                 maximum likelihood (HLML) detection algorithm is
                 introduced to calculate the modulation symbol. For the
                 M-PSK constellation, a low-complexity maximum
                 likelihood (LCML) algorithm is introduced to calculate
                 the modulation symbol. The computational complexity of
                 these two algorithms for calculating the modulation
                 symbol are independent of modulation order. The
                 simulation results show that for GSM systems with a
                 large number of TACs, the proposed two algorithms not
                 only achieve almost the same bit error rate (BER)
                 performance as the ML algorithm, but also can greatly
                 reduce the computational complexity.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bilami:2022:LBB,
  author =       "Karam Eddine Bilami and Pascal Lorenz",
  title =        "Lightweight Blockchain-Based Scheme to Secure Wireless
                 {M2M} Area Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "158",
  day =          "23",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050158",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/158",
  abstract =     "Security is a challenging issue for M2M/IoT
                 applications due to the deployment, decentralization
                 and heterogeneity of M2M and IoT devices. Typical
                 security solutions may not be suitable for M2M/IoT
                 systems regarding the difficulties encountered for
                 their implementation on resource-constrained devices.
                 In this paper, we discuss the architectures deployed
                 for M2M communications and the security challenges, as
                 well as the vulnerabilities and solutions to counter
                 possible attacks. We present a lightweight design based
                 on a private blockchain to secure wireless M2M
                 communications at the device domain level. Blockchain
                 integration provides secure storage of data while
                 preserving integrity traceability and availability.
                 Besides, the evaluation and experimentations under NS3
                 simulator of the proposed scheme show that the
                 authentication mechanism is lightweight, and presents
                 better performances comparatively to other protocols in
                 terms of key parameters as communication and
                 computational overheads, average delay and energy
                 consumption.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{S:2022:QSL,
  author =       "Shrisha H. S. and Uma Boregowda",
  title =        "Quality-of-Service-Linked Privileged Content-Caching
                 Mechanism for Named Data Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "157",
  day =          "20",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050157",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/157",
  abstract =     "The domain of information-centric networking (ICN) is
                 expanding as more devices are becoming a part of
                 connected technologies. New methods for serving content
                 from a producer to a consumer are being explored, and
                 Named Data Networking (NDN) is one of them. The NDN
                 protocol routes the content from a producer to a
                 consumer in a network using content names, instead of
                 IP addresses. This facility, combined with content
                 caching, efficiently serves content for very large
                 networks consisting of a hybrid and ad hoc topology
                 with both wired and wireless media. This paper
                 addresses the issue of the quality-of-service (QoS)
                 dimension for content delivery in NDN-based networks.
                 The Internet Engineering Task Force (IETF) classifies
                 QoS traffic as (prompt, reliable), prompt, reliable,
                 and regular, and assigns corresponding priorities for
                 managing the content. QoS-linked privileged content
                 caching (QLPCC) proposes strategies for Pending
                 Interest Table (PIT) and content store (CS) management
                 in dedicated QoS nodes for handling priority content.
                 QoS nodes are intermediately resourceful NDN nodes
                 between content producers and consumers which
                 specifically manage QoS traffic. The results of this
                 study are compared with EQPR, PRR probability cache,
                 and Least Frequently Used (LFU) and Least Fresh First
                 (LFF) schemes, and QLPCC outperformed the
                 latter-mentioned schemes in terms of QoS-node CS size
                 vs. hit rate (6\% to 47\%), response time vs, QoS-node
                 CS size (65\% to 90\%), and hop count vs. QoS-node CS
                 size (60\% to 84\%) from the perspectives of priority
                 traffic and overall traffic. QLPCC performed
                 predictably when the NDN node count was increased from
                 500 to 1000, showing that the strategy is scalable.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Cox:2022:PEN,
  author =       "Bert Cox and Chesney Buyle and Daan Delabie and Lieven
                 {De Strycker} and Liesbet {Van der Perre}",
  title =        "Positioning Energy-Neutral Devices: Technological
                 Status and Hybrid {RF}-Acoustic Experiments",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "156",
  day =          "20",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050156",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/156",
  abstract =     "The digital transformation is exciting the uptake of
                 Internet-of-Things technologies, and raises the
                 questions surrounding our knowledge of the positions of
                 many of these things. A review of indoor localization
                 technologies summarized in this paper shows that with
                 conventional RF-based techniques, a significant
                 challenge exists in terms of achieving good accuracy
                 with a low power consumption at the device side. We
                 present hybrid RF-acoustic approaches as an interesting
                 alternative: the slow propagation speed of sound allows
                 for accurate distance measurements, while RF can easily
                 provide synchronization, data, and power to the
                 devices. We explain how the combination of adequate
                 signaling realizing a late wake-up of the devices with
                 backscattering could position energy-neutral devices.
                 Experiments in a real-life testbed confirmed the
                 potential 10 cm-accuracy based on RF-harvested energy.
                 Nonetheless, these also expose open challenges to be
                 resolved in order to achieve accurate 3D positioning.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{ZareRavasan:2022:ESI,
  author =       "Ahad ZareRavasan and Taha Mansouri and Michal
                 Krc{\'a}l and Saeed Rouhani",
  title =        "Editorial for the Special Issue on Blockchain:
                 Applications, Challenges, and Solutions",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "155",
  day =          "19",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050155",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/155",
  abstract =     "The digital transformation is exciting the uptake of
                 Internet-of-Things technologies, and raises the
                 questions surrounding our knowledge of the positions of
                 many of these things. A review of indoor localization
                 technologies summarized in this paper shows that with
                 conventional RF-based techniques, a significant
                 challenge exists in terms of achieving good accuracy
                 with a low power consumption at the device side. We
                 present hybrid RF-acoustic approaches as an interesting
                 alternative: the slow propagation speed of sound allows
                 for accurate distance measurements, while RF can easily
                 provide synchronization, data, and power to the
                 devices. We explain how the combination of adequate
                 signaling realizing a late wake-up of the devices with
                 backscattering could position energy-neutral devices.
                 Experiments in a real-life testbed confirmed the
                 potential 10 cm-accuracy based on RF-harvested energy.
                 Nonetheless, these also expose open challenges to be
                 resolved in order to achieve accurate 3D positioning.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Manolopoulos:2022:VME,
  author =       "Ioannis Manolopoulos and Dimitrios Loukatos and Kimon
                 Kontovasilis",
  title =        "A Versatile {MANET} Experimentation Platform and Its
                 Evaluation through Experiments on the Performance of
                 Routing Protocols under Diverse Conditions",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "154",
  day =          "19",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050154",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/154",
  abstract =     "Mobile Ad hoc Networks (MANETs) are characterized by
                 highly dynamic phenomena and volatility. These features
                 have a significant impact on network performance and
                 should be present in the scenarios of experiments for
                 the assessment of MANET-related technologies. However,
                 the currently available experimentation approaches
                 suffer from limitations, either employing overly
                 abstract simulation-based models that cannot capture
                 real-world imperfections or drawing upon ``monolithic''
                 testbeds suited only to a narrow set of predetermined
                 technologies, operational scenarios, or environmental
                 conditions. Toward addressing these limitations, this
                 work proposes a versatile platform that can accommodate
                 many of the complexities present in real-world
                 scenarios while still remaining highly flexible and
                 customizable to enable a wide variety of MANET-related
                 experiments. The platform is characterized by a modular
                 architecture with clearly defined modules for the
                 signaling between peer mobile nodes, the tracking of
                 each node's location and motion, the routing protocol
                 functionality, and the management of communication
                 messages at each node. The relevant software runs on
                 inexpensive Raspberry Pi-based commodity hardware,
                 which can be readily attached to robotic devices for
                 moving the network nodes in accordance with controlled
                 mobility patterns. Moreover, through an appropriate
                 tuning of certain modules, a number of important
                 operational conditions can be precisely controlled
                 through software, e.g., restricting the communications
                 range (thus reducing the network density) or for
                 emulating the mobility patterns of nodes. The
                 effectiveness and versatility of the proposed platform
                 are demonstrated through the realization of a series of
                 experiments on the performance comparison of selected
                 routing protocols under diverse network density
                 conditions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ogundokun:2022:MIT,
  author =       "Roseline Oluwaseun Ogundokun and Sanjay Misra and
                 Mychal Douglas and Robertas Damasevicius and Rytis
                 Maskeliunas",
  title =        "{Medical Internet-of-Things} Based Breast Cancer
                 Diagnosis Using Hyperparameter-Optimized Neural
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "153",
  day =          "18",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050153",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/153",
  abstract =     "In today's healthcare setting, the accurate and timely
                 diagnosis of breast cancer is critical for recovery and
                 treatment in the early stages. In recent years, the
                 Internet of Things (IoT) has experienced a
                 transformation that allows the analysis of real-time
                 and historical data using artificial intelligence (AI)
                 and machine learning (ML) approaches. Medical IoT
                 combines medical devices and AI applications with
                 healthcare infrastructure to support medical
                 diagnostics. The current state-of-the-art approach
                 fails to diagnose breast cancer in its initial period,
                 resulting in the death of most women. As a result,
                 medical professionals and researchers are faced with a
                 tremendous problem in early breast cancer detection. We
                 propose a medical IoT-based diagnostic system that
                 competently identifies malignant and benign people in
                 an IoT environment to resolve the difficulty of
                 identifying early-stage breast cancer. The artificial
                 neural network (ANN) and convolutional neural network
                 (CNN) with hyperparameter optimization are used for
                 malignant vs. benign classification, while the Support
                 Vector Machine (SVM) and Multilayer Perceptron (MLP)
                 were utilized as baseline classifiers for comparison.
                 Hyperparameters are important for machine learning
                 algorithms since they directly control the behaviors of
                 training algorithms and have a significant effect on
                 the performance of machine learning models. We employ a
                 particle swarm optimization (PSO) feature selection
                 approach to select more satisfactory features from the
                 breast cancer dataset to enhance the classification
                 performance using MLP and SVM, while grid-based search
                 was used to find the best combination of the
                 hyperparameters of the CNN and ANN models. The
                 Wisconsin Diagnostic Breast Cancer (WDBC) dataset was
                 used to test the proposed approach. The proposed model
                 got a classification accuracy of 98.5\% using CNN, and
                 99.2\% using ANN.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liu:2022:DBA,
  author =       "Yazhi Liu and Dongyu Wei and Chunyang Zhang and Wei
                 Li",
  title =        "Distributed Bandwidth Allocation Strategy for {QoE}
                 Fairness of Multiple Video Streams in Bottleneck
                 Links",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "152",
  day =          "18",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050152",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/152",
  abstract =     "In QoE fairness optimization of multiple video
                 streams, a distributed video stream fairness scheduling
                 strategy based on federated deep reinforcement learning
                 is designed to address the problem of low bandwidth
                 utilization due to unfair bandwidth allocation and the
                 problematic convergence of distributed algorithms in
                 cooperative control of multiple video streams. The
                 proposed strategy predicts a reasonable bandwidth
                 allocation weight for the current video stream
                 according to its player state and the global
                 characteristics provided by the server. Then the
                 congestion control protocol allocates the proportion of
                 available bandwidth, matching its bandwidth allocation
                 weight to each video stream in the bottleneck link. The
                 strategy trains a local predictive model on each client
                 and periodically performs federated aggregation to
                 generate the optimal global scheme. In addition, the
                 proposed strategy constructs global parameters
                 containing information about the overall state of the
                 video system to improve the performance of the
                 distributed scheduling algorithm. The experimental
                 results show that the introduction of global parameters
                 can improve the algorithm's QoE fairness and overall
                 QoE efficiency by 10\% and 8\%, respectively. The QoE
                 fairness and overall QoE efficiency are improved by 8\%
                 and 7\%, respectively, compared with the latest
                 scheme.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Nguyen:2022:QMA,
  author =       "Duc Nguyen and Nam Pham Ngoc and Truong Cong Thang",
  title =        "{QoE} Models for Adaptive Streaming: a Comprehensive
                 Evaluation",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "151",
  day =          "13",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050151",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/151",
  abstract =     "Adaptive streaming has become a key technology for
                 various multimedia services, such as online learning,
                 mobile streaming, Internet TV, etc. However, because of
                 throughput fluctuations, video quality may be
                 dramatically varying during a streaming session. In
                 addition, stalling events may occur when segments do
                 not reach the user device before their playback
                 deadlines. It is well-known that quality variations and
                 stalling events cause negative impacts on Quality of
                 Experience (QoE). Therefore, a main challenge in
                 adaptive streaming is how to evaluate the QoE of
                 streaming sessions taking into account the influences
                 of these factors. Thus far, many models have been
                 proposed to tackle this issue. In addition, a lot of
                 QoE databases have been publicly available. However,
                 there have been no extensive evaluations of existing
                 models using various databases. To fill this gap, in
                 this study, we conduct an extensive evaluation of
                 thirteen models on twelve databases with different
                 characteristics of viewing devices, codecs, and session
                 durations. Through experiment results, important
                 findings are provided with regard to QoE prediction of
                 streaming sessions. In addition, some suggestions on
                 the effective employment of QoE models are presented.
                 The findings and suggestions are expected to be useful
                 for researchers and service providers to make QoE
                 assessments and improvements of streaming solutions in
                 adaptive streaming.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Florea:2022:RBT,
  author =       "Alexandru-Ioan Florea and Ionut Anghel and Tudor
                 Cioara",
  title =        "A Review of Blockchain Technology Applications in
                 Ambient Assisted Living",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "150",
  day =          "12",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050150",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/150",
  abstract =     "The adoption of remote assisted care was accelerated
                 by the COVID-19 pandemic. This type of system acquires
                 data from various sensors, runs analytics to understand
                 people's activities, behavior, and living problems, and
                 disseminates information with healthcare stakeholders
                 to support timely follow-up and intervention.
                 Blockchain technology may offer good technical
                 solutions for tackling Internet of Things monitoring,
                 data management, interventions, and privacy concerns in
                 ambient assisted living applications. Even though the
                 integration of blockchain technology with assisted care
                 is still at the beginning, it has the potential to
                 change the health and care processes through a secure
                 transfer of patient data, better integration of care
                 services, or by increasing coordination and awareness
                 across the continuum of care. The motivation of this
                 paper is to systematically review and organize these
                 elements according to the main problems addressed. To
                 the best of our knowledge, there are no studies
                 conducted that address the solutions for integrating
                 blockchain technology with ambient assisted living
                 systems. To conduct the review, we have followed the
                 Preferred Reporting Items for Systematic Reviews and
                 Meta-Analyses (PRISMA) methodology with clear criteria
                 for including and excluding papers, allowing the reader
                 to effortlessly gain insights into the current
                 state-of-the-art research in the field. The results
                 highlight the advantages and open issues that would
                 require increased attention from the research community
                 in the coming years. As for directions for further
                 research, we have identified data sharing and
                 integration of care paths with blockchain, storage, and
                 transactional costs, personalization of data disclosure
                 paths, interoperability with legacy care systems, legal
                 issues, and digital rights management.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Leech:2022:FMB,
  author =       "Sonya Leech and Jonathan Dunne and David Malone",
  title =        "A Framework to Model Bursty Electronic Data
                 Interchange Messages for Queueing Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "149",
  day =          "12",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050149",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/149",
  abstract =     "Within a supply chain organisation, where millions of
                 messages are processed, reliability and performance of
                 message throughput are important. Problems can occur
                 with the ingestion of messages; if they arrive more
                 quickly than they can be processed, they can cause
                 queue congestion. This paper models data interchange
                 (EDI) messages. We sought to understand how best DevOps
                 should model these messages for performance testing and
                 how best to apply smart EDI content awareness that
                 enhance the realms of Ambient Intelligence (Aml) with a
                 Business-to business (B2B) supply chain organisation.
                 We considered key performance indicators (KPI) for
                 over- or under-utilisation of these queueing systems.
                 We modelled message service and inter-arrival times,
                 partitioned data along various axes to facilitate
                 statistical modelling and used continuous parametric
                 and non-parametric techniques. Our results include the
                 best fit for parametric and non-parametric techniques.
                 We noted that a one-size-fits-all model is
                 inappropriate for this heavy-tailed enterprise dataset.
                 Our results showed that parametric distribution models
                 were suitable for modelling the distribution's tail,
                 whilst non-parametric kernel density estimation models
                 were better suited for modelling the head of a
                 distribution. Depending on how we partitioned our data
                 along the axes, our data suffer from quantisation
                 noise.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Razak:2022:MUA,
  author =       "Siti Fatimah Abdul Razak and Sumendra Yogarayan and
                 Mohd Fikri Azli Abdullah and Afizan Azman",
  title =        "Modeling User Acceptance of In-Vehicle Applications
                 for Safer Road Environment",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "148",
  day =          "11",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050148",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/148",
  abstract =     "Driver acceptance studies are vital from the
                 manufacturer's perspective as well as the driver's
                 perspective. Most empirical investigations are limited
                 to populations in the United States and Europe. Asian
                 communities, particularly in Southeast Asia, which make
                 for a large proportion of global car users, are
                 underrepresented. To better understand the user
                 acceptance toward in-vehicle applications, additional
                 factors need to be included in order to complement the
                 existing constructs in the Technology Acceptance Model
                 (TAM). Hypotheses were developed and survey items were
                 designed to validate the constructs in the research
                 model. A total of 308 responses were received among
                 Malaysians via convenience sampling and analyzed using
                 linear and non-linear regression analyses. Apart from
                 that, a mediating effect analysis was also performed to
                 assess the indirect effect a variable has on another
                 associated variable. We extended the TAM by including
                 personal characteristics, system characteristics,
                 social influence and trust, which could influence
                 users' intention to use the in-vehicle applications. We
                 found that users from Malaysia are more likely to
                 accept in-vehicle applications when they have the
                 information about the system and believe that the
                 applications are reliable and give an advantage in
                 their driving experience. Without addressing the user
                 acceptance, the adoption of the applications may
                 progress more slowly, with the additional unfortunate
                 result that potentially avoidable crashes will continue
                 to occur.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Papadopoulou:2022:MNN,
  author =       "Olga Papadopoulou and Themistoklis Makedas and Lazaros
                 Apostolidis and Francesco Poldi and Symeon Papadopoulos
                 and Ioannis Kompatsiaris",
  title =        "{MeVer NetworkX}: Network Analysis and Visualization
                 for Tracing Disinformation",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "147",
  day =          "10",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050147",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/147",
  abstract =     "The proliferation of online news, especially during
                 the ``infodemic'' that emerged along with the COVID-19
                 pandemic, has rapidly increased the risk of and, more
                 importantly, the volume of online misinformation.
                 Online Social Networks (OSNs), such as Facebook,
                 Twitter, and YouTube, serve as fertile ground for
                 disseminating misinformation, making the need for tools
                 for analyzing the social web and gaining insights into
                 communities that drive misinformation online vital. We
                 introduce the MeVer NetworkX analysis and visualization
                 tool, which helps users delve into social media
                 conversations, helps users gain insights about how
                 information propagates, and provides intuition about
                 communities formed via interactions. The contributions
                 of our tool lie in easy navigation through a multitude
                 of features that provide helpful insights about the
                 account behaviors and information propagation, provide
                 the support of Twitter, Facebook, and Telegram graphs,
                 and provide the modularity to integrate more platforms.
                 The tool also provides features that highlight
                 suspicious accounts in a graph that a user should
                 investigate further. We collected four Twitter datasets
                 related to COVID-19 disinformation to present the
                 tool's functionalities and evaluate its
                 effectiveness.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Asad:2022:SMS,
  author =       "Arghavan Asad and Rupinder Kaur and Farah Mohammadi",
  title =        "A Survey on Memory Subsystems for Deep Neural Network
                 Accelerators",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "146",
  day =          "10",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050146",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/146",
  abstract =     "From self-driving cars to detecting cancer, the
                 applications of modern artificial intelligence (AI)
                 rely primarily on deep neural networks (DNNs). Given
                 raw sensory data, DNNs are able to extract high-level
                 features after the network has been trained using
                 statistical learning. However, due to the massive
                 amounts of parallel processing in computations, the
                 memory wall largely affects the performance. Thus, a
                 review of the different memory architectures applied in
                 DNN accelerators would prove beneficial. While the
                 existing surveys only address DNN accelerators in
                 general, this paper investigates novel advancements in
                 efficient memory organizations and design methodologies
                 in the DNN accelerator. First, an overview of the
                 various memory architectures used in DNN accelerators
                 will be provided, followed by a discussion of memory
                 organizations on non-ASIC DNN accelerators.
                 Furthermore, flexible memory systems incorporating an
                 adaptable DNN computation will be explored. Lastly, an
                 analysis of emerging memory technologies will be
                 conducted. The reader, through this article, will:
                 1---gain the ability to analyze various proposed memory
                 architectures; 2---discern various DNN accelerators
                 with different memory designs; 3---become familiar with
                 the trade-offs associated with memory organizations;
                 and 4---become familiar with proposed new memory
                 systems for modern DNN accelerators to solve the memory
                 wall and other mentioned current issues.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tropea:2022:SWS,
  author =       "Mauro Tropea and Mattia Giovanni Spina and Floriano
                 {De Rango} and Antonio Francesco Gentile",
  title =        "Security in Wireless Sensor Networks: a Cryptography
                 Performance Analysis at {MAC} Layer",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "145",
  day =          "10",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050145",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/145",
  abstract =     "Wireless Sensor Networks (WSNs) are networks of small
                 devices with limited resources which are able to
                 collect different information for a variety of
                 purposes. Energy and security play a key role in these
                 networks and MAC aspects are fundamental in their
                 management. The classical security approaches are not
                 suitable in WSNs given the limited resources of the
                 nodes, which subsequently require lightweight
                 cryptography mechanisms in order to achieve high
                 security levels. In this paper, a security analysis is
                 provided comparing BMAC and LMAC protocols, in order to
                 determine, using AES, RSA, and elliptic curve
                 techniques, the protocol with the best trade-off in
                 terms of received packets and energy consumption.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gatziolis:2022:AUP,
  author =       "Kleanthis G. Gatziolis and Nikolaos D. Tselikas and
                 Ioannis D. Moscholios",
  title =        "Adaptive User Profiling in E-Commerce and
                 Administration of Public Services",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "144",
  day =          "09",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050144",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/144",
  abstract =     "The World Wide Web is evolving rapidly, and the
                 Internet is now accessible to millions of users,
                 providing them with the means to access a wealth of
                 information, entertainment and e-commerce
                 opportunities. Web browsing is largely impersonal and
                 anonymous, and because of the large population that
                 uses it, it is difficult to separate and categorize
                 users according to their preferences. One solution to
                 this problem is to create a web-platform that acts as a
                 middleware between end users and the web, in order to
                 analyze the data that is available to them. The method
                 by which user information is collected and sorted
                 according to preference is called `user profiling`.
                 These profiles could be enriched using neural networks.
                 In this article, we present our implementation of an
                 online profiling mechanism in a virtual e-shop and how
                 neural networks could be used to predict the
                 characteristics of new users. The major contribution of
                 this article is to outline the way our online profiles
                 could be beneficial both to customers and stores. When
                 shopping at a traditional physical store, real time
                 targeted `` personalized '' advertisements can be
                 delivered directly to the mobile devices of consumers
                 while they are walking around the stores next to
                 specific products, which match their buying habits.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Agbo:2022:MDI,
  author =       "Benjamin Agbo and Hussain Al-Aqrabi and Richard Hill
                 and Tariq Alsboui",
  title =        "Missing Data Imputation in the {Internet of Things}
                 Sensor Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "143",
  day =          "06",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050143",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/143",
  abstract =     "The Internet of Things (IoT) has had a tremendous
                 impact on the evolution and adoption of information and
                 communication technology. In the modern world, data are
                 generated by individuals and collected automatically by
                 physical objects that are fitted with electronics,
                 sensors, and network connectivity. IoT sensor networks
                 have become integral aspects of environmental
                 monitoring systems. However, data collected from IoT
                 sensor devices are usually incomplete due to various
                 reasons such as sensor failures, drifts, network faults
                 and various other operational issues. The presence of
                 incomplete or missing values can substantially affect
                 the calibration of on-field environmental sensors. The
                 aim of this study is to identify efficient missing data
                 imputation techniques that will ensure accurate
                 calibration of sensors. To achieve this, we propose an
                 efficient and robust imputation technique based on k
                 -means clustering that is capable of selecting the best
                 imputation technique for missing data imputation. We
                 then evaluate the accuracy of our proposed technique
                 against other techniques and test their effect on
                 various calibration processes for data collected from
                 on-field low-cost environmental sensors in urban air
                 pollution monitoring stations. To test the efficiency
                 of the imputation techniques, we simulated missing data
                 rates at 10--40\% and also considered missing values
                 occurring over consecutive periods of time (1 day, 1
                 week and 1 month). Overall, our proposed BFMVI model
                 recorded the best imputation accuracy (0.011758 RMSE
                 for 10\% missing data and 0.169418 RMSE at 40\% missing
                 data) compared to the other techniques ( k
                 Nearest-Neighbour ( k NN), Regression Imputation (RI),
                 Expectation Maximization (EM) and MissForest
                 techniques) when evaluated using different performance
                 indicators. Moreover, the results show a trade-off
                 between imputation accuracy and computational
                 complexity with benchmark techniques showing a low
                 computational complexity at the expense of accuracy
                 when compared with our proposed technique.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Atif:2022:TMM,
  author =       "Muhammad Atif and Valentina Franzoni",
  title =        "Tell Me More: Automating Emojis Classification for
                 Better Accessibility and Emotional Context
                 Recognition",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "142",
  day =          "05",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050142",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/142",
  abstract =     "Users of web or chat social networks typically use
                 emojis (e.g., smilies, memes, hearts) to convey in
                 their textual interactions the emotions underlying the
                 context of the communication, aiming for better
                 interpretability, especially for short polysemous
                 phrases. Semantic-based context recognition tools,
                 employed in any chat or social network, can directly
                 comprehend text-based emoticons (i.e., emojis created
                 from a combination of symbols and characters) and
                 translate them into audio information (e.g.,
                 text-to-speech readers for individuals with vision
                 impairment). On the other hand, for a comprehensive
                 understanding of the semantic context, image-based
                 emojis require image-recognition algorithms. This study
                 aims to explore and compare different classification
                 methods for pictograms, applied to emojis collected
                 from Internet sources. Each emoji is labeled according
                 to the basic Ekman model of six emotional states. The
                 first step involves extraction of emoji features
                 through convolutional neural networks, which are then
                 used to train conventional supervised machine learning
                 classifiers for purposes of comparison. The second
                 experimental step broadens the comparison to deep
                 learning networks. The results reveal that both the
                 conventional and deep learning classification
                 approaches accomplish the goal effectively, with deep
                 transfer learning exhibiting a highly satisfactory
                 performance, as expected.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhao:2022:EST,
  author =       "Jie Zhao and Fangwei Xiong and Peiquan Jin",
  title =        "Enhancing Short-Term Sales Prediction with Microblogs:
                 a Case Study of the Movie Box Office",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "141",
  day =          "04",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050141",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/141",
  abstract =     "Microblogs are one of the major social networks in
                 people's daily life. The increasing amount of timely
                 microblog data brings new opportunities for enterprises
                 to predict short-term product sales based on microblogs
                 because the daily microblogs posted by various users
                 can express people's sentiments on specific products,
                 such as movies and books. Additionally, the social
                 influence of microblogging platforms enables the rapid
                 spread of product information, implemented by users'
                 forwarding and commenting behavior. To verify the
                 usefulness of microblogs in enhancing the prediction of
                 short-term product sales, in this paper, we first
                 present a new framework that adopts the sentiment and
                 influence features of microblogs. Then, we describe the
                 detailed feature computation methods for sentiment
                 polarity detection and influence measurement. We also
                 implement the Linear Regression (LR) model and the
                 Support Vector Regression (SVR) model, selected as the
                 representatives of linear and nonlinear regression
                 models, to predict short-term product sales. Finally,
                 we take movie box office predictions as an example and
                 conduct experiments to evaluate the performance of the
                 proposed features and models. The results show that the
                 proposed sentiment feature and influence feature of
                 microblogs play a positive role in improving the
                 prediction precision. In addition, both the LR model
                 and the SVR model can lower the MAPE metric of the
                 prediction effectively.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Cocco:2022:SPI,
  author =       "Luisanna Cocco and Roberto Tonelli and Michele
                 Marchesi",
  title =        "A System Proposal for Information Management in
                 Building Sector Based on {BIM}, {SSI}, {IoT} and
                 Blockchain",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "140",
  day =          "30",
  month =        apr,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050140",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/140",
  abstract =     "This work presents a Self Sovereign Identity based
                 system proposal to show how Blockchain, Building
                 Information Modeling, Internet of Thing devices, and
                 Self Sovereign Identity concepts can support the
                 process of building digitalization, guaranteeing the
                 compliance standards and technical regulations. The
                 proposal ensures eligibility, transparency and
                 traceability of all information produced by
                 stakeholders, or generated by IoT devices appropriately
                 placed, during the entire life cycle of a building
                 artifact. By exploiting the concepts of the Self
                 Sovereign Identity, our proposal allows the
                 identification of all involved stakeholders, the
                 storage off-chain of all information, and that on-chain
                 of the sole data necessary for the information
                 notarization and certification, adopting
                 multi-signature approval mechanisms where appropriate.
                 In addition it allows the eligibility verification of
                 the certificated information, providing also useful
                 information for facility management. It is proposed as
                 an innovative system and companies that adopt the Open
                 Innovation paradigm might want to pursue it. The model
                 proposal is designed exploiting the Veramo platform,
                 hence the Ethereum Blockchain, and all the
                 recommendations about Self Sovereign Identity systems
                 given by the European Blockchain Partnership, and by
                 the World Wide Web Consortium.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{DelPuerto-Flores:2022:CCS,
  author =       "Jose Alberto {Del Puerto-Flores} and Jos{\'e} Luis
                 Naredo and Fernando Pe{\~n}a-Campos and Carolina
                 Del-Valle-Soto and Leonardo J. Valdivia and Ram{\'o}n
                 Parra-Michel",
  title =        "Channel Characterization and {SC-FDM} Modulation for
                 {PLC} in High-Voltage Power Lines",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "139",
  day =          "30",
  month =        apr,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050139",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/139",
  abstract =     "Digital communication over power lines is an active
                 field of research and most studies in this field focus
                 on low-voltage (LV) and medium-voltage (MV) power
                 systems. Nevertheless, as power companies are starting
                 to provide communication services and as smart-grid
                 technologies are being incorporated into power
                 networks, high-voltage (HV) power-line communication
                 has become attractive. The main constraint of
                 conventional HV power-line carrier (PLC) systems is
                 their unfeasibility for being migrated to wideband
                 channels, even with a high signal-to-noise ratio (SNR).
                 In this scenario, none of the current linear/non-linear
                 equalizers used in single carrier schemes achieve the
                 complete compensation of the highly dispersive
                 conditions, which limits their operation to 4 kHz
                 channels. In this paper, a new PLC-channel model is
                 introduced for transmission lines incorporating the
                 effects of the coupling equipment. In addition, the use
                 of the single-carrier frequency-division modulation
                 (SC-FDM) is proposed as a solution to operate PLC
                 systems in a wide bandwidth, achieving transmission
                 speeds above those of the conventional PLC system. The
                 results presented in this paper demonstrate the
                 superior performance of the SC-FDM-PLC over
                 conventional PLC systems, obtaining a higher
                 transmission capacity in 10 to 30 times.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chen:2022:FAP,
  author =       "Zheyi Chen and Weixian Liao and Pu Tian and Qianlong
                 Wang and Wei Yu",
  title =        "A Fairness-Aware Peer-to-Peer Decentralized Learning
                 Framework with Heterogeneous Devices",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "138",
  day =          "30",
  month =        apr,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050138",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/138",
  abstract =     "Distributed machine learning paradigms have benefited
                 from the concurrent advancement of deep learning and
                 the Internet of Things (IoT), among which federated
                 learning is one of the most promising frameworks, where
                 a central server collaborates with local learners to
                 train a global model. The inherent heterogeneity of IoT
                 devices, i.e., non-independent and identically
                 distributed (non-i.i.d.) data, and the inconsistent
                 communication network environment results in the
                 bottleneck of a degraded learning performance and slow
                 convergence. Moreover, most weight averaging-based
                 model aggregation schemes raise learning fairness
                 concerns. In this paper, we propose a peer-to-peer
                 decentralized learning framework to tackle the above
                 issues. Particularly, each local client iteratively
                 finds a learning pair to exchange the local learning
                 model. By doing this, multiple learning objectives are
                 optimized to advocate for learning fairness while
                 avoiding small-group domination. The proposed
                 fairness-aware approach allows local clients to
                 adaptively aggregate the received model based on the
                 local learning performance. The experimental results
                 demonstrate that the proposed approach is capable of
                 significantly improving the efficacy of federated
                 learning and outperforms the state-of-the-art schemes
                 under real-world scenarios, including balanced-i.i.d.,
                 unbalanced-i.i.d., balanced-non.i.i.d., and
                 unbalanced-non.i.i.d. environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Guia:2022:CSM,
  author =       "Sana Sahar Guia and Abdelkader Laouid and Mohammad
                 Hammoudeh and Ahc{\`e}ne Bounceur and Mai Alfawair and
                 Amna Eleyan",
  title =        "Co-Simulation of Multiple Vehicle Routing Problem
                 Models",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "137",
  day =          "29",
  month =        apr,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050137",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/137",
  abstract =     "Complex systems are often designed in a decentralized
                 and open way so that they can operate on heterogeneous
                 entities that communicate with each other. Numerous
                 studies consider the process of components simulation
                 in a complex system as a proven approach to
                 realistically predict the behavior of a complex system
                 or to effectively manage its complexity. The simulation
                 of different complex system components can be coupled
                 via co-simulation to reproduce the behavior emerging
                 from their interaction. On the other hand, multi-agent
                 simulations have been largely implemented in complex
                 system modeling and simulation. Each multi-agent
                 simulator's role is to solve one of the VRP objectives.
                 These simulators interact within a co-simulation
                 platform called MECSYCO, to ensure the integration of
                 the various proposed VRP models. This paper presents
                 the Vehicle Routing Problem (VRP) simulation results in
                 several aspects, where the main goal is to satisfy
                 several client demands. The experiments show the
                 performance of the proposed VRP multi-model and carry
                 out its improvement in terms of computational
                 complexity.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kapassa:2022:BTA,
  author =       "Evgenia Kapassa and Marinos Themistocleous",
  title =        "Blockchain Technology Applied in {IoV} Demand Response
                 Management: a Systematic Literature Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "136",
  day =          "29",
  month =        apr,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050136",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/136",
  abstract =     "Energy management in the Internet of Vehicles (IoV) is
                 becoming more prevalent as the usage of distributed
                 Electric Vehicles (EV) grows. As a result, Demand
                 Response (DR) management has been introduced to achieve
                 efficient energy management in IoV. Through DR
                 management, EV drivers are allowed to adjust their
                 energy consumption and generation based on a variety of
                 parameters, such as cost, driving patterns and driving
                 routes. Nonetheless, research in IoV DR management is
                 still in its early stages, and the implementation of DR
                 schemes faces a number of significant hurdles.
                 Blockchain is used to solve some of them (e.g.,
                 incentivization, privacy and security issues, lack of
                 interoperability and high mobility). For instance,
                 blockchain enables the introduction of safe, reliable
                 and decentralized Peer-to-Peer (P2P) energy trading.
                 The combination of blockchain and IoV is a new
                 promising approach to further improve/overcome the
                 aforementioned limitations. However, there is limited
                 literature in Demand Response Management (DRM) schemes
                 designed for IoV. Therefore, there is a need for a
                 systematic literature review (SLR) to collect and
                 critically analyze the existing relevant literature, in
                 an attempt to highlight open issues. Thus, in this
                 article, we conduct a SLR, investigating how blockchain
                 technology assists the area of DRM in IoV. We
                 contribute to the body of knowledge by offering a set
                 of observations and research challenges on
                 blockchain-based DRM in IoV. In doing so, we allow
                 other researchers to focus their work on them, and
                 further contribute to this area.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wei:2022:BTM,
  author =       "Lijun Wei and Yuhan Yang and Jing Wu and Chengnian
                 Long and Yi-Bing Lin",
  title =        "A Bidirectional Trust Model for Service Delegation in
                 {Social Internet of Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "135",
  day =          "29",
  month =        apr,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050135",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/135",
  abstract =     "As an emerging paradigm of service infrastructure,
                 social internet of things (SIoT) applies the social
                 networking aspects to the internet of things (IoT).
                 Each object in SIoT can establish the social
                 relationship without human intervention, which will
                 enhance the efficiency of interaction among objects,
                 thus boosting the service efficiency. The issue of
                 trust is regarded as an important issue in the
                 development of SIoT. It will influence the object to
                 make decisions about the service delegation. In the
                 current literature, the solutions for the trust issue
                 are always unidirectional, that is, only consider the
                 needs of the service requester to evaluate the trust of
                 service providers. Moreover, the relationship between
                 the service delegation and trust model is still
                 ambiguous. In this paper, we present a bidirectional
                 trust model and construct an explicit approach to
                 address the issue of service delegation based on the
                 trust model. We comprehensively consider the context of
                 the SIoT services or tasks for enhancing the
                 feasibility of our model. The subjective logic is used
                 for trust quantification and we design two optimized
                 operators for opinion convergence. Finally, the
                 proposed trust model and trust-based service delegation
                 method are validated through a series of numerical
                 tests.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rozanec:2022:EAI,
  author =       "Joze Rozanec and Elena Trajkova and Inna Novalija and
                 Patrik Zajec and Klemen Kenda and Blaz Fortuna and
                 Dunja Mladeni{\'c}",
  title =        "Enriching Artificial Intelligence Explanations with
                 Knowledge Fragments",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "134",
  day =          "29",
  month =        apr,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050134",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/134",
  abstract =     "Artificial intelligence models are increasingly used
                 in manufacturing to inform decision making. Responsible
                 decision making requires accurate forecasts and an
                 understanding of the models' behavior. Furthermore, the
                 insights into the models' rationale can be enriched
                 with domain knowledge. This research builds
                 explanations considering feature rankings for a
                 particular forecast, enriching them with media news
                 entries, datasets' metadata, and entries from the
                 Google knowledge graph. We compare two approaches
                 (embeddings-based and semantic-based) on a real-world
                 use case regarding demand forecasting. The
                 embeddings-based approach measures the similarity
                 between relevant concepts and retrieved media news
                 entries and datasets' metadata based on the word
                 movers' distance between embeddings. The semantic-based
                 approach recourses to wikification and measures the
                 Jaccard distance instead. The semantic-based approach
                 leads to more diverse entries when displaying media
                 events and more precise and diverse results regarding
                 recommended datasets. We conclude that the explanations
                 provided can be further improved with information
                 regarding the purpose of potential actions that can be
                 taken to influence demand and to provide ``what-if''
                 analysis capabilities.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Altuntas:2022:MEV,
  author =       "Erkin Altuntas and Peter A. Gloor and Pascal Budner",
  title =        "Measuring Ethical Values with {AI} for Better
                 Teamwork",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "133",
  day =          "27",
  month =        apr,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050133",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/133",
  abstract =     "Do employees with high ethical and moral values
                 perform better? Comparing personality characteristics,
                 moral values, and risk-taking behavior with individual
                 and team performance has long been researched. Until
                 now, these determinants of individual personality have
                 been measured through surveys. However, individuals are
                 notoriously bad at self-assessment. Combining machine
                 learning (ML) with social network analysis (SNA) and
                 natural language processing (NLP), this research draws
                 on email conversations to predict the personal values
                 of individuals. These values are then compared with the
                 individual and team performance of employees. This
                 prediction builds on a two-layered ML model. Building
                 on features of social network structure, network
                 dynamics, and network content derived from email
                 conversations, we predict personality characteristics,
                 moral values, and the risk-taking behavior of
                 employees. In turn, we use these values to predict
                 individual and team performance. Our results indicate
                 that more conscientious and less extroverted team
                 members increase the performance of their teams.
                 Willingness to take social risks decreases the
                 performance of innovation teams in a healthcare
                 environment. Similarly, a focus on values such as power
                 and self-enhancement increases the team performance of
                 a global services provider. In sum, the contributions
                 of this paper are twofold: it first introduces a novel
                 approach to measuring personal values based on ``honest
                 signals'' in emails. Second, these values are then used
                 to build better teams by identifying ideal personality
                 characteristics for a chosen task.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zargayouna:2022:UMA,
  author =       "Mahdi Zargayouna",
  title =        "On the Use of the Multi-Agent Environment for Mobility
                 Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "132",
  day =          "27",
  month =        apr,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050132",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/132",
  abstract =     "The multi-agent environment is now widely recognised
                 as a key design abstraction for constructing
                 multi-agent systems, equally important as the agents.
                 An explicitly designed environment may have several
                 roles, such as the inter-mediation between agents, the
                 support for interaction, the embodiment of rules and
                 constraints, etc. Mobility applications fit perfectly
                 with a design in the form of a multi-agent system with
                 an explicit environment model. Indeed, in these
                 applications, the components of the system are
                 autonomous and intelligent (drivers, travellers,
                 vehicles, etc.), and the transportation network is a
                 natural environment that they perceive and on which
                 they act. However, the concept of the multi-agent
                 environment may be profitably used beyond this specific
                 geographical context. This paper discusses the
                 relevance of the multi-agent environment in mobility
                 applications and describes different use cases in
                 simulation and optimisation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Khan:2022:RSR,
  author =       "Hassan Mahmood Khan and Fang-Fang Chua and Timothy
                 Tzen Vun Yap",
  title =        "{ReSQoV}: a Scalable Resource Allocation Model for
                 {QoS}-Satisfied Cloud Services",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "131",
  day =          "26",
  month =        apr,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050131",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/131",
  abstract =     "Dynamic resource provisioning is made more accessible
                 with cloud computing. Monitoring a running service is
                 critical, and modifications are performed when specific
                 criteria are exceeded. It is a standard practice to add
                 or delete resources in such situations. We investigate
                 the method to ensure the Quality of Service (QoS),
                 estimate the required resources, and modify allotted
                 resources depending on workload, serialization, and
                 parallelism due to resources. This article focuses on
                 cloud QoS violation remediation using resource planning
                 and scaling. A Resource Quantified Scaling for QoS
                 Violation (ReSQoV) model is proposed based on the
                 Universal Scalability Law (USL), which provides cloud
                 service capacity for specific workloads and generates a
                 capacity model. ReSQoV considers the system overheads
                 while allocating resources to maintain the agreed QoS.
                 As the QoS violation detection decision is Probably
                 Violation and Definitely Violation, the remedial action
                 is triggered, and required resources are added to the
                 virtual machine as vertical scaling. The scenarios
                 emulate QoS parameters and their respective resource
                 utilization for ReSQoV compared to policy-based
                 resource allocation. The results show that after
                 USLbased Quantified resource allocation, QoS is
                 regained, and validation of the ReSQoV is performed
                 through the statistical test ANOVA that shows the
                 significant difference before and after
                 implementation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yang:2022:CTC,
  author =       "Hua Yang and Teresa Gon{\c{c}}alves and Paulo Quaresma
                 and Renata Vieira and Rute Veladas and C{\'a}tia Sousa
                 Pinto and Jo{\~a}o Oliveira and Maria Cortes Ferreira
                 and J{\'e}ssica Morais and Ana Raquel Pereira and Nuno
                 Fernandes and Carolina Gon{\c{c}}alves",
  title =        "Clinical Trial Classification of {SNS24} Calls with
                 Neural Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "5",
  pages =        "130",
  day =          "26",
  month =        apr,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14050130",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri May 27 12:03:38 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/5/130",
  abstract =     "SNS24, the Portuguese National Health Contact Center,
                 is a telephone and digital public service that provides
                 clinical services. SNS24 plays an important role in the
                 identification of users' clinical situations according
                 to their symptoms. Currently, there are a number of
                 possible clinical algorithms defined, and selecting the
                 appropriate clinical algorithm is very important in
                 each telephone triage episode. Decreasing the duration
                 of the phone calls and allowing a faster interaction
                 between citizens and SNS24 service can further improve
                 the performance of the telephone triage service. In
                 this paper, we present a study using deep learning
                 approaches to build classification models, aiming to
                 support the nurses with the clinical algorithm's
                 choice. Three different deep learning architectures,
                 namely convolutional neural network (CNN), recurrent
                 neural network (RNN), and transformers-based approaches
                 are applied across a total number of 269,654 call
                 records belonging to 51 classes. The CNN, RNN, and
                 transformers-based model each achieve an accuracy of
                 76.56\%, 75.88\%, and 78.15\% over the test set in the
                 preliminary experiments. Models using the
                 transformers-based architecture are further fine-tuned,
                 achieving an accuracy of 79.67\% with Adam and 79.72\%
                 with SGD after learning rate fine-tuning; an accuracy
                 of 79.96\% with Adam and 79.76\% with SGD after epochs
                 fine-tuning; an accuracy of 80.57\% with Adam after the
                 batch size fine-tuning. Analysis of similar clinical
                 symptoms is carried out using the fine-tuned neural
                 network model. Comparisons are done over the labels
                 predicted by the neural network model, the support
                 vector machines model, and the original labels from
                 SNS24. These results suggest that using deep learning
                 is an effective and promising approach to aid the
                 clinical triage of the SNS24 phone call services.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Suraci:2022:TDD,
  author =       "Chiara Suraci and Sara Pizzi and Federico Montori and
                 Marco {Di Felice} and Giuseppe Araniti",
  title =        "{6G} to Take the Digital Divide by Storm: Key
                 Technologies and Trends to Bridge the Gap",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "189",
  day =          "19",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060189",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/189",
  abstract =     "The pandemic caused by COVID-19 has shed light on the
                 urgency of bridging the digital divide to guarantee
                 equity in the fruition of different services by all
                 citizens. The inability to access the digital world may
                 be due to a lack of network infrastructure, which we
                 refer to as service-delivery divide, or to the physical
                 conditions, handicaps, age, or digital illiteracy of
                 the citizens, that is mentioned as service-fruition
                 divide. In this paper, we discuss the way how future
                 sixth-generation (6G) systems can remedy actual
                 limitations in the realization of a truly digital
                 world. Hence, we introduce the key technologies for
                 bridging the digital gap and show how they can work in
                 two use cases of particular importance, namely eHealth
                 and education, where digital inequalities have been
                 dramatically augmented by the pandemic. Finally,
                 considerations about the socio-economical impacts of
                 future 6G solutions are drawn.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Paligu:2022:BFI,
  author =       "Furkan Paligu and Cihan Varol",
  title =        "Browser Forensic Investigations of {Instagram}
                 Utilizing {IndexedDB} Persistent Storage",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "188",
  day =          "17",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060188",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/188",
  abstract =     "Social media usage is increasing at a rapid rate.
                 Everyday users are leaving a substantial amount of data
                 as artifacts in these applications. As the size and
                 velocity of data increase, innovative technologies such
                 as Web Storage and IndexedDB are emerging.
                 Consequently, forensic investigators are facing
                 challenges to adapt to the emerging technologies to
                 establish reliable techniques for extracting and
                 analyzing suspect information. This paper investigates
                 the convenience and efficacy of performing forensic
                 investigations with a time frame and social network
                 connection analysis on IndexedDB technology. It focuses
                 on artifacts from prevalently used social networking
                 site Instagram on the Mozilla Firefox browser. A single
                 case pretest-posttest quasi-experiment is designed and
                 executed over Instagram web application to produce
                 artifacts that are later extracted, processed,
                 characterized, and presented in forms of information
                 suited to forensic investigation. The artifacts
                 obtained from Mozilla Firefox are crossed-checked with
                 artifacts of Google Chrome for verification. In the
                 end, the efficacy of using these artifacts in forensic
                 investigations is shown with a demonstration through a
                 proof-of-concept tool. The results indicate that
                 Instagram artifacts stored in IndexedDB technology can
                 be utilized efficiently for forensic investigations,
                 with a large variety of information ranging from fully
                 constructed user data to time and location
                 indicators.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Carchiolo:2022:CAN,
  author =       "Vincenza Carchiolo and Marco Grassia and Michele
                 Malgeri and Giuseppe Mangioni",
  title =        "Co-Authorship Networks Analysis to Discover
                 Collaboration Patterns among {Italian} Researchers",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "187",
  day =          "16",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060187",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/187",
  abstract =     "The study of the behaviors of large community of
                 researchers and what correlations exist between their
                 environment, such as grouping rules by law or specific
                 institution policies, and their performance is an
                 important topic since it affects the metrics used to
                 evaluate the quality of the research. Moreover, in
                 several countries, such as Italy, these metrics are
                 also used to define the recruitment and funding
                 policies. To effectively study these topics, we created
                 a procedure that allow us to craft a large dataset of
                 Italian Academic researchers, having the most important
                 performance indices together with co-authorships
                 information, mixing data extracted from the official
                 list of academic researchers provided by Italian
                 Ministry of University and Research and the Elsevier's
                 Scopus database. In this paper, we discuss our approach
                 to automate the process of correct association of
                 profiles and the mapping of publications reducing the
                 use of computational resources. We also present the
                 characteristics of four datasets related to specific
                 research fields defined by the Italian Ministry of
                 University and Research used to group the Italian
                 researchers. Then, we present several examples of how
                 the information extracted from these datasets can help
                 to achieve a better understanding of the dynamics
                 influencing scientist performances.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fragkou:2022:MBI,
  author =       "Evangelia Fragkou and Dimitrios Papakostas and
                 Theodoros Kasidakis and Dimitrios Katsaros",
  title =        "Multilayer Backbones for {Internet of Battlefield
                 Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "186",
  day =          "15",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060186",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/186",
  abstract =     "The Internet of Battlefield Things is a newly born
                 cyberphysical system and, even though it shares a lot
                 with the Internet of Things and with ad hoc networking,
                 substantial research is required to cope with its scale
                 and peculiarities. This article examines a fundamental
                 problem pertaining to the routing of information, i.e.,
                 the calculation of a backbone network. We model an IoBT
                 network as a network with multiple layers and employ
                 the concept of domination for multilayer networks. This
                 is a significant departure from earlier works, and in
                 spite of the huge literature on the topic during the
                 past twenty years, the problem in IoBT networks is
                 different since these networks are multilayer networks,
                 thus making inappropriate all the past, related
                 literature because it deals with single layer (flat)
                 networks. We establish the computational complexity of
                 our problem, and design a distributed algorithm for
                 computing connected dominating sets with small
                 cardinality. We analyze the performance of the proposed
                 algorithm on generated topologies, and compare it
                 against two-the only existing-competitors. The proposed
                 algorithm establishes itself as the clear winner in all
                 experiments concerning the dominating set from a
                 size-wise and an energy-wise perspective achieving a
                 performance gain of about 15\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Stranieri:2022:ISP,
  author =       "Silvia Stranieri",
  title =        "An Indoor Smart Parking Algorithm Based on
                 Fingerprinting",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "185",
  day =          "14",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060185",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/185",
  abstract =     "In the last few years, researchers from many research
                 fields are investigating the problem affecting all the
                 drivers in big and populated cities: the parking
                 problem. In outdoor environments, the problem can be
                 solved by relying on vehicular ad hoc networks, which
                 guarantee communication among vehicles populating the
                 network. When it comes to indoor settings, the problem
                 gets harder, since drivers cannot count on classic GPS
                 localization. In this work, a smart parking solution
                 for a specific indoor setting is provided, exploiting
                 the fingerprint approach for indoor localization. The
                 considered scenario is a multi-level car park inside an
                 airport building. The algorithm provides a vehicle
                 allocation inside the car park in quadratic time over
                 the number of parking slots, by also considering the
                 driver's preferences on the terminal to be reached.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Balmuri:2022:LST,
  author =       "Kavitha Rani Balmuri and Srinivas Konda and Wen-Cheng
                 Lai and Parameshachari Bidare Divakarachari and Kavitha
                 Malali Vishveshwarappa Gowda and Hemalatha
                 Kivudujogappa Lingappa",
  title =        "A Long Short-Term Memory Network-Based Radio Resource
                 Management for {5G} Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "184",
  day =          "14",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060184",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/184",
  abstract =     "Nowadays, the Long-Term Evolution-Advanced system is
                 widely used to provide 5G communication due to its
                 improved network capacity and less delay during
                 communication. The main issues in the 5G network are
                 insufficient user resources and burst errors, because
                 it creates losses in data transmission. In order to
                 overcome this, an effective Radio Resource Management
                 (RRM) is required to be developed in the 5G network. In
                 this paper, the Long Short-Term Memory (LSTM) network
                 is proposed to develop the radio resource management in
                 the 5G network. The proposed LSTM-RRM is used for
                 assigning an adequate power and bandwidth to the
                 desired user equipment of the network. Moreover, the
                 Grid Search Optimization (GSO) is used for identifying
                 the optimal hyperparameter values for LSTM. In radio
                 resource management, a request queue is used to avoid
                 the unwanted resource allocation in the network.
                 Moreover, the losses during transmission are minimized
                 by using frequency interleaving and guard level
                 insertion. The performance of the LSTM-RRM method has
                 been analyzed in terms of throughput, outage
                 percentage, dual connectivity, User Sum Rate (USR),
                 Threshold Sum Rate (TSR), Outdoor Sum Rate (OSR),
                 threshold guaranteed rate, indoor guaranteed rate, and
                 outdoor guaranteed rate. The indoor guaranteed rate of
                 LSTM-RRM for 1400 m of building distance improved up to
                 75.38\% compared to the existing QOC-RRM.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{DeFazio:2022:BCP,
  author =       "Roberto {De Fazio} and Massimo {De Vittorio} and Paolo
                 Visconti",
  title =        "A {BLE}-Connected Piezoresistive and Inertial Chest
                 Band for Remote Monitoring of the Respiratory Activity
                 by an {Android} Application: Hardware Design and
                 Software Optimization",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "183",
  day =          "11",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060183",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/183",
  abstract =     "Breathing is essential for human life. Issues related
                 to respiration can be an indicator of problems related
                 to the cardiorespiratory system; thus, accurate
                 breathing monitoring is fundamental for establishing
                 the patient's condition. This paper presents a
                 ready-to-use and discreet chest band for monitoring the
                 respiratory parameters based on the piezoresistive
                 transduction mechanism. In detail, it relies on a
                 strain sensor realized with a pressure-sensitive fabric
                 (EeonTex LTT-SLPA-20K) for monitoring the chest
                 movements induced by respiration. In addition, the band
                 includes an Inertial Measurement Unit (IMU), which is
                 used to remove the motion artefacts from the acquired
                 signal, thereby improving the measurement reliability.
                 Moreover, the band comprises a low-power conditioning
                 and acquisition section that processes the signal from
                 sensors, providing a reliable measurement of the
                 respiration rate (RR), in addition to other breathing
                 parameters, such as inhalation (TI) and exhalation (TE)
                 times, inhalation-to-exhalation ratio (IER), and flow
                 rate (V). The device wirelessly transmits the extracted
                 parameters to a host device, where a custom mobile
                 application displays them. Different test campaigns
                 were carried out to evaluate the performance of the
                 designed chest band in measuring the RR, by comparing
                 the measurements provided by the chest band with those
                 obtained by breath count. In detail, six users, of
                 different genders, ages, and physical constitutions,
                 were involved in the tests. The obtained results
                 demonstrated the effectiveness of the proposed approach
                 in detecting the RR. The achieved performance was in
                 line with that of other RR monitoring systems based on
                 piezoresistive textiles, but which use more powerful
                 acquisition systems or have low wearability. In
                 particular, the inertia-assisted piezoresistive chest
                 band obtained a Pearson correlation coefficient with
                 respect to the measurements based on breath count of
                 0.96 when the user was seated. Finally, Bland-Altman
                 analysis demonstrated that the developed system
                 obtained 0.68 Breaths Per Minute (BrPM) mean difference
                 (MD), and Limits of Agreement (LoAs) of +3.20 and -1.75
                 BrPM when the user was seated.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zheng:2022:DRB,
  author =       "Jason Zheng and Chidinma Dike and Stefan Pancari and
                 Yi Wang and George C. Giakos and Wafa Elmannai and
                 Bingyang Wei",
  title =        "An In-Depth Review on Blockchain Simulators for {IoT}
                 Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "182",
  day =          "10",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060182",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/182",
  abstract =     "Simulating blockchain technology within the IoT has
                 never been as important. Along with this comes the need
                 to find suitable blockchain simulators capable of
                 simulating blockchain networks within an IoT
                 environment. Despite there being a wide variety of
                 blockchain simulators, not all are capable of
                 simulating within an IoT environment and not all are
                 suitable for every IoT environment. This article will
                 review previously published works and present a list of
                 suitable blockchain simulators as well as a few
                 untested simulators that have the potential to simulate
                 blockchain networks within an IoT environment. A total
                 of 18 blockchain simulators are presented and discussed
                 in this paper. In addition, a comprehensive list of the
                 advantages and limitations of each simulator is
                 presented to demonstrate the best situation in which
                 simulators should be used. Finally, recommendations are
                 made on when each simulator should be used and in what
                 situation it should be avoided.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chen:2022:MVF,
  author =       "Qifan Chen and Yang Lu and Charmaine S. Tam and Simon
                 K. Poon",
  title =        "A Multi-View Framework to Detect Redundant Activity
                 Labels for More Representative Event Logs in Process
                 Mining",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "181",
  day =          "09",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060181",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/181",
  abstract =     "Process mining aims to gain knowledge of business
                 processes via the discovery of process models from
                 event logs generated by information systems. The
                 insights revealed from process mining heavily rely on
                 the quality of the event logs. Activities extracted
                 from different data sources or the free-text nature
                 within the same system may lead to inconsistent labels.
                 Such inconsistency would then lead to redundancy in
                 activity labels, which refer to labels that have
                 different syntax but share the same behaviours.
                 Redundant activity labels can introduce unnecessary
                 complexities to the event logs. The identification of
                 these labels from data-driven process discovery are
                 difficult and rely heavily on human intervention.
                 Neither existing process discovery algorithms nor event
                 data preprocessing techniques can solve such redundancy
                 efficiently. In this paper, we propose a multi-view
                 approach to automatically detect redundant activity
                 labels by using not only context-aware features such as
                 control-flow relations and attribute values but also
                 semantic features from the event logs. Our evaluation
                 of several publicly available datasets and a real-life
                 case study demonstrate that our approach can
                 efficiently detect redundant activity labels even with
                 low-occurrence frequencies. The proposed approach can
                 add value to the preprocessing step to generate more
                 representative event logs.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Deng:2022:HFD,
  author =       "Shangkun Deng and Yingke Zhu and Xiaoru Huang and
                 Shuangyang Duan and Zhe Fu",
  title =        "High-Frequency Direction Forecasting of the Futures
                 Market Using a Machine-Learning-Based Method",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "180",
  day =          "09",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060180",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/180",
  abstract =     "Futures price-movement-direction forecasting has
                 always been a significant and challenging subject in
                 the financial market. In this paper, we propose a
                 combination approach that integrates the XGBoost
                 (eXtreme Gradient Boosting), SMOTE (Synthetic Minority
                 Oversampling Technique), and NSGA-II (Non-dominated
                 Sorting Genetic Algorithm-II) methods. We applied the
                 proposed approach on the direction prediction and
                 simulation trading of rebar futures, which are traded
                 on the Shanghai Futures Exchange. Firstly, the minority
                 classes of the high-frequency rebar futures price
                 change magnitudes are oversampled using the SMOTE
                 algorithm to overcome the imbalance problem of the
                 class data. Then, XGBoost is adopted to construct a
                 multiclassification model for the
                 price-movement-direction prediction. Next, the proposed
                 approach employs NSGA-II to optimize the parameters of
                 the pre-designed trading rule for trading simulation.
                 Finally, the price-movement direction is predicted, and
                 we conducted the high-frequency trading based on the
                 optimized XGBoost model and the trading rule, with the
                 classification and trading performances empirically
                 evaluated by four metrics over four testing periods.
                 Meanwhile, the LIME (Local Interpretable Model-agnostic
                 Explanations) is applied as a model explanation
                 approach to quantify the prediction contributions of
                 features to the forecasting samples. From the
                 experimental results, we found that the proposed
                 approach performed best in terms of direction
                 prediction accuracy, profitability, and return-risk
                 ratio. The proposed approach could be beneficial for
                 decision-making of the rebar traders and related
                 companies engaged in rebar futures trading.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kankanamge:2022:GCE,
  author =       "Nayomi Kankanamge and Tan Yigitcanlar and Ashantha
                 Goonetilleke",
  title =        "Gamifying Community Education for Enhanced Disaster
                 Resilience: an Effectiveness Testing Study from
                 {Australia}",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "179",
  day =          "09",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060179",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/179",
  abstract =     "Providing convenient and effective online education is
                 important for the public to be better prepared for
                 disaster events. Nonetheless, the effectiveness of such
                 education is questionable due to the limited use of
                 online tools and platforms, which also results in
                 narrow community outreach. Correspondingly,
                 understanding public perceptions of disaster education
                 methods and experiences for the adoption of novel
                 methods is critical, but this is an understudied area
                 of research. The aim of this study is to understand
                 public perceptions towards online disaster education
                 practices for disaster preparedness and evaluate the
                 effectiveness of the gamification method in increasing
                 public awareness. This study utilizes social media
                 analytics and conducts a gamification exercise. The
                 analysis involved Twitter posts ( n = 13,683) related
                 to the 2019-2020 Australian bushfires, and surveyed
                 participants ( n = 52) before and after experiencing a
                 gamified application-i.e., STOP Disasters! The results
                 revealed that: (a) The public satisfaction level is
                 relatively low for traditional bushfire disaster
                 education methods; (b) The study participants'
                 satisfaction level is relatively high for an online
                 gamified application used for disaster education; and
                 (c) The use of virtual and augmented reality was found
                 to be promising for increasing the appeal of gamified
                 applications, along with using a blended traditional
                 and gamified approach.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Feng:2022:EEB,
  author =       "Jinghui Feng and Haopeng Kuang and Lihua Zhang",
  title =        "{EBBA}: an Enhanced Binary Bat Algorithm Integrated
                 with Chaos Theory and {L{\'e}vy} Flight for Feature
                 Selection",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "178",
  day =          "09",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060178",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/178",
  abstract =     "Feature selection can efficiently improve
                 classification accuracy and reduce the dimension of
                 datasets. However, feature selection is a challenging
                 and complex task that requires a high-performance
                 optimization algorithm. In this paper, we propose an
                 enhanced binary bat algorithm (EBBA) which is
                 originated from the conventional binary bat algorithm
                 (BBA) as the learning algorithm in a wrapper-based
                 feature selection model. First, we model the feature
                 selection problem and then transfer it as a fitness
                 function. Then, we propose an EBBA for solving the
                 feature selection problem. In EBBA, we introduce the
                 L{\'e}vy flight-based global search method, population
                 diversity boosting method and chaos-based loudness
                 method to improve the BA and make it more applicable to
                 feature selection problems. Finally, the simulations
                 are conducted to evaluate the proposed EBBA and the
                 simulation results demonstrate that the proposed EBBA
                 outmatches other comparison benchmarks. Moreover, we
                 also illustrate the effectiveness of the proposed
                 improved factors by tests.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hou:2022:EOT,
  author =       "Changbo Hou and Jiajun Ai and Yun Lin and Chenyang
                 Guan and Jiawen Li and Wenyu Zhu",
  title =        "Evaluation of Online Teaching Quality Based on Facial
                 Expression Recognition",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "177",
  day =          "08",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060177",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/177",
  abstract =     "In 21st-century society, with the rapid development of
                 information technology, the scientific and
                 technological strength of all walks of life is
                 increasing, and the field of education has also begun
                 to introduce high and new technologies gradually.
                 Affected by the epidemic, online teaching has been
                 implemented all over the country, forming an education
                 model of ``dual integration'' of online and offline
                 teaching. However, the disadvantages of online teaching
                 are also very obvious; that is, teachers cannot
                 understand the students' listening status in real-time.
                 Therefore, our study adopts automatic face detection
                 and expression recognition based on a deep learning
                 framework and other related technologies to solve this
                 problem, and it designs an analysis system of students'
                 class concentration based on expression recognition.
                 The students' class concentration analysis system can
                 help teachers detect students' class concentration and
                 improve the efficiency of class evaluation. In this
                 system, OpenCV is used to call the camera to collect
                 the students' listening status in real-time, and the
                 MTCNN algorithm is used to detect the face of the video
                 to frame the location of the student's face image.
                 Finally, the obtained face image is used for real-time
                 expression recognition by using the VGG16 network added
                 with ECANet, and the students' emotions in class are
                 obtained. The experimental results show that the method
                 in our study can more accurately identify students'
                 emotions in class and carry out a teaching effect
                 evaluation, which has certain application value in
                 intelligent education fields, such as the smart
                 classroom and distance learning. For example, a
                 teaching evaluation module can be added to the teaching
                 software, and teachers can know the listening emotions
                 of each student in class while lecturing.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kallempudi:2022:TSS,
  author =       "Goutham Kallempudi and Khurram Azeem Hashmi and Alain
                 Pagani and Marcus Liwicki and Didier Stricker and
                 Muhammad Zeshan Afzal",
  title =        "Toward Semi-Supervised Graphical Object Detection in
                 Document Images",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "176",
  day =          "08",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060176",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/176",
  abstract =     "The graphical page object detection classifies and
                 localizes objects such as Tables and Figures in a
                 document. As deep learning techniques for object
                 detection become increasingly successful, many
                 supervised deep neural network-based methods have been
                 introduced to recognize graphical objects in documents.
                 However, these models necessitate a substantial amount
                 of labeled data for the training process. This paper
                 presents an end-to-end semi-supervised framework for
                 graphical object detection in scanned document images
                 to address this limitation. Our method is based on a
                 recently proposed Soft Teacher mechanism that examines
                 the effects of small percentage-labeled data on the
                 classification and localization of graphical objects.
                 On both the PubLayNet and the IIIT-AR-13K datasets, the
                 proposed approach outperforms the supervised models by
                 a significant margin in all labeling ratios (1\%, 5\%
                 (1\%, 5\% (1\%, 5\%, and 10\%) 10\%) 10\%).
                 Furthermore, the 10\% 10\% 10\% PubLayNet Soft Teacher
                 model improves the average precision of Table, Figure,
                 and List by +5.4, +1.2 +5.4, +1.2 +5.4, +1.2, and +3.2
                 +3.2 +3.2 points, respectively, with a similar total
                 mAP as the Faster-RCNN baseline. Moreover, our model
                 trained on 10\% 10\% 10\% of IIIT-AR-13K labeled data
                 beats the previous fully supervised method +4.5 +4.5
                 +4.5 points.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Caldarelli:2022:OBO,
  author =       "Giulio Caldarelli",
  title =        "Overview of Blockchain Oracle Research",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "175",
  day =          "08",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060175",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/175",
  abstract =     "Whereas the use of distributed ledger technologies has
                 previously been limited to cryptocurrencies, other
                 sectors-such as healthcare, supply chain, and
                 finance-can now benefit from them because of bitcoin
                 scripts and smart contracts. However, these
                 applications rely on oracles to fetch data from the
                 real world, which cannot reproduce the trustless
                 environment provided by blockchain networks. Despite
                 their crucial role, academic research on blockchain
                 oracles is still in its infancy, with few contributions
                 and a heterogeneous approach. This study undertakes a
                 bibliometric analysis by highlighting institutions and
                 authors that are actively contributing to the oracle
                 literature. Investigating blockchain oracle research
                 state of the art, research themes, research directions,
                 and converging studies will also be highlighted to
                 discuss, on the one hand, current advancements in the
                 field and, on the other hand, areas that require more
                 investigation. The results also show that although
                 worldwide collaboration is still lacking, various
                 authors and institutions have been working in similar
                 directions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Giannakoulopoulos:2022:ICO,
  author =       "Andreas Giannakoulopoulos and Minas Pergantis and
                 Laida Limniati and Alexandros Kouretsis",
  title =        "Investigating the Country of Origin and the Role of
                 the {\tt .eu} {TLD} in External Trade of {European
                 Union} Member States",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "174",
  day =          "04",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060174",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/174",
  abstract =     "The Internet, and specifically the World Wide Web, has
                 always been a useful tool in the effort to achieve more
                 outward-looking economies. The launch of the .eu TLD
                 (top-level domain) in December of 2005 introduced the
                 concept of a pan-European Internet identity that aimed
                 to enhance the status of European citizens and
                 businesses on the global Web. In this study, the
                 countries of origin of websites that choose to use the
                 .eu TLD are investigated and the reasoning behind that
                 choice, as well as its relation to each country's
                 economy and external trade are discussed. Using the Web
                 as a tool, information regarding a vast number of
                 existing .eu websites was collected, through means of
                 Web data extraction, and this information was analyzed
                 and processed by a detailed algorithm that produced
                 results concerning each website's most probable country
                 of origin based on a multitude of factors. This
                 acquired knowledge was then used to investigate
                 relations with each member-state's presence in its
                 local ccTLD, its GDP and its external trade revenue.
                 The study establishes a correlation between presence in
                 the .eu TLD and external trade that is both independent
                 of a country's GDP and stronger than the relation
                 between its local ccTLD presence and external trade.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fotiou:2022:IGM,
  author =       "Nikos Fotiou and Vasilios A. Siris and George
                 Xylomenos and George C. Polyzos",
  title =        "{IoT} Group Membership Management Using Decentralized
                 Identifiers and Verifiable Credentials",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "173",
  day =          "01",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060173",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/173",
  abstract =     "Many IoT use cases can benefit from group
                 communication, where a user requests an IoT resource
                 and this request can be handled by multiple IoT
                 devices, each of which may respond back to the user.
                 IoT group communication involves one-to-many requests
                 and many-to-one responses, and this creates security
                 challenges. In this paper, we focus on the provenance
                 that has been received by an authorized device. We
                 provide an effective and flexible solution for securing
                 IoT group communication using CoAP, where a CoAP client
                 sends a request to a CoAP group and receives multiple
                 responses by many IoT devices, acting as CoAP servers.
                 We design a solution that allows CoAP servers to
                 digitally sign their responses in a way that clients
                 can verify that a response has been generated by an
                 authorized member of the CoAP group. In order to
                 achieve our goal, we leverage Decentralized Identifiers
                 (DIDs) and Verifiable Credentials (VCs). In particular,
                 we consider that each group is identified by a DID, and
                 each group member has received a VC that allows it to
                 participate in that group. The only information a
                 client needs to know is the DID of the group, which is
                 learned using DNSSEC. Our solution allows group members
                 to rotate their signing keys, it achieves group member
                 revocation, and it has minimal communication and
                 computational overhead.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{S:2022:AEV,
  author =       "Sofana Reka S and Prakash Venugopal and Ravi V and
                 Hassan Haes Alhelou and Amer Al-Hinai and Pierluigi
                 Siano",
  title =        "Analysis of Electric Vehicles with an Economic
                 Perspective for the Future Electric Market",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "172",
  day =          "31",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060172",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/172",
  abstract =     "The automotive industry is marching towards cleaner
                 energy in the impending future. The need for cleaner
                 energy is promoted by the government to a large degree
                 in the global market in order to reduce pollution.
                 Automobiles contribute to an upper scale in regard to
                 the level of pollution in the environment. For cleaner
                 energy in automobiles, the industry needs to be
                 revolutionized in all needed ways to a massive extent.
                 The industry has to move from the traditional internal
                 combustion engine, for which the main sources of energy
                 are nonrenewable sources, to alternative methods and
                 sources of energy. The automotive industry is now
                 focusing on electric vehicles, and more research is
                 being highlighted from vehicle manufacturers to find
                 solutions for the problems faced in the field of
                 electrification. Therefore, to accomplish full
                 electrification, there is a long way to go, and this
                 also requires a change in the existing infrastructure
                 in addition to many innovations in the fields of
                 infrastructure and grid connectively as well as the
                 economic impacts of electric vehicles in society. In
                 this work, an analysis of the electric vehicle market
                 with the economic impacts of electric vehicles is
                 studied. This therefore requires the transformation of
                 the automotive industry.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2022:TSP,
  author =       "Tingting Wang and Zhuolin Li and Xiulin Geng and
                 Baogang Jin and Lingyu Xu",
  title =        "Time Series Prediction of Sea Surface Temperature
                 Based on an Adaptive Graph Learning Neural Model",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "171",
  day =          "31",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060171",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/171",
  abstract =     "The accurate prediction of sea surface temperature
                 (SST) is the basis for our understanding of local and
                 global climate characteristics. At present, the
                 existing sea temperature prediction methods fail to
                 take full advantage of the potential spatial dependence
                 between variables. Among them, graph neural networks
                 (GNNs) modeled on the relationships between variables
                 can better deal with space-time dependency issues.
                 However, most of the current graph neural networks are
                 applied to data that already have a good graph
                 structure, while in SST data, the dependency
                 relationship between spatial points needs to be
                 excavated rather than existing as prior knowledge. In
                 order to predict SST more accurately and break through
                 the bottleneck of existing SST prediction methods, we
                 urgently need to develop an adaptive SST prediction
                 method that is independent of predefined graph
                 structures and can take full advantage of the real
                 temporal and spatial correlations hidden indata sets.
                 Therefore, this paper presents a graph neural network
                 model designed specifically for space-time sequence
                 prediction that can automatically learn the
                 relationships between variables and model them. The
                 model automatically extracts the dependencies between
                 sea temperature multi-variates by embedding the nodes
                 of the adaptive graph learning module, so that the
                 fine-grained spatial correlations hidden in the
                 sequence data can be accurately captured. Figure
                 learning modules, graph convolution modules, and time
                 convolution modules are integrated into a unified
                 end-to-end framework for learning. Experiments were
                 carried out on the Bohai Sea surface temperature data
                 set and the South China Sea surface temperature data
                 set, and the results show that the model presented in
                 this paper is significantly better than other sea
                 temperature model predictions in two remote-sensing sea
                 temperature data sets and the surface temperature of
                 the South China Sea is easier to predict than the
                 surface temperature of the Bohai Sea.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alhazmi:2022:DSP,
  author =       "Huda Alhazmi",
  title =        "Detection of Students' Problems in Distance Education
                 Using Topic Modeling and Machine Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "170",
  day =          "31",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060170",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/170",
  abstract =     "Following the rapid spread of COVID-19 to all the
                 world, most countries decided to temporarily close
                 their educational institutions. Consequently, distance
                 education opportunities have been created for education
                 continuity. The abrupt change presented educational
                 challenges and issues. The aim of this study is to
                 investigate the content of Twitter posts to detect the
                 arising topics regarding the challenges of distance
                 education. We focus on students in Saudi Arabia to
                 identify the problems they faced in their distance
                 education experience. We developed a workflow that
                 integrates unsupervised and supervised machine learning
                 techniques in two phases. An unsupervised topic
                 modeling algorithm was applied on a subset of tweets to
                 detect underlying latent themes related to distance
                 education issues. Then, a multi-class supervised
                 machine learning classification technique was carried
                 out in two levels to classify the tweets under
                 discussion to categories and further to sub-categories.
                 We found that 76,737 tweets revealed five underlying
                 themes: educational issues, social issues,
                 technological issues, health issues, and attitude and
                 ethical issues. This study presents an automated
                 methodology that identifies underlying themes in
                 Twitter content with a minimum human involvement. The
                 results of this work suggest that the proposed model
                 could be utilized for collecting and analyzing social
                 media data to provide insights into students'
                 educational experience.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fan:2022:IOM,
  author =       "Guangwei Fan and Chuanzhen Sheng and Baoguo Yu and Lu
                 Huang and Qiang Rong",
  title =        "An Indoor and Outdoor Multi-Source Elastic Fusion
                 Navigation and Positioning Algorithm Based on Particle
                 Filters",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "169",
  day =          "31",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060169",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/169",
  abstract =     "In terms of indoor and outdoor positioning, in recent
                 years, researchers at home and abroad have proposed
                 some multisource integrated navigation and positioning
                 methods, but these methods are navigation and
                 positioning methods for a single scene. When it comes
                 to the switching of indoor and outdoor complex scenes,
                 these methods will cause the results of position with a
                 marked jump and affect the accuracy of navigation and
                 positioning. Aiming at the navigation and positioning
                 problem in the case of indoor and outdoor complex scene
                 switching, this paper proposes a multisource elastic
                 navigation and positioning method based on particle
                 filters, which makes full use of the redundant
                 information of multisource sensors, constructs an
                 elastic multisource fusion navigation and positioning
                 model after eliminating abnormal data, elastically
                 gives different particle weights to multisource sensors
                 according to environmental changes and realizes the
                 elastic fusion and positioning of multisource sensors
                 through filtering. The test results show that this
                 method has high navigation and positioning accuracy,
                 the dynamic positioning accuracy is better than 0.7 m
                 and there will be no jumping of positioning results in
                 the process of scene switching, which improves the
                 navigation and positioning accuracy and stability in
                 complex and changeable indoor and outdoor
                 environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Murorunkwere:2022:FDU,
  author =       "Belle Fille Murorunkwere and Origene Tuyishimire and
                 Dominique Haughton and Joseph Nzabanita",
  title =        "Fraud Detection Using Neural Networks: a Case Study of
                 Income Tax",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "168",
  day =          "31",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060168",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/168",
  abstract =     "Detecting tax fraud is a top objective for practically
                 all tax agencies in order to maximize revenues and
                 maintain a high level of compliance. Data mining,
                 machine learning, and other approaches such as
                 traditional random auditing have been used in many
                 studies to deal with tax fraud. The goal of this study
                 is to use Artificial Neural Networks to identify
                 factors of tax fraud in income tax data. The results
                 show that Artificial Neural Networks perform well in
                 identifying tax fraud with an accuracy of 92\%, a
                 precision of 85\%, a recall score of 99\%, and an
                 AUC-ROC of 95\%. All businesses, either cross-border or
                 domestic, the period of the business, small businesses,
                 and corporate businesses, are among the factors
                 identified by the model to be more relevant to income
                 tax fraud detection. This study is consistent with the
                 previous closely related work in terms of features
                 related to tax fraud where it covered all tax types
                 together using different machine learning models. To
                 the best of our knowledge, this study is the first to
                 use Artificial Neural Networks to detect income tax
                 fraud in Rwanda by comparing different parameters such
                 as layers, batch size, and epochs and choosing the
                 optimal ones that give better accuracy than others. For
                 this study, a simple model with no hidden layers,
                 softsign activation function performs better. The
                 evidence from this study will help auditors in
                 understanding the factors that contribute to income tax
                 fraud which will reduce the audit time and cost, as
                 well as recover money foregone in income tax fraud.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tomas:2022:DAE,
  author =       "Joana Tom{\'a}s and Deolinda Rasteiro and Jorge
                 Bernardino",
  title =        "Data Anonymization: an Experimental Evaluation Using
                 Open-Source Tools",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "167",
  day =          "30",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060167",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/gnu.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/167",
  abstract =     "In recent years, the use of personal data in
                 marketing, scientific and medical investigation, and
                 forecasting future trends has really increased. This
                 information is used by the government, companies, and
                 individuals, and should not contain any sensitive
                 information that allows the identification of an
                 individual. Therefore, data anonymization is essential
                 nowadays. Data anonymization changes the original data
                 to make it difficult to identify an individual. ARX
                 Data Anonymization and Amnesia are two popular
                 open-source tools that simplify this process. In this
                 paper, we evaluate these tools in two ways: with the
                 OSSpal methodology, and using a public dataset with the
                 most recent tweets about the Pfizer and BioNTech
                 vaccine. The assessment with the OSSpal methodology
                 determines that ARX Data Anonymization has better
                 results than Amnesia. In the experimental evaluation
                 using the public dataset, it is possible to verify that
                 Amnesia has some errors and limitations, but the
                 anonymization process is simpler. Using ARX Data
                 Anonymization, it is possible to upload big datasets
                 and the tool does not show any error in the
                 anonymization process. We concluded that ARX Data
                 Anonymization is the one recommended to use in data
                 anonymization.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Huang:2022:OPC,
  author =       "Zhaohui Huang and Vasilis Friderikos",
  title =        "Optimal Proactive Caching for Multi-View Streaming
                 Mobile Augmented Reality",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "166",
  day =          "30",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060166",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/166",
  abstract =     "Mobile Augmented Reality (MAR) applications demand
                 significant communication, computing and caching
                 resources to support an efficient amalgamation of
                 augmented reality objects (AROs) with the physical
                 world in multiple video view streams. In this paper,
                 the MAR service is decomposed and anchored at different
                 edge cloud locations to optimally explore the scarce
                 edge cloud resources, especially during congestion
                 episodes. In that way, the proposed scheme enables an
                 efficient processing of popular view streams embedded
                 with AROs. More specifically, in this paper, we
                 explicitly utilize the notion of content popularity not
                 only to synthetic objects but also to the video view
                 streams. In this case, popular view streams are cached
                 in a proactive manner, together with preferred/popular
                 AROs, in selected edge caching locations to improve the
                 overall user experience during different mobility
                 events. To achieve that, a joint optimization problem
                 considering mobility, service decomposition, and the
                 balance between service delay and the preference of
                 view streams and embedded AROs is proposed. To tackle
                 the curse of dimensionality of the optimization
                 problem, a nominal long short-term memory (LSTM) neural
                 network is proposed, which is trained offline with
                 optimal solutions and provides high-quality real-time
                 decision making within a gap between 5.6\% and 9.8\%
                 during inference. Evidence from a wide set of numerical
                 investigations shows that the proposed set of schemes
                 owns around 15\% to 38\% gains in delay and hence
                 substantially outperforms nominal schemes, which are
                 oblivious to user mobility and the inherent
                 multi-modality and potential decomposition of the MAR
                 services.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Moubayed:2022:EEI,
  author =       "Abdallah Moubayed and Abdallah Shami and Anwer
                 Al-Dulaimi",
  title =        "On End-to-End Intelligent Automation of {6G}
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "165",
  day =          "29",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060165",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/165",
  abstract =     "The digital transformation of businesses and services
                 is currently in full force, opening the world to a new
                 set of unique challenges and opportunities. In this
                 context, 6G promises to be the set of technologies,
                 architectures, and paradigms that will promote the
                 digital transformation and enable growth and
                 sustainability by offering the means to interact and
                 control the digital and virtual worlds that are
                 decoupled from their physical location. One of the main
                 challenges facing 6G networks is ``end-to-end network
                 automation''. This is because such networks have to
                 deal with more complex infrastructure and a diverse set
                 of heterogeneous services and fragmented use cases.
                 Accordingly, this paper aims at envisioning the role of
                 different enabling technologies towards end-to-end
                 intelligent automated 6G networks. To this end, this
                 paper first reviews the literature focusing on the
                 orchestration and automation of next-generation
                 networks by discussing in detail the challenges facing
                 efficient and fully automated 6G networks. This
                 includes automating both the operational and functional
                 elements for 6G networks. Additionally, this paper
                 defines some of the key technologies that will play a
                 vital role in addressing the research gaps and tackling
                 the aforementioned challenges. More specifically, it
                 outlines how advanced data-driven paradigms such as
                 reinforcement learning and federated learning can be
                 incorporated into 6G networks for more dynamic,
                 efficient, effective, and intelligent network
                 automation and orchestration.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Khamaiseh:2022:RDK,
  author =       "Samer Khamaiseh and Abdullah Al-Alaj and Mohammad
                 Adnan and Hakam W. Alomari",
  title =        "The Robustness of Detecting Known and Unknown {DDoS}
                 Saturation Attacks in {SDN} via the Integration of
                 Supervised and Semi-Supervised Classifiers",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "164",
  day =          "27",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060164",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/164",
  abstract =     "The design of existing machine-learning-based DoS
                 detection systems in software-defined networking (SDN)
                 suffers from two major problems. First, the proper time
                 window for conducting network traffic analysis is
                 unknown and has proven challenging to determine.
                 Second, it is unable to detect unknown types of DoS
                 saturation attacks. An unknown saturation attack is an
                 attack that is not represented in the training data. In
                 this paper, we evaluate three supervised classifiers
                 for detecting a family of DDoS flooding attacks (UDP,
                 TCP-SYN, IP-Spoofing, TCP-SARFU, and ICMP) and their
                 combinations using different time windows. This work
                 represents an extension of the runner-up best-paper
                 award entitled `Detecting Saturation Attacks in SDN via
                 Machine Learning' published in the 2019 4th
                 International Conference on Computing, Communications
                 and Security (ICCCS). The results in this paper show
                 that the trained supervised models fail in detecting
                 unknown saturation attacks, and their overall detection
                 performance decreases when the time window of the
                 network traffic increases. Moreover, we investigate the
                 performance of four semi-supervised classifiers in
                 detecting unknown flooding attacks. The results
                 indicate that semi-supervised classifiers outperform
                 the supervised classifiers in the detection of unknown
                 flooding attacks. Furthermore, to further increase the
                 possibility of detecting the known and unknown flooding
                 attacks, we propose an enhanced hybrid approach that
                 combines two supervised and semi-supervised
                 classifiers. The results demonstrate that the hybrid
                 approach has outperformed individually supervised or
                 semi-supervised classifiers in detecting the known and
                 unknown flooding DoS attacks in SDN.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Araujo:2022:OSA,
  author =       "Andreia Ara{\'u}jo and Filipe Portela and Filipe
                 Alvelos and Saulo Ruiz",
  title =        "Optimization of the System of Allocation of Overdue
                 Loans in a {Sub-Saharan Africa} Microfinance
                 Institution",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "163",
  day =          "27",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060163",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/163",
  abstract =     "In microfinance, with more loans, there is a high risk
                 of increasing overdue loans by overloading the
                 resources available to take actions on the repayment.
                 So, three experiments were conducted to search for a
                 distribution of the loans through the officers
                 available to maximize the probability of recovery.
                 Firstly, the relation between the loan and some
                 characteristics of the officers was analyzed. The
                 results were not that strong with F1 scores between 0
                 and 0.74, with a lot of variation in the scores of the
                 good predictions. Secondly, the loan is classified as
                 paid/unpaid based on what prediction could result of
                 the analysis of the characteristics of the loan. The
                 Support Vector Machine had potential to be a solution
                 with a F1 score average of 0.625; however, when
                 predicting the unpaid loans, it showed to be random
                 with a score of 0.55. Finally, the experiment focused
                 on segmentation of the overdue loans in different
                 groups, from where it would be possible to know their
                 prioritization. The visualization of three clusters in
                 the data was clear through Principal Component
                 Analysis. To reinforce this good visualization, the
                 final silhouette score was 0.194, which reflects that
                 is a model that can be trusted. This way, an
                 implementation of clustering loans into three groups,
                 and a respective prioritization scale would be the best
                 strategy to organize and assign the loans to maximize
                 recovery.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Treiblmaier:2022:WCA,
  author =       "Horst Treiblmaier",
  title =        "What Is Coming across the Horizon and How Can We
                 Handle It? {Bitcoin} Scenarios as a Starting Point for
                 Rigorous and Relevant Research",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "162",
  day =          "26",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060162",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/162",
  abstract =     "The disruptive impact of blockchain technologies can
                 be felt across numerous industries as it threatens to
                 disrupt existing business models and economic
                 structures. To better understand this impact, academic
                 researchers regularly apply well-established theories
                 and methods. The vast majority of these approaches are
                 based on multivariate methods that rely on average
                 behavior and treat extreme cases as outliers. However,
                 as recent history has shown, current developments in
                 blockchain and cryptocurrencies are frequently
                 characterized by aberrant behavior and unexpected
                 events that shape individuals' perceptions, market
                 behavior, and public policymaking. In this paper, I
                 apply various scenario tools to identify such extreme
                 scenarios and illustrate their underlying structure as
                 bundles of interdependent factors. Using the case of
                 Bitcoin, I illustrate that the identification of
                 extreme positive and negative scenarios is complex and
                 heavily depends on underlying economic assumptions. I
                 present three scenarios in which Bitcoin is
                 characterized as a financial savior, as a severe threat
                 to economic stability, or as a substitute to overcome
                 several shortcomings of the existing financial system.
                 The research questions that can be derived from these
                 scenarios bridge behavioral and design science research
                 and provide a fertile ground for impactful future
                 research.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rejeb:2022:CPP,
  author =       "Abderahman Rejeb and John G. Keogh and Wayne
                 Martindale and Damion Dooley and Edward Smart and
                 Steven Simske and Samuel Fosso Wamba and John G.
                 Breslin and Kosala Yapa Bandara and Subhasis Thakur and
                 Kelly Liu and Bridgette Crowley and Sowmya Desaraju and
                 Angela Ospina and Horia Bradau",
  title =        "Charting Past, Present, and Future Research in the
                 {Semantic Web} and Interoperability",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "161",
  day =          "25",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060161",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/161",
  abstract =     "Huge advances in peer-to-peer systems and attempts to
                 develop the semantic web have revealed a critical issue
                 in information systems across multiple domains: the
                 absence of semantic interoperability. Today, businesses
                 operating in a digital environment require increased
                 supply-chain automation, interoperability, and data
                 governance. While research on the semantic web and
                 interoperability has recently received much attention,
                 a dearth of studies investigates the relationship
                 between these two concepts in depth. To address this
                 knowledge gap, the objective of this study is to
                 conduct a review and bibliometric analysis of 3511
                 Scopus-registered papers on the semantic web and
                 interoperability published over the past two decades.
                 In addition, the publications were analyzed using a
                 variety of bibliometric indicators, such as publication
                 year, journal, authors, countries, and institutions.
                 Keyword co-occurrence and co-citation networks were
                 utilized to identify the primary research hotspots and
                 group the relevant literature. The findings of the
                 review and bibliometric analysis indicate the dominance
                 of conference papers as a means of disseminating
                 knowledge and the substantial contribution of developed
                 nations to the semantic web field. In addition, the
                 keyword co-occurrence network analysis reveals a
                 significant emphasis on semantic web languages, sensors
                 and computing, graphs and models, and linking and
                 integration techniques. Based on the co-citation
                 clustering, the Internet of Things, semantic web
                 services, ontology mapping, building information
                 modeling, bioinformatics, education and e-learning, and
                 semantic web languages were identified as the primary
                 themes contributing to the flow of knowledge and the
                 growth of the semantic web and interoperability field.
                 Overall, this review substantially contributes to the
                 literature and increases scholars' and practitioners'
                 awareness of the current knowledge composition and
                 future research directions of the semantic web field.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Pedone:2022:QKD,
  author =       "Ignazio Pedone and Antonio Lioy",
  title =        "Quantum Key Distribution in {Kubernetes} Clusters",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "6",
  pages =        "160",
  day =          "25",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14060160",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Jun 24 09:41:47 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/6/160",
  abstract =     "Quantum Key Distribution (QKD) represents a reasonable
                 countermeasure to the advent of Quantum Computing and
                 its impact on current public-key cryptography. So far,
                 considerable efforts have been devoted to investigate
                 possible application scenarios for QKD in several
                 domains such as Cloud Computing and NFV. This paper
                 extends a previous work whose main objective was to
                 propose a new software stack, the Quantum Software
                 Stack (QSS), to integrate QKD into software-defined
                 infrastructures. The contribution of this paper is
                 twofold: enhancing the previous work adding
                 functionalities to the first version of the QSS, and
                 presenting a practical integration of the QSS in
                 Kubernetes, which is the de-facto standard for
                 container orchestration.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alzoubi:2022:ITB,
  author =       "Yehia Ibrahim Alzoubi and Ahmad Al-Ahmad and Hasan
                 Kahtan and Ashraf Jaradat",
  title =        "{Internet of Things} and Blockchain Integration:
                 Security, Privacy, Technical, and Design Challenges",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "7",
  pages =        "216",
  day =          "21",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14070216",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 26 06:44:01 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/7/216",
  abstract =     "The Internet of things model enables a world in which
                 all of our everyday devices can be integrated and
                 communicate with each other and their surroundings to
                 gather and share data and simplify task implementation.
                 Such an Internet of things environment would require
                 seamless authentication, data protection, stability,
                 attack resistance, ease of deployment, and
                 self-maintenance, among other things. Blockchain, a
                 technology that was born with the cryptocurrency
                 Bitcoin, may fulfill Internet of things requirements.
                 However, due to the characteristics of both Internet of
                 things devices and Blockchain technology, integrating
                 Blockchain and the Internet of things can cause several
                 challenges. Despite a large number of papers that have
                 been published in the field of Blockchain and the
                 Internet of things, the problems of this combination
                 remain unclear and scattered. Accordingly, this paper
                 aims to provide a comprehensive survey of the
                 challenges related to Blockchain-Internet of things
                 integration by evaluating the related peer-reviewed
                 literature. The paper also discusses some of the
                 recommendations for reducing the effects of these
                 challenges. Moreover, the paper discusses some of the
                 unsolved concerns that must be addressed before the
                 next generation of integrated Blockchain-Internet of
                 things applications can be deployed. Lastly, future
                 trends in the context of Blockchain-Internet of things
                 integration are discussed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Watorek:2022:MCC,
  author =       "Marcin Watorek and Jaros{\l}aw Kwapie{\'n} and
                 Stanis{\l}aw Drozdz",
  title =        "Multifractal Cross-Correlations of Bitcoin and Ether
                 Trading Characteristics in the Post-{COVID-19} Time",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "7",
  pages =        "215",
  day =          "21",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14070215",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 26 06:44:01 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/7/215",
  abstract =     "Unlike price fluctuations, the temporal structure of
                 cryptocurrency trading has seldom been a subject of
                 systematic study. In order to fill this gap, we analyse
                 detrended correlations of the price returns, the
                 average number of trades in time unit, and the traded
                 volume based on high-frequency data representing two
                 major cryptocurrencies: bitcoin and ether. We apply the
                 multifractal detrended cross-correlation analysis,
                 which is considered the most reliable method for
                 identifying nonlinear correlations in time series. We
                 find that all the quantities considered in our study
                 show an unambiguous multifractal structure from both
                 the univariate (auto-correlation) and bivariate
                 (cross-correlation) perspectives. We looked at the
                 bitcoin-ether cross-correlations in simultaneously
                 recorded signals, as well as in time-lagged signals, in
                 which a time series for one of the cryptocurrencies is
                 shifted with respect to the other. Such a shift
                 suppresses the cross-correlations partially for short
                 time scales, but does not remove them completely. We
                 did not observe any qualitative asymmetry in the
                 results for the two choices of a leading asset. The
                 cross-correlations for the simultaneous and lagged time
                 series became the same in magnitude for the
                 sufficiently long scales.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mir:2022:EGR,
  author =       "Mohd-Yaseen Mir and Hengbing Zhu and Chih-Lin Hu",
  title =        "Enhanced Geographic Routing with One- and Two-Hop
                 Movement Information in Opportunistic Ad Hoc Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "7",
  pages =        "214",
  day =          "20",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14070214",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 26 06:44:01 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/7/214",
  abstract =     "Opportunistic ad hoc networks are characterized by
                 intermittent and infrastructure-less connectivity among
                 mobile nodes. Because of the lack of up-to-date network
                 topology information and frequent link failures,
                 geographic routing utilizes location information and
                 adopts the store-carry-forward data delivery model to
                 relay messages in a delay-tolerant manner. This paper
                 proposes a message-forwarding policy based on movement
                 patterns (MPMF). First, one- and two-hop location
                 information in a geographic neighborhood is exploited
                 to select relay nodes moving closer to a destination
                 node. Message-forwarding decisions are made by
                 referring to selected relay nodes' weight values
                 obtained by calculating the contact frequency of each
                 node with the destination node. Second, when relays in
                 the vicinity of a message-carrying node are not
                 qualified due to the sparse node density and nodal
                 motion status, the destination's movement and the
                 location information of a one-hop relay are jointly
                 utilized to improve the message-forwarding decision. If
                 the one-hop relay is not closer to the destination node
                 or moving away from it, its centrality value in the
                 network is used instead. Based on both synthetic and
                 real mobility scenarios, the simulation results show
                 that the proposed policy performs incomparable efforts
                 to some typical routing policies, such as Epidemic,
                 PRoPHETv2, temporal closeness and centrality-based
                 (TCCB), transient community-based (TC), and
                 geographic-based spray-and-relay (GSaR) routing
                 policies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Jesus:2022:SMQ,
  author =       "Thiago C. Jesus and Daniel G. Costa and Paulo Portugal
                 and Francisco Vasques",
  title =        "A Survey on Monitoring Quality Assessment for Wireless
                 Visual Sensor Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "7",
  pages =        "213",
  day =          "19",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14070213",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 26 06:44:01 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/7/213",
  abstract =     "Wireless visual sensor networks have been adopted in
                 different contexts to provide visual information in a
                 more flexible and distributed way, supporting the
                 development of different innovative applications.
                 Although visual data may be central for a considerable
                 set of applications in areas such as Smart Cities,
                 Industry 4.0, and Vehicular Networks, the actual visual
                 data quality may be not easily determined since it may
                 be associated with many factors that depend on the
                 characteristics of the considered application scenario.
                 This entails several aspects from the quality of
                 captured images (sharpness, definition, resolution) to
                 the characteristics of the networks such as employed
                 hardware, power consumption, and networking efficiency.
                 In order to better support quality analysis and
                 performance comparisons among different wireless visual
                 sensor networks, which could be valuable in many
                 monitoring scenarios, this article surveys this area
                 with special concern on assessment mechanisms and
                 quality metrics. In this context, a novel
                 classification approach is proposed to better
                 categorize the diverse applicable metrics for quality
                 assessment of visual monitoring procedures. Hence, this
                 article yields a practical guide for analyzing
                 different visual sensor network implementations,
                 allowing fairer evaluations and comparisons among a
                 variety of research works. Critical analysis are also
                 performed regarding the relevance and usage of the
                 proposed categories and identified quality metrics.
                 Finally, promising open issues and research directions
                 are discussed in order to guide new developments in
                 this research field.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2022:ISR,
  author =       "Kangying Li and Jiayun Wang and Biligsaikhan Batjargal
                 and Akira Maeda",
  title =        "Intuitively Searching for the Rare Colors from Digital
                 Artwork Collections by Text Description: A Case
                 Demonstration of {Japanese} Ukiyo-e Print Retrieval",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "7",
  pages =        "212",
  day =          "18",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14070212",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 26 06:44:01 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/7/212",
  abstract =     "In recent years, artworks have been increasingly
                 digitized and built into databases, and such databases
                 have become convenient tools for researchers.
                 Researchers who retrieve artwork are not only
                 researchers of humanities, but also researchers of
                 materials science, physics, art, and so on. It may be
                 difficult for researchers of various fields whose
                 studies focus on the colors of artwork to find the
                 required records in existing databases, that are
                 color-based and only queried by the metadata. Besides,
                 although some image retrieval engines can be used to
                 retrieve artwork by text description, the existing
                 image retrieval systems mainly retrieve the main colors
                 of the images, and rare cases of color use are
                 difficult to find. This makes it difficult for many
                 researchers who focus on toning, colors, or pigments to
                 use search engines for their own needs. To solve the
                 two problems, we propose a cross-modal multi-task
                 fine-tuning method based on CLIP (Contrastive
                 Language-Image Pre-Training), which uses the human
                 sensory characteristics of colors contained in the
                 language space and the geometric characteristics of the
                 sketches of a given artwork in order to gain better
                 representations of that artwork piece. The experimental
                 results show that the proposed retrieval framework is
                 efficient for intuitively searching for rare colors,
                 and that a small amount of data can improve the
                 correspondence between text descriptions and color
                 information.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Uhm:2022:ZIP,
  author =       "Daiho Uhm and Sunghae Jun",
  title =        "Zero-Inflated Patent Data Analysis Using Generating
                 Synthetic Samples",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "7",
  pages =        "211",
  day =          "16",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14070211",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 26 06:44:01 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/7/211",
  abstract =     "Due to the expansion of the internet, we encounter
                 various types of big data such as web documents or
                 sensing data. Compared to traditional small data such
                 as experimental samples, big data provide more chances
                 to find hidden and novel patterns with big data
                 analysis using statistics and machine learning
                 algorithms. However, as the use of big data increases,
                 problems also occur. One of them is a zero-inflated
                 problem in structured data preprocessed from big data.
                 Most count values are zeros because a specific word is
                 found in only some documents. In particular, since most
                 of the patent data are in the form of a text document,
                 they are more affected by the zero-inflated problem. To
                 solve this problem, we propose a generation of
                 synthetic samples using statistical inference and tree
                 structure. Using patent document and simulation data,
                 we verify the performance and validity of our proposed
                 method. In this paper, we focus on patent keyword
                 analysis as text big data analysis, and we encounter
                 the zero-inflated problem just like other text data.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Pinto:2022:BDC,
  author =       "Flavio Pinto and Yogachandran Rahulamathavan and James
                 Skinner",
  title =        "Blockchain for Doping Control Applications in Sports:
                 A Conceptual Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "7",
  pages =        "210",
  day =          "14",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14070210",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 26 06:44:01 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/7/210",
  abstract =     "Doping is a well-known problem in competitive sports.
                 Along the years, several cases have come to public,
                 evidencing corrupt practices from within the sports
                 environment. To guarantee fair play and prevent public
                 health issues, anti-doping organizations and sports
                 authorities are expected to cooperate in the fight
                 against doping. To achieve this mission, doping-related
                 data must be produced, stored, accessed, and shared in
                 a secure, tamperproof, and privacy-preserving manner.
                 This paper investigates the processes and tools
                 established by the World Anti-Doping Agency for the
                 global harmonization of doping control activities. From
                 this investigation, it is possible to conclude that
                 there is an inherent trust problem, in part due to a
                 centralized data management paradigm and to the lack of
                 fully digitalized processes. Therefore, this paper
                 presents two main contributions: the concept of a
                 multiorganizational decentralized data governance model
                 and a blockchain-based design for one of the most
                 sensitive data-sharing processes within the anti-doping
                 ecosystem. Throughout this article, it is shown that
                 the adoption of a permissioned blockchain can benefit
                 the whole anti-doping community, creating more reliable
                 processes for handling data, where privacy and security
                 are enhanced.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yang:2022:TPD,
  author =       "Cheng Yang and Tianliang Lu and Shangyi Yan and
                 Jianling Zhang and Xingzhan Yu",
  title =        "N-Trans: Parallel Detection Algorithm for {DGA} Domain
                 Names",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "7",
  pages =        "209",
  day =          "13",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14070209",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 26 06:44:01 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/7/209",
  abstract =     "Domain name generation algorithms are widely used in
                 malware, such as botnet binaries, to generate large
                 sequences of domain names of which some are registered
                 by cybercriminals. Accurate detection of malicious
                 domains can effectively defend against cyber attacks.
                 The detection of such malicious domain names by the use
                 of traditional machine learning algorithms has been
                 explored by many researchers, but still is not perfect.
                 To further improve on this, we propose a novel parallel
                 detection model named N-Trans that is based on the
                 N-gram algorithm with the Transformer model. First, we
                 add flag bits to the first and last positions of the
                 domain name for the parallel combination of the N-gram
                 algorithm and Transformer framework to detect a domain
                 name. The model can effectively extract the letter
                 combination features and capture the position features
                 of letters in the domain name. It can capture features
                 such as the first and last letters in the domain name
                 and the position relationship between letters. In
                 addition, it can accurately distinguish between
                 legitimate and malicious domain names. In the
                 experiment, the dataset is the legal domain name of
                 Alexa and the malicious domain name collected by the
                 360 Security Lab. The experimental results show that
                 the parallel detection model based on N-gram and
                 Transformer achieves 96.97\% accuracy for DGA malicious
                 domain name detection. It can effectively and
                 accurately identify malicious domain names and
                 outperforms the mainstream malicious domain name
                 detection algorithms.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ertek:2022:AME,
  author =       "Gurdal Ertek and Aysha Al-Kaabi and Aktham Issa
                 Maghyereh",
  title =        "Analytical Modeling and Empirical Analysis of Binary
                 Options Strategies",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "7",
  pages =        "208",
  day =          "06",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14070208",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 26 06:44:01 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/7/208",
  abstract =     "This study analyzes binary option investment
                 strategies by developing mathematical formalism and
                 formulating analytical models. The binary outcome of
                 binary options represents either an increase or a
                 decrease in a parameter, typically an asset or
                 derivative. The investor receives only partial returns
                 if the prediction is correct but loses all the
                 investment otherwise. Mainstream research on binary
                 options aims to develop the best dynamic trading
                 strategies. This study focuses on static tactical
                 easy-to-implement strategies and investigates the
                 performance of such strategies in relation to
                 prediction accuracy, payout percentage, and investment
                 strategy decisions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Cheng:2022:RRE,
  author =       "Hengfei Cheng and Zhaobin Xu and Xiaoxu Guo and Jia
                 Yang and Kedi Xu and Shuqin Liu and Zhonghe Jin and
                 Xiaojun Jin",
  title =        "Research on Routing Equalization Algorithm of
                 Inter-Satellite Partition for Low-Orbit
                 Micro-Satellites",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "7",
  pages =        "207",
  day =          "04",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14070207",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 26 06:44:01 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/7/207",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kouretsis:2022:MAK,
  author =       "Alexandros Kouretsis and Iraklis Varlamis and Laida
                 Limniati and Minas Pergantis and Andreas
                 Giannakoulopoulos",
  title =        "Mapping Art to a Knowledge Graph: Using Data for
                 Exploring the Relations among Visual Objects in
                 {Renaissance} Art",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "7",
  pages =        "206",
  day =          "03",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14070206",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 26 06:44:01 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/7/206",
  abstract =     "Graph-like structures, which are increasingly popular
                 in data representation, stand out since they enable the
                 integration of information from multiple sources. At
                 the same time, clustering algorithms applied on graphs
                 allow for group entities based on similar
                 characteristics, and discover statistically important
                 information. This paper aims to explore the
                 associations between the visual objects of the
                 Renaissance in the Europeana database, based on the
                 results of topic modeling and analysis. For this
                 purpose, we employ Europeana's Search and Report API to
                 investigate the relations between the visual objects
                 from this era, spanning from the 14th to the 17th
                 century, and to create clusters of similar art objects.
                 This approach will lead in transforming a cultural
                 heritage database with semantic technologies into a
                 dynamic digital knowledge representation graph that
                 will relate art objects and their attributes. Based on
                 associations between metadata, we will conduct a
                 statistic analysis utilizing the knowledge graph of
                 Europeana and topic modeling analysis.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Baig:2022:SSC,
  author =       "Zubair Baig and Naeem Syed and Nazeeruddin Mohammad",
  title =        "Securing the Smart City Airspace: Drone Cyber Attack
                 Detection through Machine Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "7",
  pages =        "205",
  day =          "30",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14070205",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 26 06:44:01 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/7/205",
  abstract =     "Drones are increasingly adopted to serve a smart city
                 through their ability to render quick and adaptive
                 services. They are also known as unmanned aerial
                 vehicles (UAVs) and are deployed to conduct area
                 surveillance, monitor road networks for traffic,
                 deliver goods and observe environmental phenomena.
                 Cyber threats posed through compromised drones
                 contribute to sabotage in a smart city's airspace, can
                 prove to be catastrophic to its operations, and can
                 also cause fatalities. In this contribution, we propose
                 a machine learning-based approach for detecting
                 hijacking, GPS signal jamming and denial of service
                 (DoS) attacks that can be carried out against a drone.
                 A detailed machine learning-based classification of
                 drone datasets for the DJI Phantom 4 model,
                 compromising both normal and malicious signatures, is
                 conducted, and results obtained yield advisory to
                 foster futuristic opportunities to safeguard a drone
                 system against such cyber threats.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lamprogeorgos:2022:ATS,
  author =       "Aristeidis Lamprogeorgos and Minas Pergantis and
                 Michail Panagopoulos and Andreas Giannakoulopoulos",
  title =        "Aesthetic Trends and Semantic {Web} Adoption of Media
                 Outlets Identified through Automated Archival Data
                 Extraction",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "7",
  pages =        "204",
  day =          "30",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14070204",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 26 06:44:01 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/7/204",
  abstract =     "The last decade has been a time of great progress in
                 the World Wide Web and this progress has manifested in
                 multiple ways, including both the diffusion and
                 expansion of Semantic Web technologies and the
                 advancement of the aesthetics and usability of Web user
                 interfaces. Online media outlets have often been
                 popular Web destinations and so they are expected to be
                 at the forefront of innovation, both in terms of the
                 integration of new technologies and in terms of the
                 evolution of their interfaces. In this study, various
                 Web data extraction techniques were employed to collect
                 current and archival data from news websites that are
                 popular in Greece, in order to monitor and record their
                 progress through time. This collected information,
                 which took the form of a website's source code and an
                 impression of their homepage in different time
                 instances of the last decade, has been used to identify
                 trends concerning Semantic Web integration, DOM
                 structure complexity, number of graphics, color usage,
                 and more. The identified trends were analyzed and
                 discussed with the purpose of gaining a better
                 understanding of the ever-changing presence of the
                 media industry on the Web. The study concluded that the
                 introduction of Semantic Web technologies in online
                 media outlets was rapid and extensive and that website
                 structural and visual complexity presented a steady and
                 significant positive trend, accompanied by increased
                 adherence to color harmony.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Park:2022:CBH,
  author =       "Minwoo Park and Euichul Lee",
  title =        "Correlation between Human Emotion and
                 Temporal--spatial Contexts by Analyzing Environmental
                 Factors",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "7",
  pages =        "203",
  day =          "30",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14070203",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 26 06:44:01 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/7/203",
  abstract =     "In this paper, we propose a method for extracting
                 emotional factors through audiovisual quantitative
                 feature analysis from images of the surrounding
                 environment. Nine features were extracted such as time
                 complexity, spatial complexity (horizontal and
                 vertical), color components (hue and saturation),
                 intensity, contrast, sound amplitude, and sound
                 frequency. These nine features were used to infer
                 ``pleasant-unpleasant'' and ``arousal-relaxation''
                 scores through two support vector regressions. First,
                 the inference accuracy for each of the nine features
                 was calculated as a hit ratio to check the
                 distinguishing power of the features. Next, the
                 difference between the position in the two-dimensional
                 emotional plane inferred through SVR and the ground
                 truth determined subjectively by the subject was
                 examined. As a result of the experiment, it was
                 confirmed that the time-complexity feature had the best
                 classification performance, and it was confirmed that
                 the emotion inferred through SVR can be valid when the
                 two-dimensional emotional plane is divided into 3 $
                 \times $ 3.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2022:TSR,
  author =       "Yingxun Wang and Hushairi Zen and Mohamad Faizrizwan
                 Mohd Sabri and Xiang Wang and Lee Chin Kho",
  title =        "Towards Strengthening the Resilience of {IoV} Networks
                 --- a Trust Management Perspective",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "7",
  pages =        "202",
  day =          "30",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14070202",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 26 06:44:01 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/7/202",
  abstract =     "Over the past decade or so, considerable and rapid
                 advancements in the state of the art within the
                 promising paradigms of the Internet of Things (IoT) and
                 Artificial Intelligence (AI) have accelerated the
                 development of conventional Vehicular Ad Hoc Networks
                 (VANETS) into the Internet of Vehicles (IoV), thereby
                 bringing both connected and autonomous driving much
                 closer to realization. IoV is a new concept in the
                 Intelligent Traffic System (ITS) and an extended
                 application of IoV in intelligent transportation. It
                 enhances the existing capabilities of mobile ad hoc
                 networks by integrating them with IoT so as to build an
                 integrated and unified vehicle-to-vehicle network. It
                 is worth mentioning that academic and industrial
                 researchers are paying increasing attention to the
                 concept of trust. Reliable trust models and accurate
                 trust assessments are anticipated to improve the
                 security of the IoV. This paper, therefore, focuses on
                 the existing trustworthiness management models along
                 with their corresponding trust parameters, as well as
                 the corresponding trust evaluation parameters and
                 simulation, which provide the basis for intelligent and
                 efficient model suggestions and optimal parameter
                 integration. In addition, this paper also puts forward
                 some open research directions that need to be seriously
                 solved before trust can play its due role in enhancing
                 IoV network elasticity.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alnaim:2022:MPT,
  author =       "Abdulrahman K. Alnaim",
  title =        "Misuse Patterns from the Threat of Modification of
                 Non-Control Data in Network Function Virtualization",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "7",
  pages =        "201",
  day =          "30",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14070201",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 26 06:44:01 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/7/201",
  abstract =     "Network Function Virtualization (NFV) is a virtual
                 network model, the goal of which is a cost-efficient
                 transition of the hardware infrastructure into a
                 flexible and reliable software platform. However, this
                 transition comes at the cost of more security threats.
                 A key part of this virtualization environment is the
                 hypervisor, which emulates the hardware resources to
                 provide a runtime environment for virtual machines
                 (VMs). The hypervisor is considered a major attack
                 vector and must be secured to ensure network service
                 continuity. The virtualization environment contains
                 critical non-control data where compromise could lead
                 to several misuses, including information leakage and
                 privilege and resource modification. In this paper, we
                 present a misuse pattern for an attack that exploits
                 the security vulnerabilities of the hypervisor to
                 compromise the integrity of non-control data in the NFV
                 environment. Misuse patterns are used to describe how
                 attacks are carried out from the attackers'
                 perspective. The threat of modification of non-control
                 data can lead to several misuses, and in this paper, we
                 discuss three of them. The defenses to this attack can
                 be incorporated into the Security Reference
                 Architecture (SRA) of the NFV system to prevent these
                 misuses.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Carnley:2022:PIT,
  author =       "Renee Carnley and Sikha Bagui",
  title =        "A Public Infrastructure for a Trusted Wireless World",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "7",
  pages =        "200",
  day =          "30",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14070200",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 26 06:44:01 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/7/200",
  abstract =     "The novelty of this work lies in examining how 5G,
                 blockchain-based public key infrastructure (PKI), near
                 field communication (NFC), and zero trust architecture
                 securely provide not only a trusted digital identity
                 for telework but also a trusted digital identity for
                 secure online voting. The paper goes on to discuss how
                 blockchain-based PKI, NFC, and the cloud provide a
                 roadmap for how industry and governments can update
                 existing frameworks to obtain a trusted digital
                 identity in cyberspace that would provide secure
                 telework and online voting capabilities.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alibabaei:2022:RTD,
  author =       "Khadijeh Alibabaei and Eduardo Assun{\c{c}}{\~a}o and
                 Pedro D. Gaspar and Vasco N. G. J. Soares and Jo{\~a}o
                 M. L. P. Caldeira",
  title =        "Real-Time Detection of Vine Trunk for Robot
                 Localization Using Deep Learning Models Developed for
                 Edge {TPU} Devices",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "7",
  pages =        "199",
  day =          "29",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14070199",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 26 06:44:01 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/7/199",
  abstract =     "The concept of the Internet of Things (IoT) in
                 agriculture is associated with the use of high-tech
                 devices such as robots and sensors that are
                 interconnected to assess or monitor conditions on a
                 particular plot of land and then deploy the various
                 factors of production such as seeds, fertilizer, water,
                 etc., accordingly. Vine trunk detection can help create
                 an accurate map of the vineyard that the agricultural
                 robot can rely on to safely navigate and perform a
                 variety of agricultural tasks such as harvesting,
                 pruning, etc. In this work, the state-of-the-art
                 single-shot multibox detector (SSD) with MobileDet Edge
                 TPU and MobileNet Edge TPU models as the backbone was
                 used to detect the tree trunks in the vineyard.
                 Compared to the SSD with MobileNet-V1, MobileNet-V2,
                 and MobileDet as backbone, the SSD with MobileNet Edge
                 TPU was more accurate in inference on the Raspberrypi,
                 with almost the same inference time on the TPU. The SSD
                 with MobileDet Edge TPU achieved the second-best
                 accurate model. Additionally, this work examines the
                 effects of some features, including the size of the
                 input model, the quantity of training data, and the
                 diversity of the training dataset. Increasing the size
                 of the input model and the training dataset increased
                 the performance of the model.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhu:2022:DIC,
  author =       "Yancong Zhu and Juan Zhang and Zhaoxi Zhang and Gina
                 Clepper and Jingpeng Jia and Wei Liu",
  title =        "Designing an Interactive Communication Assistance
                 System for Hearing-Impaired {College} Students Based on
                 Gesture Recognition and Representation",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "7",
  pages =        "198",
  day =          "29",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14070198",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 26 06:44:01 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/7/198",
  abstract =     "Developing a smart classroom can make the modern
                 classroom more efficient and intelligent. Much research
                 has been conducted pertaining to smart classrooms for
                 hearing-impaired college students. However, there have
                 been few significant breakthroughs in mobilizing
                 students' learning efficiency as measured by
                 information transmission, communication, and
                 interaction in class. This research collects data
                 through nonparticipatory observation and in-depth
                 interviews and analyzes available data on classroom
                 interaction needs of these students. We found that
                 diversified explanations, recordable interactive
                 contents, and interaction between teachers and students
                 could improve the learning effects in the classroom. We
                 also propose a tracking-processing method based on
                 gesture recognition and representation and present a
                 design for a processing system based on AT89C52
                 microcontroller and Kinect. In this way, sign language
                 can be translated into text and all students can
                 receive the information and participate in the
                 interaction, which greatly improves students' autonomy
                 and enthusiasm of learning. This design enables deaf
                 students to fully use classroom learning resources,
                 reduces learning time costs, and improves learning
                 efficiency. It can assist teachers in teaching and
                 tutoring students to enhance their experience.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Pappalardo:2022:EOC,
  author =       "Martina Pappalardo and Antonio Virdis and Enzo
                 Mingozzi",
  title =        "Energy-Optimized Content Refreshing of
                 Age-of-Information-Aware Edge Caches in {IoT} Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "7",
  pages =        "197",
  day =          "28",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14070197",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 26 06:44:01 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/7/197",
  abstract =     "The Internet of Things (IoT) brings internet
                 connectivity to everyday devices. These devices
                 generate a large volume of information that needs to be
                 transmitted to the nodes running the IoT applications,
                 where they are processed and used to make some output
                 decisions. On the one hand, the quality of these
                 decisions is typically affected by the freshness of the
                 received information, thus requesting frequent updates
                 from the IoT devices. On the other hand, the severe
                 energy, memory, processing, and communication
                 constraints of IoT devices and networks pose
                 limitations in the frequency of sensing and reporting.
                 So, it is crucial to minimize the energy consumed by
                 the device for sensing the environment and for
                 transmitting the update messages, while taking into
                 account the requirements for information freshness.
                 Edge-caching can be effective in reducing the sensing
                 and the transmission frequency; however, it requires a
                 proper refreshing scheme to avoid staleness of
                 information, as IoT applications need timeliness of
                 status updates. Recently, the Age of Information (AoI)
                 metric has been introduced: it is the time elapsed
                 since the generation of the last received update, hence
                 it can describe the timeliness of the IoT application's
                 knowledge of the process sampled by the IoT device. In
                 this work, we propose a model-driven and AoI-aware
                 optimization scheme for information caching at the
                 network edge. To configure the cache parameters, we
                 formulate an optimization problem that minimizes the
                 energy consumption, considering both the sampling
                 frequency and the average frequency of the requests
                 sent to the device for refreshing the cache, while
                 satisfying an AoI requirement expressed by the IoT
                 application. We apply our caching scheme in an emulated
                 IoT network, and we show that it minimizes the energy
                 cost while satisfying the AoI requirement. We also
                 compare the case in which the proposed caching scheme
                 is implemented at the network edge against the case in
                 which there is not a cache at the network edge. We show
                 that the optimized cache can significantly lower the
                 energy cost of devices that have a high transmission
                 cost because it can reduce the number of transmissions.
                 Moreover, the cache makes the system less sensitive to
                 higher application-request rates, as the number of
                 messages forwarded to the devices depends on the cache
                 parameters.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gameiro:2022:IEN,
  author =       "Lu{\'\i}s Gameiro and Carlos Senna and Miguel
                 Lu{\'\i}s",
  title =        "Insights from the Experimentation of Named Data
                 Networks in Mobile Wireless Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "7",
  pages =        "196",
  day =          "27",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14070196",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 26 06:44:01 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/7/196",
  abstract =     "The Information-Centric Network (ICN) paradigm has
                 been touted as one of the candidates for the Internet
                 of the future, where the Named Data Network (NDN)
                 architecture is the one leading the way. Despite the
                 large amount of works published in the literature
                 targeting new implementations of such architecture,
                 covering different network topologies and use cases,
                 there are few NDN implementations in real networks.
                 Moreover, most of these real-world NDN implementations,
                 especially those addressing wireless and wired
                 communication channels, are at a small scale, in
                 laboratory environments. In this work, we evaluate the
                 performance of an NDN-based implementation in a mobile
                 wireless network, as part of a smart city
                 infrastructure, making use of multiple wireless
                 interfaces. We start by showing how we have implemented
                 the NDN stack in current network nodes of the smart
                 city infrastructure, following a hybrid solution where
                 both TCP/IP and NDN paradigms can coexist. The
                 implementation is evaluated in three scenarios,
                 targeting different situations: mobility, the
                 simultaneous use of different wireless interfaces and
                 the network characteristics. The results show that our
                 implementation works properly and insights about the
                 correct NDN parameterization are derived.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mpimis:2022:CDG,
  author =       "Thanassis Mpimis and Theodore T. Kapsis and Athanasios
                 D. Panagopoulos and Vassilis Gikas",
  title =        "Cooperative {D-GNSS} Aided with Multi Attribute
                 Decision Making Module: a Rigorous Comparative
                 Analysis",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "7",
  pages =        "195",
  day =          "27",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14070195",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 26 06:44:01 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/7/195",
  abstract =     "Satellite positioning lies within the very core of
                 numerous Intelligent Transportation Systems (ITS) and
                 Future Internet applications. With the emergence of
                 connected vehicles, the performance requirements of
                 Global Navigation Satellite Systems (GNSS) are
                 constantly pushed to their limits. To this end,
                 Cooperative Positioning (CP) solutions have attracted
                 attention in order to enhance the accuracy and
                 reliability of low-cost GNSS receivers, especially in
                 complex propagation environments. In this paper, the
                 problem of efficient and robust CP employing low-cost
                 GNSS receivers is investigated over critical ITS
                 scenarios. By adopting a Cooperative-Differential GNSS
                 (C-DGNSS) framework, the target's vehicle receiver can
                 obtain Position-Velocity-Time (PVT) corrections from a
                 neighboring vehicle and update its own position in
                 real-time. A ranking module based on multi-attribute
                 decision-making (MADM) algorithms is proposed for the
                 neighboring vehicle rating and optimal selection. The
                 considered MADM techniques are simulated with various
                 weightings, normalization techniques, and criteria
                 associated with positioning accuracy and reliability.
                 The obtained criteria values are experimental GNSS
                 measurements from several low-cost receivers. A
                 comparative and sensitivity analysis are provided by
                 evaluating the MADM algorithms in terms of ranking
                 performance and robustness. The positioning data time
                 series and the numerical results are then presented,
                 and comments are made. Scoring-based and distance-based
                 MADM methods perform better, while L1 RMS, HDOP, and Hz
                 std are the most critical criteria. The multi-purpose
                 applicability of the proposed scheme, not only for land
                 vehicles, is also discussed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alhaj:2022:NTC,
  author =       "Yousif A. Alhaj and Abdelghani Dahou and Mohammed A.
                 A. Al-qaness and Laith Abualigah and Aaqif Afzaal
                 Abbasi and Nasser Ahmed Obad Almaweri and Mohamed Abd
                 Elaziz and Robertas Damasevicius",
  title =        "A Novel Text Classification Technique Using Improved
                 Particle Swarm Optimization: a Case Study of {Arabic}
                 Language",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "7",
  pages =        "194",
  day =          "27",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14070194",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 26 06:44:01 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/7/194",
  abstract =     "We propose a novel text classification model, which
                 aims to improve the performance of Arabic text
                 classification using machine learning techniques. One
                 of the effective solutions in Arabic text
                 classification is to find the suitable feature
                 selection method with an optimal number of features
                 alongside the classifier. Although several text
                 classification methods have been proposed for the
                 Arabic language using different techniques, such as
                 feature selection methods, an ensemble of classifiers,
                 and discriminative features, choosing the optimal
                 method becomes an NP-hard problem considering the huge
                 search space. Therefore, we propose a method, called
                 Optimal Configuration Determination for Arabic text
                 Classification (OCATC), which utilized the Particle
                 Swarm Optimization (PSO) algorithm to find the optimal
                 solution (configuration) from this space. The proposed
                 OCATC method extracts and converts the features from
                 the textual documents into a numerical vector using the
                 Term Frequency-Inverse Document Frequency (TF-IDF)
                 approach. Finally, the PSO selects the best
                 architecture from a set of classifiers to feature
                 selection methods with an optimal number of features.
                 Extensive experiments were carried out to evaluate the
                 performance of the OCATC method using six datasets,
                 including five publicly available datasets and our
                 proposed dataset. The results obtained demonstrate the
                 superiority of OCATC over individual classifiers and
                 other state-of-the-art methods.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kondratyeva:2022:CDB,
  author =       "Anastasia Kondratyeva and Daria Ivanova and Vyacheslav
                 Begishev and Ekaterina Markova and Evgeni Mokrov and
                 Yuliya Gaidamaka and Konstantin Samouylov",
  title =        "Characterization of Dynamic Blockage Probability in
                 Industrial Millimeter Wave {5G} Deployments",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "7",
  pages =        "193",
  day =          "27",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14070193",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 26 06:44:01 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/7/193",
  abstract =     "5G New Radio (NR) systems promise to expand offered
                 services to enable industrial automation scenarios. To
                 enable ultra-low latency at the air interface and to
                 exploit spatial redundancy for applications such as
                 synchronization and motion control, user equipment (UE)
                 will naturally require device-to-device (D2D) and base
                 station (BS) to UE communications and directional
                 transmissions provided by millimeter wave (mmWave)
                 frequencies. However, the performance of such systems
                 is affected by the blockage phenomenon. In this paper,
                 we propose a simple line-of-sight (LoS) blockage model
                 for Industrial mmWave-based industrial Internet of
                 Things (IIoT) deployments. The model is based on two
                 sub-models, where each part can be changed/replaced to
                 fit the scenario of interest. The first part is based
                 on photogrammetry and provides the transparency
                 probability for a single element on the factory floor.
                 The second one utilizes these models of industrial
                 elements to form the deployment and then applies
                 stochastic geometry to derive the blockage probability.
                 The proposed model can be utilized for any type of
                 industrial machine, accounts for their inherent regular
                 deployments on the factory floor, and provides the
                 final results in an easy-to-compute form. Our results
                 indicate that direct UE-UE communications are feasible
                 in sparse deployments (less than 0.1 machine/m 2 ) or
                 at small communications distances (less than 5-10 m) or
                 in deployments with highly transparent machines
                 (machine transparency less than 0.5). Otherwise, BS-UE
                 communications need to be utilized. In this case, BS
                 height becomes a critical parameter affecting the LoS
                 probability. Specifically, using a BS height of 10 m
                 allows blockage probability to be improved by 20-30\%
                 as compared to a BS of height 4 m. Finally, as UE
                 height produces more impact on the blockage probability
                 as compared to a machine height, in real deployments,
                 one needs to ensure that the height of communications
                 modules at UEs are maximized.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Musa:2022:CIC,
  author =       "Salahadin Seid Musa and Marco Zennaro and Mulugeta
                 Libsie and Ermanno Pietrosemoli",
  title =        "Convergence of Information-Centric Networks and Edge
                 Intelligence for {IoV}: Challenges and Future
                 Directions",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "7",
  pages =        "192",
  day =          "25",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14070192",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 26 06:44:01 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/7/192",
  abstract =     "Recently the Internet of Vehicles (IoV) has become a
                 promising research area in the field of the Internet of
                 Things (IoT), which enables vehicles to communicate and
                 exchange real-time information with each other, as well
                 as with infrastructure, people, and other sensors and
                 actuators through various communication interfaces. The
                 realization of IoV networks faces various communication
                 and networking challenges to meet stringent
                 requirements of low latency, dynamic topology, high
                 data-rate connectivity, resource allocation, multiple
                 access, and QoS. Advances in information-centric
                 networks (ICN), edge computing (EC), and artificial
                 intelligence (AI) will transform and help to realize
                 the Intelligent Internet of Vehicles (IIoV).
                 Information-centric networks have emerged as a paradigm
                 promising to cope with the limitations of the current
                 host-based network architecture (TCP/IP-based networks)
                 by providing mobility support, efficient content
                 distribution, scalability and security based on content
                 names, regardless of their location. Edge computing
                 (EC), on the other hand, is a key paradigm to provide
                 computation, storage and other cloud services in close
                 proximity to where they are requested, thus enabling
                 the support of real-time services. It is promising for
                 computation-intensive applications, such as autonomous
                 and cooperative driving, and to alleviate storage
                 burdens (by caching). AI has recently emerged as a
                 powerful tool to break through obstacles in various
                 research areas including that of intelligent transport
                 systems (ITS). ITS are smart enough to make decisions
                 based on the status of a great variety of inputs. The
                 convergence of ICN and EC with AI empowerment will
                 bring new opportunities while also raising
                 not-yet-explored obstacles to realize Intelligent IoV.
                 In this paper, we discuss the applicability of AI
                 techniques in solving challenging vehicular problems
                 and enhancing the learning capacity of edge devices and
                 ICN networks. A comprehensive review is provided of
                 utilizing intelligence in EC and ICN to address current
                 challenges in their application to IIoV. In particular,
                 we focus on intelligent edge computing and networking,
                 offloading, intelligent mobility-aware caching and
                 forwarding and overall network performance.
                 Furthermore, we discuss potential solutions to the
                 presented issues. Finally, we highlight potential
                 research directions which may illuminate efforts to
                 develop new intelligent IoV applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Satapathy:2022:PSD,
  author =       "Ranjan Satapathy and Shweta Rajesh Pardeshi and Erik
                 Cambria",
  title =        "Polarity and Subjectivity Detection with Multitask
                 Learning and {BERT} Embedding",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "7",
  pages =        "191",
  day =          "22",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14070191",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 26 06:44:01 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/7/191",
  abstract =     "In recent years, deep learning-based sentiment
                 analysis has received attention mainly because of the
                 rise of social media and e-commerce. In this paper, we
                 showcase the fact that the polarity detection and
                 subjectivity detection subtasks of sentiment analysis
                 are inter-related. To this end, we propose a
                 knowledge-sharing-based multitask learning framework.
                 To ensure high-quality knowledge sharing between the
                 tasks, we use the Neural Tensor Network, which consists
                 of a bilinear tensor layer that links the two entity
                 vectors. We show that BERT-based embedding with our MTL
                 framework outperforms the baselines and achieves a new
                 state-of-the-art status in multitask learning. Our
                 framework shows that the information across datasets
                 for related tasks can be helpful for understanding
                 task-specific features.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ajami:2022:FSA,
  author =       "Hicham Ajami and Hamid Mcheick and Catherine Laprise",
  title =        "First Steps of Asthma Management with a Personalized
                 Ontology Model",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "7",
  pages =        "190",
  day =          "22",
  month =        jun,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14070190",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 26 06:44:01 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/7/190",
  abstract =     "Asthma is a chronic respiratory disease characterized
                 by severe inflammation of the bronchial mucosa.
                 Allergic asthma is the most common form of this health
                 issue. Asthma is classified into allergic and
                 non-allergic asthma, and it can be triggered by several
                 factors such as indoor and outdoor allergens, air
                 pollution, weather conditions, tobacco smoke, and food
                 allergens, as well as other factors. Asthma symptoms
                 differ in their frequency and severity since each
                 patient reacts differently to these triggers. Formal
                 knowledge is selected as one of the most promising
                 solutions to deal with these challenges. This paper
                 presents a new personalized approach to manage asthma.
                 An ontology-driven model supported by Semantic Web Rule
                 Language (SWRL) medical rules is proposed to provide
                 personalized care for an asthma patient by identifying
                 the risk factors and the development of possible
                 exacerbations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lombardo:2022:MLB,
  author =       "Gianfranco Lombardo and Mattia Pellegrino and George
                 Adosoglou and Stefano Cagnoni and Panos M. Pardalos and
                 Agostino Poggi",
  title =        "Machine Learning for Bankruptcy Prediction in the
                 {American} Stock Market: Dataset and Benchmarks",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "8",
  pages =        "244",
  day =          "22",
  month =        aug,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14080244",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 2 12:13:30 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/8/244",
  abstract =     "Predicting corporate bankruptcy is one of the
                 fundamental tasks in credit risk assessment. In
                 particular, since the 2007/2008 financial crisis, it
                 has become a priority for most financial institutions,
                 practitioners, and academics. The recent advancements
                 in machine learning (ML) enabled the development of
                 several models for bankruptcy prediction. The most
                 challenging aspect of this task is dealing with the
                 class imbalance due to the rarity of bankruptcy events
                 in the real economy. Furthermore, a fair comparison in
                 the literature is difficult to make because bankruptcy
                 datasets are not publicly available and because studies
                 often restrict their datasets to specific economic
                 sectors and markets and/or time periods. In this work,
                 we investigated the design and the application of
                 different ML models to two different tasks related to
                 default events: (a) estimating survival probabilities
                 over time; (b) default prediction using time-series
                 accounting data with different lengths. The entire
                 dataset used for the experiments has been made
                 available to the scientific community for further
                 research and benchmarking purposes. The dataset
                 pertains to 8262 different public companies listed on
                 the American stock market between 1999 and 2018.
                 Finally, in light of the results obtained, we
                 critically discuss the most interesting metrics as
                 proposed benchmarks for future studies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Buccafurri:2022:BBF,
  author =       "Francesco Buccafurri and Vincenzo {De Angelis} and
                 Sara Lazzaro",
  title =        "A Blockchain-Based Framework to Enhance Anonymous
                 Services with Accountability Guarantees",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "8",
  pages =        "243",
  day =          "21",
  month =        aug,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14080243",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 2 12:13:30 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/8/243",
  abstract =     "Anonymous service delivery has attracted the interest
                 of research and the industry for many decades. To
                 obtain effective solutions, anonymity should be
                 guaranteed against the service provider itself.
                 However, if the full anonymity of users is implemented,
                 no accountability mechanism can be provided. This
                 represents a problem, especially when referring to
                 scenarios in which a user, protected by anonymity, may
                 perform illegally when leveraging the anonymous
                 service. In this paper, we propose a blockchain-based
                 solution to the trade-off between anonymity and
                 accountability. In particular, our solution relies on
                 three independent parties (one of which is the service
                 provider itself) such that only the collaboration of
                 all three actors allows for the disclosure of the real
                 identity of the user. In all other cases, anonymity is
                 guaranteed. To show the feasibility of the proposal, we
                 developed a prototype with user-friendly interfaces
                 that minimize the client-side operations. Our solution
                 is then also effective from the point of view of
                 usability.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kallitsis:2022:PED,
  author =       "Georgios Kallitsis and Vasileios Karyotis and Symeon
                 Papavassiliou",
  title =        "On the Potential of Enhancing Delay-Tolerant Routing
                 Protocols via Age of Information",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "8",
  pages =        "242",
  day =          "17",
  month =        aug,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14080242",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 2 12:13:30 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/8/242",
  abstract =     "In this paper, we study the potential of using the
                 metric of Age of Information (AoI) for enhancing
                 delay-tolerant routing protocols. The latter have been
                 proposed for alleviating the impact of long roundtrip
                 time in networks operating in harsh environments, e.g.,
                 in distributed applications deployed in a
                 desert/sparsely populated area without infrastructure,
                 a space network, etc. Delay-tolerant routing protocols
                 can prevent excessive packet timer expiration, but do
                 not provide any packet delivery time guarantee. Thus,
                 they are unsuitable for time-sensitive applications
                 that are more intensely desired nowadays in the next
                 generation networking applications. By incorporating
                 AoI into the operation of delay-tolerant routing
                 protocols, we aim at devising routing protocols that
                 can cope with both long propagation times and
                 challenges related to time-sensitivity in packet
                 delivery. More specifically, in this work, we modify
                 the operation of a well-known delay-tolerant routing
                 protocol, namely FRESH, to make AoI-based packet
                 forwarding decisions, aiming at achieving specific
                 delay guarantees regarding the end-to-end delivery
                 time. We investigate the advantages and disadvantages
                 of such an approach compared to the traditional FRESH
                 protocol. This work serves as a cornerstone for
                 successfully demonstrating the potential of exploiting
                 AoI in delay-tolerant routing and its applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Panda:2022:NLI,
  author =       "Padmalochan Panda and Alekha Kumar Mishra and Deepak
                 Puthal",
  title =        "A Novel Logo Identification Technique for Logo-Based
                 Phishing Detection in Cyber-Physical Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "8",
  pages =        "241",
  day =          "15",
  month =        aug,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14080241",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 2 12:13:30 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/8/241",
  abstract =     "The first and foremost task of a phishing-detection
                 mechanism is to confirm the appearance of a suspicious
                 page that is similar to a genuine site. Once this is
                 found, a suitable URL analysis mechanism may lead to
                 conclusions about the genuineness of the suspicious
                 page. To confirm appearance similarity, most of the
                 approaches inspect the image elements of the genuine
                 site, such as the logo, theme, font color and style. In
                 this paper, we propose a novel logo-based
                 phishing-detection mechanism that characterizes the
                 existence and unique distribution of hue values in a
                 logo image as the foundation to unambiguously represent
                 a brand logo. Using the proposed novel feature, the
                 detection mechanism optimally classifies a suspicious
                 logo to the best matching brand logo. The experiment is
                 performed over our customized dataset based on the
                 popular phishing brands in the South-Asia region. A set
                 of five machine-learning algorithms is used to train
                 and test the prepared dataset. We inferred from the
                 experimental results that the ensemble random forest
                 algorithm achieved the high accuracy of 87\% with our
                 prepared dataset.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yaser:2022:IDD,
  author =       "Ahmed Latif Yaser and Hamdy M. Mousa and Mahmoud
                 Hussein",
  title =        "Improved {DDoS} Detection Utilizing Deep Neural
                 Networks and Feedforward Neural Networks as
                 Autoencoder",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "8",
  pages =        "240",
  day =          "12",
  month =        aug,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14080240",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 2 12:13:30 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/8/240",
  abstract =     "Software-defined networking (SDN) is an innovative
                 network paradigm, offering substantial control of
                 network operation through a network's architecture. SDN
                 is an ideal platform for implementing projects
                 involving distributed applications, security solutions,
                 and decentralized network administration in a
                 multitenant data center environment due to its
                 programmability. As its usage rapidly expands, network
                 security threats are becoming more frequent, leading
                 SDN security to be of significant concern.
                 Machine-learning (ML) techniques for intrusion
                 detection of DDoS attacks in SDN networks utilize
                 standard datasets and fail to cover all classification
                 aspects, resulting in under-coverage of attack
                 diversity. This paper proposes a hybrid technique to
                 recognize denial-of-service (DDoS) attacks that combine
                 deep learning and feedforward neural networks as
                 autoencoders. Two datasets were analyzed for the
                 training and testing model, first statically and then
                 iteratively. The auto-encoding model is constructed by
                 stacking the input layer and hidden layer of
                 self-encoding models' layer by layer, with each
                 self-encoding model using a hidden layer. To evaluate
                 our model, we use a three-part data split (train, test,
                 and validate) rather than the common two-part split
                 (train and test). The resulting proposed model achieved
                 a higher accuracy for the static dataset, where for
                 ISCX-IDS-2012 dataset, accuracy reached a high of
                 99.35\% in training, 99.3\% in validation and 99.99\%
                 in precision, recall, and F1-score. for the UNSW2018
                 dataset, the accuracy reached a high of 99.95\% in
                 training, 0.99.94\% in validation, and 99.99\% in
                 precision, recall, and F1-score. In addition, the model
                 achieved great results with a dynamic dataset (using an
                 emulator), reaching a high of 97.68\% in accuracy.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ali:2022:DDA,
  author =       "Usman Ali and Giuseppe Caso and Luca {De Nardis} and
                 Konstantinos Kousias and Mohammad Rajiullah and
                 {\"O}zg{\"u} Alay and Marco Neri and Anna Brunstrom and
                 Maria-Gabriella {Di Benedetto}",
  title =        "Data-Driven Analysis of Outdoor-to-Indoor Propagation
                 for {5G} Mid-Band Operational Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "8",
  pages =        "239",
  day =          "11",
  month =        aug,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14080239",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 2 12:13:30 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/8/239",
  abstract =     "The successful rollout of fifth-generation (5G)
                 networks requires a full understanding of the behavior
                 of the propagation channel, taking into account the
                 signal formats and the frequencies standardized by the
                 Third Generation Partnership Project (3GPP). In the
                 past, channel characterization for 5G has been
                 addressed mainly based on the measurements performed on
                 dedicated links in experimental setups. This paper
                 presents a state-of-the-art contribution to the
                 characterization of the outdoor-to-indoor radio channel
                 in the 3.5 GHz band, based on experimental data for
                 commercial, deployed 5G networks, collected during a
                 large scale measurement campaign carried out in the
                 city of Rome, Italy. The analysis presented in this
                 work focuses on downlink, outdoor-to-indoor propagation
                 for two operators adopting two different beamforming
                 strategies, single wide-beam and multiple
                 synchronization signal blocks (SSB) based beamforming;
                 it is indeed the first contribution studying the impact
                 of beamforming strategy in real 5G networks. The time
                 and power-related channel characteristics, i.e., mean
                 excess delay and Root Mean Square (RMS) delay spread,
                 path loss, and K-factor are studied for the two
                 operators in multiple measurement locations. The
                 analysis of time and power-related parameters is
                 supported and extended by a correlation analysis
                 between each pair of parameters. The results show that
                 beamforming strategy has a marked impact on
                 propagation. A single wide-beam transmission leads, in
                 fact, to lower RMS delay spread and lower mean excess
                 delay compared to a multiple SSB-based transmission
                 strategy. In addition, the single wide-beam
                 transmission system is characterized by a smaller path
                 loss and a higher K-factor, suggesting that the
                 adoption of a multiple SSB-based transmission strategy
                 may have a negative impact on downlink performance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Raheman:2022:WZV,
  author =       "Fazal Raheman and Tejas Bhagat and Brecht Vermeulen
                 and Peter {Van Daele}",
  title =        "Will Zero Vulnerability Computing ({ZVC}) Ever Be
                 Possible? {Testing} the Hypothesis",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "8",
  pages =        "238",
  day =          "30",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14080238",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 2 12:13:30 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/8/238",
  abstract =     "Life without computers is unimaginable. However,
                 computers remain vulnerable to cybercrimes, a USD 6
                 trillion industry that the world has come to accept as
                 a ``necessary evil''. Third-party permissions resulting
                 in an attack surface (AS) and in-computer storage that
                 computers mandate are key design elements that hackers
                 exploit, formerly by remote malware installation and
                 later by stealing personal data using authentication
                 faking techniques. In legacy computers, the AS cannot
                 be completely eliminated, nor can a connected device
                 retain data offline, rendering fool-proof cybersecurity
                 impossible. Although the architects of legacy computers
                 made perfectly reasonable engineering trade-offs for
                 their world, our world is very different. Zero
                 vulnerability computing (ZVC) challenges the impossible
                 with in-computer offline storage (ICOS) and Supra OS
                 (SOS), to deliver comprehensive protection against
                 vulnerabilities. The feasibility of ZVC is demonstrated
                 in a tiny permanently computer-mounted hardware wallet,
                 providing the first evidence of the complete
                 obliteration of the AS. Malware cannot infect the ZVC
                 device on account of lacking an AS, nor can personal
                 data be hacked as they mostly remain offline, except
                 for sporadic processing. Further research should
                 explore whether ZVC can fully secure computers in more
                 complex real-world scenarios and open a new epoch in
                 the evolution of computers and the Internet.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fallucchi:2022:DQQ,
  author =       "Francesca Fallucchi and Bouchra Ghattas and Riem
                 Spielhaus and Ernesto William {De Luca}",
  title =        "Digital Qualitative and Quantitative Analysis of
                 {Arabic} Textbooks",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "8",
  pages =        "237",
  day =          "29",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14080237",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 2 12:13:30 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/8/237",
  abstract =     "Digital Humanities (DH) provide a broad spectrum of
                 functionalities and tools that enable the enrichment of
                 both quantitative and qualitative research methods in
                 the humanities. It has been widely recognized that DH
                 can help in curating and analysing large amounts of
                 data. However, digital tools can also support research
                 processes in the humanities that are interested in
                 detailed analyses of how empirical sources are
                 patterned. Following a methodological differentiation
                 between close and distant reading with regard to
                 textual analysis, this article describes the Edumeres
                 Toolbox, a digital tool for textbook analysis. The
                 Edumeres Toolbox is an outcome of the continuous
                 interdisciplinary exchange between computer scientists
                 and humanist researchers, whose expertise is crucial to
                 convert information into knowledge by means of
                 (critical) interpretation and contextualization. This
                 paper presents a use case in order to describe the
                 various functionalities of the Edumeres Toolbox and
                 their use for the analysis of a collection of Arabic
                 textbooks. Hereby, it shows how the interaction between
                 humanist researchers and computer scientists in this
                 digital process produces innovative research solutions
                 and how the tool enables users to discover structural
                 and linguistic patterns and develop innovative research
                 questions. Finally, the paper describes challenges
                 recognized by humanist researchers in using digital
                 tools in their work, which still require in-depth
                 research and practical efforts from both parties to
                 improve the tool performance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Jian:2022:STW,
  author =       "Bijian Jian and Chunbo Ma and Dejian Zhu and Yixiao
                 Sun and Jun Ao",
  title =        "Seeing through Wavy Water--Air Interface: a
                 Restoration Model for Instantaneous Images Distorted by
                 Surface Waves",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "8",
  pages =        "236",
  day =          "29",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14080236",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 2 12:13:30 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/8/236",
  abstract =     "Imaging through a wavy water--air interface is
                 challenging since light rays are bent by unknown
                 amounts, leading to complex geometric distortions.
                 Considering the restoration of instantaneous distorted
                 images, this paper proposes an image recovery model via
                 structured light projection. The algorithm is composed
                 of two separate parts. In the first part, an algorithm
                 for the determination of the instantaneous shape of the
                 water surface via structured light projection is
                 developed. Then, we synchronously recover the distorted
                 airborne scene image through reverse ray tracing in the
                 second part. The experimental results show that,
                 compared with the state-of-the-art methods, the
                 proposed method not only can overcome the influence of
                 changes in natural illumination conditions for WAI
                 reconstruction, but also can significantly reduce the
                 distortion and achieve better performance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2022:CFM,
  author =       "Yaning Li and Hongsheng Li and Baoguo Yu and Jun Li",
  title =        "A {CSI} Fingerprint Method for Indoor Pseudolite
                 Positioning Based on {RT-ANN}",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "8",
  pages =        "235",
  day =          "29",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14080235",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 2 12:13:30 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/8/235",
  abstract =     "At present, the interaction mechanism between the
                 complex indoor environment and pseudolite signals has
                 not been fundamentally resolved, and the stability,
                 continuity, and accuracy of indoor positioning are
                 still technical bottlenecks. In view of the
                 shortcomings of the existing indoor fingerprint
                 positioning methods, this paper proposes a hybrid CSI
                 fingerprint method for indoor pseudolite positioning
                 based on Ray Tracing and artificial neural network
                 (RT-ANN), which combines the advantages of actual
                 acquisition, deterministic simulation, and artificial
                 neural network, and adds the simulation CSI feature
                 parameters generated by modeling and simulation to the
                 input of the neural network, extending the sample
                 features of the neural network input dataset. Taking an
                 airport environment as an example, it is proved that
                 the hybrid method can improve the positioning accuracy
                 in the area where the fingerprints have been collected,
                 the positioning error is reduced by 54.7\% compared
                 with the traditional fingerprint positioning method. It
                 is also proved that preliminary positioning can be
                 completed in the area without fingerprint collection.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yan:2022:MSA,
  author =       "Shangyi Yan and Jingya Wang and Zhiqiang Song",
  title =        "Microblog Sentiment Analysis Based on Dynamic
                 Character-Level and Word-Level Features and Multi-Head
                 Self-Attention Pooling",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "8",
  pages =        "234",
  day =          "29",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14080234",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 2 12:13:30 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/8/234",
  abstract =     "To address the shortcomings of existing deep learning
                 models and the characteristics of microblog speech, we
                 propose the DCCMM model to improve the effectiveness of
                 microblog sentiment analysis. The model employs WOBERT
                 Plus and ALBERT to dynamically encode character-level
                 text and word-level text, respectively. Then, a
                 convolution operation is used to extract local key
                 features, while cross-channel feature fusion and
                 multi-head self-attention pooling operations are used
                 to extract global semantic information and filter out
                 key data, before using the multi-granularity feature
                 interaction fusion operation to effectively fuse
                 character-level and word-level semantic information.
                 Finally, the Softmax function is used to output the
                 results. On the weibo\_senti\_100k dataset, the
                 accuracy and F1 values of the DCCMM model improve by
                 0.84\% and 1.01\%, respectively, compared to the
                 best-performing comparison model. On the SMP2020-EWECT
                 dataset, the accuracy and F1 values of the DCCMM model
                 improve by 1.22\% and 1.80\%, respectively, compared
                 with the experimental results of the best-performing
                 comparison model. The results showed that DCCMM
                 outperforms existing advanced sentiment analysis
                 models.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bagha:2022:HSP,
  author =       "Hamid Bagha and Ali Yavari and Dimitrios
                 Georgakopoulos",
  title =        "Hybrid Sensing Platform for {IoT}-Based Precision
                 Agriculture",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "8",
  pages =        "233",
  day =          "28",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14080233",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 2 12:13:30 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/8/233",
  abstract =     "Precision agriculture (PA) is the field that deals
                 with the fine-tuned management of crops to increase
                 crop yield, augment profitability, and conserve the
                 environment. Existing Internet of Things (IoT)
                 solutions for PA are typically divided in terms of
                 their use of either aerial sensing using unmanned
                 aerial vehicles (UAVs) or ground-based sensing
                 approaches. Ground-based sensing provides high data
                 accuracy, but it involves large grids of ground-based
                 sensors with high operational costs and complexity. On
                 the other hand, while the cost of aerial sensing is
                 much lower than ground-based sensing alternatives, the
                 data collected via aerial sensing are less accurate and
                 cover a smaller period than ground-based sensing data.
                 Despite the contrasting virtues and limitations of
                 these two sensing approaches, there are currently no
                 hybrid sensing IoT solutions that combine aerial and
                 ground-based sensing to ensure high data accuracy at a
                 low cost. In this paper, we propose a Hybrid Sensing
                 Platform (HSP) for PA---an IoT platform that combines a
                 small number of ground-based sensors with aerial
                 sensors to improve aerial data accuracy and at the same
                 time reduce ground-based sensing costs.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chochtoula:2022:IEC,
  author =       "Despoina Chochtoula and Aristidis Ilias and Yannis C.
                 Stamatiou and Christos Makris",
  title =        "Integrating Elliptic Curve Cryptography with the
                 {Modbus TCP SCADA Communication Protocol}",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "8",
  pages =        "232",
  day =          "28",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14080232",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 2 12:13:30 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/8/232",
  abstract =     "SCADA systems monitor critical industrial, energy and
                 other physical infrastructures in order to detect
                 malfunctions, issue alerts and, in many cases, propose
                 or even take remedial actions. However, due to their
                 attachment to the Internet, SCADA systems are, today,
                 vulnerable to attacks such as, among several others,
                 interception of data traffic, malicious modifications
                 of settings and control operations data, malicious
                 modification of measurements and infrastructure data
                 and Denial-of-Service attacks. Our research focuses on
                 strengthening SCADA systems with cryptographic methods
                 and protection mechanisms with emphasis on data and
                 messaging encryption and device identification and
                 authentication. The limited availability of computing
                 power and memory in sensors and embedded devices
                 deployed in SCADA systems make render cryptographic
                 methods with higher resource requirements, such as the
                 use of conventional public key cryptography such as
                 RSA, unsuitable. We, thus, propose Elliptic Curve
                 Cryptography as an alternative cryptographic mechanism,
                 where smaller key sizes are required, with lower
                 resource requirements for cryptographic operations.
                 Accordingly, our approach integrates Modbus, a commonly
                 used SCADA communication protocol, with Elliptic Curve
                 Cryptography. We have, also, developed an experimental
                 set-up in order to demonstrate the performance of our
                 approach and draw conclusions regarding its
                 effectiveness in real SCADA installations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zali:2022:PPS,
  author =       "Siti-Aisyah Zali and Shahbe Mat-Desa and Zarina
                 Che-Embi and Wan-Noorshahida Mohd-Isa",
  title =        "Post-Processing for Shadow Detection in Drone-Acquired
                 Images Using {U-NET}",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "8",
  pages =        "231",
  day =          "28",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14080231",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 2 12:13:30 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/8/231",
  abstract =     "Shadows in drone images commonly appear in various
                 shapes, sizes, and brightness levels, as the images
                 capture a wide view of scenery under many conditions,
                 such as varied flying height and weather. This property
                 of drone images leads to a major problem when it comes
                 to detecting shadow and causes the presence of noise in
                 the predicted shadow mask. The purpose of this study is
                 to improve shadow detection results by implementing
                 post-processing methods related to automatic
                 thresholding and binary mask refinement. The aim is to
                 discuss how the selected automatic thresholding and two
                 methods of binary mask refinement perform to increase
                 the efficiency and accuracy of shadow detection. The
                 selected automatic thresholding method is Otsu's
                 thresholding, and methods for binary mask refinement
                 are morphological operation and dense CRF. The study
                 shows that the proposed methods achieve an acceptable
                 accuracy of 96.43\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Arzo:2022:MAB,
  author =       "Sisay Tadesse Arzo and Zeinab Akhavan and Mona
                 Esmaeili and Michael Devetsikiotis and Fabrizio
                 Granelli",
  title =        "Multi-Agent-Based Traffic Prediction and Traffic
                 Classification for Autonomic Network Management Systems
                 for Future Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "8",
  pages =        "230",
  day =          "28",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14080230",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 2 12:13:30 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/8/230",
  abstract =     "Recently, a multi-agent based network automation
                 architecture has been proposed. The architecture is
                 named multi-agent based network automation of the
                 network management system (MANA-NMS). The architectural
                 framework introduced atomized network functions (ANFs).
                 ANFs should be autonomous, atomic, and intelligent
                 agents. Such agents should be implemented as an
                 independent decision element, using machine/deep
                 learning (ML/DL) as an internal cognitive and reasoning
                 part. Using these atomic and intelligent agents as a
                 building block, a MANA-NMS can be composed using the
                 appropriate functions. As a continuation toward
                 implementation of the architecture MANA-NMS, this paper
                 presents a network traffic prediction agent (NTPA) and
                 a network traffic classification agent (NTCA) for a
                 network traffic management system. First, an NTPA is
                 designed and implemented using DL algorithms, i.e.,
                 long short-term memory (LSTM), gated recurrent unit
                 (GRU), multilayer perceptrons (MLPs), and convolutional
                 neural network (CNN) algorithms as a reasoning and
                 cognitive part of the agent. Similarly, an NTCA is
                 designed using decision tree (DT), K-nearest neighbors
                 (K-NN), support vector machine (SVM), and naive Bayes
                 (NB) as a cognitive component in the agent design. We
                 then measure the NTPA prediction accuracy, training
                 latency, prediction latency, and computational resource
                 consumption. The results indicate that the LSTM-based
                 NTPA outperforms compared to GRU, MLP, and CNN-based
                 NTPA in terms of prediction accuracy, and prediction
                 latency. We also evaluate the accuracy of the
                 classifier, training latency, classification latency,
                 and computational resource consumption of NTCA using
                 the ML models. The performance evaluation shows that
                 the DT-based NTCA performs the best.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Moedjahedy:2022:CCC,
  author =       "Jimmy Moedjahedy and Arief Setyanto and Fawaz Khaled
                 Alarfaj and Mohammed Alreshoodi",
  title =        "{CCrFS}: Combine Correlation Features Selection for
                 Detecting Phishing {Websites} Using Machine Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "8",
  pages =        "229",
  day =          "27",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14080229",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 2 12:13:30 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/8/229",
  abstract =     "Internet users are continually exposed to phishing as
                 cybercrime in the 21st century. The objective of
                 phishing is to obtain sensitive information by
                 deceiving a target and using the information for
                 financial gain. The information may include a login
                 detail, password, date of birth, credit card number,
                 bank account number, and family-related information. To
                 acquire these details, users will be directed to fill
                 out the information on false websites based on
                 information from emails, adverts, text messages, or
                 website pop-ups. Examining the website's URL address is
                 one method for avoiding this type of deception.
                 Identifying the features of a phishing website URL
                 takes specialized knowledge and investigation. Machine
                 learning is one method that uses existing data to teach
                 machines to distinguish between legal and phishing
                 website URLs. In this work, we proposed a method that
                 combines correlation and recursive feature elimination
                 to determine which URL characteristics are useful for
                 identifying phishing websites by gradually decreasing
                 the number of features while maintaining accuracy
                 value. In this paper, we use two datasets that contain
                 48 and 87 features. The first scenario combines power
                 predictive score correlation and recursive feature
                 elimination; the second scenario is the maximal
                 information coefficient correlation and recursive
                 feature elimination. The third scenario combines
                 Spearman correlation and recursive feature elimination.
                 All three scenarios from the combined findings of the
                 proposed methodologies achieve a high level of accuracy
                 even with the smallest feature subset. For dataset 1,
                 the accuracy value for the 10 features result is
                 97.06\%, and for dataset 2 the accuracy value is
                 95.88\% for 10 features.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Petrolini:2022:ADS,
  author =       "Michael Petrolini and Stefano Cagnoni and Monica
                 Mordonini",
  title =        "Automatic Detection of Sensitive Data Using
                 Transformer-Based Classifiers",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "8",
  pages =        "228",
  day =          "27",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14080228",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 2 12:13:30 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/8/228",
  abstract =     "The General Data Protection Regulation (GDPR) has
                 allowed EU citizens and residents to have more control
                 over their personal data, simplifying the regulatory
                 environment affecting international business and
                 unifying and homogenising privacy legislation within
                 the EU. This regulation affects all companies that
                 process data of European residents regardless of the
                 place in which they are processed and their registered
                 office, providing for a strict discipline of data
                 protection. These companies must comply with the GDPR
                 and be aware of the content of the data they manage;
                 this is especially important if they are holding
                 sensitive data, that is, any information regarding
                 racial or ethnic origin, political opinions, religious
                 or philosophical beliefs, trade union membership, data
                 relating to the sexual life or sexual orientation of
                 the person, as well as data on physical and mental
                 health. These classes of data are hardly structured,
                 and most frequently they appear within a document such
                 as an email message, a review or a post. It is
                 extremely difficult to know if a company is in
                 possession of sensitive data at the risk of not
                 protecting them properly. The goal of the study
                 described in this paper is to use Machine Learning, in
                 particular the Transformer deep-learning model, to
                 develop classifiers capable of detecting documents that
                 are likely to include sensitive data. Additionally, we
                 want the classifiers to recognize the particular type
                 of sensitive topic with which they deal, in order for a
                 company to have a better knowledge of the data they
                 own. We expect to make the model described in this
                 paper available as a web service, customized to private
                 data of possible customers, or even in a free-to-use
                 version based on the freely available data set we have
                 built to train the classifiers.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Xia:2022:RUT,
  author =       "Zhuofei Xia and Jiayuan Gong and Hailong Yu and Wenbo
                 Ren and Jingnan Wang",
  title =        "Research on Urban Traffic Incident Detection Based on
                 Vehicle Cameras",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "8",
  pages =        "227",
  day =          "26",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14080227",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 2 12:13:30 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/8/227",
  abstract =     "Situational detection in the traffic system is of
                 great significance to traffic management and even urban
                 management. Traditional detection methods are generally
                 based on roadside equipment monitoring roads, and it is
                 difficult to support large-scale and fine-grained
                 traffic incident detection. In this study, we propose a
                 detection method applied to the mobile edge, which
                 detects traffic incidents based on the video captured
                 by vehicle cameras, so as to overcome the limitations
                 of roadside terminal perception. For swarm intelligence
                 detection, we propose an improved YOLOv5s object
                 detection network, adding an atrous pyramid pooling
                 layer to the network and introducing a fusion attention
                 mechanism to improve the model accuracy. Compared with
                 the raw YOLOv5s, the mAP metrics of our improved model
                 are increased by 3.3\% to 84.2\%, enabling it to detect
                 vehicles, pedestrians, traffic accidents, and fire
                 traffic incidents on the road with high precision in
                 real time. This provides information for city managers
                 to help them grasp the abnormal operation status of
                 roads and cities in a timely and effective manner.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Dai:2022:ESS,
  author =       "Zhiqiang Dai and Gaochao Xu and Ziqi Liu and Jiaqi Ge
                 and Wei Wang",
  title =        "Energy Saving Strategy of {UAV} in {MEC} Based on Deep
                 Reinforcement Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "8",
  pages =        "226",
  day =          "26",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14080226",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 2 12:13:30 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/8/226",
  abstract =     "Unmanned aerial vehicles (UAVs) have the
                 characteristics of portability, safety, and strong
                 adaptability. In the case of a maritime disaster, they
                 can be used for personnel search and rescue, real-time
                 monitoring, and disaster assessment. However, the
                 power, computing power, and other resources of UAVs are
                 often limited. Therefore, this paper combines a UAV and
                 mobile edge computing (MEC), and designs a deep
                 reinforcement learning-based online task offloading
                 (DOTO) algorithm. The algorithm can obtain an online
                 offloading strategy that maximizes the residual energy
                 of the UAV by jointly optimizing the UAV's time and
                 communication resources. The DOTO algorithm adopts time
                 division multiple access (TDMA) to offload and schedule
                 the UAV computing task, integrates wireless power
                 transfer (WPT) to supply power to the UAV, calculates
                 the residual energy corresponding to the offloading
                 action through the convex optimization method, and uses
                 an adaptive K method to reduce the computational
                 complexity of the algorithm. The simulation results
                 show that the DOTO algorithm proposed in this paper for
                 the energy-saving goal of maximizing the residual
                 energy of UAVs in MEC can provide the UAV with an
                 online task offloading strategy that is superior to
                 other traditional benchmark schemes. In particular,
                 when an individual UAV exits the system due to
                 insufficient power or failure, or a new UAV is
                 connected to the system, it can perform timely and
                 automatic adjustment without manual participation, and
                 has good stability and adaptability.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ren:2022:AVN,
  author =       "Wenbo Ren and Xinran Bian and Jiayuan Gong and Anqing
                 Chen and Ming Li and Zhuofei Xia and Jingnan Wang",
  title =        "Analysis and Visualization of New Energy Vehicle
                 Battery Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "8",
  pages =        "225",
  day =          "26",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14080225",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 2 12:13:30 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/8/225",
  abstract =     "In order to safely and efficiently use their power as
                 well as to extend the life of Li-ion batteries, it is
                 important to accurately analyze original battery data
                 and quickly predict SOC. However, today, most of them
                 are analyzed directly for SOC, and the analysis of the
                 original battery data and how to obtain the factors
                 affecting SOC are still lacking. Based on this, this
                 paper uses the visualization method to preprocess,
                 clean, and parse collected original battery data
                 (hexadecimal), followed by visualization and analysis
                 of the parsed data, and finally the K-Nearest Neighbor
                 (KNN) algorithm is used to predict the SOC. Through
                 experiments, the method can completely analyze the
                 hexadecimal battery data based on the GB/T32960
                 standard, including three different types of messages:
                 vehicle login, real-time information reporting, and
                 vehicle logout. At the same time, the visualization
                 method is used to intuitively and concisely analyze the
                 factors affecting SOC. Additionally, the KNN algorithm
                 is utilized to identify the K value and P value using
                 dynamic parameters, and the resulting mean square error
                 (MSE) and test score are 0.625 and 0.998, respectively.
                 Through the overall experimental process, this method
                 can well analyze the battery data from the source,
                 visually analyze various factors and predict SOC.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rubart:2022:AIC,
  author =       "Jessica Rubart and Valentin Grimm and Jonas Potthast",
  title =        "Augmenting Industrial Control Rooms with Multimodal
                 Collaborative Interaction Techniques",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "8",
  pages =        "224",
  day =          "26",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14080224",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 2 12:13:30 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/8/224",
  abstract =     "The German manufacturing industry has been carrying
                 out new developments towards the next industrial
                 revolution, focusing on smart manufacturing
                 environments. Our work emphasizes human-centered
                 control rooms in the context of production plants.
                 Increased automation does not have to come with less
                 human control. Therefore, we report on multimodal
                 collaborative interaction techniques to augment
                 industrial control rooms. In particular, we include
                 mobile workers who use the control room while being in
                 the production hall using tablets or specifically mixed
                 reality glasses. Collaborative annotation dashboards
                 support discussions and a shared understanding among
                 analysts. Manufacturing-related data can be integrated
                 into business analytics environments so that holistic
                 analyses can be performed. Multimodal interaction
                 techniques can support effective interaction with the
                 control room based on the users' preferences. Immersive
                 experience through mixed reality-based
                 three-dimensional visualizations and interaction
                 possibilities support users in obtaining a clear
                 understanding of the underlying data.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alkhalidy:2022:NSD,
  author =       "Muhsen Alkhalidy and Atalla Fahed Al-Serhan and Ayoub
                 Alsarhan and Bashar Igried",
  title =        "A New Scheme for Detecting Malicious Nodes in
                 Vehicular Ad Hoc Networks Based on Monitoring Node
                 Behavior",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "8",
  pages =        "223",
  day =          "26",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14080223",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 2 12:13:30 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/8/223",
  abstract =     "Vehicular ad hoc networks have played a key role in
                 intelligent transportation systems that considerably
                 improve road safety and management. This new technology
                 allows vehicles to communicate and share road
                 information. However, malicious users may inject false
                 emergency alerts into vehicular ad hoc networks,
                 preventing nodes from accessing accurate road
                 information. In order to assure the reliability and
                 trustworthiness of information through the networks,
                 assessing the credibility of nodes has become a
                 critical task in vehicular ad hoc networks. A new
                 scheme for malicious node detection is proposed in this
                 work. Multiple factors are fed into a fuzzy logic model
                 for evaluating the trust for each node. Vehicles are
                 divided into clusters in our approach, and a road side
                 unit manages each cluster. The road side unit assesses
                 the credibility of nodes before accessing vehicular ad
                 hoc networks. The road side unit evicts a malicious
                 node based on trust value. Simulations are used to
                 validate our technique. We demonstrate that our scheme
                 can detect and evict all malicious nodes in the
                 vehicular ad hoc network over time, lowering the ratio
                 of malicious nodes. Furthermore, it has a positive
                 impact on selfish node participation. The scheme
                 increases the success rate of delivered data to the
                 same level as the ideal cases when no selfish node is
                 present.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ahamed:2022:IMB,
  author =       "Farhad Ahamed and Farnaz Farid and Basem Suleiman and
                 Zohaib Jan and Luay A. Wahsheh and Seyed Shahrestani",
  title =        "An Intelligent Multimodal Biometric Authentication
                 Model for Personalised Healthcare Services",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "8",
  pages =        "222",
  day =          "26",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14080222",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 2 12:13:30 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/8/222",
  abstract =     "With the advent of modern technologies, the healthcare
                 industry is moving towards a more personalised smart
                 care model. The enablers of such care models are the
                 Internet of Things (IoT) and Artificial Intelligence
                 (AI). These technologies collect and analyse data from
                 persons in care to alert relevant parties if any
                 anomaly is detected in a patient's regular pattern.
                 However, such reliance on IoT devices to capture
                 continuous data extends the attack surfaces and demands
                 high-security measures. Both patients and devices need
                 to be authenticated to mitigate a large number of
                 attack vectors. The biometric authentication method has
                 been seen as a promising technique in these scenarios.
                 To this end, this paper proposes an AI-based multimodal
                 biometric authentication model for single and
                 group-based users' device-level authentication that
                 increases protection against the traditional single
                 modal approach. To test the efficacy of the proposed
                 model, a series of AI models are trained and tested
                 using physiological biometric features such as ECG
                 (Electrocardiogram) and PPG (Photoplethysmography)
                 signals from five public datasets available in
                 Physionet and Mendeley data repositories. The
                 multimodal fusion authentication model shows promising
                 results with 99.8\% accuracy and an Equal Error Rate
                 (EER) of 0.16.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ferretti:2022:DLF,
  author =       "Marco Ferretti and Ugo Fiore and Francesca Perla and
                 Marcello Risitano and Salvatore Scognamiglio",
  title =        "Deep Learning Forecasting for Supporting Terminal
                 Operators in Port Business Development",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "8",
  pages =        "221",
  day =          "25",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14080221",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 2 12:13:30 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/8/221",
  abstract =     "Accurate forecasts of containerised freight volumes
                 are unquestionably important for port terminal
                 operators to organise port operations and develop
                 business plans. They are also relevant for port
                 authorities, regulators, and governmental agencies
                 dealing with transportation. In a time when deep
                 learning is in the limelight, owing to a consistent
                 strip of success stories, it is natural to apply it to
                 the tasks of forecasting container throughput. Given
                 the number of options, practitioners can benefit from
                 the lessons learned in applying deep learning models to
                 the problem. Coherently, in this work, we devise a
                 number of multivariate predictive models based on deep
                 learning, analysing and assessing their performance to
                 identify the architecture and set of hyperparameters
                 that prove to be better suited to the task, also
                 comparing the quality of the forecasts with seasonal
                 autoregressive integrated moving average models.
                 Furthermore, an innovative representation of
                 seasonality is given by means of an embedding layer
                 that produces a mapping in a latent space, with the
                 parameters of such mapping being tuned using the
                 quality of the predictions. Finally, we present some
                 managerial implications, also putting into evidence the
                 research limitations and future opportunities.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{James:2022:EDD,
  author =       "Nicholas James and Lee-Yeng Ong and Meng-Chew Leow",
  title =        "Exploring Distributed Deep Learning Inference Using
                 {Raspberry Pi Spark} Cluster",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "8",
  pages =        "220",
  day =          "25",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14080220",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 2 12:13:30 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/8/220",
  abstract =     "Raspberry Pi (Pi) is a versatile general-purpose
                 embedded computing device that can be used for both
                 machine learning (ML) and deep learning (DL) inference
                 applications such as face detection. This study trials
                 the use of a Pi Spark cluster for distributed inference
                 in TensorFlow. Specifically, it investigates the
                 performance difference between a 2-node Pi 4B Spark
                 cluster and other systems, including a single Pi 4B and
                 a mid-end desktop computer. Enhancements for the Pi 4B
                 were studied and compared against the Spark cluster to
                 identify the more effective method in increasing the Pi
                 4B's DL performance. Three experiments involving DL
                 inference, which in turn involve image classification
                 and face detection tasks, were carried out. Results
                 showed that enhancing the Pi 4B was faster than using a
                 cluster as there was no significant performance
                 difference between using the cluster and a single Pi
                 4B. The difference between the mid-end computer and a
                 single Pi 4B was between 6 and 15 times in the
                 experiments. In the meantime, enhancing the Pi 4B is
                 the more effective approach for increasing the DL
                 performance, and more work needs to be done for
                 scalable distributed DL inference to eventuate.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kadusic:2022:SPS,
  author =       "Esad Kadusic and Natasa Zivic and Christoph Ruland and
                 Narcisa Hadzajlic",
  title =        "A Smart Parking Solution by Integrating {NB-IoT} Radio
                 Communication Technology into the Core {IoT} Platform",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "8",
  pages =        "219",
  day =          "25",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14080219",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 2 12:13:30 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/8/219",
  abstract =     "With the emerging Internet of Things (IoT)
                 technologies, the smart city paradigm has become a
                 reality. Wireless low-power communication technologies
                 (LPWAN) are widely used for device connection in smart
                 homes, smart lighting, mitering, and so on. This work
                 suggests a new approach to a smart parking solution
                 using the benefits of narrowband Internet of Things
                 (NB-IoT) technology. NB-IoT is an LPWAN technology
                 dedicated to sensor communication within 5G mobile
                 networks. This paper proposes the integration of NB-IoT
                 into the core IoT platform, enabling direct sensor data
                 navigation to the IoT radio stations for processing,
                 after which they are forwarded to the user application
                 programming interface (API). Showcasing the results of
                 our research and experiments, this work suggests the
                 ability of NB-IoT technology to support geolocation and
                 navigation services, as well as payment and reservation
                 services for vehicle parking to make the smart parking
                 solutions smarter.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chen:2022:ULP,
  author =       "Xieling Chen and Fu Lee Wang and Gary Cheng and
                 Man-Kong Chow and Haoran Xie",
  title =        "Understanding Learners' Perception of {MOOCs} Based on
                 Review Data Analysis Using Deep Learning and Sentiment
                 Analysis",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "8",
  pages =        "218",
  day =          "25",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14080218",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 2 12:13:30 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/8/218",
  abstract =     "Massive open online courses (MOOCs) have exploded in
                 popularity; course reviews are important sources for
                 exploring learners' perceptions about different factors
                 associated with course design and implementation. This
                 study aims to investigate the possibility of automatic
                 classification for the semantic content of MOOC course
                 reviews to understand factors that can predict
                 learners' satisfaction and their perceptions of these
                 factors. To do this, this study employs a quantitative
                 research methodology based on sentiment analysis and
                 deep learning. Learners' review data from Class Central
                 are analyzed to automatically identify the key factors
                 related to course design and implementation and the
                 learners' perceptions of these factors. A total of
                 186,738 review sentences associated with 13 subject
                 areas are analyzed, and consequently, seven course
                 factors that learners frequently mentioned are found.
                 These factors include: ``Platforms and tools'',
                 ``Course quality'', ``Learning resources'',
                 ``Instructor'', ``Relationship'', ``Process'', and
                 ``Assessment''. Subsequently, each factor is assigned a
                 sentimental value using lexicon-driven methodologies,
                 and the topics that can influence learners' learning
                 experiences the most are decided. In addition,
                 learners' perceptions across different topics and
                 subjects are explored and discussed. The findings of
                 this study contribute to helping MOOC instructors in
                 tailoring course design and implementation to bring
                 more satisfactory learning experiences for learners.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alazab:2022:DOM,
  author =       "Ammar Alazab and Ansam Khraisat and Moutaz Alazab and
                 Sarabjot Singh",
  title =        "Detection of Obfuscated Malicious {JavaScript} Code",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "8",
  pages =        "217",
  day =          "22",
  month =        jul,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14080217",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 2 12:13:30 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/java2020.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/8/217",
  abstract =     "Websites on the Internet are becoming increasingly
                 vulnerable to malicious JavaScript code because of its
                 strong impact and dramatic effect. Numerous recent
                 cyberattacks use JavaScript vulnerabilities, and in
                 some cases employ obfuscation to conceal their malice
                 and elude detection. To secure Internet users, an
                 adequate intrusion-detection system (IDS) for malicious
                 JavaScript must be developed. This paper proposes an
                 automatic IDS of obfuscated JavaScript that employs
                 several features and machine-learning techniques that
                 effectively distinguish malicious and benign JavaScript
                 codes. We also present a new set of features, which can
                 detect obfuscation in JavaScript. The features are
                 selected based on identifying obfuscation, a popular
                 method to bypass conventional malware detection
                 systems. The performance of the suggested approach has
                 been tested on JavaScript obfuscation attacks. The
                 studies have shown that IDS based on selected features
                 has a detection rate of 94\% for malicious samples and
                 81\% for benign samples within the dimension of the
                 feature vector of 60.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chaabane:2022:LPB,
  author =       "Faten Chaabane and Jalel Ktari and Tarek Frikha and
                 Habib Hamam",
  title =        "Low Power Blockchained {E}-Vote Platform for
                 University Environment",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "9",
  pages =        "269",
  day =          "19",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14090269",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 23 06:03:23 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/9/269",
  abstract =     "With the onset of the COVID-19 pandemic and the
                 succession of its waves, the transmission of this
                 disease and the number of deaths caused by it have been
                 increasing. Despite the various vaccines, the COVID-19
                 virus is still contagious and dangerous for affected
                 people. One of the remedies to this is precaution, and
                 particularly social distancing. In the same vein, this
                 paper proposes a remote voting system, which has to be
                 secure, anonymous, irreversible, accessible, and simple
                 to use. It therefore allows voters to have the
                 possibility to vote for their candidate without having
                 to perform the operation on site. This system will be
                 used for university elections and particularly for
                 student elections. We propose a platform based on a
                 decentralized system. This system will use two
                 blockchains communicating with each other: the public
                 Ethereum blockchain and the private Quorum blockchain.
                 The private blockchain will be institution-specific.
                 All these blockchains send the necessary data to the
                 public blockchain which manages different data related
                 to the universities and the ministry. This system
                 enables using encrypted data with the SHA-256 algorithm
                 to have both security and information security.
                 Motivated by the high energy consumption of blockchain
                 and by the performance improvements in low-power, a
                 test is performed on a low-power embedded platform
                 Raspberry PI4 showing the possibility to use the
                 Blockchain with limited resources.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Nafeh:2022:JSV,
  author =       "Majd Nafeh and Arash Bozorgchenani and Daniele
                 Tarchi",
  title =        "Joint Scalable Video Coding and Transcoding Solutions
                 for Fog-Computing-Assisted {DASH} Video Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "9",
  pages =        "268",
  day =          "17",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14090268",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 23 06:03:23 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/9/268",
  abstract =     "Video streaming solutions have increased their
                 importance in the last decade, enabling video on demand
                 (VoD) services. Among several innovative services, 5G
                 and Beyond 5G (B5G) systems consider the possibility of
                 providing VoD-based solutions for surveillance
                 applications, citizen information and e-tourism
                 applications, to name a few. Although the majority of
                 the implemented solutions resort to a centralized
                 cloud-based approach, the interest in edge/fog-based
                 approaches is increasing. Fog-based VoD services result
                 in fulfilling the stringent low-latency requirement of
                 5G and B5G networks. In the following, by resorting to
                 the Dynamic Adaptive Streaming over HTTP (DASH)
                 technique, we design a video-segment deployment
                 algorithm for streaming services in a fog computing
                 environment. In particular, by exploiting the inherent
                 adaptation of the DASH approach, we embed in the system
                 a joint transcoding and scalable video coding (SVC)
                 approach able to deploy at run-time the video segments
                 upon the user's request. With this in mind, two
                 algorithms have been developed aiming at maximizing the
                 marginal gain with respect to a pre-defined delay
                 threshold and enabling video quality downgrade for
                 faster video deployment. Numerical results demonstrate
                 that by effectively mapping the video segments, it is
                 possible to minimize the streaming latency while
                 maximising the users' target video quality.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Feng:2022:EBT,
  author =       "Hangwei Feng and Jinlin Wang and Yang Li",
  title =        "An Efficient Blockchain Transaction Retrieval System",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "9",
  pages =        "267",
  day =          "15",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14090267",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 23 06:03:23 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/9/267",
  abstract =     "In the era of the digital economy, blockchain has
                 developed well in various fields, such as finance and
                 digital copyright, due to its unique decentralization
                 and traceability characteristics. However, blockchain
                 gradually exposes the storage problem, and the current
                 blockchain stores the block data in third-party storage
                 systems to reduce the node storage pressure. The new
                 blockchain storage method brings the blockchain
                 transaction retrieval problem. The problem is that when
                 unable to locate the block containing this transaction,
                 the user must fetch the entire blockchain ledger data
                 from the third-party storage system, resulting in huge
                 communication overhead. For this problem, we exploit
                 the semi-structured data in the blockchain and extract
                 the universal blockchain transaction characteristics,
                 such as account address and time. Then we establish a
                 blockchain transaction retrieval system. Responding to
                 the lacking efficient retrieval data structure, we
                 propose a scalable secondary search data structure BB+
                 tree for account address and introduce the I2B+ tree
                 for time. Finally, we analyze the proposed scheme's
                 performance through experiments. The experiment results
                 prove that our system is superior to the existing
                 methods in single-feature retrieval, concurrent
                 retrieval, and multi-feature hybrid retrieval. The
                 retrieval time under single feature retrieval is
                 reduced by 40.54\%, and the retrieval time is decreased
                 by 43.16\% under the multi-feature hybrid retrieval. It
                 has better stability in different block sizes and
                 concurrent retrieval scales.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Villegas-Ch:2022:AST,
  author =       "William Villegas-Ch. and Angel Jaramillo-Alc{\'a}zar
                 and Aracely Mera-Navarrete",
  title =        "Assistance System for the Teaching of Natural Numbers
                 to Preschool Children with the Use of Artificial
                 Intelligence Algorithms",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "9",
  pages =        "266",
  day =          "15",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14090266",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 23 06:03:23 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/9/266",
  abstract =     "This research was aimed at designing an image
                 recognition system that can help increase children's
                 interest in learning natural numbers between 0 and 9.
                 The research method used was qualitative descriptive,
                 observing early childhood learning in a face-to-face
                 education model, especially in the learning of numbers,
                 with additional data from literature studies. For the
                 development of the system, the cascade method was used,
                 consisting of three stages: identification of the
                 population, design of the artificial intelligence
                 architecture, and implementation of the recognition
                 system. The method of the system sought to replicate a
                 mechanic that simulates a game, whereby the child
                 trains the artificial intelligence algorithm such that
                 it recognizes the numbers that the child draws on a
                 blackboard. The system is expected to help increase the
                 ability of children in their interest to learn numbers
                 and identify the meaning of quantities to help improve
                 teaching success with a fun and engaging teaching
                 method for children. The implementation of learning in
                 this system is expected to make it easier for children
                 to learn to write, read, and conceive the quantities of
                 numbers, in addition to exploring their potential,
                 creativity, and interest in learning, with the use of
                 technologies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sayeed:2022:ACI,
  author =       "Aqsa Sayeed and Chaman Verma and Neerendra Kumar and
                 Neha Koul and Zolt{\'a}n Ill{\'e}s",
  title =        "Approaches and Challenges in {Internet of Robotic
                 Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "9",
  pages =        "265",
  day =          "14",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14090265",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 23 06:03:23 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/9/265",
  abstract =     "The Internet of robotic things (IoRT) is the
                 combination of different technologies including cloud
                 computing, robots, Internet of things (IoT), artificial
                 intelligence (AI), and machine learning (ML). IoRT
                 plays a major role in manufacturing, healthcare,
                 security, and transport. IoRT can speed up human
                 development by a very significant percentage. IoRT
                 allows robots to transmit and receive data to and from
                 other devices and users. In this paper, IoRT is
                 reviewed in terms of the related techniques,
                 architectures, and abilities. Consequently, the related
                 research challenges are presented. IoRT architectures
                 are vital in the design of robotic systems and robotic
                 things. The existing 3--7-tier IoRT architectures are
                 studied. Subsequently, a detailed IoRT architecture is
                 proposed. Robotic technologies provide the means to
                 increase the performance and capabilities of the user,
                 product, or process. However, robotic technologies are
                 vulnerable to attacks on data security. Trust-based and
                 encryption-based mechanisms can be used for secure
                 communication among robotic things. A security method
                 is recommended to provide a secure and trustworthy
                 data-sharing mechanism in IoRT. Significant security
                 challenges are also discussed. Several known attacks on
                 ad hoc networks are illustrated. Threat models ensure
                 integrity confidentiality and availability of the data.
                 In a network, trust models are used to boost a system's
                 security. Trust models and IoRT networks play a key
                 role in obtaining a steady and nonvulnerable
                 configuration in the network. In IoRT, remote server
                 access results in remote software updates of robotic
                 things. To study navigation strategies, navigation
                 using fuzzy logic, probabilistic roadmap algorithms,
                 laser scan matching algorithms, heuristic functions,
                 bumper events, and vision-based navigation techniques
                 are considered. Using the given research challenges,
                 future researchers can get contemporary ideas of IoRT
                 implementation in the real world.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gentile:2022:VPA,
  author =       "Antonio Francesco Gentile and Davide Macr{\`\i} and
                 Floriano {De Rango} and Mauro Tropea and Emilio Greco",
  title =        "A {VPN} Performances Analysis of Constrained Hardware
                 Open Source Infrastructure Deploy in {IoT}
                 Environment",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "9",
  pages =        "264",
  day =          "13",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14090264",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 23 06:03:23 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/9/264",
  abstract =     "Virtual private network (VPN) represents an HW/SW
                 infrastructure that implements private and confidential
                 communication channels that usually travel through the
                 Internet. VPN is currently one of the most reliable
                 technologies to achieve this goal, also because being a
                 consolidated technology, it is possible to apply
                 appropriate patches to remedy any security holes. In
                 this paper we analyze the performances of open source
                 firmware OpenWrt 21.x compared with a server-side
                 operating system (Debian 11 x64) and Mikrotik 7.x, also
                 virtualized, and different types of clients (Windows
                 10/11, iOS 15, Android 11, OpenWrt 21.x, Debian 11 x64
                 and Mikrotik 7.x), observing the performance of the
                 network according to the current implementation of the
                 various protocols and algorithms of VPN tunnel examined
                 on what are the most recent HW and SW for deployment in
                 outdoor locations with poor network connectivity.
                 Specifically, operating systems provide different
                 performance metric values for various combinations of
                 configuration variables. The first pursued goal is to
                 find the algorithms to guarantee a data
                 transmission/encryption ratio as efficiently as
                 possible. The second goal is to research the algorithms
                 capable of guaranteeing the widest spectrum of
                 compatibility with the current infrastructures that
                 support VPN technology, to obtain a connection system
                 secure for geographically scattered IoT networks spread
                 over difficult-to-manage areas such as suburban or
                 rural environments. The third goal is to be able to use
                 open firmware on constrained routers that provide
                 compatibility with different VPN protocols.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Astaneh:2022:TOB,
  author =       "Saeed A. Astaneh and Shahram Shah Heydari and Sara
                 Taghavi Motlagh and Alireza Izaddoost",
  title =        "Trade-offs between Risk and Operational Cost in {SDN}
                 Failure Recovery Plan",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "9",
  pages =        "263",
  day =          "13",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14090263",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 23 06:03:23 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/9/263",
  abstract =     "We consider the problem of SDN flow optimization in
                 the presence of a dynamic probabilistic link failures
                 model. We introduce a metric for path risk, which can
                 change dynamically as network conditions and failure
                 probabilities change. As these probabilities change,
                 the end-to-end path survivability probability may drop,
                 i.e., its risk may rise. The main objective is to
                 reroute at-risk end-to-end flows with the minimum
                 number of flow operation so that a fast flow recovery
                 is guaranteed. We provide various formulations for
                 optimizing network risk versus operational costs and
                 examine the trade-offs in flow recovery and the
                 connections between operational cost, path risk, and
                 path survival probability. We present our suboptimal
                 dynamic flow restoration methods and evaluate their
                 effectiveness against the Lagrangian relaxation
                 approach. Our results show a significant improvement in
                 operational cost against a shortest-path approach.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fabre:2022:RAC,
  author =       "Renaud Fabre and Otmane Azeroual and Patrice Bellot
                 and Joachim Sch{\"o}pfel and Daniel Egret",
  title =        "Retrieving Adversarial Cliques in Cognitive
                 Communities: a New Conceptual Framework for Scientific
                 Knowledge Graphs",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "9",
  pages =        "262",
  day =          "07",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14090262",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 23 06:03:23 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/9/262",
  abstract =     "The variety and diversity of published content are
                 currently expanding in all fields of scholarly
                 communication. Yet, scientific knowledge graphs (SKG)
                 provide only poor images of the varied directions of
                 alternative scientific choices, and in particular
                 scientific controversies, which are not currently
                 identified and interpreted. We propose to use the rich
                 variety of knowledge present in search histories to
                 represent cliques modeling the main interpretable
                 practices of information retrieval issued from the same
                 ``cognitive community'', identified by their use of
                 keywords and by the search experience of the users
                 sharing the same research question. Modeling typical
                 cliques belonging to the same cognitive community is
                 achieved through a new conceptual framework, based on
                 user profiles, namely a bipartite geometric scientific
                 knowledge graph, SKG GRAPHYP. Further studies of
                 interpretation will test differences of documentary
                 profiles and their meaning in various possible contexts
                 which studies on ``disagreements in scientific
                 literature'' have outlined. This final adjusted version
                 of GRAPHYP optimizes the modeling of ``Manifold
                 Subnetworks of Cliques in Cognitive Communities''
                 (MSCCC), captured from previous user experience in the
                 same search domain. Cliques are built from graph grids
                 of three parameters outlining the manifold of search
                 experiences: mass of users; intensity of uses of items;
                 and attention, identified as a ratio of ``feature
                 augmentation'' by literature on information retrieval,
                 its mean value allows calculation of an observed
                 ``steady'' value of the user/item ratio or, conversely,
                 a documentary behavior ``deviating'' from this mean
                 value. An illustration of our approach is supplied in a
                 positive first test, which stimulates further work on
                 modeling subnetworks of users in search experience,
                 that could help identify the varied alternative
                 documentary sources of information retrieval, and in
                 particular the scientific controversies and scholarly
                 disputes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yang:2022:FIB,
  author =       "Jie Yang and Jiajia Zhu and Ziyu Pan",
  title =        "A Fairness Index Based on Rate Variance for Downlink
                 Non-Orthogonal Multiple Access System",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "9",
  pages =        "261",
  day =          "31",
  month =        aug,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14090261",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 23 06:03:23 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/9/261",
  abstract =     "Aiming at the resource allocation problem of a
                 non-orthogonal multiple access (NOMA) system, a
                 fairness index based on sample variance of users'
                 transmission rates is proposed, which has a fixed range
                 and high sensitivity. Based on the proposed fairness
                 index, the fairness-constrained power allocation
                 problem in NOMA system is studied; the problem is
                 decoupled into the intra cluster power allocation
                 problem and the inter cluster power allocation problem.
                 The nonconvex optimization problem is solved by the
                 continuous convex approximation (SCA) method, and an
                 intra and inter cluster power iterative allocation
                 algorithm with fairness constrained is proposed to
                 maximize the total throughput. Simulation results show
                 that the proposed algorithm can take into account intra
                 cluster, inter cluster, and system fairness, and
                 maximize the system throughput on the premise of
                 fairness.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Maslej-Kresnakova:2022:UDA,
  author =       "Viera Maslej-Kresn{\'a}kov{\'a} and Martin
                 Sarnovsk{\'y} and J{\'u}lia Jackov{\'a}",
  title =        "Use of Data Augmentation Techniques in Detection of
                 Antisocial Behavior Using Deep Learning Methods",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "9",
  pages =        "260",
  day =          "31",
  month =        aug,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14090260",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 23 06:03:23 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/9/260",
  abstract =     "The work presented in this paper focuses on the use of
                 data augmentation techniques applied in the domain of
                 the detection of antisocial behavior. Data augmentation
                 is a frequently used approach to overcome issues
                 related to the lack of data or problems related to
                 imbalanced classes. Such techniques are used to
                 generate artificial data samples used to improve the
                 volume of the training set or to balance the target
                 distribution. In the antisocial behavior detection
                 domain, we frequently face both issues, the lack of
                 quality labeled data as well as class imbalance. As the
                 majority of the data in this domain is textual, we must
                 consider augmentation methods suitable for NLP tasks.
                 Easy data augmentation (EDA) represents a group of such
                 methods utilizing simple text transformations to create
                 the new, artificial samples. Our main motivation is to
                 explore EDA techniques' usability on the selected tasks
                 from the antisocial behavior detection domain. We focus
                 on the class imbalance problem and apply EDA techniques
                 to two problems: fake news and toxic comments
                 classification. In both cases, we train the
                 convolutional neural networks classifier and compare
                 its performance on the original and EDA-extended
                 datasets. EDA techniques prove to be very
                 task-dependent, with certain limitations resulting from
                 the data they are applied on. The model's performance
                 on the extended toxic comments dataset did improve only
                 marginally, gaining only 0.01 improvement in the F1
                 metric when applying only a subset of EDA methods. EDA
                 techniques in this case were not suitable enough to
                 handle texts written in more informal language. On the
                 other hand, on the fake news dataset, the performance
                 was improved more significantly, boosting the F1 score
                 by 0.1. Improvement was most significant in the
                 prediction of the minor class, where F1 improved from
                 0.67 to 0.86.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Afrifa:2022:MML,
  author =       "Stephen Afrifa and Tao Zhang and Peter Appiahene and
                 Vijayakumar Varadarajan",
  title =        "Mathematical and Machine Learning Models for
                 Groundwater Level Changes: a Systematic Review and
                 Bibliographic Analysis",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "9",
  pages =        "259",
  day =          "30",
  month =        aug,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14090259",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 23 06:03:23 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/9/259",
  abstract =     "With the effects of climate change such as increasing
                 heat, higher rainfall, and more recurrent extreme
                 weather events including storms and floods, a unique
                 approach to studying the effects of climatic elements
                 on groundwater level variations is required. These
                 unique approaches will help people make better
                 decisions. Researchers and stakeholders can attain
                 these goals if they become familiar with current
                 machine learning and mathematical model approaches to
                 predicting groundwater level changes. However,
                 descriptions of machine learning and mathematical model
                 approaches for forecasting groundwater level changes
                 are lacking. This study picked 117 papers from the
                 Scopus scholarly database to address this knowledge
                 gap. In a systematic review, the publications were
                 examined using quantitative and qualitative approaches,
                 and the Preferred Reporting Items for Systematic
                 Reviews and Meta-Analyses (PRISMA) was chosen as the
                 reporting format. Machine learning and mathematical
                 model techniques have made significant contributions to
                 predicting groundwater level changes, according to the
                 study. However, the domain is skewed because machine
                 learning has been more popular in recent years, with
                 random forest (RF) methods dominating, followed by the
                 methods of support vector machine (SVM) and artificial
                 neural network (ANN). Machine learning ensembles have
                 also been found to help with aspects of computational
                 complexity, such as performance and training times.
                 Furthermore, compared to mathematical model techniques,
                 machine learning approaches achieve higher accuracies,
                 according to our research. As a result, it is advised
                 that academics employ new machine learning techniques
                 while also considering mathematical model approaches to
                 predicting groundwater level changes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhu:2022:FER,
  author =       "Hongtao Zhu and Huahu Xu and Xiaojin Ma and Minjie
                 Bian",
  title =        "Facial Expression Recognition Using Dual Path Feature
                 Fusion and Stacked Attention",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "9",
  pages =        "258",
  day =          "30",
  month =        aug,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14090258",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 23 06:03:23 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/9/258",
  abstract =     "Facial Expression Recognition (FER) can achieve an
                 understanding of the emotional changes of a specific
                 target group. The relatively small dataset related to
                 facial expression recognition and the lack of a high
                 accuracy of expression recognition are both a challenge
                 for researchers. In recent years, with the rapid
                 development of computer technology, especially the
                 great progress of deep learning, more and more
                 convolutional neural networks have been developed for
                 FER research. Most of the convolutional neural
                 performances are not good enough when dealing with the
                 problems of overfitting from too-small datasets and
                 noise, due to expression-independent intra-class
                 differences. In this paper, we propose a Dual Path
                 Stacked Attention Network (DPSAN) to better cope with
                 the above challenges. Firstly, the features of key
                 regions in faces are extracted using segmentation, and
                 irrelevant regions are ignored, which effectively
                 suppresses intra-class differences. Secondly, by
                 providing the global image and segmented local image
                 regions as training data for the integrated dual path
                 model, the overfitting problem of the deep network due
                 to a lack of data can be effectively mitigated.
                 Finally, this paper also designs a stacked attention
                 module to weight the fused feature maps according to
                 the importance of each part for expression recognition.
                 For the cropping scheme, this paper chooses to adopt a
                 cropping method based on the fixed four regions of the
                 face image, to segment out the key image regions and to
                 ignore the irrelevant regions, so as to improve the
                 efficiency of the algorithm computation. The
                 experimental results on the public datasets, CK+ and
                 FERPLUS, demonstrate the effectiveness of DPSAN, and
                 its accuracy reaches the level of current
                 state-of-the-art methods on both CK+ and FERPLUS, with
                 93.2\% and 87.63\% accuracy on the CK+ dataset and
                 FERPLUS dataset, respectively.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Pokhrel:2022:GTR,
  author =       "Shiva Raj Pokhrel and Carey Williamson",
  title =        "A Game-Theoretic Rent-Seeking Framework for Improving
                 Multipath {TCP} Performance",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "9",
  pages =        "257",
  day =          "29",
  month =        aug,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14090257",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 23 06:03:23 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/9/257",
  abstract =     "There is no well-defined utility function for existing
                 multipath TCP algorithms. Therefore, network utility
                 maximization (NUM) for MPTCP is a complex undertaking.
                 To resolve this, we develop a novel condition under
                 which Kelly's NUM mechanism may be used to explicitly
                 compute the equilibrium. We accomplish this by defining
                 a new utility function for MPTCP by employing Tullock's
                 rent-seeking paradigm from game theory. We investigate
                 the convergence of no-regret learning in the underlying
                 network games with continuous actions. Based on our
                 understanding of the design space, we propose an
                 original MPTCP algorithm that generalizes existing
                 algorithms and strikes a good balance among the
                 important properties. We implemented this algorithm in
                 the Linux kernel, and we evaluated its performance
                 experimentally.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sultana:2022:IRS,
  author =       "Ajmery Sultana and Xavier Fernando",
  title =        "Intelligent Reflecting Surface-Aided Device-to-Device
                 Communication: a Deep Reinforcement Learning Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "9",
  pages =        "256",
  day =          "29",
  month =        aug,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14090256",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 23 06:03:23 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/9/256",
  abstract =     "Recently, the growing demand of various emerging
                 applications in the realms of sixth-generation (6G)
                 wireless networks has made the term internet of Things
                 (IoT) very popular. Device-to-device (D2D)
                 communication has emerged as one of the significant
                 enablers for the 6G-based IoT network. Recently, the
                 intelligent reflecting surface (IRS) has been
                 considered as a hardware-efficient innovative scheme
                 for future wireless networks due to its ability to
                 mitigate propagation-induced impairments and to realize
                 a smart radio environment. Such an IRS-assisted D2D
                 underlay cellular network is investigated in this
                 paper. Our aim is to maximize the network's spectrum
                 efficiency (SE) by jointly optimizing the transmit
                 power of both the cellular users (CUs) and the D2D
                 pairs, the resource reuse indicators, and the IRS
                 reflection coefficients. Instead of using traditional
                 optimization solution schemes to solve this mixed
                 integer nonlinear optimization problem, a reinforcement
                 learning (RL) approach is used in this paper. The
                 IRS-assisted D2D communication network is structured by
                 the Markov Decision Process (MDP) in the RL framework.
                 First, a Q-learning-based solution is studied. Then, to
                 make a scalable solution with large dimension state and
                 action spaces, a deep Q-learning-based solution scheme
                 using experience replay is proposed. Lastly, an
                 actor-critic framework based on the deep deterministic
                 policy gradient (DDPG) scheme is proposed to learn the
                 optimal policy of the constructed optimization problem
                 considering continuous-valued state and action spaces.
                 Simulation outcomes reveal that the proposed RL-based
                 solution schemes can provide significant SE
                 enhancements compared to the existing optimization
                 schemes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Venkatraman:2022:SCT,
  author =       "Sitalakshmi Venkatraman and Fahri Benli and Ye Wei and
                 Fiona Wahr",
  title =        "Smart Classroom Teaching Strategy to Enhance Higher
                 Order Thinking Skills ({HOTS}) --- an Agile Approach
                 for {Education 4.0}",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "9",
  pages =        "255",
  day =          "28",
  month =        aug,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14090255",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 23 06:03:23 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/9/255",
  abstract =     "The development of Industry 4.0 revolutionising the
                 concept of automation and digitisation in an
                 organisation poses a huge challenge in employee
                 knowledge and skills to cope with the huge leap from
                 Industry 3.0. The high-level digitisation of an
                 organisation requires the workforce to possess higher
                 order thinking skills (HOTS) for the changing job roles
                 matching the rapid technological advancements. The
                 Education 4.0 framework is aimed at supporting the
                 Industry 4.0 skills requirement not only in digital
                 technologies but more towards soft skill development
                 such as collaboration and lifelong learning. However,
                 the education sector is also facing challenges in its
                 transition from Education 3.0 to Education 4.0. The
                 main purpose of the paper is to propose an Agile
                 approach for developing smart classroom teaching
                 strategies that foster employee adaptability with the
                 new learning paradigm of upskilling in line with
                 Industry 4.0. By adopting an exploratory research
                 methodology, the pilot study investigates the
                 implementation of the proposed Agile approach in a
                 higher education setting for graduates to achieve HOTS
                 using smart classroom teaching strategies. This study
                 uses learning theories such as experiential learning in
                 smart classroom environments to enhance students' HOTS
                 individually as well as collaboratively in an Agile
                 iterative manner. This is the first empirical study
                 carried out for graduates specialising in the Business
                 Analytics skillset required for Industry 4.0. The
                 findings of the pilot study show promising results that
                 pave the way for further exploration and pedagogical
                 insights in this research direction.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Pilania:2022:FVS,
  author =       "Urmila Pilania and Rohit Tanwar and Mazdak Zamani and
                 Azizah Abdul Manaf",
  title =        "Framework for Video Steganography Using Integer
                 Wavelet Transform and {JPEG} Compression",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "9",
  pages =        "254",
  day =          "25",
  month =        aug,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14090254",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 23 06:03:23 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/9/254",
  abstract =     "In today's world of computers everyone is
                 communicating their personal information through the
                 web. So, the security of personal information is the
                 main concern from the research point of view.
                 Steganography can be used for the security purpose of
                 personal information. Storing and forwarding of
                 embedded personal information specifically in public
                 places is gaining more attention day by day. In this
                 research work, the Integer Wavelet Transform technique
                 along with JPEG (Joint Photograph Expert Group)
                 compression is proposed to overcome some of the issues
                 associated with steganography techniques. Video cover
                 files and JPEG compression improve concealing capacity
                 because of their intrinsic properties. Integer Wavelet
                 Transform is used to improve the imperceptibility and
                 robustness of the proposed technique. The
                 Imperceptibility of the proposed work is analyzed
                 through evaluation parameters such as PSNR (Peak Signal
                 to Noise Ratio), MSE (Mean Square Error), SSIM
                 (Structure Similarity Metric), and CC (Correlation
                 Coefficient). Robustness is validated through some
                 image processing attacks. Complexity is calculated in
                 terms of concealing and retrieval time along with the
                 amount of secret information hidden.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sharma:2022:TSI,
  author =       "Purushottam Sharma and Devesh Tulsian and Chaman Verma
                 and Pratibha Sharma and Nancy Nancy",
  title =        "Translating Speech to {Indian} Sign Language Using
                 Natural Language Processing",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "9",
  pages =        "253",
  day =          "25",
  month =        aug,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14090253",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 23 06:03:23 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/9/253",
  abstract =     "Language plays a vital role in the communication of
                 ideas, thoughts, and information to others.
                 Hearing-impaired people also understand our thoughts
                 using a language known as sign language. Every country
                 has a different sign language which is based on their
                 native language. In our research paper, our major focus
                 is on Indian Sign Language, which is mostly used by
                 hearing- and speaking-impaired communities in India.
                 While communicating our thoughts and views with others,
                 one of the most essential factors is listening. What if
                 the other party is not able to hear or grasp what you
                 are talking about? This situation is faced by nearly
                 every hearing-impaired person in our society. This led
                 to the idea of introducing an audio to Indian Sign
                 Language translation system which can erase this gap in
                 communication between hearing-impaired people and
                 society. The system accepts audio and text as input and
                 matches it with the videos present in the database
                 created by the authors. If matched, it shows
                 corresponding sign movements based on the grammar rules
                 of Indian Sign Language as output; if not, it then goes
                 through the processes of tokenization and
                 lemmatization. The heart of the system is natural
                 language processing which equips the system with
                 tokenization, parsing, lemmatization, and
                 part-of-speech tagging.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Akter:2022:FRF,
  author =       "Mst. Shapna Akter and Hossain Shahriar and Reaz
                 Chowdhury and M. R. C. Mahdy",
  title =        "Forecasting the Risk Factor of Frontier Markets: a
                 Novel Stacking Ensemble of Neural Network Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "9",
  pages =        "252",
  day =          "25",
  month =        aug,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14090252",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 23 06:03:23 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/9/252",
  abstract =     "Forecasting the risk factor of the financial frontier
                 markets has always been a very challenging task. Unlike
                 an emerging market, a frontier market has a missing
                 parameter named ``volatility'', which indicates the
                 market's risk and as a result of the absence of this
                 missing parameter and the lack of proper prediction, it
                 has almost become difficult for direct customers to
                 invest money in frontier markets. However, the noises,
                 seasonality, random spikes and trends of the
                 time-series datasets make it even more complicated to
                 predict stock prices with high accuracy. In this work,
                 we have developed a novel stacking ensemble of the
                 neural network model that performs best on multiple
                 data patterns. We have compared our model's performance
                 with the performance results obtained by using some
                 traditional machine learning ensemble models such as
                 Random Forest, AdaBoost, Gradient Boosting Machine and
                 Stacking Ensemble, along with some traditional deep
                 learning models such as Convolutional Neural Network
                 (CNN), Long Short-Term Memory (LSTM) and Bidirectional
                 Long Short-Term (BiLSTM). We have calculated the
                 missing parameter named ``volatility'' using stock
                 price (Close price) for 20 different companies of the
                 frontier market and then made predictions using the
                 aforementioned machine learning ensemble models, deep
                 learning models and our proposed stacking ensemble of
                 the neural network model. The statistical evaluation
                 metrics RMSE and MAE have been used to evaluate the
                 performance of the models. It has been found that our
                 proposed stacking ensemble neural network model
                 outperforms all other traditional machine learning and
                 deep learning models which have been used for
                 comparison in this paper. The lowest RMSE and MAE
                 values we have received using our proposed model are
                 0.3626 and 0.3682 percent, respectively, and the
                 highest RMSE and MAE values are 2.5696 and 2.444
                 percent, respectively. The traditional ensemble
                 learning models give the highest RMSE and MAE error
                 rate of 20.4852 and 20.4260 percent, while the deep
                 learning models give 15.2332 and 15.1668 percent,
                 respectively, which clearly states that our proposed
                 model provides a very low error value compared with the
                 traditional models.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fior:2022:LEA,
  author =       "Jacopo Fior and Luca Cagliero and Paolo Garza",
  title =        "Leveraging Explainable {AI} to Support Cryptocurrency
                 Investors",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "9",
  pages =        "251",
  day =          "24",
  month =        aug,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14090251",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 23 06:03:23 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/9/251",
  abstract =     "In the last decade, cryptocurrency trading has
                 attracted the attention of private and professional
                 traders and investors. To forecast the financial
                 markets, algorithmic trading systems based on
                 Artificial Intelligence (AI) models are becoming more
                 and more established. However, they suffer from the
                 lack of transparency, thus hindering domain experts
                 from directly monitoring the fundamentals behind market
                 movements. This is particularly critical for
                 cryptocurrency investors, because the study of the main
                 factors influencing cryptocurrency prices, including
                 the characteristics of the blockchain infrastructure,
                 is crucial for driving experts' decisions. This paper
                 proposes a new visual analytics tool to support domain
                 experts in the explanation of AI-based cryptocurrency
                 trading systems. To describe the rationale behind AI
                 models, it exploits an established method, namely
                 SHapley Additive exPlanations, which allows experts to
                 identify the most discriminating features and provides
                 them with an interactive and easy-to-use graphical
                 interface. The simulations carried out on 21
                 cryptocurrencies over a 8-year period demonstrate the
                 usability of the proposed tool.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chaganti:2022:BBC,
  author =       "Rajasekhar Chaganti and Vijayakumar Varadarajan and
                 Venkata Subbarao Gorantla and Thippa Reddy Gadekallu
                 and Vinayakumar Ravi",
  title =        "Blockchain-Based Cloud-Enabled Security Monitoring
                 Using {Internet} of Things in Smart Agriculture",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "9",
  pages =        "250",
  day =          "24",
  month =        aug,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14090250",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 23 06:03:23 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/9/250",
  abstract =     "The Internet of Things (IoT) has rapidly progressed in
                 recent years and immensely influenced many industries
                 in how they operate. Consequently, IoT technology has
                 improved productivity in many sectors, and smart
                 farming has also hugely benefited from the IoT. Smart
                 farming enables precision agriculture, high crop yield,
                 and the efficient utilization of natural resources to
                 sustain for a longer time. Smart farming includes
                 sensing capabilities, communication technologies to
                 transmit the collected data from the sensors, and data
                 analytics to extract meaningful information from the
                 collected data. These modules will enable farmers to
                 make intelligent decisions and gain profits. However,
                 incorporating new technologies includes inheriting
                 security and privacy consequences if they are not
                 implemented in a secure manner, and smart farming is
                 not an exception. Therefore, security monitoring is an
                 essential component to be implemented for smart
                 farming. In this paper, we propose a cloud-enabled
                 smart-farm security monitoring framework to monitor
                 device status and sensor anomalies effectively and
                 mitigate security attacks using behavioral patterns.
                 Additionally, a blockchain-based smart-contract
                 application was implemented to securely store
                 security-anomaly information and proactively mitigate
                 similar attacks targeting other farms in the community.
                 We implemented the security-monitoring-framework
                 prototype for smart farms using Arduino Sensor Kit,
                 ESP32, AWS cloud, and the smart contract on the
                 Ethereum Rinkeby Test Network and evaluated network
                 latency to monitor and respond to security events. The
                 performance evaluation of the proposed framework showed
                 that our solution could detect security anomalies
                 within real-time processing time and update the other
                 farm nodes to be aware of the situation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Vgena:2022:DRS,
  author =       "Katerina Vgena and Angeliki Kitsiou and Christos
                 Kalloniatis and Stefanos Gritzalis",
  title =        "Determining the Role of Social Identity Attributes to
                 the Protection of Users' Privacy in Social Media",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "9",
  pages =        "249",
  day =          "24",
  month =        aug,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14090249",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 23 06:03:23 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/9/249",
  abstract =     "Drawing on digital identity theories, social software
                 engineering theory (SSE), and the Privacy Safeguard
                 (PriS) methodology, we examined the way that personal
                 information uploaded on social media (SM) imposes
                 privacy issues. Throughout a review on users'
                 self-representation on SM, we examined the impact of
                 self-determination and self-disclosure on users'
                 privacy, and we identified the social attributes (SA)
                 that cause privacy implications. This paper specifies
                 18 SA that users employ to achieve their optimal level
                 of representation while summarizing possible ways that
                 these attributes provoke users' identification. In
                 particular, our research has shown that SM users
                 represent their personas by unveiling SA to construct
                 popular, representative, and conversational profiles.
                 As disclosing SA increases privacy implications, we
                 intend to help users build profiles that respect their
                 privacy. Examining users' SA deepens our understanding
                 of disclosing personal information on SM while leading
                 to a better quantification of identity attributes;
                 furthermore, users' top five most revealing attributes
                 were summarized. Considering that SSE addresses users'
                 privacy implications from an early stage of systems
                 designing, our research, identifying the SA, will be
                 helpful in addressing privacy from a socio-technical
                 aspect, aiming at bridging the socio-technical gap by
                 drawing designers' attention to users' social
                 aspects.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Orlova:2022:DTA,
  author =       "Ekaterina V. Orlova",
  title =        "Design Technology and {AI}-Based Decision Making Model
                 for Digital Twin Engineering",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "9",
  pages =        "248",
  day =          "24",
  month =        aug,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14090248",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 23 06:03:23 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/9/248",
  abstract =     "This research considers the problem of digital twin
                 engineering in organizational and technical systems.
                 The theoretical and methodological basis is a
                 fundamental scientific work in the field of digital
                 twins engineering and applied models. We use methods of
                 a system approach, statistical analysis, operational
                 research and artificial intelligence. The study
                 proposes a comprehensive technology (methodological
                 approach) for digital twin design in order to
                 accelerate its engineering. This technology consists of
                 design steps, methods and models, and provides systems
                 synthesis of digital twins for a complex system (object
                 or process) operating under uncertainty and that is
                 able to reconfigure in response to internal faults or
                 environment changes and perform preventive maintenance.
                 In the technology structure, we develop a simulation
                 model using situational ``what-if'' analysis and based
                 on fuzzy logic methods. We apply this technology to
                 develop the digital twin prototype for a device at the
                 creation life cycle stage in order to reduce the
                 consequences of unpredicted and undesirable states. We
                 study possible unforeseen problems and device faults
                 during its further operation. The model identifies a
                 situation as a combination of failure factors of the
                 internal and external environment and provides an
                 appropriate decision about actions with the device. The
                 practical significance of the research is the developed
                 decision support model, which is the basis for control
                 systems to solve problems related to monitoring the
                 current state of technical devices (instruments,
                 equipment) and to support adequate decisions to
                 eliminate their dysfunctions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Islam:2022:NML,
  author =       "Mohammad S. Islam and Shahid Husain and Jawed Mustafa
                 and Yuantong Gu",
  title =        "A Novel Machine Learning Prediction Model for Aerosol
                 Transport in Upper 17-Generations of the Human
                 Respiratory Tract",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "9",
  pages =        "247",
  day =          "24",
  month =        aug,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14090247",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 23 06:03:23 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/9/247",
  abstract =     "The main challenge of the health risk assessment of
                 the aerosol transport and deposition to the lower
                 airways is the high computational cost. A standard
                 large-scale airway model needs a week to a month of
                 computational time in a high-performance computing
                 system. Therefore, developing an innovative tool that
                 accurately predicts transport behaviour and reduces
                 computational time is essential. This study aims to
                 develop a novel and innovative machine learning (ML)
                 model to predict particle deposition to the lower
                 airways. The first-ever study uses ML techniques to
                 explore the pulmonary aerosol TD in a digital
                 17-generation airway model. The ML model uses the
                 computational data for a 17-generation airway model and
                 four standard ML regression models are used to save the
                 computational cost. Random forest (RF), k -nearest
                 neighbour ( k -NN), multi-layer perceptron (MLP) and
                 Gaussian process regression (GPR) techniques are used
                 to develop the ML models. The MLP regression model
                 displays more accurate estimates than other ML models.
                 Finally, a prediction model is developed, and the
                 results are significantly closer to the measured
                 values. The prediction model predicts the deposition
                 efficiency (DE) for different particle sizes and flow
                 rates. A comprehensive lobe-specific DE is also
                 predicted for various flow rates. This first-ever
                 aerosol transport prediction model can accurately
                 predict the DE in different regions of the airways in a
                 couple of minutes. This innovative approach and
                 accurate prediction will improve the literature and
                 knowledge of the field.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alam:2022:FLR,
  author =       "Tanweer Alam and Ruchi Gupta",
  title =        "Federated Learning and Its Role in the Privacy
                 Preservation of {IoT} Devices",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "9",
  pages =        "246",
  day =          "23",
  month =        aug,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14090246",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 23 06:03:23 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/9/246",
  abstract =     "Federated learning (FL) is a cutting-edge artificial
                 intelligence approach. It is a decentralized
                 problem-solving technique that allows users to train
                 using massive data. Unprocessed information is stored
                 in advanced technology by a secret confidentiality
                 service, which incorporates machine learning (ML)
                 training while removing data connections. As
                 researchers in the field promote ML configurations
                 containing a large amount of private data, systems and
                 infrastructure must be developed to improve the
                 effectiveness of advanced learning systems. This study
                 examines FL in-depth, focusing on application and
                 system platforms, mechanisms, real-world applications,
                 and process contexts. FL creates robust classifiers
                 without requiring information disclosure, resulting in
                 highly secure privacy policies and access control
                 privileges. The article begins with an overview of FL.
                 Then, we examine technical data in FL, enabling
                 innovation, contracts, and software. Compared with
                 other review articles, our goal is to provide a more
                 comprehensive explanation of the best procedure systems
                 and authentic FL software to enable scientists to
                 create the best privacy preservation solutions for IoT
                 devices. We also provide an overview of similar
                 scientific papers and a detailed analysis of the
                 significant difficulties encountered in recent
                 publications. Furthermore, we investigate the benefits
                 and drawbacks of FL and highlight comprehensive
                 distribution scenarios to demonstrate how specific FL
                 models could be implemented to achieve the desired
                 results.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Dong:2022:AIA,
  author =       "Jingwen Dong and Siti Nurulain Mohd Rum and Khairul
                 Azhar Kasmiran and Teh Noranis Mohd Aris and Raihani
                 Mohamed",
  title =        "Artificial Intelligence in Adaptive and Intelligent
                 Educational System: a Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "9",
  pages =        "245",
  day =          "23",
  month =        aug,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14090245",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Sep 23 06:03:23 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/9/245",
  abstract =     "There has been much discussion among academics on how
                 pupils may be taught online while yet maintaining a
                 high degree of learning efficiency, in part because of
                 the worldwide COVID-19 pandemic in the previous two
                 years. Students may have trouble focusing due to a lack
                 of teacher--student interaction, yet online learning
                 has some advantages that are unavailable in traditional
                 classrooms. The architecture of online courses for
                 students is integrated into a system called the
                 Adaptive and Intelligent Education System (AIES). In
                 AIESs, reinforcement learning is often used in
                 conjunction with the development of teaching
                 strategies, and this reinforcement-learning-based
                 system is known as RLATES. As a prerequisite to
                 conducting research in this field, this paper
                 undertakes the consolidation and analysis of existing
                 research, design approaches, and model categories for
                 adaptive and intelligent educational systems, with the
                 hope of serving as a reference for scholars in the same
                 field to help them gain access to the relevant
                 information quickly and easily.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sagu:2022:HDL,
  author =       "Amit Sagu and Nasib Singh Gill and Preeti Gulia and
                 Jyotir Moy Chatterjee and Ishaani Priyadarshini",
  title =        "A Hybrid Deep Learning Model with Self-Improved
                 Optimization Algorithm for Detection of Security
                 Attacks in {IoT} Environment",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "301",
  day =          "19",
  month =        oct,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100301",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/301",
  abstract =     "With the growth of the Internet of Things (IoT),
                 security attacks are also rising gradually. Numerous
                 centralized mechanisms have been introduced in the
                 recent past for the detection of attacks in IoT, in
                 which an attack recognition scheme is employed at the
                 network's vital point, which gathers data from the
                 network and categorizes it as ``Attack'' or ``Normal''.
                 Nevertheless, these schemes were unsuccessful in
                 achieving noteworthy results due to the diverse
                 necessities of IoT devices such as distribution,
                 scalability, lower latency, and resource limits. The
                 present paper proposes a hybrid model for the detection
                 of attacks in an IoT environment that involves three
                 stages. Initially, the higher-order statistical
                 features (kurtosis, variance, moments), mutual
                 information (MI), symmetric uncertainty, information
                 gain ratio (IGR), and relief-based features are
                 extracted. Then, detection takes place using Gated
                 Recurrent Unit (GRU) and Bidirectional Long Short-Term
                 Memory (Bi-LSTM) to recognize the existence of network
                 attacks. For improving the classification accuracy, the
                 weights of Bi-LSTM are optimally tuned via a
                 self-upgraded Cat and Mouse Optimizer (SU-CMO). The
                 improvement of the employed scheme is established
                 concerning a variety of metrics using two distinct
                 datasets which comprise classification accuracy, and
                 index, f-measure and MCC. In terms of all performance
                 measures, the proposed model outperforms both
                 traditional and state-of-the-art techniques.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mojzis:2022:TRB,
  author =       "J{\'a}n Mojzis and Peter Krammer and Marcel Kvassay
                 and Lenka Skovajsov{\'a} and Ladislav Hluch{\'y}",
  title =        "Towards Reliable Baselines for Document-Level
                 Sentiment Analysis in the {Czech} and {Slovak}
                 Languages",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "300",
  day =          "19",
  month =        oct,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100300",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/300",
  abstract =     "This article helps establish reliable baselines for
                 document-level sentiment analysis in highly inflected
                 languages like Czech and Slovak. We revisit an earlier
                 study representing the first comprehensive formulation
                 of such baselines in Czech and show that some of its
                 reported results need to be significantly revised. More
                 specifically, we show that its online product review
                 dataset contained more than 18\% of non-trivial
                 duplicates, which incorrectly inflated its macro
                 F1-measure results by more than 19 percentage points.
                 We also establish that part-of-speech-related features
                 have no damaging effect on machine learning algorithms
                 (contrary to the claim made in the study) and
                 rehabilitate the Chi-squared metric for feature
                 selection as being on par with the best performing
                 metrics such as Information Gain. We demonstrate that
                 in feature selection experiments with Information Gain
                 and Chi-squared metrics, the top 10\% of ranked unigram
                 and bigram features suffice for the best results
                 regarding online product and movie reviews, while the
                 top 5\% of ranked unigram and bigram features are
                 optimal for the Facebook dataset. Finally, we reiterate
                 an important but often ignored warning by George Forman
                 and Martin Scholz that different possible ways of
                 averaging the F1-measure in cross-validation studies of
                 highly unbalanced datasets can lead to results
                 differing by more than 10 percentage points. This can
                 invalidate the comparisons of F1-measure results across
                 different studies if incompatible ways of averaging F1
                 are used.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Adou:2022:MAP,
  author =       "Yves Adou and Ekaterina Markova and Yuliya Gaidamaka",
  title =        "Modeling and Analyzing Preemption-Based Service
                 Prioritization in {5G} Networks Slicing Framework",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "299",
  day =          "18",
  month =        oct,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100299",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/299",
  abstract =     "The Network Slicing (NS) technology, recognized as one
                 of the key enabling features of Fifth Generation (5G)
                 wireless systems, provides very flexible ways to
                 efficiently accommodate common physical
                 infrastructures, e.g., Base Station (BS), multiple
                 logical networks referred to as Network Slice Instances
                 (NSIs). To ensure the required Quality of Service (QoS)
                 levels, the NS-technology relies on classical Resource
                 Reservation(RR) or Service Prioritization schemes.
                 Thus, the current paper aims to propose a
                 Preemption-based Prioritization (PP) scheme ``merging''
                 the classical RR and Service Prioritization schemes.
                 The proposed PP-scheme efficiency is evaluated or
                 estimated given a Queueing system (QS) model analyzing
                 the operation of multiple NSIs with various
                 requirements at common 5G BSs. As a key result, the
                 proposed PP-scheme can provide up to 100\% gain in
                 terms of blocking probabilities of arriving requests
                 with respect to some baseline.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Serrano:2022:UPC,
  author =       "Ronaldo Serrano and Ckristian Duran and Marco
                 Sarmiento and Tuan-Kiet Dang and Trong-Thuc Hoang and
                 Cong-Kha Pham",
  title =        "A Unified {PUF} and Crypto Core Exploiting the
                 Metastability in Latches",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "298",
  day =          "17",
  month =        oct,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100298",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/298",
  abstract =     "Hardware acceleration of cryptography algorithms
                 represents an emerging approach to obtain benefits in
                 terms of speed and side-channel resistance compared to
                 software implementations. In addition, a hardware
                 implementation can provide the possibility of unifying
                 the functionality with some secure primitive, for
                 example, a true random number generator (TRNG) or a
                 physical unclonable function (PUF). This paper presents
                 a unified PUF-ChaCha20 in a field-programmable
                 gate-array (FPGA) implementation. The problems and
                 solutions of the PUF implementation are described,
                 exploiting the metastability in latches. The Xilinx
                 Artix-7 XC7A100TCSG324-1 FPGA implementation occupies
                 2416 look-up tables (LUTs) and 1026 flips-flops (FFs),
                 reporting a 3.11\% area overhead. The PUF exhibits
                 values of 49.15\%, 47.52\%, and 99.25\% for the average
                 uniformity, uniqueness, and reliability, respectively.
                 Finally, ChaCha20 reports a speed of 0.343 cycles per
                 bit with the unified implementation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Meqdad:2022:IDO,
  author =       "Maytham N. Meqdad and Seifedine Kadry and Hafiz Tayyab
                 Rauf",
  title =        "Improved Dragonfly Optimization Algorithm for
                 Detecting {IoT} Outlier Sensors",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "297",
  day =          "17",
  month =        oct,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100297",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/297",
  abstract =     "Things receive digital intelligence by being connected
                 to the Internet and by adding sensors. With the use of
                 real-time data and this intelligence, things may
                 communicate with one another autonomously. The
                 environment surrounding us will become more intelligent
                 and reactive, merging the digital and physical worlds
                 thanks to the Internet of things (IoT). In this paper,
                 an optimal methodology has been proposed for
                 distinguishing outlier sensors of the Internet of
                 things based on a developed design of a dragonfly
                 optimization technique. Here, a modified structure of
                 the dragonfly optimization algorithm is utilized for
                 optimal area coverage and energy consumption reduction.
                 This paper uses four parameters to evaluate its
                 efficiency: the minimum number of nodes in the coverage
                 area, the lifetime of the network, including the time
                 interval from the start of the first node to the
                 shutdown time of the first node, and the network power.
                 The results of the suggested method are compared with
                 those of some other published methods. The results show
                 that by increasing the number of steps, the energy of
                 the live nodes will eventually run out and turn off. In
                 the LEACH method, after 350 steps, the RED-LEACH
                 method, after 750 steps, and the GSA-based method,
                 after 915 steps, the nodes start shutting down, which
                 occurs after 1227 steps for the proposed method. This
                 means that the nodes are turned off later. Simulations
                 indicate that the suggested method achieves better
                 results than the other examined techniques according to
                 the provided performance parameters.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chemrov:2022:SPC,
  author =       "Kirill Chemrov and Dmitry Bankov and Evgeny Khorov and
                 Andrey Lyakhov",
  title =        "Smart Preliminary Channel Access to Support Real-Time
                 Traffic in {Wi-Fi} Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "296",
  day =          "16",
  month =        oct,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100296",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/296",
  abstract =     "Real-time applications (RTA) are an important use case
                 for IEEE 802.11be, a new amendment to the Wi-Fi
                 standard. This amendment introduces new complicated
                 mechanisms to provide low delay and high reliability
                 for RTA, but many of them are not supported by legacy
                 devices that may be present in future Wi-Fi networks.
                 In contrast, the preliminary channel access (PCA)
                 method is designed to satisfy strict RTA requirements
                 even in the presence of legacy devices and does not
                 require significant changes to the Wi-Fi protocol.
                 However, it significantly reduces the capacity for
                 non-RTA traffic. This paper introduces a Smart PCA
                 method, which improves the performance of all the
                 stations in scenarios with multiple RTA stations.
                 Extensive simulation shows that the Smart PCA method
                 guarantees low delays for intensive RTA traffic in
                 these scenarios. Moreover, it doubles the network
                 capacity for the stations with non-RTA traffic.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Matviichuk:2022:SOI,
  author =       "Liudmyla Matviichuk and Stefano Ferilli and Nataliia
                 Hnedko",
  title =        "Study of the Organization and Implementation of
                 E-Learning in Wartime Inside {Ukraine}",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "295",
  day =          "15",
  month =        oct,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100295",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/295",
  abstract =     "The article provides a factual foundation for the
                 possibility of organizing and implementing e-learning
                 in Ukrainian higher educational institutions during the
                 war. The current research topicality is supported by
                 the urgent need for training experience, organization
                 and implementation during wartime because of the fact
                 that both the educational process and the opportunity
                 to obtain an education should not be halted. The
                 study's goal is to assess the current state of the
                 e-learning organization and implementation, as well as
                 to examine students' attitude towards the educational
                 process during wartime. Methods such as scientific
                 source analysis, generalization and systematization of
                 the e-learning experience and its practical application
                 were used to achieve the goal. Furthermore, empirical
                 methods such as interviewing and observation were used.
                 Questionnaires have been proposed as important research
                 tools for this purpose. Four structured groups for the
                 use of e-learning have been formed and identified based
                 on the findings. We created an e-learning organization
                 and support model based on them. Furthermore, we
                 identified ten poignant factors as the sources of
                 difficulties for teachers when implementing
                 innovations, with limited resources and a lack of time
                 being among the most significant.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alghamdi:2022:CST,
  author =       "Taghreed Alghamdi and Sifatul Mostafi and Ghadeer
                 Abdelkader and Khalid Elgazzar",
  title =        "A Comparative Study on Traffic Modeling Techniques for
                 Predicting and Simulating Traffic Behavior",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "294",
  day =          "15",
  month =        oct,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100294",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/294",
  abstract =     "The significant advancements in intelligent
                 transportation systems (ITS) have contributed to the
                 increased development in traffic modeling. These
                 advancements include prediction and simulation models
                 that are used to simulate and predict traffic behaviors
                 on highway roads and urban networks. These models are
                 capable of precise modeling of the current traffic
                 status and accurate predictions of the future status
                 based on varying traffic conditions. However, selecting
                 the appropriate traffic model for a specific
                 environmental setting is challenging and expensive due
                 to the different requirements that need to be
                 considered, such as accuracy, performance, and
                 efficiency. In this research, we present a
                 comprehensive literature review of the research related
                 to traffic prediction and simulation models. We start
                 by highlighting the challenges in the long-term and
                 short-term prediction of traffic modeling. Then, we
                 review the most common nonparametric prediction models.
                 Lastly, we look into the existing literature on traffic
                 simulation tools and traffic simulation algorithms. We
                 summarize the available traffic models, define the
                 required parameters, and discuss the limitations of
                 each model. We hope that this survey serves as a useful
                 resource for traffic management engineers, researchers,
                 and practitioners in this domain.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mozaffariahrar:2022:SWF,
  author =       "Erfan Mozaffariahrar and Fabrice Theoleyre and Michael
                 Menth",
  title =        "A Survey of {Wi-Fi} 6: Technologies, Advances, and
                 Challenges",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "293",
  day =          "14",
  month =        oct,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100293",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/293",
  abstract =     "Wi-Fi is a popular wireless technology and is
                 continuously extended to keep pace with requirements
                 such as high throughput, real-time communication, dense
                 networks, or resource and energy efficiency. The IEEE
                 802.11ax standard, also known as Wi-Fi 6, promises to
                 provide data rates of up to almost 10 Gb/s, lower
                 energy consumption, and higher reliability. Its
                 capabilities go far beyond Wi-Fi 5 (802.11ac) and novel
                 technical concepts have been introduced for this
                 purpose. As such, the Wi-Fi 6 standard includes
                 Multi-User Orthogonal Frequency Division Multiple
                 Access (MU OFDMA), Multi-User Multiple-Input
                 Multiple-Output (MU MIMO), new mechanisms for Spatial
                 Reuse (SR), new mechanisms for power saving,
                 higher-order modulation, and additional minor
                 improvements. In this paper, we provide a survey of
                 Wi-Fi 6. Initially, we provide a compact technological
                 summary of Wi-Fi 5 and its predecessors. Then, we
                 discuss the potential application domains of Wi-Fi 6,
                 which are enabled through its novel features.
                 Subsequently, we explain these features and review the
                 related works in these areas. Finally, performance
                 evaluation tools for Wi-Fi 6 and future roadmaps are
                 discussed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alberro:2022:ERP,
  author =       "Leonardo Alberro and Felipe Vel{\'a}zquez and Sara
                 Azpiroz and Eduardo Grampin and Mat{\'\i}as Richart",
  title =        "Experimenting with Routing Protocols in the Data
                 Center: an ns-3 Simulation Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "292",
  day =          "14",
  month =        oct,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100292",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/292",
  abstract =     "Massive scale data centers (MSDC) have become a key
                 component of current content-centric Internet
                 architecture. With scales of up to hundreds of
                 thousands servers, conveying traffic inside these
                 infrastructures requires much greater connectivity
                 resources than traditional broadband Internet transit
                 networks. MSDCs use Fat-Tree type topologies, which
                 ensure multipath connectivity and constant bisection
                 bandwidth between servers. To properly use the
                 potential advantages of these topologies, specific
                 routing protocols are needed, with multipath support
                 and low control messaging load. These infrastructures
                 are enormously expensive, and therefore it is not
                 possible to use them to experiment with new protocols;
                 that is why scalable and realistic emulation/simulation
                 environments are needed. Based on previous experiences,
                 in this paper we present extensions to the ns-3 network
                 simulator that allow executing the Free Range Routing
                 (FRR) protocol suite, which support some of the
                 specific MSDC routing protocols. Focused on the Border
                 Gateway Protocol (BGP), we run a comprehensive set of
                 control plane experiments over Fat-Tree topologies,
                 achieving competitive scalability running on a
                 single-host environment, which demonstrates that the
                 modified ns-3 simulator can be effectively used for
                 experimenting in the MSDC. Moreover, the validation was
                 complemented with a theoretical analysis of BGP
                 behavior over selected scenarios. The whole project is
                 available to the community and fully reproducible.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Claus:2022:NLP,
  author =       "Stefan Claus and Massimo Stella",
  title =        "Natural Language Processing and Cognitive Networks
                 Identify {UK} Insurers' Trends in Investor Day
                 Transcripts",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "291",
  day =          "12",
  month =        oct,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100291",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/291",
  abstract =     "The ability to spot key ideas, trends, and
                 relationships between them in documents is key to
                 financial services, such as banks and insurers.
                 Identifying patterns across vast amounts of
                 domain-specific reports is crucial for devising
                 efficient and targeted supervisory plans, subsequently
                 allocating limited resources where most needed. Today,
                 insurance supervisory planning primarily relies on
                 quantitative metrics based on numerical data (e.g.,
                 solvency financial returns). The purpose of this work
                 is to assess whether Natural Language Processing (NLP)
                 and cognitive networks can highlight events and
                 relationships of relevance for regulators that
                 supervise the insurance market, replacing human coding
                 of information with automatic text analysis. To this
                 aim, this work introduces a dataset of NIDT=829
                 investor transcripts from Bloomberg and explores/tunes
                 3 NLP techniques: (1) keyword extraction enhanced by
                 cognitive network analysis; (2) valence/sentiment
                 analysis; and (3) topic modelling. Results highlight
                 that keyword analysis, enriched by term
                 frequency-inverse document frequency scores and
                 semantic framing through cognitive networks, could
                 detect events of relevance for the insurance system
                 like cyber-attacks or the COVID-19 pandemic. Cognitive
                 networks were found to highlight events that related to
                 specific financial transitions: The semantic frame of
                 ``climate'' grew in size by +538\% between 2018 and
                 2020 and outlined an increased awareness that agents
                 and insurers expressed towards climate change. A
                 lexicon-based sentiment analysis achieved a Pearson's
                 correlation of {\rho}=0.16 ( {p$<$0}.001,N=829 )
                 between sentiment levels and daily share prices.
                 Although relatively weak, this finding indicates that
                 insurance jargon is insightful to support risk
                 supervision. Topic modelling is considered less
                 amenable to support supervision, because of a lack of
                 results' stability and an intrinsic difficulty to
                 interpret risk patterns. We discuss how these automatic
                 methods could complement existing supervisory tools in
                 supporting effective oversight of the insurance
                 market.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2022:UPC,
  author =       "Gengxian Li and Chundong Wang and Huaibin Wang",
  title =        "Unreachable Peers Communication Scheme in
                 Decentralized Networks Based on Peer-to-Peer Overlay
                 Approaches",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "290",
  day =          "12",
  month =        oct,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100290",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/290",
  abstract =     "Decentralized networks bring us many benefits, but as
                 networks evolve, many nodes either actively or
                 passively become unreachable behind an NAT or a
                 firewall. This has become a hindrance to the
                 development of decentralized networks, where
                 peer-to-peer communication data transfer between
                 unreachable nodes cannot be accomplished, whether in
                 decentralized file systems, decentralized social, or
                 decentralized IoT. The existing scheme requires a
                 series of centralized servers or requires network-wide
                 flooding for consensus data, which can lead to the loss
                 of decentralized nature of the network and cause
                 flooding bottlenecks, contrary to the design concept of
                 decentralization. In this paper, our proposed scheme
                 uses a structured P2P overlay network to store the
                 indexes of unreachable nodes in the whole network, so
                 that the characteristics of a decentralized network are
                 still maintained while ensuring the efficiency of
                 lookup. When nodes communicate, the transmission
                 channel is established so that both nodes continuously
                 transmit data streams peer-to-peer without relying on
                 the central server. Moreover, the scheme guarantees the
                 security and privacy of nodes' data transmission and
                 the P2P overlay network without relying on centralized
                 trusted institutions. Finally, we deploy a real cluster
                 environment to verify the effectiveness of each module
                 at different network sizes and prove the overall
                 feasibility of the scheme. The scheme has certain
                 advantages over existing solutions in terms of
                 security, privacy, communication efficiency, device
                 democracy, etc.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wei:2022:SSL,
  author =       "Dawei Wei and Feifei Shi and Sahraoui Dhelim",
  title =        "A Self-Supervised Learning Model for Unknown
                 {Internet} Traffic Identification Based on Surge
                 Period",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "289",
  day =          "10",
  month =        oct,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100289",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/289",
  abstract =     "The identification of Internet protocols provides a
                 significant basis for keeping Internet security and
                 improving Internet Quality of Service (QoS). However,
                 the overwhelming developments and updating of Internet
                 technologies and protocols have led to large volumes of
                 unknown Internet traffic, which threaten the safety of
                 the network environment a lot. Since most of the
                 unknown Internet traffic does not have any labels, it
                 is difficult to adopt deep learning directly.
                 Additionally, the feature accuracy and identification
                 model also impact the identification accuracy a lot. In
                 this paper, we propose a surge period-based feature
                 extraction method that helps remove the negative
                 influence of background traffic in network sessions and
                 acquire as many traffic flow features as possible. In
                 addition, we also establish an identification model of
                 unknown Internet traffic based on JigClu, the
                 self-supervised learning approach to training unlabeled
                 datasets. It finally combines with the clustering
                 method and realizes the further identification of
                 unknown Internet traffic. The model has been
                 demonstrated with an accuracy of no less than 74\% in
                 identifying unknown Internet traffic with the public
                 dataset ISCXVPN2016 under different scenarios. The work
                 provides a novel solution for unknown Internet traffic
                 identification, which is the most difficult task in
                 identifying Internet traffic. We believe it is a great
                 leap in Internet traffic identification and is of great
                 significance to maintaining the security of the network
                 environment.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Carroll:2022:PMM,
  author =       "John M. Carroll and Fanlu Gui and Srishti Gupta and
                 Tiffany Knearem",
  title =        "Playful Meaning-Making as Prosocial Fun",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "288",
  day =          "30",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100288",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/288",
  abstract =     "Smart city infrastructures enable the routine
                 interleaving and integration of diverse activities,
                 including new ways to play, to be playful, and to
                 participate. We discuss three examples: (1)
                 citizen-based water quality monitoring, which combines
                 outdoor exercise and social interaction with
                 safeguarding public water supplies, (2) a digital
                 scavenger hunt, which combines the experiences of a
                 community arts festival with shared reflections about
                 significant community places and events, and (3) public
                 thanking, which encourages people to acknowledge
                 neighbors and local groups that serve and strengthen
                 the community. Each of these interaction possibilities
                 in itself alters lived experience modestly. We argue
                 that lightweight and playful meaning making activities
                 can be prosocial fun, that is to say, they can
                 simultaneously be playful and fun, but also substantive
                 contributions to the coherence and richness of a
                 community.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kurtukova:2022:CCS,
  author =       "Anna Kurtukova and Aleksandr Romanov and Alexander
                 Shelupanov and Anastasia Fedotova",
  title =        "Complex Cases of Source Code Authorship Identification
                 Using a Hybrid Deep Neural Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "287",
  day =          "30",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100287",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/287",
  abstract =     "This paper is a continuation of our previous work on
                 solving source code authorship identification problems.
                 The analysis of heterogeneous source code is a relevant
                 issue for copyright protection in commercial software
                 development. This is related to the specificity of
                 development processes and the usage of collaborative
                 development tools (version control systems). As a
                 result, there are source codes written according to
                 different programming standards by a team of
                 programmers with different skill levels. Another
                 application field is information security---in
                 particular, identifying the author of computer viruses.
                 We apply our technique based on a hybrid of
                 Inception-v1 and Bidirectional Gated Recurrent Units
                 architectures on heterogeneous source codes and
                 consider the most common commercial development complex
                 cases that negatively affect the authorship
                 identification process. The paper is devoted to the
                 possibilities and limitations of the author's technique
                 in various complex cases. For situations where a
                 programmer was proficient in two programming languages,
                 the average accuracy was 87\%; for proficiency in three
                 or more---76\%. For the artificially generated source
                 code case, the average accuracy was 81.5\%. Finally,
                 the average accuracy for source codes generated from
                 commits was 84\%. The comparison with state-of-the-art
                 approaches showed that the proposed method has no
                 full-functionality analogs covering actual practical
                 cases.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Roumeliotis:2022:MTO,
  author =       "Anargyros J. Roumeliotis and Christos N. Efrem and
                 Athanasios D. Panagopoulos",
  title =        "Minimization of $n$-th Order Rate Matching in
                 Satellite Networks with One to Many Pairings",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "286",
  day =          "30",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100286",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/286",
  abstract =     "This paper studies the minimization of n th (positive
                 integer) order rate matching in high-throughput
                 multi-beam satellite systems, based on one-to-many
                 capacity allocation pairings, for the first time in the
                 literature. The offered and requested capacities of
                 gateways and users' beams are exploited, respectively.
                 Due to the high complexity of the binary optimization
                 problem, its solution is approached with a two-step
                 heuristic scheme. Firstly, the corresponding
                 continuous, in [0, 1], pairing problem is solved
                 applying the difference of convex optimization theory,
                 and then, a transformation from continuous to binary
                 feasible allocation is provided to extract the pairings
                 among gateways and users' beams. Comparing with the
                 exponential-time optimal exhaustive mechanism that
                 investigates all possible pairs to extract the best
                 matching for minimizing the rate matching, extended
                 simulations show that the presented approximation for
                 the solution of the non-convex optimization problem has
                 fast convergence and achieves a generally low relative
                 error for lower value of n. Finally, the simulation
                 results show the importance of n in the examined
                 problem. Specifically, pairings originated by the
                 minimization of rate matching with larger n result in
                 more fair rate matching among users' beams, which is a
                 valuable result for satellite and generally wireless
                 systems operators.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Iglesias-Sanuy:2022:ELB,
  author =       "Pablo Iglesias-Sanuy and Jos{\'e} Carlos
                 L{\'o}pez-Ardao and Miguel Rodr{\'\i}guez-P{\'e}rez and
                 Sergio Herrer{\'\i}a-Alonso and Andr{\'e}s
                 Su{\'a}rez-Gonz{\'a}lez and Ra{\'u}l F.
                 Rodr{\'\i}guez-Rubio",
  title =        "An Efficient Location-Based Forwarding Strategy for
                 Named Data Networking and {LEO} Satellite
                 Communications",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "285",
  day =          "29",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100285",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/285",
  abstract =     "Low Earth orbit (LEO) satellite constellations are
                 increasingly gaining attention as future global
                 Internet providers. At the same time, named data
                 networking (NDN) is a new data-centric architecture
                 that has been recently proposed to replace the classic
                 TCP/IP architecture since it is particularly well
                 suited to the most common usage of the Internet
                 nowadays as a content delivery network. Certainly, the
                 use of NDN is especially convenient in highly dynamic
                 network environments, such as those of next LEO
                 constellations incorporating inter-satellite links
                 (ISL). Among other native facilities, such as inbuilt
                 security, NDN readily supports the mobility of clients,
                 thus helping to overcome one of the main problems
                 raised in LEO satellite networks. Moreover, thanks to a
                 stateful forwarding plane with support for multicast
                 transmission and inbuilt data caches, NDN is also able
                 to provide a more efficient usage of the installed
                 transmission capacity. In this paper, we propose a new
                 location-based forwarding strategy for LEO satellite
                 networks that takes advantage of the knowledge of the
                 relative position of the satellites and the grid
                 structure formed by the ISLs to perform the forwarding
                 of NDN packets. So, forwarding at each node is done
                 using only local information (node and destination
                 locations), without the need of interchanging
                 information between nodes, as is the case with
                 conventional routing protocols. Using simulation, we
                 show that the proposed forwarding strategy is a good
                 candidate to promote the efficient and effective future
                 use of the NDN architecture in LEO satellite
                 networks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Spyridou:2022:MVN,
  author =       "Paschalia (Lia) Spyridou and Constantinos Djouvas and
                 Dimitra Milioni",
  title =        "Modeling and Validating a News Recommender Algorithm
                 in a Mainstream Medium-Sized News Organization: an
                 Experimental Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "284",
  day =          "29",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100284",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/284",
  abstract =     "News recommending systems (NRSs) are algorithmic tools
                 that filter incoming streams of information according
                 to the users' preferences or point them to additional
                 items of interest. In today's high-choice media
                 environment, attention shifts easily between platforms
                 and news sites and is greatly affected by algorithmic
                 technologies; news personalization is increasingly used
                 by news media to woo and retain users' attention and
                 loyalty. The present study examines the implementation
                 of a news recommender algorithm in a leading news media
                 organization on the basis of observation of the
                 recommender system's outputs. Drawing on an
                 experimental design employing the `algorithmic audit'
                 method, and more specifically the `collaborative audit'
                 which entails utilizing users as testers of algorithmic
                 systems, we analyze the composition of the personalized
                 MyNews area in terms of accuracy and user engagement.
                 Premised on the idea of algorithms being black boxes,
                 the study has a two-fold aim: first, to identify the
                 implicated design parameters enlightening the
                 underlying functionality of the algorithm, and second,
                 to evaluate in practice the NRS through the deployed
                 experimentation. Results suggest that although the
                 recommender algorithm manages to discriminate between
                 different users on the basis of their past behavior,
                 overall, it underperforms. We find that this is related
                 to flawed design decisions rather than technical
                 deficiencies. The study offers insights to guide the
                 improvement of NRSs' design that both considers the
                 production capabilities of the news organization and
                 supports business goals, user demands and journalism's
                 civic values.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ruffo:2022:FES,
  author =       "Giancarlo Ruffo and Alfonso Semeraro",
  title =        "{FakeNewsLab}: Experimental Study on Biases and
                 Pitfalls Preventing Us from Distinguishing True from
                 False News",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "283",
  day =          "29",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100283",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/283",
  abstract =     "Misinformation posting and spreading in social media
                 is ignited by personal decisions on the truthfulness of
                 news that may cause wide and deep cascades at a large
                 scale in a fraction of minutes. When individuals are
                 exposed to information, they usually take a few seconds
                 to decide if the content (or the source) is reliable
                 and whether to share it. Although the opportunity to
                 verify the rumour is often just one click away, many
                 users fail to make a correct evaluation. We studied
                 this phenomenon with a web-based questionnaire that was
                 compiled by 7298 different volunteers, where the
                 participants were asked to mark 20 news items as true
                 or false. Interestingly, false news is correctly
                 identified more frequently than true news, but showing
                 the full article instead of just the title,
                 surprisingly, does not increase general accuracy.
                 Additionally, displaying the original source of the
                 news may contribute to misleading the user in some
                 cases, while the genuine wisdom of the crowd can
                 positively assist individuals' ability to classify news
                 correctly. Finally, participants whose browsing
                 activity suggests a parallel fact-checking activity
                 show better performance and declare themselves as young
                 adults. This work highlights a series of pitfalls that
                 can influence human annotators when building false news
                 datasets, which in turn can fuel the research on the
                 automated fake news detection; furthermore, these
                 findings challenge the common rationale of AI that
                 suggest users read the full article before
                 re-sharing.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Pflanzner:2022:LAB,
  author =       "Tamas Pflanzner and Hamza Baniata and Attila Kertesz",
  title =        "Latency Analysis of Blockchain-Based {SSI}
                 Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "282",
  day =          "29",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100282",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/python.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/282",
  abstract =     "Several revolutionary applications have been built on
                 the distributed ledgers of blockchain (BC) technology.
                 Besides cryptocurrencies, many other application fields
                 can be found in smart systems exploiting smart
                 contracts and Self Sovereign Identity (SSI) management.
                 The Hyperledger Indy platform is a suitable open-source
                 solution for realizing permissioned BC systems for SSI
                 projects. SSI applications usually require short
                 response times from the underlying BC network, which
                 may vary highly depending on the application type, the
                 used BC software, and the actual BC deployment
                 parameters. To support the developers and users of SSI
                 applications, we present a detailed latency analysis of
                 a permissioned BC system built with Indy and Aries. To
                 streamline our experiments, we developed a Python
                 application using containerized Indy and Aries
                 components from official Hyperledger repositories. We
                 deployed our experimental application on multiple
                 virtual machines in the public Google Cloud Platform
                 and on our local, private cloud using a Docker platform
                 with Kubernetes. We evaluated and compared their
                 performance benchmarked by Read and Write latencies. We
                 found that the local Indy ledger reads and writes
                 30--50\%, and 65--85\% faster than the Indy ledger
                 running on the Google Cloud Platform, respectively.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Al-Khafaji:2022:IQI,
  author =       "Hamza Mohammed Ridha Al-Khafaji",
  title =        "Improving Quality Indicators of the Cloud-Based {IoT}
                 Networks Using an Improved Form of Seagull Optimization
                 Algorithm",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "281",
  day =          "29",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100281",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/281",
  abstract =     "The Internet of things (IoT) points to billions of
                 devices located worldwide which are connected and share
                 their data based on the Internet. Due to the new
                 technologies that provide cheap computer chips and
                 universal wireless networks, it is feasible that
                 everything from a small tablet to a very large airplane
                 will be connected to the Internet and will be a part of
                 the IoT. In most applications, IoT network nodes face
                 limitations in terms of energy source and cost.
                 Therefore, the need for innovative methods to improve
                 quality indicators that increase the lifespan of
                 networks is evident. Here, a novel technique is
                 presented to increase the quality of service (QoS) in
                 IoT using an improved meta-heuristic algorithm, called
                 the improved seagull optimization algorithm (ISOA),
                 along with traffic management in these networks. Based
                 on this subject, the traffic-aware algorithm can manage
                 the sending of packets and increase the QoS provision
                 in terms of time to a great extent. The performance
                 evaluation of the proposed method and comparison with
                 the previous methods demonstrated the accuracy and
                 efficiency of this method and its superiority over the
                 previous works.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Pirotti:2022:ITR,
  author =       "Francesco Pirotti and Marco Piragnolo and Marika
                 D'Agostini and Raffaele Cavalli",
  title =        "Information Technologies for Real-Time Mapping of
                 Human Well-Being Indicators in an Urban Historical
                 Garden",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "280",
  day =          "29",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100280",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/280",
  abstract =     "The post-pandemic era has raised awareness on the
                 importance of physical and psychological well-being for
                 decreasing the vulnerability of both individuals and
                 populations. Citizens in urban areas are subject to
                 numerous stress factors which can be mitigated by green
                 spaces such as parks and gardens. Sensor and internet
                 technologies support nature-based solutions in various
                 ways. In this paper, we show the results of ongoing
                 research on the use of spatially distributed IoT
                 sensors that collect climate data in an $ \approx $8 ha
                 urban garden. The novelty resides in the method for
                 merging the IoT data with a detailed 3D model created
                 by a laser scan survey from a drone flight. The end
                 products are 1 m resolution thermal comfort maps of
                 user-defined scenarios, e.g., at specific times or
                 aggregated in daily/monthly/yearly statistics that
                 represent a thermal comfort distribution. For full
                 replicability, the code is open source and available as
                 an R package on Github.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yang:2022:MAN,
  author =       "Sa Yang and Suoping Li and Nana Yang and Ying Lin",
  title =        "Modelling Analysis of a Novel Frameless
                 Slotted-{ALOHA} Protocol Based on the Number of
                 Detectable Conflicting Users",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "279",
  day =          "28",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100279",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/279",
  abstract =     "To solve the conflict when multi-user packets are
                 transmitted in a shared wireless link, a novel
                 frameless slotted-ALOHA protocol is proposed. Signature
                 codes are used to help the receiver identify the set of
                 transmitting users, and successive interference
                 cancellation technology is employed to recover
                 conflicting packets. Thus, the information in the
                 conflicting slot can be reused to reduce the number of
                 retransmissions. Taking the number of backlogged users
                 in each slot as a system state, a Markov chain model is
                 established to analyze the protocol, in which the state
                 transition probabilities are obtained based on the
                 binomial distribution of packets sent in a slot. Under
                 the maximum number of detectable conflicting users, the
                 best value is taken, traffic balance equations are
                 obtained, and the expressions of throughput, average
                 number of backlogged users, average successful
                 transmission probability and average memory size are
                 derived. Finally, a numerical simulation is carried out
                 to accurately analyze the influence of the first
                 transmission probability of the packets on various
                 performance indexes and the effectiveness of the
                 theoretical analysis is further verified by the
                 simulation results.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Giacco:2022:RGI,
  author =       "Giovanni Giacco and Stefano Marrone and Giuliano
                 Langella and Carlo Sansone",
  title =        "{ReFuse}: Generating Imperviousness Maps from
                 Multi-Spectral {Sentinel-2} Satellite Imagery",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "278",
  day =          "28",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100278",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/278",
  abstract =     "Continual mapping and monitoring of impervious
                 surfaces are crucial activities to support sustainable
                 urban management strategies and to plan effective
                 actions for environmental changes. In this context,
                 impervious surface coverage is increasingly becoming an
                 essential indicator for assessing urbanization and
                 environmental quality, with several works relying on
                 satellite imagery to determine it. However, although
                 satellite imagery is typically available with a
                 frequency of 3--10 days worldwide, imperviousness maps
                 are released at most annually as they require a huge
                 human effort to be produced and validated. Attempts
                 have been made to extract imperviousness maps from
                 satellite images using machine learning, but (i) the
                 scarcity of reliable and detailed ground truth (ii)
                 together with the need to manage different spectral
                 bands (iii) while making the resulting system easily
                 accessible to the end users is limiting their
                 diffusion. To tackle these problems, in this work we
                 introduce a deep-learning-based approach to extract
                 imperviousness maps from multi-spectral Sentinel-2
                 images leveraging a very detailed imperviousness map
                 realised by the Italian department for environment
                 protection as ground truth. We also propose a scalable
                 and portable inference pipeline designed to easily
                 scale the approach, integrating it into a web-based
                 Geographic Information System (GIS) application. As a
                 result, even non-expert GIS users can quickly and
                 easily calculate impervious surfaces for any place on
                 Earth (accuracy {$>$95}\% ), with a frequency limited
                 only by the availability of new satellite images.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Manugunta:2022:DLB,
  author =       "Ramya Krishna Manugunta and Rytis Maskeliunas and
                 Robertas Damasevicius",
  title =        "Deep Learning Based Semantic Image Segmentation
                 Methods for Classification of {Web} Page Imagery",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "277",
  day =          "27",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100277",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/277",
  abstract =     "Semantic segmentation is the task of clustering
                 together parts of an image that belong to the same
                 object class. Semantic segmentation of webpages is
                 important for inferring contextual information from the
                 webpage. This study examines and compares deep learning
                 methods for classifying webpages based on imagery that
                 is obscured by semantic segmentation. Fully
                 convolutional neural network architectures (UNet and
                 FCN-8) with defined hyperparameters and loss functions
                 are used to demonstrate how they can support an
                 efficient method of this type of classification
                 scenario in custom-prepared webpage imagery data that
                 are labeled multi-class and semantically segmented
                 masks using HTML elements such as paragraph text,
                 images, logos, and menus. Using the proposed Seg-UNet
                 model achieved the best accuracy of 95\%. A comparison
                 with various optimizer functions demonstrates the
                 overall efficacy of the proposed semantic segmentation
                 approach.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Akhilesh:2022:APT,
  author =       "Rohit Akhilesh and Oliver Bills and Naveen Chilamkurti
                 and Mohammad Jabed Morshed Chowdhury",
  title =        "Automated Penetration Testing Framework for
                 Smart-Home-Based {IoT} Devices",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "276",
  day =          "27",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100276",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/276",
  abstract =     "Security testing is fundamental to identifying
                 security vulnerabilities on smart home-based IoT
                 devices. For this, penetration testing is the most
                 prominent and effective solution. However, testing the
                 IoT manually is cumbersome and time-consuming. In
                 addition, penetration testing requires a deep knowledge
                 of the possible attacks and the available hacking
                 tools. Therefore, this study emphasises building an
                 automated penetration testing framework to discover the
                 most common vulnerabilities in smart home-based IoT
                 devices. This research involves exploring (studying)
                 different IoT devices to select five devices for
                 testing. Then, the common vulnerabilities for the five
                 selected smart home-based IoT devices are examined, and
                 the corresponding penetration testing tools required
                 for the detection of these vulnerabilities are
                 identified. The top five vulnerabilities are identified
                 from the most common vulnerabilities, and accordingly,
                 the corresponding tools for these vulnerabilities are
                 discovered. These tools are combined using a script
                 which is then implemented into a framework written in
                 Python 3.6. The selected IoT devices are tested
                 individually for known vulnerabilities using the
                 proposed framework. For each vulnerability discovered
                 in the device, the Common Vulnerability Scoring System
                 (CVSS) Base score is calculated and the summation of
                 these scores is taken to calculate the total score (for
                 each device). In our experiment, we found that the
                 Tp-Link Smart Bulb and the Tp-Link Smart Camera had the
                 highest score and were the most vulnerable and the
                 Google Home Mini had the least score and was the most
                 secure device of all the devices. Finally, we conclude
                 that our framework does not require technical expertise
                 and thus can be used by common people. This will help
                 improve the field of IoT security and ensure the
                 security of smart homes to build a safe and secure
                 future.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lucena:2022:CUU,
  author =       "Felipe Lucena and Fabio Marcelo Breunig and Hermann
                 Kux",
  title =        "The Combined Use of {UAV}-Based {RGB} and {DEM} Images
                 for the Detection and Delineation of Orange Tree Crowns
                 with {Mask R-CNN}: an Approach of Labeling and Unified
                 Framework",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "275",
  day =          "27",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100275",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/275",
  abstract =     "In this study, we used images obtained by Unmanned
                 Aerial Vehicles (UAV) and an instance segmentation
                 model based on deep learning (Mask R-CNN) to evaluate
                 the ability to detect and delineate canopies in high
                 density orange plantations. The main objective of the
                 work was to evaluate the improvement acquired by the
                 segmentation model when integrating the Canopy Height
                 Model (CHM) as a fourth band to the images. Two models
                 were evaluated, one with RGB images and the other with
                 RGB + CHM images, and the results indicated that the
                 model with combined images presents better results
                 (overall accuracy from 90.42\% to 97.01\%). In addition
                 to the comparison, this work suggests a more efficient
                 ground truth mapping method and proposes a methodology
                 for mosaicking the results by Mask R-CNN on remotely
                 sensed images.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kratzke:2022:CNO,
  author =       "Nane Kratzke",
  title =        "Cloud-Native Observability: The Many-Faceted Benefits
                 of Structured and Unified Logging---a Multi-Case
                 Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "274",
  day =          "26",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100274",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/274",
  abstract =     "Background: Cloud-native software systems often have a
                 much more decentralized structure and many
                 independently deployable and (horizontally) scalable
                 components, making it more complicated to create a
                 shared and consolidated picture of the overall
                 decentralized system state. Today, observability is
                 often understood as a triad of collecting and
                 processing metrics, distributed tracing data, and
                 logging. The result is often a complex observability
                 system composed of three stovepipes whose data are
                 difficult to correlate. Objective: This study analyzes
                 whether these three historically emerged observability
                 stovepipes of logs, metrics and distributed traces
                 could be handled in a more integrated way and with a
                 more straightforward instrumentation approach. Method:
                 This study applied an action research methodology used
                 mainly in industry--academia collaboration and common
                 in software engineering. The research design utilized
                 iterative action research cycles, including one
                 long-term use case. Results: This study presents a
                 unified logging library for Python and a unified
                 logging architecture that uses the structured logging
                 approach. The evaluation shows that several thousand
                 events per minute are easily processable. Conclusions:
                 The results indicate that a unification of the current
                 observability triad is possible without the necessity
                 to develop utterly new toolchains.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Xu:2022:DBD,
  author =       "Xingjian Xu and Lijun Sun and Fanjun Meng",
  title =        "Distributed Big Data Storage Infrastructure for
                 Biomedical Research Featuring High-Performance and
                 Rich-Features",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "273",
  day =          "24",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100273",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/273",
  abstract =     "The biomedical field entered the era of ``big data''
                 years ago, and a lot of software is being developed to
                 tackle the analysis problems brought on by big data.
                 However, very few programs focus on providing a solid
                 foundation for file systems of biomedical big data.
                 Since file systems are a key prerequisite for efficient
                 big data utilization, the absence of specialized
                 biomedical big data file systems makes it difficult to
                 optimize storage, accelerate analysis, and enrich
                 functionality, resulting in inefficiency. Here we
                 present F3BFS, a functional, fundamental, and
                 future-oriented distributed file system, specially
                 designed for various kinds of biomedical data. F3BFS
                 makes it possible to boost existing software's
                 performance without modifying its main algorithms by
                 transmitting raw datasets from generic file systems.
                 Further, F3BFS has various built-in features to help
                 researchers manage biology datasets more efficiently
                 and productively, including metadata management, fuzzy
                 search, automatic backup, transparent compression,
                 etc.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Dhar:2022:AIL,
  author =       "Ankita Dhar and Himadri Mukherjee and Shibaprasad Sen
                 and Md Obaidullah Sk and Amitabha Biswas and Teresa
                 Gon{\c{c}}alves and Kaushik Roy",
  title =        "Author Identification from Literary Articles with
                 Visual Features: a Case Study with {Bangla} Documents",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "10",
  pages =        "272",
  day =          "23",
  month =        sep,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14100272",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Oct 26 11:06:06 MDT 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/10/272",
  abstract =     "Author identification is an important aspect of
                 literary analysis, studied in natural language
                 processing (NLP). It aids identify the most probable
                 author of articles, news texts or social media comments
                 and tweets, for example. It can be applied to other
                 domains such as criminal and civil cases,
                 cybersecurity, forensics, identification of
                 plagiarizer, and many more. An automated system in this
                 context can thus be very beneficial for society. In
                 this paper, we propose a convolutional neural network
                 (CNN)-based author identification system from literary
                 articles. This system uses visual features along with a
                 five-layer convolutional neural network for the
                 identification of authors. The prime motivation behind
                 this approach was the feasibility to identify distinct
                 writing styles through a visualization of the writing
                 patterns. Experiments were performed on 1200 articles
                 from 50 authors achieving a maximum accuracy of
                 93.58\%. Furthermore, to see how the system performed
                 on different volumes of data, the experiments were
                 performed on partitions of the dataset. The system
                 outperformed standard handcrafted feature-based
                 techniques as well as established works on publicly
                 available datasets.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Polyakov:2022:ALP,
  author =       "Nikita Polyakov and Anna Platonova",
  title =        "Assessing Latency of Packet Delivery in the {5G}
                 {3GPP} Integrated Access and Backhaul Architecture with
                 Half-Duplex Constraints",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "345",
  day =          "21",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110345",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/345",
  abstract =     "Integrated Access and Backhaul (IAB) is an enabling
                 technology for efficient 5G millimeter wave (mmWave)
                 New Radio (NR) deployment. The key feature of IAB is
                 multi-hop wireless backhauling, allowing utilizing
                 relaying IAB-nodes to provide cost-efficient access
                 network densification and alleviate the problem of
                 blockages. One of the critical performance measures in
                 such systems is the latency of packet delivery over the
                 multi-hop paths. The paper aims at assessing the impact
                 of multi-hop transmission on the end-to-end delay in an
                 IAB radio access network, taking into account the
                 half-duplex constraint. We build a detailed queuing
                 theory model for latency assessment in
                 time-division-multiplexing (TDM)-based IAB deployments
                 and evaluate the delay due to queuing in the network
                 nodes for several cell topologies and under different
                 time allocation strategies between access and backhaul.
                 The paper considers a practical Manhattan-style urban
                 deployment, which is characteristically impaired by the
                 blockage of buildings. The numerical results show that
                 balancing the access and backhaul micro phases is
                 crucial for reducing the end-to-end packet delay, at
                 least in the uplink, while increasing the number of
                 network hops yields a linear increase in the total
                 packet delay for both the uplink and downlink. The
                 numerical results were obtained via simulation using
                 the open-source software OMNeT++.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Csirmaz:2022:DSC,
  author =       "Elod P. Csirmaz and Laszlo Csirmaz",
  title =        "Data Synchronization: a Complete Theoretical Solution
                 for Filesystems",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "344",
  day =          "21",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110344",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/344",
  abstract =     "Data reconciliation in general, and filesystem
                 synchronization in particular, lacks rigorous
                 theoretical foundation. This paper presents, for the
                 first time, a complete analysis of synchronization for
                 two replicas of a theoretical filesystem.
                 Synchronization has two main stages: identifying the
                 conflicts, and resolving them. All existing (both
                 theoretical and practical) synchronizers are
                 operation-based: they define, using some rationale or
                 heuristics, how conflicts are to be resolved without
                 considering the effect of the resolution on subsequent
                 conflicts. Instead, our approach is declaration-based:
                 we define what constitutes the resolution of all
                 conflicts, and for each possible scenario we prove the
                 existence of sequences of operations/commands which
                 convert the replicas into a common synchronized state.
                 These sequences consist of operations rolling back some
                 local changes, followed by operations performed on the
                 other replica. The set of rolled-back operations
                 provides the user with clear and intuitive information
                 on the proposed changes, so she can easily decide
                 whether to accept them or ask for other alternatives.
                 All possible synchronized states are described by
                 specifying a set of conflicts, a partial order on the
                 conflicts describing the order in which they need to be
                 resolved, as well as the effect of each decision on
                 subsequent conflicts. Using this classification, the
                 outcomes of different conflict resolution policies can
                 be investigated easily.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kotenidis:2022:ICM,
  author =       "Efthimis Kotenidis and Nikolaos Vryzas and Andreas
                 Veglis and Charalampos Dimoulas",
  title =        "Integrating Chatbot Media Automations in Professional
                 Journalism: an Evaluation Framework",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "343",
  day =          "21",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110343",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/343",
  abstract =     "Interactivity has been a very sought-after feature in
                 professional journalism ever since the media industry
                 transitioned from print into the online space. Within
                 this context, chatbots started to infiltrate the media
                 sphere and provide news organizations with new and
                 innovative ways to create and share their content, with
                 an even larger emphasis on back-and-forth communication
                 and news reporting personalization. The present
                 research highlights two important factors that can
                 determine the efficient integration of chatbots in
                 professional journalism: the feasibility of chatbot
                 programming by journalists without a background in
                 computer science using coding-free platforms and the
                 usability of the created chatbot agents for news
                 reporting to the audience. This paper aims to review
                 some of the most popular, coding-free chatbot creation
                 platforms that are available to journalists today. To
                 that end, a three-phase evaluation framework is
                 introduced. First off, the interactivity features that
                 they offer to media industry workers are evaluated
                 using an appropriate metrics framework. Secondly, a
                 two- part workshop is conducted where journalists use
                 the aforementioned platforms to create their own
                 chatbot news reporting agents with minimum training,
                 and lastly, the created chatbots are evaluated by a
                 larger audience concerning the usability and overall
                 user experience.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mackay:2022:ESI,
  author =       "Michael Mackay",
  title =        "Editorial for the Special Issue on {5G} Enabling
                 Technologies and Wireless Networking",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "342",
  day =          "21",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110342",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/342",
  abstract =     "The ongoing deployment of 5G networks is seen as a key
                 enabler for realizing upcoming interconnected services
                 at scale, including the massive deployment of the
                 Internet of Things, providing V2X communications to
                 support autonomous vehicles, and the increase in smart
                 homes, smart cities, and Industry 4 \ldots{}",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Habib:2022:BTB,
  author =       "Gousia Habib and Sparsh Sharma and Sara Ibrahim and
                 Imtiaz Ahmad and Shaima Qureshi and Malik Ishfaq",
  title =        "Blockchain Technology: Benefits, Challenges,
                 Applications, and Integration of Blockchain Technology
                 with Cloud Computing",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "341",
  day =          "21",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110341",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/341",
  abstract =     "The real-world use cases of blockchain technology,
                 such as faster cross-border payments, identity
                 management, smart contracts, cryptocurrencies, and
                 supply chain--blockchain technology are here to stay
                 and have become the next innovation, just like the
                 Internet. There have been attempts to formulate digital
                 money, but they have not been successful due to
                 security and trust issues. However, blockchain needs no
                 central authority, and its operations are controlled by
                 the people who use it. Furthermore, it cannot be
                 altered or forged, resulting in massive market hype and
                 demand. Blockchain has moved past cryptocurrency and
                 discovered implementations in other real-life
                 applications; this is where we can expect blockchain
                 technology to be simplified and not remain a complex
                 concept. Blockchain technology's desirable
                 characteristics are decentralization, integrity,
                 immutability, verification, fault tolerance, anonymity,
                 audibility, and transparency. We first conduct a
                 thorough analysis of blockchain technology in this
                 paper, paying particular attention to its evolution,
                 applications and benefits, the specifics of
                 cryptography in terms of public key cryptography, and
                 the challenges of blockchain in distributed transaction
                 ledgers, as well as the extensive list of blockchain
                 applications in the financial transaction system. This
                 paper presents a detailed review of blockchain
                 technology, the critical challenges faced, and its
                 applications in different fields. Blockchain in the
                 transaction system is explained in detail with a
                 summary of different cryptocurrencies. Some of the
                 suggested solutions are given in the overall study of
                 the paper.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Roy:2022:MPU,
  author =       "Sanjiban Sekhar Roy and Ali Ismail Awad and Lamesgen
                 Adugnaw Amare and Mabrie Tesfaye Erkihun and Mohd
                 Anas",
  title =        "Multimodel Phishing {URL} Detection Using {LSTM},
                 Bidirectional {LSTM}, and {GRU} Models",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "340",
  day =          "21",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110340",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/340",
  abstract =     "In today's world, phishing attacks are gradually
                 increasing, resulting in individuals losing valuables,
                 assets, personal information, etc., to unauthorized
                 parties. In phishing, attackers craft malicious
                 websites disguised as well-known, legitimate sites and
                 send them to individuals to steal personal information
                 and other related private details. Therefore, an
                 efficient and accurate method is required to determine
                 whether a website is malicious. Numerous methods have
                 been proposed for detecting malicious uniform resource
                 locators (URLs) using deep learning, machine learning,
                 and other approaches. In this study, we have used
                 malicious and benign URLs datasets and have proposed a
                 detection mechanism for detecting malicious URLs using
                 recurrent neural network models such as long short-term
                 memory (LSTM), bidirectional long short-term memory
                 (Bi-LSTM), and the gated recurrent unit (GRU).
                 Experimental results have shown that the proposed
                 mechanism achieved an accuracy of 97.0\% for LSTM,
                 99.0\% for Bi-LSTM, and 97.5\% for GRU, respectively.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alsadeh:2022:DFI,
  author =       "Ahmad Alsadeh and Nasri Yatim and Yousef Hassouneh",
  title =        "A Dynamic Federated Identity Management Using {OpenID}
                 Connect",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "339",
  day =          "21",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110339",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/339",
  abstract =     "Identity federation allows one to link a user's
                 digital identities across several identity management
                 systems. Federated identity management (FIM) ensures
                 that users have easy access to the available resources.
                 However, scaling FIM to numerous partners is a
                 challenging process due to the interoperability issue
                 between different federation architectures. This study
                 proposes a dynamic identity federation model to
                 eliminate the manual configuration steps needed to
                 establish an organizational identity federation by
                 utilizing the OpenID Connect (OIDC) framework. The
                 proposed model consists of three major steps to
                 establish dynamic FIM: first, the discovery of the
                 OpenID service provider, which indicates the location
                 of the partner organization; second, the registration
                 of the OpenID relying party, which allows the
                 organization and its partner to negotiate information
                 for establishing the federation; finally, establishing
                 the dynamic trust federation. The proposed dynamic FIM
                 model allows applications to provide services to
                 end-users coming from various domains while maintaining
                 a trust between clients and service providers. Through
                 our proposed dynamic identity federation model,
                 organizations can save hundreds of hours by achieving
                 dynamic federation in runtime and serving a large
                 number of end-users.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Asad:2022:SKA,
  author =       "Muhammad Asad and Muhammad Aslam and Syeda Fizzah
                 Jilani and Saima Shaukat and Manabu Tsukada",
  title =        "{SHFL}: {$K$}-Anonymity-Based Secure Hierarchical
                 Federated Learning Framework for Smart Healthcare
                 Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "338",
  day =          "18",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110338",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/338",
  abstract =     "Dynamic and smart Internet of Things (IoT)
                 infrastructures allow the development of smart
                 healthcare systems, which are equipped with mobile
                 health and embedded healthcare sensors to enable a
                 broad range of healthcare applications. These IoT
                 applications provide access to the clients' health
                 information. However, the rapid increase in the number
                 of mobile devices and social networks has generated
                 concerns regarding the secure sharing of a client's
                 location. In this regard, federated learning (FL) is an
                 emerging paradigm of decentralized machine learning
                 that guarantees the training of a shared global model
                 without compromising the data privacy of the client. To
                 this end, we propose a K-anonymity-based secure
                 hierarchical federated learning (SHFL) framework for
                 smart healthcare systems. In the proposed hierarchical
                 FL approach, a centralized server communicates
                 hierarchically with multiple directly and indirectly
                 connected devices. In particular, the proposed SHFL
                 formulates the hierarchical clusters of location-based
                 services to achieve distributed FL. In addition, the
                 proposed SHFL utilizes the K-anonymity method to hide
                 the location of the cluster devices. Finally, we
                 evaluated the performance of the proposed SHFL by
                 configuring different hierarchical networks with
                 multiple model architectures and datasets. The
                 experiments validated that the proposed SHFL provides
                 adequate generalization to enable network scalability
                 of accurate healthcare systems without compromising the
                 data and location privacy.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Grobelna:2022:ITC,
  author =       "Iwona Grobelna",
  title =        "{Internet of Things} and Cyber--Physical Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "337",
  day =          "18",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110337",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/337",
  abstract =     "Dynamic and smart Internet of Things (IoT)
                 infrastructures allow the development of smart
                 healthcare systems, which are equipped with mobile
                 health and embedded healthcare sensors to enable a
                 broad range of healthcare applications. These IoT
                 applications provide access to the clients' health
                 information. However, the rapid increase in the number
                 of mobile devices and social networks has generated
                 concerns regarding the secure sharing of a client's
                 location. In this regard, federated learning (FL) is an
                 emerging paradigm of decentralized machine learning
                 that guarantees the training of a shared global model
                 without compromising the data privacy of the client. To
                 this end, we propose a K-anonymity-based secure
                 hierarchical federated learning (SHFL) framework for
                 smart healthcare systems. In the proposed hierarchical
                 FL approach, a centralized server communicates
                 hierarchically with multiple directly and indirectly
                 connected devices. In particular, the proposed SHFL
                 formulates the hierarchical clusters of location-based
                 services to achieve distributed FL. In addition, the
                 proposed SHFL utilizes the K-anonymity method to hide
                 the location of the cluster devices. Finally, we
                 evaluated the performance of the proposed SHFL by
                 configuring different hierarchical networks with
                 multiple model architectures and datasets. The
                 experiments validated that the proposed SHFL provides
                 adequate generalization to enable network scalability
                 of accurate healthcare systems without compromising the
                 data and location privacy.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Honecker:2022:CDT,
  author =       "Fabian Honecker and Julian Dreyer and Ralf
                 T{\"o}njes",
  title =        "Comparison of Distributed Tamper-Proof Storage Methods
                 for Public Key Infrastructures",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "336",
  day =          "18",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110336",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/336",
  abstract =     "Modern Public Key Infrastructures (PKIs) allow users
                 to create and maintain centrally stored cryptographic
                 certificates. These infrastructures use a so-called
                 certificate chain. At the root of the chain, a root
                 Certification Authority (CA) is responsible for issuing
                 the base certificate. Every verification and
                 certification step within the chain is based upon the
                 security of said root CA. Thus, its operation security
                 is of great concern. Since the root certificates are
                 stored locally on the root CA, any Denial of Service
                 (DoS) attack may render the whole certificate chain,
                 which is based on of the attacked root CA, inoperable.
                 Therefore, this article evaluates different approaches
                 to a decentralized data storage system that is based on
                 the Distributed Ledger Technology (DLT). To show the
                 real-world potential of the proposed approaches, we
                 also evaluate the different technologies using a novel
                 PKI mechanism called Near Field Communication Key
                 Exchange (NFC-KE). The results indicate that modern
                 distributed data storage solutions such as
                 Interplanetary Filesystem (IPFS) and SIA can have
                 significant performance and decentralization benefits
                 in comparison to purely Blockchain-based technologies
                 like Hyperledger Fabric. However, they lack any Smart
                 Contract functionality, which requires a software
                 developer to implement verification mechanisms in
                 centralized software solutions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Raheman:2022:FCA,
  author =       "Fazal Raheman",
  title =        "The Future of Cybersecurity in the Age of Quantum
                 Computers",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "335",
  day =          "16",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110335",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/335",
  abstract =     "The first week of August 2022 saw the world's
                 cryptographers grapple with the second shocker of the
                 year. Another one of the four post-quantum cryptography
                 (PQC) algorithms selected by the NIST (National
                 Institute of Standards and Technology) in a rigorous
                 5-year process was cracked by a team from Belgium. They
                 took just 62 min and a standard laptop to break the PQC
                 algorithm to win a USD 50,000 bounty from Microsoft.
                 The first shocker came 6 months earlier, when another
                 of the NIST finalists (Rainbow) was taken down.
                 Unfortunately, both failed PQC algorithms are
                 commercially available to consumers. With 80 of the 82
                 PQC candidates failing the NIST standardization
                 process, the future of the remaining two PQC algorithms
                 is, at best, questionable, placing the rigorous 5-year
                 NIST exercise to build a quantum-safe encryption
                 standard in jeopardy. Meanwhile, there is no respite
                 from the quantum threat that looms large. It is time we
                 take a step back and review the etiology of the problem
                 de novo. Although state-of-the-art computer security
                 heavily relies on cryptography, it can indeed transcend
                 beyond encryption. This paper analyzes an
                 encryption-agnostic approach that can potentially
                 render computers quantum-resistant. Zero-vulnerability
                 computing (ZVC) secures computers by banning all
                 third-party permissions, a root cause of most
                 vulnerabilities. ZVC eliminates the complexities of the
                 multi-layered architecture of legacy computers and
                 builds a minimalist, compact solid-state software on a
                 chip (3SoC) that is robust, energy-efficient, and
                 potentially resistant to malware as well as quantum
                 threats.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bodrunova:2022:ESI,
  author =       "Svetlana S. Bodrunova",
  title =        "Editorial for the Special Issue {``Selected Papers
                 from the 9th Annual Conference `Comparative Media
                 Studies in Today's World' (CMSTW'2021)''}",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "334",
  day =          "16",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110334",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/334",
  abstract =     "The first week of August 2022 saw the world's
                 cryptographers grapple with the second shocker of the
                 year. Another one of the four post-quantum cryptography
                 (PQC) algorithms selected by the NIST (National
                 Institute of Standards and Technology) in a rigorous
                 5-year process was cracked by a team from Belgium. They
                 took just 62 min and a standard laptop to break the PQC
                 algorithm to win a USD 50,000 bounty from Microsoft.
                 The first shocker came 6 months earlier, when another
                 of the NIST finalists (Rainbow) was taken down.
                 Unfortunately, both failed PQC algorithms are
                 commercially available to consumers. With 80 of the 82
                 PQC candidates failing the NIST standardization
                 process, the future of the remaining two PQC algorithms
                 is, at best, questionable, placing the rigorous 5-year
                 NIST exercise to build a quantum-safe encryption
                 standard in jeopardy. Meanwhile, there is no respite
                 from the quantum threat that looms large. It is time we
                 take a step back and review the etiology of the problem
                 de novo. Although state-of-the-art computer security
                 heavily relies on cryptography, it can indeed transcend
                 beyond encryption. This paper analyzes an
                 encryption-agnostic approach that can potentially
                 render computers quantum-resistant. Zero-vulnerability
                 computing (ZVC) secures computers by banning all
                 third-party permissions, a root cause of most
                 vulnerabilities. ZVC eliminates the complexities of the
                 multi-layered architecture of legacy computers and
                 builds a minimalist, compact solid-state software on a
                 chip (3SoC) that is robust, energy-efficient, and
                 potentially resistant to malware as well as quantum
                 threats.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Suleiman:2022:CAF,
  author =       "Husam Suleiman",
  title =        "A Cost-Aware Framework for {QoS}-Based and
                 Energy-Efficient Scheduling in Cloud--Fog Computing",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "333",
  day =          "14",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110333",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/333",
  abstract =     "Cloud--fog computing is a large-scale service
                 environment developed to deliver fast, scalable
                 services to clients. The fog nodes of such environments
                 are distributed in diverse places and operate
                 independently by deciding on which data to process
                 locally and which data to send remotely to the cloud
                 for further analysis, in which a Service-Level
                 Agreement (SLA) is employed to govern Quality of
                 Service (QoS) requirements of the cloud provider to
                 such nodes. The provider experiences varying incoming
                 workloads that come from heterogeneous fog and Internet
                 of Things (IoT) devices, each of which submits jobs
                 that entail various service characteristics and QoS
                 requirements. To execute fog workloads and meet their
                 SLA obligations, the provider allocates appropriate
                 resources and utilizes load scheduling strategies that
                 effectively manage the executions of fog jobs on cloud
                 resources. Failing to fulfill such demands causes extra
                 network bottlenecks, service delays, and energy
                 constraints that are difficult to maintain at run-time.
                 This paper proposes a joint energy- and QoS-optimized
                 performance framework that tolerates delay and energy
                 risks on the cost performance of the cloud provider.
                 The framework employs scheduling mechanisms that
                 consider the SLA penalty and energy impacts of data
                 communication, service, and waiting performance metrics
                 on cost reduction. The findings prove the framework's
                 effectiveness in mitigating energy consumption due to
                 QoS penalties and therefore reducing the gross
                 scheduling cost.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2022:BBB,
  author =       "Xinlu Li and Yuanyuan Lei and Shengwei Ji",
  title =        "{BERT}- and {BiLSTM}-Based Sentiment Analysis of
                 Online {Chinese} Buzzwords",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "332",
  day =          "14",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110332",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/332",
  abstract =     "Sentiment analysis of online Chinese buzzwords (OCBs)
                 is important for healthy development of platforms, such
                 as games and social networking, which can avoid
                 transmission of negative emotions through prediction of
                 users' sentiment tendencies. Buzzwords have the
                 characteristics of varying text length, irregular
                 wording, ignoring syntactic and grammatical
                 requirements, no complete semantic structure, and no
                 obvious sentiment features. This results in
                 interference and challenges to the sentiment analysis
                 of such texts. Sentiment analysis also requires
                 capturing effective sentiment features from deeper
                 contextual information. To solve the above problems, we
                 propose a deep learning model combining BERT and
                 BiLSTM. The goal is to generate dynamic representations
                 of OCB vectors in downstream tasks by fine-tuning the
                 BERT model and to capture the rich information of the
                 text at the embedding layer to solve the problem of
                 static representations of word vectors. The generated
                 word vectors are then transferred to the BiLSTM model
                 for feature extraction to obtain the local and global
                 semantic features of the text while highlighting the
                 text sentiment polarity for sentiment classification.
                 The experimental results show that the model works well
                 in terms of the comprehensive evaluation index F1. Our
                 model also has important significance and research
                 value for sentiment analysis of irregular texts, such
                 as OCBs.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Cen:2022:FMC,
  author =       "Yuefeng Cen and Mingxing Luo and Gang Cen and Cheng
                 Zhao and Zhigang Cheng",
  title =        "Financial Market Correlation Analysis and Stock
                 Selection Application Based on {TCN}-Deep Clustering",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "331",
  day =          "14",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110331",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/331",
  abstract =     "It is meaningful to analyze the market correlations
                 for stock selection in the field of financial
                 investment. Since it is difficult for existing deep
                 clustering methods to mine the complex and nonlinear
                 features contained in financial time series, in order
                 to deeply mine the features of financial time series
                 and achieve clustering, a new end-to-end deep
                 clustering method for financial time series is
                 proposed. It contains two modules: an autoencoder
                 feature extraction network based on TCN (temporal
                 convolutional neural) networks and a temporal
                 clustering optimization algorithm with a KL
                 (Kullback--Leibler) divergence. The features of
                 financial time series are represented by the causal
                 convolution and the dilated convolution of TCN
                 networks. Then, the pre-training results based on the
                 KL divergence are fine-tuned to make the clustering
                 results discriminative. The experimental results show
                 that the proposed method outperforms existing deep
                 clustering and general clustering algorithms in the CSI
                 300 and S\&P 500 index markets. In addition, the
                 clustering results combined with an inference strategy
                 can be used to select stocks that perform well or
                 poorly, thus guiding actual stock market trades.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Su:2022:CBR,
  author =       "Yue Su and Kien Nguyen and Hiroo Sekiya",
  title =        "A Comparison of Blockchain Recovery Time in Static and
                 Mobile {IoT}-Blockchain Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "330",
  day =          "14",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110330",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/330",
  abstract =     "Many IoT-blockchain systems in which blockchain
                 connections run on an infrastructure-based network,
                 such as Wi-Fi or LTE, face a severe problem: the single
                 point of failure (SPoF) (i.e., depending on the
                 availability, an access point of an LTE base station).
                 Using infrastructure-less networks (i.e., ad hoc
                 networks) is an efficient approach to prevent such
                 highly disruptive events. An ad hoc network can
                 automatically restore blockchain communication using an
                 ad hoc routing protocol, even if a node fails.
                 Moreover, an ad hoc routing protocol is more efficient
                 when considering the IoT nodes' mobility. In this
                 paper, we first construct IoT-blockchain systems on
                 emulated and real ad hoc networks with Ethereum and
                 three ad hoc routing protocols (i.e., OLSR, BATMAN, and
                 BABEL). We then evaluate the blockchain recovery time
                 in static and mobile scenarios. The results show that
                 BATMAN achieves the best blockchain recovery
                 performance in all investigated scenarios because
                 BATMAN only determines whether to switch a route by
                 comparing the number of OGM packets received from a
                 different next-hop. More specifically, in the
                 small-scale real IoT-blockchain, BATMAN recovers at
                 least 73.9\% and 59.8\% better than OLSR and BABEL,
                 respectively. In the medium-scale emulated
                 IoT-blockchain, the recovery time of BATMAN is at least
                 69\% and 60\% shorter than OLSR or BABEL,
                 respectively.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Villarejo-Carballido:2022:KCL,
  author =       "Beatriz Villarejo-Carballido and Cristina M. Pulido
                 and Santiago Tejedor",
  title =        "Key Competences for Lifelong Learning through the
                 {``Animal} Crossing: New Horizons'' Video Game",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "329",
  day =          "13",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110329",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/329",
  abstract =     "The growth and impact of video games in education at
                 an international level is a reality. Research shows
                 that gamers can increase their knowledge, skills, and
                 behavioural flexibility. However, there has been no
                 in-depth research into the relationship between current
                 video games and the key competences for lifelong
                 learning set out by the European Commission. This
                 research focuses on learning acquisition through
                 playing the popular game ``Animal Crossing: New
                 Horizons''. The Communicative Methodology has been used
                 in this research through, on the one hand, use of the
                 Social Impact in Social Media (SISM) method involving
                 the analysis of 1000 comments posted on the social
                 network Twitter and, on the other hand, through
                 communicative inter, sanviews with five gamers and a
                 family member of a user. The results show that the
                 Animal Crossing video game promotes learning
                 achievements regarding literacy, multilingualism,
                 mathematical skills, digital competence, social skills,
                 citizenship, entrepreneurship, and cultural
                 awareness.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kitsiou:2022:RUD,
  author =       "Angeliki Kitsiou and Charikleia Despotidi and Christos
                 Kalloniatis and Stefanos Gritzalis",
  title =        "The Role of Users' Demographic and Social Attributes
                 for Accepting Biometric Systems: a {Greek} Case Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "328",
  day =          "13",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110328",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/328",
  abstract =     "Even though both internet-of-cloud services and
                 biometric systems (BSs) are used worldwide, popular and
                 expanded among public and private services, their
                 utilization has not been extended among Greek users,
                 and in particular within Greek HEIs. This paper aims to
                 examine the University of the Aegean (UA) students'
                 perceptions, especially on BS acceptance, determining
                 the impact of their sociodemographic characteristics
                 toward this. An online instrument was developed based
                 on constructs of technology acceptance models, and
                 previous research focused on BS acceptance, including a
                 great variety of sociodemographic variables. The
                 authors collected 768 complete responses to explore the
                 social and demographic attributes that impact on
                 students' BS acceptance through exploratory descriptive
                 research. This study found that several UA students'
                 sociodemographic attributes are linked to their BS
                 acceptance. Specifically, gender, age, study level,
                 year of study, professional profile and fathers'
                 occupation are useful to determine which students'
                 groups are in favor of BS, while employment status,
                 annual income and mothers' occupation are weak toward
                 this. Security and privacy concerns are indicated to
                 influence users' BS acceptance as well. This study
                 provides a unique approach to better understanding the
                 Greek students' BS acceptance, with important
                 implications for improved BS marketing in Greece in
                 synergy with the internet-of-cloud services and their
                 potential adoption in HEIs internal settings. It also
                 provides developers with further knowledge for security
                 and privacy non-functional requirements in order to
                 increase users' acceptance and to address these
                 challenges within the internet of cloud.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Brackin:2022:GID,
  author =       "Roger C. Brackin and Michael J. Jackson and Andrew
                 Leyshon and Jeremy G. Morley and Sarah Jewitt",
  title =        "Generating Indicators of Disruptive Innovation Using
                 Big Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "327",
  day =          "11",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110327",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/327",
  abstract =     "Technological evolution and its potential impacts are
                 of significant interest to governments, corporate
                 organizations and for academic enquiry; but assessments
                 of technology progression are often highly subjective.
                 This paper prototypes potential objective measures to
                 assess technology progression using internet-based
                 data. These measures may help reduce the subjective
                 nature of such assessments and, in conjunction with
                 other techniques, reduce the uncertainty of technology
                 progression assessment. The paper examines one part of
                 the technology ecosystem, namely, academic research and
                 publications. It uses analytics performed against a
                 large body of academic paper abstracts and metadata
                 published over 20 years to propose and demonstrate
                 candidate indicators of technology progression.
                 Measures prototyped are: (i) overall occurrence of
                 technologies used over time in research, (ii) the
                 fields in which this use was made; (iii) the geographic
                 spread of specific technologies within research and
                 (iv) the clustering of technology research over time.
                 An outcome of the analysis is an ability to assess the
                 measures of technology progression against a set of
                 inputs and a set of commentaries and forecasts made
                 publicly in the subject area over the last 20 years.
                 The potential automated indicators of research are
                 discussed together with other indicators which might
                 help working groups in assessing technology progression
                 using more quantitative methods.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhang:2022:TVD,
  author =       "Yujian Zhang and Daifu Liu",
  title =        "Toward Vulnerability Detection for {Ethereum} Smart
                 Contracts Using Graph-Matching Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "326",
  day =          "11",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110326",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/326",
  abstract =     "With the blooming of blockchain-based smart contracts
                 in decentralized applications, the security problem of
                 smart contracts has become a critical issue, as
                 vulnerable contracts have resulted in severe financial
                 losses. Existing research works have explored
                 vulnerability detection methods based on fuzzing,
                 symbolic execution, formal verification, and static
                 analysis. In this paper, we propose two static analysis
                 approaches called ASGVulDetector and BASGVulDetector
                 for detecting vulnerabilities in Ethereum smart
                 contacts from source-code and bytecode perspectives,
                 respectively. First, we design a novel intermediate
                 representation called abstract semantic graph (ASG) to
                 capture both syntactic and semantic features from the
                 program. ASG is based on syntax information but
                 enriched by code structures, such as control flow and
                 data flow. Then, we apply two different training
                 models, i.e., graph neural network (GNN) and graph
                 matching network (GMN), to learn the embedding of ASG
                 and measure the similarity of the contract pairs. In
                 this way, vulnerable smart contracts can be identified
                 by calculating the similarity to labeled ones. We
                 conduct extensive experiments to evaluate the
                 superiority of our approaches to state-of-the-art
                 competitors. Specifically, ASGVulDetector improves the
                 best of three source-code-only static analysis tools
                 (i.e., SmartCheck, Slither, and DR-GCN ) regarding the
                 F1 score by 12.6\% on average, while BASGVulDetector
                 improves that of the three detection tools supporting
                 bytecode (i.e., ContractFuzzer, Oyente, and Securify )
                 regarding the F1 score by 25.6\% on average. We also
                 investigate the effectiveness and advantages of the GMN
                 model for detecting vulnerabilities in smart
                 contracts.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhang:2022:EDM,
  author =       "Yiyi Zhang and Tatsuo Nakajima",
  title =        "Exploring the Design of a Mixed-Reality {3D} Minimap
                 to Enhance Pedestrian Satisfaction in Urban Exploratory
                 Navigation",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "325",
  day =          "10",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110325",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/325",
  abstract =     "The development of ubiquitous computing technology and
                 the emergence of XR could provide pedestrian navigation
                 with more options for user interfaces and interactions.
                 In this work, we aim investigate the role of a
                 mixed-reality map interface in urban exploration to
                 enhance pedestrians' mental satisfaction. We propose a
                 mixed-reality 3D minimap as a part of the navigation
                 interface which pedestrians could refer to and interact
                 during urban exploration. To further explore the
                 different levels of detail of the map interface, we
                 conducted a user study (n = 28, two groups with two
                 tasks). We designed two exploratory activities as
                 experimental tasks with two map modes (a normal one and
                 a simplified one) to discuss the detailed design of the
                 minimap interface. The results indicated that
                 participants showed a positive attitude toward our
                 method. The simplified map mode could result in a lower
                 perceived workload in both tasks while enhancing
                 performance in specific navigation, such as wayfinding.
                 However, we also found that pedestrians' preference for
                 the level of detail of the minimap interface is dynamic
                 in navigation. Thus, we suggest discussing the
                 different levels of detail further in specific
                 scenarios. Finally, we also summarize some findings
                 observed during user study for inspiring the study of
                 virtual map interface of future mixed-reality
                 navigation for urban exploration in various
                 scenarios.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Xu:2022:MLP,
  author =       "Xiaoting Xu and Tin Lai and Sayka Jahan and Farnaz
                 Farid and Abubakar Bello",
  title =        "A Machine Learning Predictive Model to Detect Water
                 Quality and Pollution",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "324",
  day =          "08",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110324",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/324",
  abstract =     "The increasing prevalence of marine pollution during
                 the past few decades motivated recent research to help
                 ease the situation. Typical water quality assessment
                 requires continuous monitoring of water and sediments
                 at remote locations with labour-intensive laboratory
                 tests to determine the degree of pollution. We propose
                 an automated water quality assessment framework where
                 we formalise a predictive model using machine learning
                 to infer the water quality and level of pollution using
                 collected water and sediments samples. Firstly, due to
                 the sparsity of sample collection locations, the amount
                 of sediment samples of water is limited, and the
                 dataset is incomplete. Therefore, after an extensive
                 investigation on various data imputation methods'
                 performance in water and sediment datasets with
                 different missing data rates, we chose the best
                 imputation method to process the missing data.
                 Afterwards, the water sediment sample will be tagged as
                 one of four levels of pollution based on some
                 guidelines and then the machine learning model will use
                 a specific technique named classification to find the
                 relationship between the data and the final result.
                 After that, the result of prediction can be compared to
                 the real result so that it can be checked whether the
                 model is good and whether the prediction is accurate.
                 Finally, the research gave improvement advice based on
                 the result obtained from the model building part.
                 Empirically, we show that our best model archives an
                 accuracy of 75\% after accounting for 57\% of missing
                 data. Experimentally, we show that our model would
                 assist in automatically assessing water quality
                 screening based on possibly incomplete real-world
                 data.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Assuncao:2022:RTI,
  author =       "Eduardo Assun{\c{c}}{\~a}o and Pedro D. Gaspar and
                 Khadijeh Alibabaei and Maria P. Sim{\~o}es and Hugo
                 Proen{\c{c}}a and Vasco N. G. J. Soares and Jo{\~a}o M.
                 L. P. Caldeira",
  title =        "Real-Time Image Detection for Edge Devices: a Peach
                 Fruit Detection Application",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "323",
  day =          "08",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110323",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/323",
  abstract =     "Within the scope of precision agriculture, many
                 applications have been developed to support decision
                 making and yield enhancement. Fruit detection has
                 attracted considerable attention from researchers, and
                 it can be used offline. In contrast, some applications,
                 such as robot vision in orchards, require computer
                 vision models to run on edge devices while performing
                 inferences at high speed. In this area, most modern
                 applications use an integrated graphics processing unit
                 (GPU). In this work, we propose the use of a tensor
                 processing unit (TPU) accelerator with a Raspberry Pi
                 target device and the state-of-the-art, lightweight,
                 and hardware-aware MobileDet detector model. Our
                 contribution is the extension of the possibilities of
                 using accelerators (the TPU) for edge devices in
                 precision agriculture. The proposed method was
                 evaluated using a novel dataset of peaches with three
                 cultivars, which will be made available for further
                 studies. The model achieved an average precision (AP)
                 of 88.2\% and a performance of 19.84 frames per second
                 (FPS) at an image size of 640 $ \times $ 480. The
                 results obtained show that the TPU accelerator can be
                 an excellent alternative for processing on the edge in
                 precision agriculture.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alsubhi:2022:RAL,
  author =       "Khalid Alsubhi and Bander Alzahrani and Nikos Fotiou
                 and Aiiad Albeshri and Mohammed Alreshoodi",
  title =        "Reliable Application Layer Routing Using Decentralized
                 Identifiers",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "322",
  day =          "06",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110322",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/322",
  abstract =     "Modern internet of things (IoT) applications can
                 benefit from advanced communication paradigms,
                 including multicast and anycast. Next-generation
                 internet architectures, such as information-centric
                 networking (ICN), promise to support these paradigms,
                 but at the same time they introduce new security
                 challenges. This paper presents a solution that extends
                 an ICN-like architecture based on software-defined
                 networking (SDN) that supports those communication
                 paradigms. Using the proposed solution, the underlying
                 architecture is enhanced with a novel security
                 mechanism that allows content ``advertisements'' only
                 from authorized endpoints. This mechanism prevents
                 ``content pollution'', which is a significant security
                 threat in ICN architectures. The proposed solution is
                 lightweight, and it enables identity sharing as well as
                 secured and controlled identity delegation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Paajala:2022:UPK,
  author =       "Iikka Paajala and Jesse Nyyss{\"o}l{\"a} and Juho
                 Mattila and Pasi Karppinen",
  title =        "Users' Perceptions of Key Blockchain Features in
                 Games",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "321",
  day =          "04",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110321",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/321",
  abstract =     "The blockchain is an emerging technology that has the
                 potential to revolutionize the gaming industry among a
                 wide range of different business fields. So far, only a
                 few studies have been conducted about blockchain
                 gaming. This study introduces a mobile game utilizing
                 blockchain asset tokens and smart contracts. It was
                 developed for research purposes and used to demonstrate
                 blockchain-based games using semi-structured
                 interviews. This study follows the exploratory research
                 paradigm, which aims to map research of little-known
                 areas. This study focuses on how participants perceived
                 blockchain attributes such as trust, transparency, and
                 user-generated content and how this affected engagement
                 and their willingness to play the game again. Based on
                 our evaluation, generating blockchain assets positively
                 impacted player retention. According to the results,
                 providing genuine asset ownership through the
                 blockchain contributes to environmental engagement and
                 self-engagement, as well as player retention. Another
                 positive blockchain feature discovered from the
                 interview data is user-generated content implementation
                 into games.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Spradling:2022:EFI,
  author =       "Matthew Spradling and Jeremy Straub",
  title =        "Evaluation of the Factors That Impact the Perception
                 of Online Content Trustworthiness by Income, Political
                 Affiliation and Online Usage Time",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "320",
  day =          "03",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110320",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/320",
  abstract =     "Intentionally deceptive online content represents a
                 significant issue for society. Multiple techniques have
                 been proposed to identify and combat its spread. To
                 understand how to inform individuals most effectively
                 about the potential biases of and other issues with
                 content, this article studies factors that impact the
                 perception of online content. Specifically, it looks at
                 how these factors have similar or different impact
                 depending on the income level, political affiliation
                 and online usage time of Americans. A national survey
                 was conducted that asked respondents about multiple
                 factors that influence their and others' perception of
                 online content trustworthiness. It also asked what the
                 ideal impact of these factors should be. This data is
                 presented and analyzed herein, conclusions are drawn
                 and their implications, with regard to preventing the
                 spread of deceptive online content, are discussed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Daraghmi:2022:IBS,
  author =       "Yousef-Awwad Daraghmi and Mamoun Abu Helou and
                 Eman-Yasser Daraghmi and Waheeb Abu-ulbeh",
  title =        "{IoT}-Based System for Improving Vehicular Safety by
                 Continuous Traffic Violation Monitoring",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "319",
  day =          "02",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110319",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/319",
  abstract =     "The violation traffic laws by driving at high speeds,
                 the overloading of passengers, and the unfastening of
                 seatbelts are of high risk and can be fatal in the
                 event of any accident. Several systems have been
                 proposed to improve passenger safety, and the systems
                 either use the sensor-based approach or the
                 computer-vision-based approach. However, the accuracy
                 of these systems still needs enhancement because the
                 entire road network is not covered; the approaches
                 utilize complex estimation techniques, and they are
                 significantly influenced by the surrounding
                 environment, such as the weather and physical
                 obstacles. Therefore, this paper proposes a novel
                 IoT-based traffic violation monitoring system that
                 accurately estimates the vehicle speed, counts the
                 number of passengers, and detects the seatbelt status
                 on the entire road network. The system also utilizes
                 edge computing, fog computing, and cloud computing
                 technologies to achieve high accuracy. The system is
                 evaluated using real-life experiments and compared with
                 another system where the edge and cloud layers are used
                 without the fog layer. The results show that adding a
                 fog layer improves the monitoring accuracy as the
                 accuracy of passenger counting rises from 94\% to 97\%,
                 the accuracy of seatbelt detection rises from 95\% to
                 99\%, and the root mean square error of speed
                 estimation is reduced from 2.64 to 1.87.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Varela:2022:CIN,
  author =       "Leonilde Varela and Goran D. Putnik",
  title =        "Collaborative and Intelligent Networks and Decision
                 Systems and Services for Supporting Engineering and
                 Production Management",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "318",
  day =          "02",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110318",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/318",
  abstract =     "The violation traffic laws by driving at high speeds,
                 the overloading of passengers, and the unfastening of
                 seatbelts are of high risk and can be fatal in the
                 event of any accident. Several systems have been
                 proposed to improve passenger safety, and the systems
                 either use the sensor-based approach or the
                 computer-vision-based approach. However, the accuracy
                 of these systems still needs enhancement because the
                 entire road network is not covered; the approaches
                 utilize complex estimation techniques, and they are
                 significantly influenced by the surrounding
                 environment, such as the weather and physical
                 obstacles. Therefore, this paper proposes a novel
                 IoT-based traffic violation monitoring system that
                 accurately estimates the vehicle speed, counts the
                 number of passengers, and detects the seatbelt status
                 on the entire road network. The system also utilizes
                 edge computing, fog computing, and cloud computing
                 technologies to achieve high accuracy. The system is
                 evaluated using real-life experiments and compared with
                 another system where the edge and cloud layers are used
                 without the fog layer. The results show that adding a
                 fog layer improves the monitoring accuracy as the
                 accuracy of passenger counting rises from 94\% to 97\%,
                 the accuracy of seatbelt detection rises from 95\% to
                 99\%, and the root mean square error of speed
                 estimation is reduced from 2.64 to 1.87.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Stach:2022:SIS,
  author =       "Christoph Stach",
  title =        "Special Issue on Security and Privacy in Blockchains
                 and the {IoT}",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "317",
  day =          "01",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110317",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/317",
  abstract =     "The violation traffic laws by driving at high speeds,
                 the overloading of passengers, and the unfastening of
                 seatbelts are of high risk and can be fatal in the
                 event of any accident. Several systems have been
                 proposed to improve passenger safety, and the systems
                 either use the sensor-based approach or the
                 computer-vision-based approach. However, the accuracy
                 of these systems still needs enhancement because the
                 entire road network is not covered; the approaches
                 utilize complex estimation techniques, and they are
                 significantly influenced by the surrounding
                 environment, such as the weather and physical
                 obstacles. Therefore, this paper proposes a novel
                 IoT-based traffic violation monitoring system that
                 accurately estimates the vehicle speed, counts the
                 number of passengers, and detects the seatbelt status
                 on the entire road network. The system also utilizes
                 edge computing, fog computing, and cloud computing
                 technologies to achieve high accuracy. The system is
                 evaluated using real-life experiments and compared with
                 another system where the edge and cloud layers are used
                 without the fog layer. The results show that adding a
                 fog layer improves the monitoring accuracy as the
                 accuracy of passenger counting rises from 94\% to 97\%,
                 the accuracy of seatbelt detection rises from 95\% to
                 99\%, and the root mean square error of speed
                 estimation is reduced from 2.64 to 1.87.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bai:2022:PPO,
  author =       "Tianyu Bai and Song Fu and Qing Yang",
  title =        "Privacy-Preserving Object Detection with Secure
                 Convolutional Neural Networks for Vehicular Edge
                 Computing",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "11",
  pages =        "316",
  day =          "31",
  month =        oct,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14110316",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 25 11:05:26 MST 2022",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/11/316",
  abstract =     "With the wider adoption of edge computing services,
                 intelligent edge devices, and high-speed V2X
                 communication, compute-intensive tasks for autonomous
                 vehicles, such as object detection using camera, LiDAR,
                 and/or radar data, can be partially offloaded to
                 road-side edge servers. However, data privacy becomes a
                 major concern for vehicular edge computing, as
                 sensitive sensor data from vehicles can be observed and
                 used by edge servers. We aim to address the privacy
                 problem by protecting both vehicles' sensor data and
                 the detection results. In this paper, we present
                 vehicle--edge cooperative deep-learning networks with
                 privacy protection for object-detection tasks, named
                 vePOD for short. In vePOD, we leverage the additive
                 secret sharing theory to develop secure functions for
                 every layer in an object-detection convolutional neural
                 network (CNN). A vehicle's sensor data is split and
                 encrypted into multiple secret shares, each of which is
                 processed on an edge server by going through the secure
                 layers of a detection network. The detection results
                 can only be obtained by combining the partial results
                 from the participating edge servers. We have developed
                 proof-of-concept detection networks with secure layers:
                 vePOD Faster R-CNN (two-stage detection) and vePOD YOLO
                 (single-stage detection). Experimental results on
                 public datasets show that vePOD does not degrade the
                 accuracy of object detection and, most importantly, it
                 protects data privacy for vehicles. The execution of a
                 vePOD object-detection network with secure layers is
                 orders of magnitude faster than the existing approaches
                 for data privacy. To the best of our knowledge, this is
                 the first work that targets privacy protection in
                 object-detection tasks with vehicle--edge cooperative
                 computing.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hu:2022:SSG,
  author =       "Jingyuan Hu and Zhouwang Yang",
  title =        "Single-Shot Global and Local Context Refinement Neural
                 Network for Head Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "384",
  day =          "19",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120384",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/384",
  abstract =     "Head detection is a fundamental task, and it plays an
                 important role in many head-related problems. The
                 difficulty in creating the local and global context in
                 the face of significant lighting, orientation, and
                 occlusion uncertainty, among other factors, still makes
                 this task a remarkable challenge. To tackle these
                 problems, this paper proposes an effective detector,
                 the Context Refinement Network (CRN), that captures not
                 only the refined global context but also the enhanced
                 local context. We use simplified non-local (SNL) blocks
                 at hierarchical features, which can successfully
                 establish long-range dependencies between heads to
                 improve the capability of building the global context.
                 We suggest a multi-scale dilated convolutional module
                 for the local context surrounding heads that extracts
                 local context from various head characteristics. In
                 comparison to other models, our method outperforms them
                 on the Brainwash and the HollywoodHeads datasets.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kirigin:2022:GBT,
  author =       "Tajana Ban Kirigin and Sanda Bujaci{\'c} Babi{\'c} and
                 Benedikt Perak",
  title =        "Graph-Based Taxonomic Semantic Class Labeling",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "383",
  day =          "19",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120383",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/383",
  abstract =     "We present a graph-based method for the lexical task
                 of labeling senses of polysemous lexemes. The labeling
                 task aims at generalizing sense features of a lexical
                 item in a corpus using more abstract concepts. In this
                 method, a coordination dependency-based lexical graph
                 is first constructed with clusters of conceptually
                 associated lexemes representing related senses and
                 conceptual domains of a source lexeme. The label
                 abstraction is based on the syntactic patterns of the x
                 is\_a y dependency relation. For each sense cluster, an
                 additional lexical graph is constructed by extracting
                 label candidates from a corpus and selecting the most
                 prominent is\_a collocates in the constructed label
                 graph. The obtained label lexemes represent the sense
                 abstraction of the cluster of conceptually associated
                 lexemes. In a similar graph-based procedure, the
                 semantic class representation is validated by
                 constructing a WordNet hypernym relation graph. These
                 additional labels indicate the most appropriate
                 hypernym category of a lexical sense community. The
                 proposed labeling method extracts hierarchically
                 abstract conceptual content and the sense semantic
                 features of the polysemous source lexeme, which can
                 facilitate lexical understanding and build corpus-based
                 taxonomies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ghosh:2022:CPS,
  author =       "Uttam Ghosh and Deepak Tosh and Nawab Muhammad Faseeh
                 Qureshi and Ali Kashif Bashir and Al-Sakib Khan Pathan
                 and Zhaolong Ning",
  title =        "Cyber-Physical Systems: Prospects, Challenges and Role
                 in Software-Defined Networking and Blockchains",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "382",
  day =          "18",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120382",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/382",
  abstract =     "We present a graph-based method for the lexical task
                 of labeling senses of polysemous lexemes. The labeling
                 task aims at generalizing sense features of a lexical
                 item in a corpus using more abstract concepts. In this
                 method, a coordination dependency-based lexical graph
                 is first constructed with clusters of conceptually
                 associated lexemes representing related senses and
                 conceptual domains of a source lexeme. The label
                 abstraction is based on the syntactic patterns of the x
                 is\_a y dependency relation. For each sense cluster, an
                 additional lexical graph is constructed by extracting
                 label candidates from a corpus and selecting the most
                 prominent is\_a collocates in the constructed label
                 graph. The obtained label lexemes represent the sense
                 abstraction of the cluster of conceptually associated
                 lexemes. In a similar graph-based procedure, the
                 semantic class representation is validated by
                 constructing a WordNet hypernym relation graph. These
                 additional labels indicate the most appropriate
                 hypernym category of a lexical sense community. The
                 proposed labeling method extracts hierarchically
                 abstract conceptual content and the sense semantic
                 features of the polysemous source lexeme, which can
                 facilitate lexical understanding and build corpus-based
                 taxonomies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fiorentino:2022:MSS,
  author =       "Michele Fiorentino and Marina Ricci and Alessandro
                 Evangelista and Vito Modesto Manghisi and Antonio
                 Emmanuele Uva",
  title =        "A Multi-Sensory In-Store Virtual Reality Customer
                 Journey for Retailing: a Field Study in a Furniture
                 Flagship Store",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "381",
  day =          "16",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120381",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/381",
  abstract =     "The choice of furniture in a retail store is usually
                 based on a product catalog and simplistic product
                 renderings with different configurations. We present a
                 preliminary field study that tests a Multi-Sensory
                 In-Store Virtual Reality Customer Journey (MSISVRCJ)
                 through a virtual catalog and a product configurator to
                 support furnishings sales. The system allows customers
                 to stay immersed in the virtual environment (VE) while
                 the sales expert changes the colors, textures, and
                 finishes of the furniture, also exploring different
                 VEs. In addition, customers can experience realistic
                 tactile feedback with in-store samples of furniture
                 they can test. The journey is implemented for a
                 furniture manufacturer and tested in a flagship store.
                 Fifty real customers show positive feedback in terms of
                 general satisfaction, perceived realism, and
                 acceptance. This method can increase purchase
                 confidence, reduce entrepreneurial costs, and leverage
                 in-store versus online shopping.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chung:2022:CAS,
  author =       "Jen-Li Chung and Lee-Yeng Ong and Meng-Chew Leow",
  title =        "Comparative Analysis of Skeleton-Based Human Pose
                 Estimation",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "380",
  day =          "15",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120380",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/380",
  abstract =     "Human pose estimation (HPE) has become a prevalent
                 research topic in computer vision. The technology can
                 be applied in many areas, such as video surveillance,
                 medical assistance, and sport motion analysis. Due to
                 higher demand for HPE, many HPE libraries have been
                 developed in the last 20 years. In the last 5 years,
                 more and more skeleton-based HPE algorithms have been
                 developed and packaged into libraries to provide ease
                 of use for researchers. Hence, the performance of these
                 libraries is important when researchers intend to
                 integrate them into real-world applications for video
                 surveillance, medical assistance, and sport motion
                 analysis. However, a comprehensive performance
                 comparison of these libraries has yet to be conducted.
                 Therefore, this paper aims to investigate the strengths
                 and weaknesses of four popular state-of-the-art
                 skeleton-based HPE libraries for human pose detection,
                 including OpenPose, PoseNet, MoveNet, and MediaPipe
                 Pose. A comparative analysis of these libraries based
                 on images and videos is presented in this paper. The
                 percentage of detected joints (PDJ) was used as the
                 evaluation metric in all comparative experiments to
                 reveal the performance of the HPE libraries. MoveNet
                 showed the best performance for detecting different
                 human poses in static images and videos.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Anoh:2022:WCS,
  author =       "Kelvin Anoh and Chan Hwang See and Yousef Dama and
                 Raed A. Abd-Alhameed and Simeon Keates",
  title =        "{6G} Wireless Communication Systems: Applications,
                 Opportunities and Challenges",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "379",
  day =          "15",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120379",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/379",
  abstract =     "As the technical specifications of the 5th Generation
                 (5G) wireless communication standard are being wrapped
                 up, there are growing efforts amongst researchers,
                 industrialists, and standardisation bodies on the
                 enabling technologies of a 6G standard or the so-called
                 Beyond 5G (B5G) one. Although the 5G standard has
                 presented several benefits, there are still some
                 limitations within it. Such limitations have motivated
                 the setting up of study groups to determine suitable
                 technologies that should operate in the year 2030 and
                 beyond, i.e., after 5G. Consequently, this Special
                 Issue of Future Internet concerning what possibilities
                 lie ahead for a 6G wireless network includes four
                 high-quality research papers (three of which are review
                 papers with over 412 referred sources and one regular
                 research). This editorial piece summarises the major
                 contributions of the articles and the Special Issue,
                 outlining future directions for new research.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Surantha:2022:ISN,
  author =       "Nico Surantha and Noffal A. Putra",
  title =        "Integrated {SDN-NFV} {5G} Network Performance and
                 Management-Complexity Evaluation",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "378",
  day =          "14",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120378",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/378",
  abstract =     "Digitalization is one of the factors that affects the
                 acceleration of the application of telecommunications
                 technologies such as 5G. The 5G technology that has
                 been developed today does not yet meet different
                 performance and manageability standards, particularly
                 for data center networks as a supportive technology.
                 Software-defined networking (SDN) and network function
                 virtualization (NFV) are two complementary technologies
                 that are currently used by almost all data centers in
                 the telecommunications industry to rectify performance
                 and manageability issues. In this study, we deliver an
                 integrated SDN-NFV architecture to simplify network
                 management activities in telecommunication companies.
                 To improve network performance at the computing level,
                 we performed a modification of a networking system at
                 the computing level, underlying NFV devices by
                 replacing the default virtual switch with a data plane
                 development kit (DPDK) and single root I/O
                 virtualization (SR-IOV). This study evaluated the
                 proposed architecture design in terms of network
                 performance and manageability. Based on 30 days of
                 observation in prime time, the proposed solution
                 increased throughput up to 200 Mbps for the server leaf
                 and 1.6 Gbps for the border leaf compared to the legacy
                 architecture. Meanwhile, the latency decreased to 12 ms
                 for the server leaf and 17 ms for the border leaf. For
                 manageability, we tested three different scenarios and
                 achieved savings of 13 min for Scenario 1, 22 min for
                 Scenario 2 and 9 min for Scenario 3.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Al-Saedi:2022:FCE,
  author =       "Ahmed A. Al-Saedi and Veselka Boeva and Emiliano
                 Casalicchio",
  title =        "{FedCO}: Communication-Efficient Federated Learning
                 via Clustering Optimization",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "377",
  day =          "13",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120377",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/377",
  abstract =     "Federated Learning (FL) provides a promising solution
                 for preserving privacy in learning shared models on
                 distributed devices without sharing local data on a
                 central server. However, most existing work shows that
                 FL incurs high communication costs. To address this
                 challenge, we propose a clustering-based federated
                 solution, entitled Federated Learning via Clustering
                 Optimization (FedCO), which optimizes model aggregation
                 and reduces communication costs. In order to reduce the
                 communication costs, we first divide the participating
                 workers into groups based on the similarity of their
                 model parameters and then select only one
                 representative, the best performing worker, from each
                 group to communicate with the central server. Then, in
                 each successive round, we apply the Silhouette
                 validation technique to check whether each
                 representative is still made tight with its current
                 cluster. If not, the representative is either moved
                 into a more appropriate cluster or forms a cluster
                 singleton. Finally, we use split optimization to update
                 and improve the whole clustering solution. The updated
                 clustering is used to select new cluster
                 representatives. In that way, the proposed FedCO
                 approach updates clusters by repeatedly evaluating and
                 splitting clusters if doing so is necessary to improve
                 the workers' partitioning. The potential of the
                 proposed method is demonstrated on publicly available
                 datasets and LEAF datasets under the IID and Non-IID
                 data distribution settings. The experimental results
                 indicate that our proposed FedCO approach is superior
                 to the state-of-the-art FL approaches, i.e., FedAvg,
                 FedProx, and CMFL, in reducing communication costs and
                 achieving a better accuracy in both the IID and Non-IID
                 cases.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2022:EER,
  author =       "Yinglin Wang and Xinyu Xu",
  title =        "{ERGCN}: Enhanced Relational Graph Convolution
                 Network, an Optimization for Entity Prediction Tasks on
                 Temporal Knowledge Graphs",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "376",
  day =          "13",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120376",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/376",
  abstract =     "Reasoning on temporal knowledge graphs, which aims to
                 infer new facts from existing knowledge, has attracted
                 extensive attention and in-depth research recently. One
                 of the important tasks of reasoning on temporal
                 knowledge graphs is entity prediction, which focuses on
                 predicting the missing objects in facts at current time
                 step when relevant histories are known. The problem is
                 that, for entity prediction task on temporal knowledge
                 graphs, most previous studies pay attention to
                 aggregating various semantic information from entities
                 but ignore the impact of semantic information from
                 relation types. We believe that relation types is a
                 good supplement for our task and making full use of
                 semantic information of facts can promote the results.
                 Therefore, a framework of Enhanced Relational Graph
                 Convolution Network (ERGCN) is put forward in this
                 paper. Rather than only considering representations of
                 entities, the context semantic information of both
                 relations and entities is considered and merged
                 together in this framework. Experimental results show
                 that the proposed approach outperforms the
                 state-of-the-art methods.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gwyn:2022:EGB,
  author =       "Tony Gwyn and Kaushik Roy",
  title =        "Examining Gender Bias of Convolutional Neural Networks
                 via Facial Recognition",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "375",
  day =          "13",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120375",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/375",
  abstract =     "Image recognition technology systems have existed in
                 the realm of computer security since nearly the
                 inception of electronics, and have seen vast
                 improvements in recent years. Currently implemented
                 facial detection systems regularly achieve accuracy
                 rates close to 100 percent. This includes even
                 challenging environments, such as with low light or
                 skewed images. Despite this near perfect performance,
                 the problem of gender bias with respect to accuracy is
                 still inherent in many current facial recognition
                 algorithms. This bias needs to be addressed to make
                 facial recognition a more complete and useful system.
                 In particular, current image recognition system tend to
                 have poor accuracy concerning underrepresented groups,
                 including minorities and female individuals. The goal
                 of this research is to increase the awareness of this
                 bias issue, as well as to create a new model for image
                 recognition that is gender independent. To achieve this
                 goal, a variety of Convolutional Neural Networks (CNNs)
                 will be tested for accuracy as it pertains to gender
                 bias. In the future, the most accurate CNNs will then
                 be implemented into a new network with the goal of
                 creating a program which is better able to distinguish
                 individuals with a high accuracy, but without gender
                 bias. At present, our research has identified two
                 specific CNNs, VGG-16 and ResNet50, which we believe
                 will be ideal for the creation of this new CNN
                 algorithm.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Perez-Jorge:2022:GSA,
  author =       "David P{\'e}rez-Jorge and Mar{\'\i}a Carmen
                 Mart{\'\i}nez-Murciano",
  title =        "Gamification with Scratch or App Inventor in Higher
                 Education: a Systematic Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "374",
  day =          "13",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120374",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/374",
  abstract =     "Programming skills should be taught and developed;
                 Scratch and App Inventor are two tools that can
                 contribute significantly to developing this competence
                 in university students. This study aims to investigate
                 the use and effect of the programming language Scratch
                 and App Inventor on the development of skills and
                 competencies for learning (autonomy, attention,
                 motivation, critical thinking, creative thinking,
                 computational thinking, communication, problem solving
                 and social interaction) in higher education. To achieve
                 this goal, a systematic review of articles in English
                 and Spanish was carried out using the PRISMA statement
                 (research publication guidelines designed to improve
                 the integrity of systematic review and meta-analysis
                 reports). A search for studies was conducted in the Web
                 of Science (WOS), Dialnet, and SCOPUS. A total of 405
                 papers were analyzed, of which 11 were finally
                 selected. The results showed that both Scratch and App
                 Inventor favor the development of skills and
                 competencies for learning in the context of higher
                 education, despite being underutilized strategies that
                 all knowledge disciplines should promote.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Omasheye:2022:JRF,
  author =       "Okiemute Roberts Omasheye and Samuel Azi and Joseph
                 Isabona and Agbotiname Lucky Imoize and Chun-Ta Li and
                 Cheng-Chi Lee",
  title =        "Joint Random Forest and Particle Swarm Optimization
                 for Predictive Pathloss Modeling of Wireless Signals
                 from Cellular Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "373",
  day =          "12",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120373",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/373",
  abstract =     "The accurate and reliable predictive estimation of
                 signal attenuation loss is of prime importance in radio
                 resource management. During wireless network design and
                 planning, a reliable path loss model is required for
                 optimal predictive estimation of the received signal
                 strength, coverage, quality, and signal
                 interference-to-noise ratio. A set of trees (100) on
                 the target measured data was employed to determine the
                 most informative and important subset of features,
                 which were in turn employed as input data to the
                 Particle Swarm (PS) model for predictive path loss
                 analysis. The proposed Random Forest (RF-PS) based
                 model exhibited optimal precision performance in the
                 real-time prognostic analysis of measured path loss
                 over operational 4G LTE networks in Nigeria. The
                 relative performance of the proposed RF-PS model was
                 compared to the standard PS and hybrid radial basis
                 function-particle swarm optimization (RBF-PS) algorithm
                 for benchmarking. Generally, results indicate that the
                 proposed RF-PS model gave better prediction accuracy
                 than the standard PS and RBF-PS models across the
                 investigated environments. The projected hybrid model
                 would find useful applications in path loss modeling in
                 related wireless propagation environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Meng:2022:IFI,
  author =       "Weizhi Meng and Thanassis Giannetsos and Christian D.
                 Jensen",
  title =        "Information and Future {Internet} Security, Trust and
                 Privacy",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "372",
  day =          "12",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120372",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/372",
  abstract =     "The Internet has rapidly grown into a distributed and
                 collaborative network with over one billion users,
                 e.g., the Internet of Things (IoT). The future Internet
                 will become the core of the next information
                 infrastructure in regard to computation and
                 communication, being capable of extensibility,
                 survivability, mobility, and adaptability. However,
                 with the increasing complexity of the future Internet
                 and boost in information sharing, there is a threat to
                 such infrastructure in the aspects of security, trust,
                 and privacy. This editorial discusses the
                 state-of-the-art advancements in information and the
                 future internet.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Vemuru:2022:ICE,
  author =       "Krishnamurthy V. Vemuru",
  title =        "Implementation of the Canny Edge Detector Using a
                 Spiking Neural Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "371",
  day =          "11",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120371",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/371",
  abstract =     "Edge detectors are widely used in computer vision
                 applications to locate sharp intensity changes and find
                 object boundaries in an image. The Canny edge detector
                 is the most popular edge detector, and it uses a
                 multi-step process, including the first step of noise
                 reduction using a Gaussian kernel and a final step to
                 remove the weak edges by the hysteresis threshold. In
                 this work, a spike-based computing algorithm is
                 presented as a neuromorphic analogue of the Canny edge
                 detector, where the five steps of the conventional
                 algorithm are processed using spikes. A spiking neural
                 network layer consisting of a simplified version of a
                 conductance-based Hodgkin--Huxley neuron as a building
                 block is used to calculate the gradients. The
                 effectiveness of the spiking neural-network-based
                 algorithm is demonstrated on a variety of images,
                 showing its successful adaptation of the principle of
                 the Canny edge detector. These results demonstrate that
                 the proposed algorithm performs as a complete spike
                 domain implementation of the Canny edge detector.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Pires:2022:SOT,
  author =       "Ivan Miguel Pires",
  title =        "Smart Objects and Technologies for Social Good",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "370",
  day =          "09",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120370",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/370",
  abstract =     "Edge detectors are widely used in computer vision
                 applications to locate sharp intensity changes and find
                 object boundaries in an image. The Canny edge detector
                 is the most popular edge detector, and it uses a
                 multi-step process, including the first step of noise
                 reduction using a Gaussian kernel and a final step to
                 remove the weak edges by the hysteresis threshold. In
                 this work, a spike-based computing algorithm is
                 presented as a neuromorphic analogue of the Canny edge
                 detector, where the five steps of the conventional
                 algorithm are processed using spikes. A spiking neural
                 network layer consisting of a simplified version of a
                 conductance-based Hodgkin--Huxley neuron as a building
                 block is used to calculate the gradients. The
                 effectiveness of the spiking neural-network-based
                 algorithm is demonstrated on a variety of images,
                 showing its successful adaptation of the principle of
                 the Canny edge detector. These results demonstrate that
                 the proposed algorithm performs as a complete spike
                 domain implementation of the Canny edge detector.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Singh:2022:LLS,
  author =       "Surjit Singh and Vivek Mehla and Srete Nikolovski",
  title =        "{LSSDNF}: a Lightweight Secure Software Defined
                 Network Framework for Future {Internet} in {5G--6G}",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "369",
  day =          "08",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120369",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/369",
  abstract =     "As information technology advances quickly, so does
                 the 5G--6G network management system, which is moving
                 toward greater integration, decentralization,
                 diversity, and intelligence. As flexibility is a
                 crucial criterion for 5G--6G network architecture, we
                 use the Software Defined Network (SDN) paradigm to make
                 the programmability more flexible. Due to their ability
                 to replace the current TCP/IP architecture with one
                 that separates the control plane and data plane,
                 software-defined networks have gained much popularity.
                 However, they are susceptible to routing attacks.
                 Therefore, this work proposes Lightweight Security
                 Framework that combines blockchain technology with
                 Software-Defined Networking (LSSDNF) to address this
                 problem. The proposed framework adds the routing data
                 that the controller withheld to the multichain
                 blockchain. Here, a mininet network simulator is used
                 to model the proposed framework. The data transfer rate
                 or network throughput, bandwidth variation, and jitter
                 have all been used to assess the performance of
                 single-controller-SDN networks and multi-controller-SDN
                 networks. The results demonstrate that the proposed
                 framework performs better than the conventional
                 single-controller-SDN architecture in terms of
                 throughput, bandwidth fluctuation, and jitter.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Goudarzi:2022:HUS,
  author =       "Pejman Goudarzi and Mehdi Hosseinpour and Roham
                 Goudarzi and Jaime Lloret",
  title =        "Holistic Utility Satisfaction in Cloud Data Centre
                 Network Using Reinforcement Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "368",
  day =          "08",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120368",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/368",
  abstract =     "Cloud computing leads to efficient resource allocation
                 for network users. In order to achieve efficient
                 allocation, many research activities have been
                 conducted so far. Some researchers focus on classical
                 optimisation theory techniques (such as multi-objective
                 optimisation, evolutionary optimisation, game theory,
                 etc.) to satisfy network providers and network users'
                 service-level agreement (SLA) requirements. Normally,
                 in a cloud data centre network (CDCN), it is difficult
                 to jointly satisfy both the cloud provider and cloud
                 customer' utilities, and this leads to complex
                 combinatorial problems, which are usually NP-hard.
                 Recently, machine learning and artificial intelligence
                 techniques have received much attention from the
                 networking community because of their capability to
                 solve complicated networking problems. In the current
                 work, at first, the holistic utility satisfaction for
                 the cloud data centre provider and customers is
                 formulated as a reinforcement learning (RL) problem
                 with a specific reward function, which is a convex
                 summation of users' utility functions and cloud
                 provider's utility. The user utility functions are
                 modelled as a function of cloud virtualised resources
                 (such as storage, CPU, RAM), connection bandwidth, and
                 also, the network-based expected packet loss and
                 round-trip time factors associated with the cloud
                 users. The cloud provider utility function is modelled
                 as a function of resource prices and energy dissipation
                 costs. Afterwards, a Q-learning implementation of the
                 mentioned RL algorithm is introduced, which is able to
                 converge to the optimal solution in an online and fast
                 manner. The simulation results exhibit the enhanced
                 convergence speed and computational complexity
                 properties of the proposed method in comparison with
                 similar approaches from the joint cloud
                 customer/provider utility satisfaction perspective. To
                 evaluate the scalability property of the proposed
                 method, the results are also repeated for different
                 cloud user population scenarios (small, medium, and
                 large).",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Campos-Castillo:2022:PCA,
  author =       "Celeste Campos-Castillo and Noelle Chesley and Onur
                 Asan",
  title =        "Professionals as Change Agents or Instruments of
                 Reproduction? {Medical} Residents' Reasoning for Not
                 Sharing the Electronic Health Record Screen with
                 Patients",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "367",
  day =          "07",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120367",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/367",
  abstract =     "The stability of physicians' authority over patients
                 despite decades of changes in medicine conflicts with
                 newer institutionalist accounts of professionals as
                 change agents rather than instruments of reproduction.
                 We analyzed whether the cultural scripts that
                 twenty-one residents used to justify their approach to
                 a new change, the electronic health record (EHR),
                 signaled a leveling of the patient-physician hierarchy.
                 Residents are intriguing because their position makes
                 them open to change. Indeed, residents justified using
                 the EHR in ways that level the patient-physician
                 hierarchy, but also offered rationales that sustain it.
                 For the latter, residents described using the EHR to
                 substantiate their expertise, situate themselves as
                 brokers between patients and the technology, and
                 preserve the autonomy of clinicians. Our findings
                 highlight how professionals with little direct
                 experience before a change can selectively apply
                 incumbent scripts to sustain extant structures, while
                 informing newer institutionalist accounts of
                 professionals and the design of EHR systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Cheimaras:2022:LCO,
  author =       "Vasileios Cheimaras and Athanasios Trigkas and
                 Panagiotis Papageorgas and Dimitrios Piromalis and
                 Emmanouil Sofianopoulos",
  title =        "A Low-Cost Open-Source Architecture for a Digital
                 Signage Emergency Evacuation System for Cruise Ships,
                 Based on {IoT} and {LTE\slash 4G} Technologies",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "366",
  day =          "07",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120366",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/366",
  abstract =     "During a ship evacuation, many people panic as they do
                 not know the direction that leads to the emergency
                 muster station. Moreover, sometimes passengers get
                 crowded in corridors or stairs, so they cannot save
                 their lives. This paper proposes an IoT-enabled
                 architecture for digital signage systems that directs
                 passengers to the muster stations of a cruise ship by
                 following the less dangerous route. Thus, crews' and
                 passengers' safety risks during a ship evacuation can
                 be low, and human health hazards may be limited. The
                 system is based on a low-cost and open-source
                 architecture that can also be used in a variety of
                 fields in industrial IoT applications. The proposed
                 modular digital signage architecture utilizes Light
                 Emitting Diode (LED) strips that are remotely managed
                 through a private Long-Term Evolution (LTE)/Fourth
                 Generation (4G) cellular network. Publish--subscribe
                 communication protocols were used for the control of
                 the digital strips and particularly through a Message
                 Queuing Telemetry Transport (MQTT) broker who
                 publishes/subscribes every message to specific topics
                 of the realized IoT platform, while the overall digital
                 signage system centralization was implemented with an
                 appropriate dashboard supported from an open-source
                 RESTful API.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Taha:2022:ELE,
  author =       "Ashraf A. Taha and Hagar O. Abouroumia and Shimaa A.
                 Mohamed and Lamiaa A. Amar",
  title =        "Enhancing the Lifetime and Energy Efficiency of
                 Wireless Sensor Networks Using {Aquila Optimizer}
                 Algorithm",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "365",
  day =          "07",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120365",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/365",
  abstract =     "As sensors are distributed among wireless sensor
                 networks (WSNs), ensuring that the batteries and
                 processing power last for a long time, to improve
                 energy consumption and extend the lifetime of the WSN,
                 is a significant challenge in the design of network
                 clustering techniques. The sensor nodes are divided in
                 these techniques into clusters with different cluster
                 heads (CHs). Recently, certain considerations such as
                 less energy consumption and high reliability have
                 become necessary for selecting the optimal CH nodes in
                 clustering-based metaheuristic techniques. This paper
                 introduces a novel enhancement algorithm using Aquila
                 Optimizer (AO), which enhances the energy balancing in
                 clusters across sensor nodes during network
                 communications to extend the network lifetime and
                 reduce power consumption. Lifetime and
                 energy-efficiency clustering algorithms, namely the
                 low-energy adaptive clustering hierarchy (LEACH)
                 protocol as a traditional protocol, genetic algorithm
                 (GA), Coyote Optimization Algorithm (COY), Aquila
                 Optimizer (AO), and Harris Hawks Optimization (HHO),
                 are evaluated in a wireless sensor network. The paper
                 concludes that the proposed AO algorithm outperforms
                 other algorithms in terms of alive nodes analysis and
                 energy consumption.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liborio:2022:IVD,
  author =       "Joao da Mata Liborio and Cesar Melo and Marcos Silva",
  title =        "{Internet} Video Delivery Improved by Super-Resolution
                 with {GAN}",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "364",
  day =          "06",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120364",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/364",
  abstract =     "In recent years, image and video super-resolution have
                 gained attention outside the computer vision community
                 due to the outstanding results produced by applying
                 deep-learning models to solve the super-resolution
                 problem. These models have been used to improve the
                 quality of videos and images. In the last decade,
                 video-streaming applications have also become popular.
                 Consequently, they have generated traffic with an
                 increasing quantity of data in network infrastructures,
                 which continues to grow, e.g., global video traffic is
                 forecast to increase from 75\% in 2017 to 82\% in 2022.
                 In this paper, we leverage the power of
                 deep-learning-based super-resolution methods and
                 implement a model for video super-resolution, which we
                 call VSRGAN+. We train our model with a dataset
                 proposed to teach systems for high-level visual
                 comprehension tasks. We also test it on a large-scale
                 JND-based coded video quality dataset containing 220
                 video clips with four different resolutions.
                 Additionally, we propose a cloud video-delivery
                 framework that uses video super-resolution. According
                 to our findings, the VSRGAN+ model can reconstruct
                 videos without perceptual distinction of the ground
                 truth. Using this model with added compression can
                 decrease the quantity of data delivered to surrogate
                 servers in a cloud video-delivery framework. The
                 traffic decrease reaches 98.42\% in total.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Schizas:2022:TUL,
  author =       "Nikolaos Schizas and Aristeidis Karras and Christos
                 Karras and Spyros Sioutas",
  title =        "{TinyML} for Ultra-Low Power {AI} and Large Scale
                 {IoT} Deployments: a Systematic Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "363",
  day =          "06",
  month =        dec,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120363",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/363",
  abstract =     "The rapid emergence of low-power embedded devices and
                 modern machine learning (ML) algorithms has created a
                 new Internet of Things (IoT) era where lightweight ML
                 frameworks such as TinyML have created new
                 opportunities for ML algorithms running within edge
                 devices. In particular, the TinyML framework in such
                 devices aims to deliver reduced latency, efficient
                 bandwidth consumption, improved data security,
                 increased privacy, lower costs and overall network cost
                 reduction in cloud environments. Its ability to enable
                 IoT devices to work effectively without constant
                 connectivity to cloud services, while nevertheless
                 providing accurate ML services, offers a viable
                 alternative for IoT applications seeking cost-effective
                 solutions. TinyML intends to deliver on-premises
                 analytics that bring significant value to IoT services,
                 particularly in environments with limited connection.
                 This review article defines TinyML, presents an
                 overview of its benefits and uses and provides
                 background information based on up-to-date literature.
                 Then, we demonstrate the TensorFlow Lite framework
                 which supports TinyML along with analytical steps for
                 an ML model creation. In addition, we explore the
                 integration of TinyML with network technologies such as
                 5G and LPWAN. Ultimately, we anticipate that this
                 analysis will serve as an informational pillar for the
                 IoT/Cloud research community and pave the way for
                 future studies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Florea:2022:GTA,
  author =       "Razvan Florea and Mitica Craus",
  title =        "A Game-Theoretic Approach for Network Security Using
                 Honeypots",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "362",
  day =          "30",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120362",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/362",
  abstract =     "Cybersecurity plays an increasing role in today's
                 digital space, and its methods must keep pace with the
                 changes. Both public and private sector researchers
                 have put efforts into strengthening the security of
                 networks by proposing new approaches. This paper
                 presents a method to solve a game theory model by
                 defining the contents of the game payoff matrix and
                 incorporating honeypots in the defense strategy. Using
                 a probabilistic approach we propose the
                 course-of-action Stackelberg game (CoASG), where every
                 path of the graph leads to an undesirable state based
                 on security issues found in every host. The reality of
                 the system is represented by a cost function which
                 helps us to define a payoff matrix and find the best
                 possible combination of the strategies once the game is
                 run. The results show the benefits of using this model
                 in the early prevention stages for detecting
                 cyberattack patterns.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Battisti:2022:NSV,
  author =       "Anselmo Luiz {\'E}den Battisti and Evandro Luiz
                 Cardoso Macedo and Marina Ivanov Pereira Josu{\'e} and
                 Hugo Barbalho and Fl{\'a}via C. Delicato and D{\'e}bora
                 Christina Muchaluat-Saade and Paulo F. Pires and
                 Douglas Paulo de Mattos and Ana Cristina Bernardo de
                 Oliveira",
  title =        "A Novel Strategy for {VNF} Placement in Edge Computing
                 Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "361",
  day =          "30",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120361",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/361",
  abstract =     "Network function virtualization (NFV) is a novel
                 technology that virtualizes computing, network, and
                 storage resources to decouple the network functions
                 from the underlying hardware, thus allowing the
                 software implementation of such functions to run on
                 commodity hardware. By doing this, NFV provides the
                 necessary flexibility to enable agile, cost-effective,
                 and on-demand service delivery models combined with
                 automated management. Different management and
                 orchestration challenges arise in such virtualized and
                 distributed environments. A major challenge in the
                 selection of the most suitable edge nodes is that of
                 deploying virtual network functions (VNFs) to meet
                 requests from multiple users. This article addresses
                 the VNF placement problem by providing a novel integer
                 linear programming (ILP) optimization model and a novel
                 VNF placement algorithm. In our definition, the
                 multi-objective optimization problem aims to (i)
                 minimize the energy consumption in the edge nodes; (ii)
                 minimize the total latency; and (iii) reducing the
                 total cost of the infrastructure. Our new solution
                 formulates the VNF placement problem by taking these
                 three objectives into account simultaneously. In
                 addition, the novel VNF placement algorithm leverages
                 VNF sharing, which reuses VNF instances already placed
                 to potentially reduce computational resource usage.
                 Such a feature is still little explored in the
                 community. Through simulation, numerical results show
                 that our approach can perform better than other
                 approaches found in the literature regarding resource
                 consumption and the number of SFC requests met.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rodrigues:2022:QPP,
  author =       "Pedro Rodrigues and Filipe Freitas and Jos{\'e}
                 Sim{\~a}o",
  title =        "{QuickFaaS}: Providing Portability and
                 Interoperability between {FaaS} Platforms",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "360",
  day =          "30",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120360",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/360",
  abstract =     "Serverless computing hides infrastructure management
                 from developers and runs code on-demand automatically
                 scaled and billed during the code's execution time. One
                 of the most popular serverless backend services is
                 called Function-as-a-Service (FaaS), in which
                 developers are often confronted with cloud-specific
                 requirements. Function signature requirements, and the
                 usage of custom libraries that are unique to cloud
                 providers, were identified as the two main reasons for
                 portability issues in FaaS applications, leading to
                 various vendor lock-in problems. In this work, we
                 define three cloud-agnostic models that compose FaaS
                 platforms. Based on these models, we developed
                 QuickFaaS, a multi-cloud interoperability desktop tool
                 targeting cloud-agnostic functions and FaaS
                 deployments. The proposed cloud-agnostic approach
                 enables developers to reuse their serverless functions
                 in different cloud providers with no need to change
                 code or install extra software. We also provide an
                 evaluation that validates the proposed solution by
                 measuring the impact of a cloud-agnostic approach on
                 the function's performance, when compared to a
                 cloud-non-agnostic one. The study shows that a
                 cloud-agnostic approach does not significantly impact
                 the function's performance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yakunin:2022:CIT,
  author =       "Alexander V. Yakunin and Svetlana S. Bodrunova",
  title =        "Cumulative Impact of Testing Factors in Usability
                 Tests for Human-Centered {Web} Design",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "359",
  day =          "30",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120359",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/359",
  abstract =     "The study examines the cumulative impact of factors
                 that affect usability testing for user-centered web
                 design, namely the so-called `contextual fidelity
                 model' factors that include product properties, task
                 features, user traits, and environment/context factors.
                 Today, the design, user experience and usability (DUXU)
                 research experiences a lack of studies that would
                 assess combinatorial, rather than individual, effects
                 of these factors upon user performance. We address this
                 gap by seeing both independent factors and the
                 resulting user states as complex and dynamic, and
                 testing the combined impact of aesthetic quality of
                 websites, user traits, and individual/group experiment
                 settings upon formation of two dysfunctional user
                 states that critically affect user performance, namely
                 monotony and anxiety. We develop a research design that
                 allows for assessing the combinatorial effects in
                 formation of user dysfunctionality. For that, we
                 conduct a study with 80 assessors of Russian/European
                 and Chinese origin in individual/group setting,
                 employing two types of tasks and websites of high/low
                 aesthetic quality. As the results of our experiment
                 show, group task solving enhances the synchronous
                 impact of website aesthetics and task features upon
                 user states. Interaction of high-quality design, group
                 environment, and monotonous tasks provides for an
                 antagonistic effect when aesthetic layout in a group
                 environment significantly reduces the fatigue rate. Low
                 aesthetic quality in a group environment leads to
                 cumulative enhancing of dysfunctionality for both
                 monotony and anxiety. We conclude by setting questions
                 and prospects for further research.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Andelic:2022:DMW,
  author =       "Nikola Andeli{\'c} and Sandi Baressi Segota and Ivan
                 Lorencin and Matko Glucina",
  title =        "Detection of Malicious {Websites} Using Symbolic
                 Classifier",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "358",
  day =          "29",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120358",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/358",
  abstract =     "Malicious websites are web locations that attempt to
                 install malware, which is the general term for anything
                 that will cause problems in computer operation, gather
                 confidential information, or gain total control over
                 the computer. In this paper, a novel approach is
                 proposed which consists of the implementation of the
                 genetic programming symbolic classifier (GPSC)
                 algorithm on a publicly available dataset to obtain a
                 simple symbolic expression (mathematical equation)
                 which could detect malicious websites with high
                 classification accuracy. Due to a large imbalance of
                 classes in the initial dataset, several data sampling
                 methods (random undersampling/oversampling, ADASYN,
                 SMOTE, BorderlineSMOTE, and KmeansSMOTE) were used to
                 balance the dataset classes. For this investigation,
                 the hyperparameter search method was developed to find
                 the combination of GPSC hyperparameters with which high
                 classification accuracy could be achieved. The first
                 investigation was conducted using GPSC with a random
                 hyperparameter search method and each dataset variation
                 was divided on a train and test dataset in a ratio of
                 70:30. To evaluate each symbolic expression, the
                 performance of each symbolic expression was measured on
                 the train and test dataset and the mean and standard
                 deviation values of accuracy (ACC), AUC, precision,
                 recall and f1-score were obtained. The second
                 investigation was also conducted using GPSC with the
                 random hyperparameter search method; however, 70\%,
                 i.e., the train dataset, was used to perform 5-fold
                 cross-validation. If the mean accuracy, AUC, precision,
                 recall, and f1-score values were above 0.97 then final
                 training and testing (train/test 70:30) were performed
                 with GPSC with the same randomly chosen hyperparameters
                 used in a 5-fold cross-validation process and the final
                 mean and standard deviation values of the
                 aforementioned evaluation methods were obtained. In
                 both investigations, the best symbolic expression was
                 obtained in the case where the dataset balanced with
                 the KMeansSMOTE method was used for training and
                 testing. The best symbolic expression obtained using
                 GPSC with the random hyperparameter search method and
                 classic train--test procedure (70:30) on a dataset
                 balanced with the KMeansSMOTE method achieved values of
                 ACC{\={}}, AUC{\={}}, Precsion{\={}}, Recall{\={}} and
                 F1-score{\={}} (with standard deviation)
                 0.9992{\pm}2.249 $ \times $ {10$-$5}, 0.9995{\pm}9.945
                 $ \times $ {10$-$6}, 0.9995{\pm}1.09 $ \times $
                 {10$-$5}, 0.999{\pm}5.17 $ \times $ {10$-$5},
                 0.9992{\pm}5.17 $ \times $ {10$-$6}, respectively. The
                 best symbolic expression obtained using GPSC with a
                 random hyperparameter search method and 5-fold
                 cross-validation on a dataset balanced with the
                 KMeansSMOTE method achieved values of ACC{\={}},
                 AUC{\={}}, Precsion{\={}}, Recall{\={}} and
                 F1-score{\={}} (with standard deviation)
                 0.9994{\pm}1.13 $ \times $ {10$-$5}, 0.9994{\pm}1.2 $
                 \times $ {10$-$5}, 1.0{\pm}0, 0.9988{\pm}2.4 $ \times $
                 {10$-$5}, and 0.9994{\pm}1.2 $ \times $ {10$-$5},
                 respectively.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bottrighi:2022:IIP,
  author =       "Alessio Bottrighi and Marco Guazzone and Giorgio
                 Leonardi and Stefania Montani and Manuel Striani and
                 Paolo Terenziani",
  title =        "Integrating {ISA} and Part-of Domain Knowledge into
                 Process Model Discovery",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "357",
  day =          "28",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120357",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/357",
  abstract =     "The traces of process executions are a strategic
                 source of information, from which a model of the
                 process can be mined. In our recent work, we have
                 proposed SIM (semantic interactive miner), an
                 innovative process mining tool to discover the process
                 model incrementally: it supports the interaction with
                 domain experts, who can selectively merge parts of the
                 model to achieve compactness, generalization, and
                 reduced redundancy. We now propose a substantial
                 extension of SIM, making it able to exploit (both
                 automatically and interactively) pre-encoded taxonomic
                 knowledge about the refinement (ISA relations) and
                 composition (part-of relations) of process activities,
                 as is available in many domains. The extended approach
                 allows analysts to move from a process description
                 where activities are reported at the ground level to
                 more user-interpretable/compact descriptions, in which
                 sets of such activities are abstracted into the
                 ``macro-activities'' subsuming them or constituted by
                 them. An experimental evaluation based on a real-world
                 setting (stroke management) illustrates the advantages
                 of our approach.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Osial:2022:AAI,
  author =       "Magdalena Osial and Agnieszka Pregowska",
  title =        "The Application of Artificial Intelligence in Magnetic
                 Hyperthermia Based Research",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "356",
  day =          "28",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120356",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/356",
  abstract =     "The development of nanomedicine involves complex
                 nanomaterial research involving magnetic nanomaterials
                 and their use in magnetic hyperthermia. The selection
                 of the optimal treatment strategies is time-consuming,
                 expensive, unpredictable, and not consistently
                 effective. Delivering personalized therapy that obtains
                 maximal efficiency and minimal side effects is highly
                 important. Thus, Artificial Intelligence (AI) based
                 algorithms provide the opportunity to overcome these
                 crucial issues. In this paper, we briefly overview the
                 significance of the combination of AI-based methods,
                 particularly the Machine Learning (ML) technique, with
                 magnetic hyperthermia. We considered recent
                 publications, reports, protocols, and review papers
                 from Scopus and Web of Science Core Collection
                 databases, considering the PRISMA-S review methodology
                 on applying magnetic nanocarriers in magnetic
                 hyperthermia. An algorithmic performance comparison in
                 terms of their types and accuracy, data availability
                 taking into account their amount, types, and quality
                 was also carried out. Literature shows AI support of
                 these studies from the physicochemical evaluation of
                 nanocarriers, drug development and release, resistance
                 prediction, dosing optimization, the combination of
                 drug selection, pharmacokinetic profile
                 characterization, and outcome prediction to the heat
                 generation estimation. The papers reviewed here clearly
                 illustrate that AI-based solutions can be considered as
                 an effective supporting tool in drug delivery,
                 including optimization and behavior of nanocarriers,
                 both in vitro and in vivo, as well as the delivery
                 process. Moreover, the direction of future research,
                 including the prediction of optimal experiments and
                 data curation initiatives has been indicated.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kalgaonkar:2022:NES,
  author =       "Priyank Kalgaonkar and Mohamed El-Sharkawy",
  title =        "{NextDet}: Efficient Sparse-to-Dense Object Detection
                 with Attentive Feature Aggregation",
  journal =      j-FUTURE-INTERNET,
  volume =       "14",
  number =       "12",
  pages =        "355",
  day =          "28",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi14120355",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:52 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/14/12/355",
  abstract =     "Object detection is a computer vision task of
                 detecting instances of objects of a certain class,
                 identifying types of objects, determining its location,
                 and accurately labelling them in an input image or a
                 video. The scope of the work presented within this
                 paper proposes a modern object detection network called
                 NextDet to efficiently detect objects of multiple
                 classes which utilizes CondenseNeXt, an award-winning
                 lightweight image classification convolutional neural
                 network algorithm with reduced number of FLOPs and
                 parameters as the backbone, to efficiently extract and
                 aggregate image features at different granularities in
                 addition to other novel and modified strategies such as
                 attentive feature aggregation in the head, to perform
                 object detection and draw bounding boxes around the
                 detected objects. Extensive experiments and ablation
                 tests, as outlined in this paper, are performed on
                 Argoverse-HD and COCO datasets, which provide numerous
                 temporarily sparse to dense annotated images,
                 demonstrate that the proposed object detection
                 algorithm with CondenseNeXt as the backbone result in
                 an increase in mean Average Precision (mAP) performance
                 and interpretability on Argoverse-HD's monocular
                 ego-vehicle camera captured scenarios by up to 17.39\%
                 as well as COCO's large set of images of everyday
                 scenes of real-world common objects by up to 14.62\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Radam:2023:UMS,
  author =       "Neamah S. Radam and Sufyan T. Faraj Al-Janabi and
                 Khalid Sh. Jasim",
  title =        "Using Metaheuristics ({SA-MCSDN}) Optimized for
                 Multi-Controller Placement in Software-Defined
                 Networking",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "39",
  day =          "16",
  month =        jan,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010039",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/39",
  abstract =     "The multi-controller placement problem (MCPP)
                 represents one of the most challenging issues in
                 software-defined networks (SDNs). High-efficiency and
                 scalable optimized solutions can be achieved for a
                 given position in such networks, thereby enhancing
                 various aspects of programmability, configuration, and
                 construction. In this paper, we propose a model called
                 simulated annealing for multi-controllers in SDN
                 (SA-MCSDN) to solve the problem of placing multiple
                 controllers in appropriate locations by considering
                 estimated distances and distribution times among the
                 controllers, as well as between controllers and
                 switches (C2S). We simulated the proposed mathematical
                 model using Network Simulator NS3 in the Linux Ubuntu
                 environment to extract the performance results. We then
                 compared the results of this single-solution algorithm
                 with those obtained by our previously proposed
                 multi-solution harmony search particle swarm
                 optimization (HS-PSO) algorithm. The results reveal
                 interesting aspects of each type of solution. We found
                 that the proposed model works better than previously
                 proposed models, according to some of the metrics upon
                 which the network relies to achieve optimal
                 performance. The metrics considered in this work are
                 propagation delay, round-trip time (RTT), matrix of
                 time session (TS), average delay, reliability,
                 throughput, cost, and fitness value. The simulation
                 results presented herein reveal that the proposed model
                 achieves high reliability and satisfactory throughput
                 with a short access time standard, addressing the
                 issues of scalability and flexibility and achieving
                 high performance to support network efficiency.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rocha:2023:BQV,
  author =       "Geneci da Silva Ribeiro Rocha and Diego Durante
                 M{\"u}hl and Hermenegildo Almeida Chingamba and
                 Let{\'\i}cia de Oliveira and Edson Talamini",
  title =        "Blockchain, Quo Vadis? {Recent} Changes in
                 Perspectives on the Application of Technology in
                 Agribusiness",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "38",
  day =          "16",
  month =        jan,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010038",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/38",
  abstract =     "Information technologies such as blockchain are
                 developing fast, overcoming bottlenecks, and quickly
                 taking advantage of their application. The present
                 study analyzes recent changes concerning the benefits,
                 disadvantages, challenges, and opportunities of
                 blockchain applications in agribusiness. Interviews
                 were conducted with and a questionnaire was applied to
                 professionals working in the development and
                 application of blockchain technology in agribusiness,
                 to compare their perception of the recent advances. The
                 results showed that the importance of blockchain
                 technology to improve governance and information flow
                 along supply chains has increased, and this is the main
                 perceived benefit. The main disadvantages were removing
                 intermediaries and the high cost of implementing the
                 technology. The absence of a widely accepted platform
                 in blockchain operations is the leading and growing
                 challenge, while patterns for blockchain technology
                 seem to be being overcome. The integration of
                 blockchain with new technologies, and the
                 competitiveness provided by the technology, are seen as
                 the main and growing opportunities. Despite the study
                 limitations, we conclude that the benefits and
                 opportunities associated with blockchain application in
                 agribusiness outweigh the challenges and disadvantages
                 in number and importance, and are becoming more
                 relevant.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{deVries:2023:CPM,
  author =       "Sjouke de Vries and Frank Blaauw and Vasilios
                 Andrikopoulos",
  title =        "Cost-Profiling Microservice Applications Using an
                 {APM} Stack",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "37",
  day =          "13",
  month =        jan,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010037",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/37",
  abstract =     "Understanding how the different parts of a
                 cloud-native application contribute to its operating
                 expenses is an important step towards optimizing this
                 cost. However, with the adoption and rollout of
                 microservice architectures, the gathering of the
                 necessary data becomes much more involved and nuanced
                 due to the distributed and heterogeneous nature of
                 these architectures. Existing solutions for this
                 purpose are either closed-source and proprietary or
                 focus only on the infrastructural footprint of the
                 applications. In response to that, in this work, we
                 present a cost-profiling solution aimed at
                 Kubernetes-based microservice applications, building on
                 a popular open-source application performance
                 monitoring (APM) stack. By means of a case study with a
                 data engineering company, we demonstrate how our
                 proposed solution can provide deeper insights into the
                 cost profile of the various application components and
                 drive informed decision-making in managing the
                 deployment of the application.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Grimes:2023:MAA,
  author =       "Sean Grimes and David E. Breen",
  title =        "A Multi-Agent Approach to Binary Classification Using
                 Swarm Intelligence",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "36",
  day =          "12",
  month =        jan,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010036",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/36",
  abstract =     "Wisdom-of-Crowds-Bots (WoC-Bots) are simple, modular
                 agents working together in a multi-agent environment to
                 collectively make binary predictions. The agents
                 represent a knowledge-diverse crowd, with each agent
                 trained on a subset of available information. A
                 honey-bee-derived swarm aggregation mechanism is used
                 to elicit a collective prediction with an associated
                 confidence value from the agents. Due to their
                 multi-agent design, WoC-Bots can be distributed across
                 multiple hardware nodes, include new features without
                 re-training existing agents, and the aggregation
                 mechanism can be used to incorporate predictions from
                 other sources, thus improving overall predictive
                 accuracy of the system. In addition to these
                 advantages, we demonstrate that WoC-Bots are
                 competitive with other top classification methods on
                 three datasets and apply our system to a real-world
                 sports betting problem, producing a consistent return
                 on investment from 1 January 2021 through 15 November
                 2022 on most major sports.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ali:2023:RBC,
  author =       "Shams Mhmood Abd Ali and Mohd Najwadi Yusoff and Hasan
                 Falah Hasan",
  title =        "Redactable Blockchain: Comprehensive Review,
                 Mechanisms, Challenges, Open Issues and Future Research
                 Directions",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "35",
  day =          "12",
  month =        jan,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010035",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/35",
  abstract =     "The continuous advancements of blockchain applications
                 impose constant improvements on their technical
                 features. Particularly immutability, a highly secure
                 blockchain attribute forbidding unauthorized or illicit
                 data editing or deletion, which functions as crucial
                 blockchain security. Nonetheless, the security function
                 is currently being challenged due to improper data
                 stored, such as child pornography, copyright violation,
                 and lately the enaction of the ``Right to be Forgotten
                 (RtbF)'' principle disseminated by the General Data
                 Protection Regulation (GDPR), where it requires
                 blockchain data to be redacted to suit current
                 applications' urgent demands, and even compliance with
                 the regulation is a challenge and an unfeasible
                 practice for various blockchain technology providers
                 owing to the immutability characteristic. To overcome
                 this challenge, mutable blockchain is highly demanded
                 to solve previously mentioned issues, where controlled
                 and supervised amendments to certain content within
                 constrained privileges granted are suggested by several
                 researchers through numerous blockchain redaction
                 mechanisms using chameleon and non-chameleon hashing
                 function approaches, and methods were proposed to
                 achieve reasonable policies while ensuring high
                 blockchain security levels. Accordingly, the current
                 study seeks to thoroughly define redaction
                 implementation challenges and security properties
                 criteria. The analysis performed has mapped these
                 criteria with chameleon-based research methodologies,
                 technical approaches, and the latest cryptographic
                 techniques implemented to resolve the challenge posed
                 by the policy in which comparisons paved current open
                 issues, leading to shaping future research directions
                 in the scoped field.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yang:2023:DRL,
  author =       "Siyuan Yang and Mondher Bouazizi and Tomoaki Ohtsuki
                 and Yohei Shibata and Wataru Takabatake and Kenji
                 Hoshino and Atsushi Nagate",
  title =        "Deep Reinforcement Learning Evolution Algorithm for
                 Dynamic Antenna Control in Multi-Cell Configuration
                 {HAPS} System",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "34",
  day =          "12",
  month =        jan,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010034",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/34",
  abstract =     "In this paper, we propose a novel Deep Reinforcement
                 Learning Evolution Algorithm (DRLEA) method to control
                 the antenna parameters of the High-Altitude Platform
                 Station (HAPS) mobile to reduce the number of
                 low-throughput users. Considering the random movement
                 of the HAPS caused by the winds, the throughput of the
                 users might decrease. Therefore, we propose a method
                 that can dynamically adjust the antenna parameters
                 based on the throughput of the users in the coverage
                 area to reduce the number of low-throughput users by
                 improving the users' throughput. Different from other
                 model-based reinforcement learning methods, such as the
                 Deep Q Network (DQN), the proposed method combines the
                 Evolution Algorithm (EA) with Reinforcement Learning
                 (RL) to avoid the sub-optimal solutions in each state.
                 Moreover, we consider non-uniform user distribution
                 scenarios, which are common in the real world, rather
                 than ideal uniform user distribution scenarios. To
                 evaluate the proposed method, we do the simulations
                 under four different real user distribution scenarios
                 and compare the proposed method with the conventional
                 EA and RL methods. The simulation results show that the
                 proposed method effectively reduces the number of low
                 throughput users after the HAPS moves.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Vinceslas:2023:ADD,
  author =       "Leny Vinceslas and Safak Dogan and Srikumar
                 Sundareshwar and Ahmet M. Kondoz",
  title =        "Abstracting Data in Distributed Ledger Systems for
                 Higher Level Analytics and Visualizations",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "33",
  day =          "11",
  month =        jan,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010033",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/33",
  abstract =     "By design, distributed ledger technologies persist
                 low-level data, which makes conducting complex business
                 analysis of the recorded operations challenging.
                 Existing blockchain visualization and analytics tools
                 such as block explorers tend to rely on this low-level
                 data and complex interfacing to provide an enriched
                 level of analytics. The ability to derive richer
                 analytics could be improved through the availability of
                 a higher level abstraction of the data. This article
                 proposes an abstraction layer architecture that enables
                 the design of high-level analytics of distributed
                 ledger systems and the decentralized applications that
                 run on top. Based on the analysis of existing
                 initiatives and identification of the relevant user
                 requirements, this work aims to establish key insights
                 and specifications to improve the auditability and
                 intuitiveness of distributed ledger systems by
                 leveraging the development of future user interfaces.
                 To illustrate the benefits offered by the proposed
                 abstraction layer architecture, a regulated sector use
                 case is explored.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Abesinghe:2023:ICT,
  author =       "Sandulika Abesinghe and Nayomi Kankanamge and Tan
                 Yigitcanlar and Surabhi Pancholi",
  title =        "Image of a City through Big Data Analytics: {Colombo}
                 from the Lens of Geo-Coded Social Media Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "32",
  day =          "09",
  month =        jan,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010032",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/32",
  abstract =     "The image of a city represents the sum of beliefs,
                 ideas, and impressions that people have of that city.
                 Mostly, city images are assessed through direct or
                 indirect interviews and cognitive mapping exercises.
                 Such methods consume more time and effort and are
                 limited to a small number of people. However, recently,
                 people tend to use social media to express their
                 thoughts and experiences of a place. Taking this into
                 consideration, this paper attempts to explore city
                 images through social media big data, considering
                 Colombo, Sri Lanka, as the testbed. The aim of the
                 study is to examine the image of a city through
                 Lynchian elements---i.e., landmarks, paths, nodes,
                 edges, and districts---by using community sentiments
                 expressed and images posted on social media platforms.
                 For that, this study conducted various analyses---i.e.,
                 descriptive, image processing, sentiment, popularity,
                 and geo-coded social media analyses. The study findings
                 revealed that: (a) the community sentiments toward the
                 same landmarks, paths, nodes, edges, and districts
                 change over time; (b) decisions related to locating
                 landmarks, paths, nodes, edges, and districts have a
                 significant impact on community cognition in perceiving
                 cities; and (c) geo-coded social media data analytics
                 is an invaluable approach to capture the image of a
                 city. The study informs urban authorities in their
                 placemaking efforts by introducing a novel
                 methodological approach to capture an image of a
                 city.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhou:2023:PEP,
  author =       "Qingyan Zhou and Hao Li and Youhua Zhang and Junhong
                 Zheng",
  title =        "Product Evaluation Prediction Model Based on
                 Multi-Level Deep Feature Fusion",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "31",
  day =          "09",
  month =        jan,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010031",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/31",
  abstract =     "Traditional product evaluation research is to collect
                 data through questionnaires or interviews to optimize
                 product design, but the whole process takes a long time
                 to deploy and cannot fully reflect the market
                 situation. Aiming at this problem, we propose a product
                 evaluation prediction model based on multi-level deep
                 feature fusion of online reviews. It mines product
                 satisfaction from the massive reviews published by
                 users on e-commerce websites, and uses this model to
                 analyze the relationship between design attributes and
                 customer satisfaction, design products based on
                 customer satisfaction. Our proposed model can be
                 divided into the following four parts: First, the DSCNN
                 (Depthwise Separable Convolutions) layer and pooling
                 layer are used to combine extracting shallow features
                 from the primordial data. Secondly, CBAM (Convolutional
                 Block Attention Module) is used to realize the
                 dimension separation of features, enhance the
                 expressive ability of key features in the two
                 dimensions of space and channel, and suppress the
                 influence of redundant information. Thirdly, BiLSTM
                 (Bidirectional Long Short-Term Memory) is used to
                 overcome the complexity and nonlinearity of product
                 evaluation prediction, output the predicted result
                 through the fully connected layer. Finally, using the
                 global optimization capability of the genetic
                 algorithm, the hyperparameter optimization of the model
                 constructed above is carried out. The final forecasting
                 model consists of a series of decision rules that avoid
                 model redundancy and achieve the best forecasting
                 effect. It has been verified that the method proposed
                 in this paper is better than the above-mentioned models
                 in five evaluation indicators such as MSE, MAE, RMSE,
                 MAPE and SMAPE, compared with Support Vector Regression
                 (SVR), DSCNN, BiLSTM and DSCNN-BiLSTM. By predicting
                 customer emotional satisfaction, it can provide
                 accurate decision-making suggestions for enterprises to
                 design new products.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhao:2023:TSB,
  author =       "Ke Zhao and Rui Han and Xu Wang",
  title =        "Time Segmentation-Based Hybrid Caching in {5G-ICN}
                 Bearer Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "30",
  day =          "07",
  month =        jan,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010030",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/30",
  abstract =     "The fifth-generation communication technology (5G) and
                 information-centric networks (ICNs) are acquiring more
                 and more attention. Cache plays a significant part in
                 the 5G-ICN architecture that the industry has
                 suggested. 5G mobile terminals switch between different
                 base stations quickly, creating a significant amount of
                 traffic and a significant amount of network latency.
                 This brings great challenges to 5G-ICN mobile cache. It
                 appears urgent to improve the cache placement strategy.
                 This paper suggests a hybrid caching strategy called
                 time segmentation-based hybrid caching (TSBC) strategy,
                 based on the 5G-ICN bearer network infrastructure. A
                 base station's access frequency can change throughout
                 the course of the day due to the ``tidal phenomena'' of
                 mobile networks. To distinguish the access frequency,
                 we split each day into periods of high and low
                 liquidity. To maintain the diversity of cache copies
                 during periods of high liquidity, we replace the path's
                 least-used cache copy. We determine the cache value of
                 each node in the path and make caching decisions during
                 periods of low liquidity to make sure users can access
                 the content they are most interested in quickly. The
                 simulation results demonstrate that the proposed
                 strategy has a positive impact on both latency and the
                 cache hit ratio.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Pethers:2023:RAD,
  author =       "Brent Pethers and Abubakar Bello",
  title =        "Role of Attention and Design Cues for Influencing
                 Cyber-Sextortion Using Social Engineering and Phishing
                 Attacks",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "29",
  day =          "07",
  month =        jan,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010029",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/29",
  abstract =     "Cyber sextortion attacks are security and privacy
                 threats delivered to victims online, to distribute
                 sexual material in order to force the victim to act
                 against their will. This continues to be an
                 under-addressed concern in society. This study
                 investigated social engineering and phishing email
                 design and influence techniques in susceptibility to
                 cyber sextortion attacks. Using a quantitative
                 methodology, a survey measured susceptibility to cyber
                 sextortion with a focus on four different email design
                 cues. One-way repeated measures ANOVA, post hoc
                 comparison tests, Friedman nonparametric test, and
                 Spearman correlation tests were conducted with results
                 indicating that attention to email source and
                 title/subject line significantly increased individuals'
                 susceptibility, while attention to grammar and
                 spelling, and urgency cues, had lesser influence. As
                 such, the influence of these message-related factors
                 should be considered when implementing effective
                 security controls to mitigate the risks and
                 vulnerabilities to cyber sextortion attacks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kabassi:2023:ARE,
  author =       "Katerina Kabassi and Anastasia Papadaki and Athanasios
                 Botonis",
  title =        "Adapting Recommendations on Environmental Education
                 Programs",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "28",
  day =          "04",
  month =        jan,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010028",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/28",
  abstract =     "Stakeholders in Environmental Education (EE) often
                 face difficulties identifying and selecting programs
                 that best suit their needs. This is due, in part, to
                 the lack of expertise in evaluation knowledge and
                 practice, as well as to the absence of a unified
                 database of Environmental Education Programs (EEPs)
                 with a defined structure. This article presents the
                 design and development of a web application for
                 evaluating and selecting EEPs. The certified users of
                 the application can insert, view, and evaluate the
                 registered EEPs. At the same time, the application
                 creates and maintains for each user an individual and
                 dynamic user model reflecting their personal
                 preferences. Finally, using all the above information
                 and applying a combination of Multi-Criteria
                 Decision-Making Methods (MCDM), the application
                 provides a comparative and adaptive evaluation in order
                 to help each user to select the EEPs that best suit
                 his/her needs. The personalized recommendations are
                 based on the information about the user stored in the
                 user model and the results of the EEPs evaluations by
                 the users that have applied them. As a case study, we
                 used the EEPs from the Greek Educational System.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Matricciani:2023:TFL,
  author =       "Emilio Matricciani and Carlo Riva",
  title =        "Transfer Functions and Linear Distortions in
                 Ultra-Wideband Channels Faded by Rain in {GeoSurf}
                 Satellite Constellations",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "27",
  day =          "03",
  month =        jan,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010027",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/27",
  abstract =     "Because of rain attenuation, the equivalent baseband
                 transfer function of large bandwidth radio-links will
                 not be ideal. We report the results concerning radio
                 links to/from satellites orbiting in GeoSurf satellite
                 constellations located at Spino d'Adda, Prague, Madrid,
                 and Tampa, which are all sites in different climatic
                 regions. By calculating rain attenuation and phase
                 delay with the Synthetic Storm Technique, we have found
                 that in a 10-GHz bandwidth centered at 80 GHz
                 (W-Band)---to which we refer to as ``ultra-wideband-,
                 both direct and orthogonal channels will introduce
                 significant amplitude and phase distortions, which
                 increase with rain attenuation. Only ``narrow-band''
                 channels (100--200 MHz) will not be affected. The ratio
                 between the probability of bit error with rain
                 attenuation and the probability of bit error with no
                 rain attenuation increases with rain attenuation. The
                 estimated loss in the signal-to-noise ratio can reach
                 3--4 dB. All results depend on the site, Tampa being the
                 worst. To confirm these findings, future work will need
                 a full Monte Carlo digital simulation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Goncalves:2023:CSP,
  author =       "Teresa Gon{\c{c}}alves and Rute Veladas and Hua Yang
                 and Renata Vieira and Paulo Quaresma and Paulo Infante
                 and C{\'a}tia Sousa Pinto and Jo{\~a}o Oliveira and
                 Maria Cortes Ferreira and J{\'e}ssica Morais and Ana
                 Raquel Pereira and Nuno Fernandes and Carolina
                 Gon{\c{c}}alves",
  title =        "Clinical Screening Prediction in the {Portuguese
                 National Health Service}: Data Analysis, Machine
                 Learning Models, Explainability and Meta-Evaluation",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "26",
  day =          "03",
  month =        jan,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010026",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/26",
  abstract =     "This paper presents an analysis of the calls made to
                 the Portuguese National Health Contact Center (SNS24)
                 during a three years period. The final goal was to
                 develop a system to help nurse attendants select the
                 appropriate clinical pathway (from 59 options) for each
                 call. It examines several aspects of the calls
                 distribution like age and gender of the user, date and
                 time of the call and final referral, among others and
                 presents comparative results for alternative
                 classification models (SVM and CNN) and different data
                 samples (three months, one and two years data models).
                 For the task of selecting the appropriate pathway, the
                 models, learned on the basis of the available data,
                 achieved F1 values that range between 0.642 (3 months
                 CNN model) and 0.783 (2 years CNN model), with SVM
                 having a more stable performance (between 0.743 and
                 0.768 for the corresponding data samples). These
                 results are discussed regarding error analysis and
                 possibilities for explaining the system decisions. A
                 final meta evaluation, based on a clinical expert
                 overview, compares the different choices: the nurse
                 attendants (reference ground truth), the expert and the
                 automatic decisions (2 models), revealing a higher
                 agreement between the ML models, followed by their
                 agreement with the clinical expert, and minor agreement
                 with the reference.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2023:VIA,
  author =       "Qiang Li",
  title =        "A {V2V} Identity Authentication and Key Agreement
                 Scheme Based on Identity-Based Cryptograph",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "25",
  day =          "03",
  month =        jan,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010025",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/25",
  abstract =     "Cellular vehicle to everything (C-V2X) is a technology
                 to achieve vehicle networking, which can improve
                 traffic efficiency and traffic safety. As a special
                 network, the C-V2X system faces many security risks.
                 The vehicle to vehicle (V2V) communication transmits
                 traffic condition data, driving path data, user driving
                 habits data, and so on. It is necessary to ensure the
                 opposite equipment is registered C-V2X equipment
                 (installed in the vehicle), and the data transmitted
                 between the equipment is secure. This paper proposes a
                 V2V identity authentication and key agreement scheme
                 based on identity-based cryptograph (IBC). The C-V2X
                 equipment use its vehicle identification (VID) as its
                 public key. The key management center (KMC) generates a
                 private key for the C-V2X equipment according to its
                 VID. The C-V2X equipment transmit secret data encrypted
                 with the opposite equipment public key to the other
                 equipment, they authenticate each other through a
                 challenge response protocol based on identity-based
                 cryptography, and they negotiate the working key used
                 to encrypt the communication data. The scheme can
                 secure the V2V communication with low computational
                 cost and simple architecture and meet the lightweight
                 and efficient communication requirements of the C-V2X
                 system.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Du:2023:FSA,
  author =       "Jinze Du and Chengtai Gao and Tao Feng",
  title =        "Formal Safety Assessment and Improvement of {DDS}
                 Protocol for Industrial Data Distribution Service",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "24",
  day =          "31",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010024",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/24",
  abstract =     "The Data Distribution Service (DDS) for real-time
                 systems is an industrial Internet communication
                 protocol. Due to its distributed high reliability and
                 the ability to transmit device data communication in
                 real-time, it has been widely used in industry, medical
                 care, transportation, and national defense. With the
                 wide application of various protocols, protocol
                 security has become a top priority. There are many
                 studies on protocol security, but these studies lack a
                 formal security assessment of protocols. Based on the
                 above status, this paper evaluates and improves the
                 security of the DDS protocol using a model detection
                 method combining the Dolev--Yao attack model and the
                 Coloring Petri Net (CPN) theory. Because of the
                 security loopholes in the original protocol, a
                 timestamp was introduced into the original protocol,
                 and the shared key establishment process in the
                 original protocol lacked fairness and consistency. We
                 adopted a new establishment method to establish the
                 shared secret and re-verified its security. The results
                 show that the overall security of the protocol has been
                 improved by 16.7\% while effectively preventing current
                 replay attack.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Cardone:2023:GBH,
  author =       "Barbara Cardone and Ferdinando {Di Martino} and
                 Vittorio Miraglia",
  title =        "A {GIS}-Based Hot and Cold Spots Detection Method by
                 Extracting Emotions from Social Streams",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "23",
  day =          "30",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010023",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/23",
  abstract =     "Hot and cold spot identification is a spatial analysis
                 technique used in various issues to identify regions
                 where a specific phenomenon is either strongly or
                 poorly concentrated or sensed. Many hot/cold spot
                 detection techniques are proposed in literature;
                 clustering methods are generally applied in order to
                 extract hot and cold spots as polygons on the maps; the
                 more precise the determination of the area of the hot
                 (cold) spots, the greater the computational complexity
                 of the clustering algorithm. Furthermore, these methods
                 do not take into account the hidden information
                 provided by users through social networks, which is
                 significant for detecting the presence of hot/cold
                 spots based on the emotional reactions of citizens. To
                 overcome these critical points, we propose a GIS-based
                 hot and cold spot detection framework encapsulating a
                 classification model of emotion categories of documents
                 extracted from social streams connected to the
                 investigated phenomenon is implemented. The study area
                 is split into subzones; residents' postings during a
                 predetermined time period are retrieved and analyzed
                 for each subzone. The proposed model measures for each
                 subzone the prevalence of pleasant and unpleasant
                 emotional categories in different time frames; with the
                 aid of a fuzzy-based emotion classification approach,
                 subzones in which unpleasant/pleasant emotions prevail
                 over the analyzed time period are labeled as hot/cold
                 spots. A strength of the proposed framework is to
                 significantly reduce the CPU time of cluster-based hot
                 and cold spot detection methods as it does not require
                 detecting the exact geometric shape of the spot. Our
                 framework was tested to detect hot and cold spots
                 related to citizens' discomfort due to heatwaves in the
                 study area made up of the municipalities of the
                 northeastern area of the province of Naples (Italy).
                 The results show that the hot spots, where the greatest
                 discomfort is felt, correspond to areas with a high
                 population/building density. On the contrary, cold
                 spots cover urban areas having a lower population
                 density.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Huang:2023:NNA,
  author =       "Songtao Huang and Jun Shen and Qingquan Lv and Qingguo
                 Zhou and Binbin Yong",
  title =        "A Novel {NODE} Approach Combined with {LSTM} for
                 Short-Term Electricity Load Forecasting",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "22",
  day =          "30",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010022",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/22",
  abstract =     "Electricity load forecasting has seen increasing
                 importance recently, especially with the effectiveness
                 of deep learning methods growing. Improving the
                 accuracy of electricity load forecasting is vital for
                 public resources management departments. Traditional
                 neural network methods such as long short-term memory
                 (LSTM) and bidirectional LSTM (BiLSTM) have been widely
                 used in electricity load forecasting. However, LSTM and
                 its variants are not sensitive to the dynamic change of
                 inputs and miss the internal nonperiodic rules of
                 series, due to their discrete observation interval. In
                 this paper, a novel neural ordinary differential
                 equation (NODE) method, which can be seen as a
                 continuous version of residual network (ResNet), is
                 applied to electricity load forecasting to learn
                 dynamics of time series. We design three groups of
                 models based on LSTM and BiLSTM and compare the
                 accuracy between models using NODE and without NODE.
                 The experimental results show that NODE can improve the
                 prediction accuracy of LSTM and BiLSTM. It indicates
                 that NODE is an effective approach to improving the
                 accuracy of electricity load forecasting.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Khando:2023:ETD,
  author =       "Khando Khando and M. Sirajul Islam and Shang Gao",
  title =        "The Emerging Technologies of Digital Payments and
                 Associated Challenges: a Systematic Literature Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "21",
  day =          "30",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010021",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/21",
  abstract =     "The interplay between finance and technology with the
                 use of the internet triggered the emergence of digital
                 payment technologies. Such technological innovation in
                 the payment industry is the foundation for financial
                 inclusion. However, despite the continuous progress and
                 potential of moving the payment landscape towards
                 digital payments and connecting the population to the
                 ubiquitous digital environment, some critical issues
                 need to be addressed to achieve a more harmonious
                 inclusive and sustainable cashless society. The study
                 aims to provide a comprehensive literature review on
                 the emerging digital payment technologies and
                 associated challenges. By systematically reviewing
                 existing empirical studies, this study puts forward the
                 state-of-the-art classification of digital payment
                 technologies and presents four categories of digital
                 payment technologies: card payment, e-payment, mobile
                 payment and cryptocurrencies. Subsequently, the paper
                 presents the key challenges in digital payment
                 technologies categorized into broad themes: social,
                 economic, technical, awareness and legal. The
                 classification and categorization of payment
                 technologies and associated challenges can be useful to
                 both researchers and practitioners to understand,
                 elucidate and develop a coherent digital payment
                 strategy.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Perifanou:2023:TVI,
  author =       "Maria Perifanou and Anastasios A. Economides and
                 Stavros A. Nikou",
  title =        "Teachers' Views on Integrating Augmented Reality in
                 Education: Needs, Opportunities, Challenges and
                 Recommendations",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "20",
  day =          "29",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010020",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/20",
  abstract =     "The integration of augmented reality (AR) in education
                 is promising since it enhances teaching and offers more
                 engaging and appealing learning experiences. Teachers
                 can have a catalytic role towards the adoption of AR in
                 education; therefore, their perspectives with regard to
                 AR in teaching and learning are very important. The
                 current study explores teachers' views on the
                 integration of AR in education through an open-ended
                 questionnaire that has been answered by 93 educators
                 worldwide. A set of digital skills that can support
                 student-centered pedagogies in an appropriate
                 infrastructure are the main requirement for effective
                 teaching with AR. Among the perceived benefits and
                 opportunities are interactive teaching and learning,
                 increased interest and engagement, better understanding
                 of complex concepts. As barriers, participants reported
                 the lack of AR educational applications, the cost of
                 buying and maintaining AR equipment and resources, the
                 lack of teachers' and students' digital skills,
                 classroom management issues, and security and ethical
                 issues. Moreover, survey participants highlighted the
                 need for raising teachers' awareness for the added
                 value of AR in education and the need for teachers'
                 continuous professional development. Implications and
                 future research recommendations on the integration of
                 AR in education are discussed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kalafatidis:2023:LCS,
  author =       "Sarantis Kalafatidis and Sotiris Skaperas and Vassilis
                 Demiroglou and Lefteris Mamatas and Vassilis
                 Tsaoussidis",
  title =        "Logically-Centralized {SDN}-Based {NDN} Strategies for
                 Wireless Mesh Smart-City Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "19",
  day =          "29",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010019",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/19",
  abstract =     "The Internet of Things (IoT) is a key technology for
                 smart community networks, such as smart-city
                 environments, and its evolution calls for stringent
                 performance requirements (e.g., low delay) to support
                 efficient communication among a wide range of objects,
                 including people, sensors, vehicles, etc. At the same
                 time, these ecosystems usually adopt wireless mesh
                 technology to extend their communication range in
                 large-scale IoT deployments. However, due to the high
                 range of coverage, the smart-city WMNs may face
                 different network challenges according to the network
                 characteristic, for example, (i) areas that include a
                 significant number of wireless nodes or (ii) areas with
                 frequent dynamic changes such as link failures due to
                 unstable topologies. Named-Data Networking (NDN) can
                 enhance WMNs to meet such IoT requirements, thanks to
                 the content naming scheme and in-network caching, but
                 it necessitates adaptability to the challenging
                 conditions of WMNs. In this work, we aim at efficient
                 end-to-end NDN communication in terms of performance
                 (i.e., delay), performing extended experimentation over
                 a real WMN, evaluating and discussing the benefits
                 provided by two SDN-based NDN strategies: (1) a dynamic
                 SDN-based solution that integrates the NDN operation
                 with the routing decisions of a WMN routing protocol;
                 (2) a static one which based on SDN-based clustering
                 and real WMN performance measurements. Our key
                 contributions include (i) the implementation of two
                 types of NDN path selection strategies; (ii)
                 experimentation and data collection over the w-iLab.t
                 Fed4FIRE+ testbed with real WMN conditions; (ii) real
                 measurements released as open-data, related to the
                 performance of the wireless links in terms of RSSI,
                 delay, and packet loss among the wireless nodes of the
                 corresponding testbed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liccardo:2023:VAD,
  author =       "Annalisa Liccardo and Francesco Bonavolont{\`a}",
  title =        "{VR}, {AR}, and {3-D} User Interfaces for Measurement
                 and Control",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "18",
  day =          "29",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010018",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/18",
  abstract =     "The topics of virtual, mixed, and extended reality
                 have now become key areas in various fields of
                 scientific and industrial applications, and the
                 interest in them is made tangible by the numerous
                 papers available in the scientific literature. In this
                 regard, the Special Issue ``VR, AR, and 3-D User
                 Interfaces for Measurement and Control'' received a
                 fair number of varied contributions that analyzed
                 different aspects of the implementation of virtual,
                 mixed, and extended reality systems and approaches in
                 the real world. They range from investigating the
                 requirements of new potential technologies to the
                 prediction verification of the effectiveness and
                 benefits of their use, the analysis of the difficulties
                 of interaction with graphical interfaces to the
                 possibility of performing complex and risky tasks (such
                 as surgical operations) using mixed reality viewers.
                 All contributions were of a high standard and mainly
                 highlight that measurement and control applications
                 based on the new models of interaction with reality are
                 by now increasingly ready to leave laboratory spaces
                 and become objects and features of common life. The
                 significant benefits of this technology will radically
                 change the way we live and interact with information
                 and the reality around us, and it will surely be worthy
                 of further exploration, maybe even in a new Special
                 Issue of Future Internet.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liu:2023:DSP,
  author =       "Yunchuan Liu and Amir Ghasemkhani and Lei Yang",
  title =        "Drifting Streaming Peaks-Over-Threshold-Enhanced
                 Self-Evolving Neural Networks for Short-Term Wind Farm
                 Generation Forecast",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "17",
  day =          "28",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010017",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/17",
  abstract =     "This paper investigates the short-term wind farm
                 generation forecast. It is observed from the real wind
                 farm generation measurements that wind farm generation
                 exhibits distinct features, such as the
                 non-stationarity and the heterogeneous dynamics of ramp
                 and non-ramp events across different classes of wind
                 turbines. To account for the distinct features of wind
                 farm generation, we propose a Drifting Streaming
                 Peaks-over-Threshold (DSPOT)-enhanced self-evolving
                 neural networks-based short-term wind farm generation
                 forecast. Using DSPOT, the proposed method first
                 classifies the wind farm generation data into ramp and
                 non-ramp datasets, where time-varying dynamics are
                 taken into account by utilizing dynamic ramp thresholds
                 to separate the ramp and non-ramp events. We then train
                 different neural networks based on each dataset to
                 learn the different dynamics of wind farm generation by
                 the NeuroEvolution of Augmenting Topologies (NEAT),
                 which can obtain the best network topology and
                 weighting parameters. As the efficacy of the neural
                 networks relies on the quality of the training datasets
                 (i.e., the classification accuracy of the ramp and
                 non-ramp events), a Bayesian optimization-based
                 approach is developed to optimize the parameters of
                 DSPOT to enhance the quality of the training datasets
                 and the corresponding performance of the neural
                 networks. Based on the developed self-evolving neural
                 networks, both distributional and point forecasts are
                 developed. The experimental results show that compared
                 with other forecast approaches, the proposed forecast
                 approach can substantially improve the forecast
                 accuracy, especially for ramp events. The experiment
                 results indicate that the accuracy improvement in a 60
                 min horizon forecast in terms of the mean absolute
                 error (MAE) is at least 33.6\% for the whole year data
                 and at least 37\% for the ramp events. Moreover, the
                 distributional forecast in terms of the continuous rank
                 probability score (CRPS) is improved by at least 35.8\%
                 for the whole year data and at least 35.2\% for the
                 ramp events.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hamarsheh:2023:NIT,
  author =       "Qadri Hamarsheh and Omar Daoud and Mohammed Baniyounis
                 and Ahlam Damati",
  title =        "Narrowband {Internet-of-Things} to Enhance the
                 Vehicular Communications Performance",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "16",
  day =          "28",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010016",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/16",
  abstract =     "The interest in vehicle-to-vehicle communication has
                 gained a high demand in the last decade. This is due to
                 the need for safe and robust smart communication, while
                 this type of communication is vulnerable to latency and
                 power. Therefore, this work proposes the Narrowband
                 Internet-of-Things to enhance the robustness of the
                 vehicular communication system. Accordingly, the
                 system's QoS is enhanced. This enhancement is based on
                 proposing two parts to cover the latency and the
                 harmonics issues, in addition to proposing a
                 distributed antenna configuration for the moving
                 vehicles under a machine learning benchmark, which uses
                 the across-entropy algorithm. The proposed environment
                 has been simulated and compared to the state-of-the-art
                 work performance. The simulation results verify the
                 proposed work performance based on three different
                 parameters; namely the latency, the mean squared error
                 rate, and the transmitted signal block error rate. From
                 these results, the proposed work outperforms the
                 literature; at the probability of 10 {$-$3}, the
                 proposed work reduces the peak power deficiency by
                 almost 49\%, an extra 23.5\% enhancement has been
                 attained from the self-interference cancellation side,
                 and a bit error rate enhancement by a ratio of 31\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{LaQuatra:2023:BIE,
  author =       "Moreno {La Quatra} and Luca Cagliero",
  title =        "{BART-IT}: an Efficient Sequence-to-Sequence Model for
                 {Italian} Text Summarization",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "15",
  day =          "27",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010015",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/15",
  abstract =     "The emergence of attention-based architectures has led
                 to significant improvements in the performance of
                 neural sequence-to-sequence models for text
                 summarization. Although these models have proved to be
                 effective in summarizing English-written documents,
                 their portability to other languages is limited thus
                 leaving plenty of room for improvement. In this paper,
                 we present BART-IT, a sequence-to-sequence model, based
                 on the BART architecture that is specifically tailored
                 to the Italian language. The model is pre-trained on a
                 large corpus of Italian-written pieces of text to learn
                 language-specific features and then fine-tuned on
                 several benchmark datasets established for abstractive
                 summarization. The experimental results show that
                 BART-IT outperforms other state-of-the-art models in
                 terms of ROUGE scores in spite of a significantly
                 smaller number of parameters. The use of BART-IT can
                 foster the development of interesting NLP applications
                 for the Italian language. Beyond releasing the model to
                 the research community to foster further research and
                 applications, we also discuss the ethical implications
                 behind the use of abstractive summarization models.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fazio:2023:HMI,
  author =       "Roberto {De Fazio} and Vincenzo Mariano Mastronardi
                 and Matteo Petruzzi and Massimo {De Vittorio} and Paolo
                 Visconti",
  title =        "Human--Machine Interaction through Advanced Haptic
                 Sensors: a Piezoelectric Sensory Glove with Edge
                 Machine Learning for Gesture and Object Recognition",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "14",
  day =          "27",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010014",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/14",
  abstract =     "Human--machine interaction (HMI) refers to systems
                 enabling communication between machines and humans.
                 Systems for human--machine interfaces have advanced
                 significantly in terms of materials, device design, and
                 production methods. Energy supply units, logic
                 circuits, sensors, and data storage units must be
                 flexible, stretchable, undetectable, biocompatible, and
                 self-healing to act as human--machine interfaces. This
                 paper discusses the technologies for providing
                 different haptic feedback of different natures.
                 Notably, the physiological mechanisms behind touch
                 perception are reported, along with a classification of
                 the main haptic interfaces. Afterward, a comprehensive
                 overview of wearable haptic interfaces is presented,
                 comparing them in terms of cost, the number of
                 integrated actuators and sensors, their main haptic
                 feedback typology, and their future application.
                 Additionally, a review of sensing systems that use
                 haptic feedback technologies---specifically, smart
                 gloves---is given by going through their fundamental
                 technological specifications and key design
                 requirements. Furthermore, useful insights related to
                 the design of the next-generation HMI devices are
                 reported. Lastly, a novel smart glove based on thin and
                 conformable AlN (aluminum nitride) piezoelectric
                 sensors is demonstrated. Specifically, the device
                 acquires and processes the signal from the piezo
                 sensors to classify performed gestures through an
                 onboard machine learning (ML) algorithm. Then, the
                 design and testing of the electronic conditioning
                 section of AlN-based sensors integrated into the smart
                 glove are shown. Finally, the architecture of a
                 wearable visual-tactile recognition system is
                 presented, combining visual data acquired by a
                 micro-camera mounted on the user's glass with the
                 haptic ones provided by the piezoelectric sensors.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhao:2023:CPP,
  author =       "Jiaxu Zhao and Binting Su and Xuli Rao and Zhide
                 Chen",
  title =        "A Cross-Platform Personalized Recommender System for
                 Connecting E-Commerce and Social Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "13",
  day =          "27",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010013",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/13",
  abstract =     "In this paper, we build a recommender system for a new
                 study area: social commerce, which combines rich
                 information about social network users and products on
                 an e-commerce platform. The idea behind this
                 recommender system is that a social network contains
                 abundant information about its users which could be
                 exploited to create profiles of the users. For social
                 commerce, the quality of the profiles of potential
                 consumers determines whether the recommender system is
                 a success or a failure. In our work, not only the
                 user's textual information but also the tags and the
                 relationships between users have been considered in the
                 process of building user profiling model. A topic model
                 has been adopted in our system, and a feedback
                 mechanism also been design in this paper. Then, we
                 apply a collative filtering method and a clustering
                 algorithm in order to obtain a high recommendation
                 accuracy. We do an empirical analysis based on real
                 data collected on a social network and an e-commerce
                 platform. We find that the social network has an impact
                 on e-commerce, so social commerce could be realized.
                 Simulations show that our topic model has a better
                 performance in topic finding, meaning that our
                 profile-building model is suitable for a social
                 commerce recommender system.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Vizzari:2023:PSR,
  author =       "Giuseppe Vizzari and Thomas Cecconello",
  title =        "Pedestrian Simulation with Reinforcement Learning: a
                 Curriculum-Based Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "12",
  day =          "27",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010012",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/12",
  abstract =     "Pedestrian simulation is a consolidated but still
                 lively area of research. State of the art models mostly
                 take an agent-based perspective, in which pedestrian
                 decisions are made according to a manually defined
                 model. Reinforcement learning (RL), on the other hand,
                 is used to train an agent situated in an environment
                 how to act so as to maximize an accumulated numerical
                 reward signal (a feedback provided by the environment
                 to every chosen action). We explored the possibility of
                 applying RL to pedestrian simulation. We carefully
                 defined a reward function combining elements related to
                 goal orientation, basic proxemics, and basic
                 way-finding considerations. The proposed approach
                 employs a particular training curriculum, a set of
                 scenarios growing in difficulty supporting an
                 incremental acquisition of general movement competences
                 such as orientation, walking, and pedestrian
                 interaction. The learned pedestrian behavioral model is
                 applicable to situations not presented to the agents in
                 the training phase, and seems therefore reasonably
                 general. This paper describes the basic elements of the
                 approach, the training procedure, and an
                 experimentation within a software framework employing
                 Unity and ML-Agents.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ngo:2023:HNH,
  author =       "Duc-Minh Ngo and Dominic Lightbody and Andriy Temko
                 and Cuong Pham-Quoc and Ngoc-Thinh Tran and Colin C.
                 Murphy and Emanuel Popovici",
  title =        "{HH-NIDS}: Heterogeneous Hardware-Based Network
                 Intrusion Detection Framework for {IoT} Security",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "9",
  day =          "26",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010009",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/9",
  abstract =     "This study proposes a heterogeneous hardware-based
                 framework for network intrusion detection using
                 lightweight artificial neural network models. With the
                 increase in the volume of exchanged data, IoT networks'
                 security has become a crucial issue. Anomaly-based
                 intrusion detection systems (IDS) using machine
                 learning have recently gained increased popularity due
                 to their generation's ability to detect unseen attacks.
                 However, the deployment of anomaly-based AI-assisted
                 IDS for IoT devices is computationally expensive. A
                 high-performance and ultra-low power consumption
                 anomaly-based IDS framework is proposed and evaluated
                 in this paper. The framework has achieved the highest
                 accuracy of 98.57\% and 99.66\% on the UNSW-NB15 and
                 IoT-23 datasets, respectively. The inference engine on
                 the MAX78000EVKIT AI-microcontroller is 11.3 times
                 faster than the Intel Core i7-9750H 2.6 GHz and 21.3
                 times faster than NVIDIA GeForce GTX 1650 graphics
                 cards, when the power drawn was 18mW. In addition, the
                 pipelined design on the PYNQ-Z2 SoC FPGA board with the
                 Xilinx Zynq xc7z020-1clg400c device is optimised to run
                 at the on-chip frequency (100 MHz), which shows a
                 speedup of 53.5 times compared to the MAX78000EVKIT.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Orehovacki:2023:EPQ,
  author =       "Tihomir Orehovacki and Luka Blaskovi{\'c} and Matej
                 Kurevija",
  title =        "Evaluating the Perceived Quality of Mobile Banking
                 Applications in {Croatia}: an Empirical Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "1",
  pages =        "8",
  day =          "26",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15010008",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:53 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/1/8",
  abstract =     "Mobile banking is nowadays a standard service provided
                 by banks worldwide because it adds convenience for
                 people. There is no more rushing to a bank or waiting
                 in lines for a simple transaction that can be conducted
                 from anywhere and at any time in the blink of an eye.
                 To be consumed by a respective amount of bank clients
                 regularly, mobile banking applications are required to
                 be continuously improved and updated, be in line with
                 recent security standards, and meet quality
                 requirements. This paper tackles the perceived quality
                 of mobile banking applications that are most commonly
                 used in Croatia and has three objectives in that
                 respect. The first one is to identify the extent to
                 which pragmatic and hedonic dimensions of quality
                 contribute to customers' satisfaction and their
                 behavioral intentions related to the continuous use of
                 mobile banking applications. The second one is to
                 determine if there are significant differences in the
                 perceived quality between users of diverse mobile
                 banking applications as well as between users who
                 belong to different age groups. The last one is to
                 uncover the advantages and disadvantages of evaluated
                 mobile banking applications. For this purpose, an
                 empirical study was carried out, during which data were
                 collected with an online questionnaire. The sample was
                 composed of 130 participants who are representative and
                 regular users of mobile banking applications. The
                 psychometric features of the proposed research model,
                 which represents an interplay of perceived quality
                 attributes, were tested using the partial least squares
                 structural equation modeling (PLS-SEM) method.
                 Differences in the perceived quality among different
                 mobile banking applications and customers of various
                 age groups were explored with Kruskal--Wallis tests.
                 Pros and cons of mobile banking applications were
                 identified with the help of descriptive statistics.
                 Study findings indicate that, in the context of mobile
                 banking applications used in Croatia, feedback quality
                 and responsiveness contribute to the ease of use,
                 usefulness is affected by both ease of use and
                 efficiency, responsiveness has a significant impact on
                 efficiency while ease of use, usefulness, and security
                 of personal data are predictors of customers'
                 satisfaction which in turn influences their behavioral
                 intentions. While no significant difference exists in
                 the perceived quality of four examined mobile banking
                 applications, we found a significant difference in the
                 perceived quality among three age groups of users of
                 mobile banking applications. The most commonly reported
                 advantages of mobile banking applications were related
                 to facets of their efficiency and usefulness, whereas
                 their main drawback appeared to be the lack of features
                 dealing with the personalization of offered services.
                 The reported and discussed results of an empirical
                 study can be used as a set of guidelines for future
                 advances in the evaluation and design of mobile banking
                 applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{AlZubi:2023:DMS,
  author =       "Shadi AlZu'bi and Mohammad Elbes and Ala Mughaid and
                 Noor Bdair and Laith Abualigah and Agostino Forestiero
                 and Raed Abu Zitar",
  title =        "Diabetes Monitoring System in Smart Health Cities
                 Based on Big Data Intelligence",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "85",
  day =          "20",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020085",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/85",
  abstract =     "Diabetes is a metabolic disorder in which the body is
                 unable to properly regulate blood sugar levels. It can
                 occur when the body does not produce enough insulin or
                 when cells become resistant to insulin's effects. There
                 are two main types of diabetes, Type 1 and Type 2,
                 which have different causes and risk factors. Early
                 detection of diabetes allows for early intervention and
                 management of the condition. This can help prevent or
                 delay the development of serious complications
                 associated with diabetes. Early diagnosis also allows
                 for individuals to make lifestyle changes to prevent
                 the progression of the disease. Healthcare systems play
                 a vital role in the management and treatment of
                 diabetes. They provide access to diabetes education,
                 regular check-ups, and necessary medications for
                 individuals with diabetes. They also provide monitoring
                 and management of diabetes-related complications, such
                 as heart disease, kidney failure, and neuropathy.
                 Through early detection, prevention and management
                 programs, healthcare systems can help improve the
                 quality of life and outcomes for people with diabetes.
                 Current initiatives in healthcare systems for diabetes
                 may fail due to lack of access to education and
                 resources for individuals with diabetes. There may also
                 be inadequate follow-up and monitoring for those who
                 have been diagnosed, leading to poor management of the
                 disease and lack of prevention of complications.
                 Additionally, current initiatives may not be tailored
                 to specific cultural or demographic groups, resulting
                 in a lack of effectiveness for certain populations. In
                 this study, we developed a diabetes prediction system
                 using a healthcare framework. The system employs
                 various machine learning methods, such as K-nearest
                 neighbors, decision tree, deep learning, SVM, random
                 forest, AdaBoost and logistic regression. The
                 performance of the system was evaluated using the PIMA
                 Indians Diabetes dataset and achieved a training
                 accuracy of 82\% and validation accuracy of 80\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Latifinavid:2023:DVB,
  author =       "Masoud Latifinavid and Aydin Azizi",
  title =        "Development of a Vision-Based Unmanned Ground Vehicle
                 for Mapping and Tennis Ball Collection: a Fuzzy Logic
                 Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "84",
  day =          "19",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020084",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/84",
  abstract =     "The application of robotic systems is widespread in
                 all fields of life and sport. Tennis ball collection
                 robots have recently become popular because of their
                 potential for saving time and energy and increasing the
                 efficiency of training sessions. In this study, an
                 unmanned and autonomous tennis ball collection robot
                 was designed and produced that used LiDAR for 2D
                 mapping of the environment and a single camera for
                 detecting tennis balls. A novel method was used for the
                 path planning and navigation of the robot. A fuzzy
                 controller was designed for controlling the robot
                 during the collection operation. The developed robot
                 was tested, and it successfully detected 91\% of the
                 tennis balls and collected 83\% of them.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mazhar:2023:ACS,
  author =       "Tehseen Mazhar and Hafiz Muhammad Irfan and Sunawar
                 Khan and Inayatul Haq and Inam Ullah and Muhammad Iqbal
                 and Habib Hamam",
  title =        "Analysis of Cyber Security Attacks and Its Solutions
                 for the Smart grid Using Machine Learning and
                 Blockchain Methods",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "83",
  day =          "19",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020083",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/83",
  abstract =     "Smart grids are rapidly replacing conventional
                 networks on a worldwide scale. A smart grid has
                 drawbacks, just like any other novel technology. A
                 smart grid cyberattack is one of the most challenging
                 things to stop. The biggest problem is caused by
                 millions of sensors constantly sending and receiving
                 data packets over the network. Cyberattacks can
                 compromise the smart grid's dependability,
                 availability, and privacy. Users, the communication
                 network of smart devices and sensors, and network
                 administrators are the three layers of an innovative
                 grid network vulnerable to cyberattacks. In this study,
                 we look at the many risks and flaws that can affect the
                 safety of critical, innovative grid network components.
                 Then, to protect against these dangers, we offer
                 security solutions using different methods. We also
                 provide recommendations for reducing the chance that
                 these three categories of cyberattacks may occur.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Flamini:2023:OPR,
  author =       "Marta Flamini and Maurizio Naldi",
  title =        "Optimal Pricing in a Rented {5G} Infrastructure
                 Scenario with Sticky Customers",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "82",
  day =          "19",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020082",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/82",
  abstract =     "The ongoing deployment of 5G is accompanied by
                 architecture and pricing decisions. Network sharing is
                 a critical feature, allowing operators to reduce their
                 costs, but introducing a mixed partnering/competition
                 situation, where the infrastructure owner, renting out
                 their infrastructure to virtual operators (who act as
                 customers), also provides services to end customers,
                 competing with virtual operators. Pricing is the
                 leverage through which an optimal balance between the
                 two roles is accomplished. However, pricing may not be
                 the only variable affecting customers' choice, which
                 may prefer (stick to) one operator for several reasons.
                 In this paper, we formulate a game model to analyse the
                 optimal pricing decisions for operators in the presence
                 of such sticky behaviour of customers. After concluding
                 that the game does not allow for a Nash equilibrium, we
                 consider a case when one of the parties (the
                 infrastructure owner, the virtual operators, or the
                 regulator) is responsible for setting prices and
                 analyse how operators' profits are impacted when
                 price-setting powers are shifted among the parties. The
                 scenario where the regulator sets prices leads to the
                 lowest profits for the operators, even lower than when
                 competitors set prices.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kulakli:2023:RTI,
  author =       "Atik Kulakli and Cenk Lacin Arikan",
  title =        "Research Trends of the {Internet of Things} in
                 Relation to Business Model Innovation: Results from
                 Co-Word and Content Analyses",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "81",
  day =          "17",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020081",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/81",
  abstract =     "In the era of the Internet of Things, innovative
                 business model initiatives continue to deepen, and the
                 trend of search domains continues to expand. This paper
                 aims to scientifically analyze research trends of the
                 Internet of Things in relation to Business Model
                 Innovation through bibliometric studies. The data were
                 collected using the Clarivate Web of Science (WoS) Core
                 Collection (SSCI and SCI indexed) from 2005 to 2022
                 (November). However, the publications for the research
                 domains started in 2015. The results show that
                 scientific publications on the Internet of Things in
                 relation to Business Model Innovation have increased
                 gradually since 2019. The WoS database is utilized for
                 analyses because it contains journals and conference
                 proceedings deemed more relevant by the academic domain
                 and highly reputable sources for bibliometric studies.
                 The VOS viewer, R Language, and Microsoft Excel were
                 also used to analyze and complete the study.
                 Bibliometric and scientometric analyses were conducted
                 to identify publication patterns, text analysis, most
                 important keywords (co-word, word cloud, and
                 co-occurrence), trends for the topicality, and content
                 clustering for the publication periods. The
                 visualization of the research trends of the Internet of
                 Things in relation to Business Model Innovation
                 resulted in four co-occurrence clusters leading to some
                 of the topic areas mentioned as follows: (1) The
                 Internet of Things, (2) Business model innovation, (3)
                 Technology infrastructure, and (4) Digital
                 transformation and capabilities. The results of this
                 study will assist academics in identifying worldwide
                 research trends related to the Internet of Things and
                 Business Model Innovation as well as recommending
                 future research areas.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Xu:2023:NMT,
  author =       "Yong Xu and Hong Ni and Xiaoyong Zhu",
  title =        "A Novel Multipath Transmission Scheme for
                 Information-Centric Networking",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "80",
  day =          "17",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020080",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/80",
  abstract =     "Due to the overload of IP semantics, the traditional
                 TCP/IP network has a number of problems in scalability,
                 mobility, and security. In this context,
                 information-centric networking (ICN) is proposed to
                 solve these problems. To reduce the cost of deployment
                 and smoothly evolve, the ICN architecture needs to be
                 compatible with existing IP infrastructure. However,
                 the rigid underlying IP routing regulation limits the
                 data transmission efficiency of ICN. In this paper, we
                 propose a novel multipath transmission scheme by
                 utilizing the characteristics and functions of ICN to
                 enhance data transmission. The process of multipath
                 transmission can be regarded as a service, and a
                 multipath transmission service ID (MPSID) is assigned.
                 By using the ICN routers bound to the MPSID as relay
                 nodes, multiple parallel paths between the data source
                 and the receiver are constructed. Moreover, we design a
                 path management mechanism, including path selection and
                 path switching. It can determine the initial path based
                 on historical transmission information and switch to
                 other optimal paths according to the congestion degree
                 during transmission. The experimental results show that
                 our proposed method can improve the average throughput
                 and reduce the average flow completion time and the
                 average chunk completion time.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mehmood:2023:UKT,
  author =       "Tahir Mehmood and Ivan Serina and Alberto Lavelli and
                 Luca Putelli and Alfonso Gerevini",
  title =        "On the Use of Knowledge Transfer Techniques for
                 Biomedical Named Entity Recognition",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "79",
  day =          "17",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020079",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/79",
  abstract =     "Biomedical named entity recognition (BioNER) is a
                 preliminary task for many other tasks, e.g., relation
                 extraction and semantic search. Extracting the text of
                 interest from biomedical documents becomes more
                 demanding as the availability of online data is
                 increasing. Deep learning models have been adopted for
                 biomedical named entity recognition (BioNER) as deep
                 learning has been found very successful in many other
                 tasks. Nevertheless, the complex structure of
                 biomedical text data is still a challenging aspect for
                 deep learning models. Limited annotated biomedical text
                 data make it more difficult to train deep learning
                 models with millions of trainable parameters. The
                 single-task model, which focuses on learning a specific
                 task, has issues in learning complex feature
                 representations from a limited quantity of annotated
                 data. Moreover, manually constructing annotated data is
                 a time-consuming job. It is, therefore, vital to
                 exploit other efficient ways to train deep learning
                 models on the available annotated data. This work
                 enhances the performance of the BioNER task by taking
                 advantage of various knowledge transfer techniques:
                 multitask learning and transfer learning. This work
                 presents two multitask models (MTMs), which learn
                 shared features and task-specific features by
                 implementing the shared and task-specific layers. In
                 addition, the presented trained MTM is also fine-tuned
                 for each specific dataset to tailor it from a general
                 features representation to a specialized features
                 representation. The presented empirical results and
                 statistical analysis from this work illustrate that the
                 proposed techniques enhance significantly the
                 performance of the corresponding single-task model
                 (STM).",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sharma:2023:CSD,
  author =       "Sachin Sharma and Avishek Nag",
  title =        "Cognitive Software Defined Networking and Network
                 Function Virtualization and Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "78",
  day =          "17",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020078",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/78",
  abstract =     "The emergence of Software-Defined Networking (SDN) and
                 Network Function Virtualization (NFV) has
                 revolutionized the Internet. Using SDN, network devices
                 can be controlled from a centralized, programmable
                 control plane that is decoupled from their data plane,
                 whereas with NFV, network functions (such as network
                 address translation, firewall, and intrusion detection)
                 can be virtualized instead of being implemented on
                 proprietary hardware. In addition, Artificial
                 Intelligence (AI) and Machine Learning (ML) techniques
                 will be key to automating network operations and
                 enhancing customer service. Many of the challenges
                 behind SDN and NFV are currently being investigated in
                 several projects all over the world using AI and ML
                 techniques, such as AI- and software-based networking,
                 autonomic networking, and policy-based network
                 management. Contributions to this Special Issue come
                 from the above areas of research. Following a rigorous
                 review process, four excellent articles were accepted
                 that address and go beyond many of the challenges
                 mentioned above.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Seiger:2023:IMD,
  author =       "Ronny Seiger and Marco Franceschetti and Barbara
                 Weber",
  title =        "An Interactive Method for Detection of Process
                 Activity Executions from {IoT} Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "77",
  day =          "16",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020077",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/77",
  abstract =     "The increasing number of IoT devices equipped with
                 sensors and actuators pervading every domain of
                 everyday life allows for improved automated monitoring
                 and analysis of processes executed in IoT-enabled
                 environments. While sophisticated analysis methods
                 exist to detect specific types of activities from
                 low-level IoT data, a general approach for detecting
                 activity executions that are part of more complex
                 business processes does not exist. Moreover, dedicated
                 information systems to orchestrate or monitor process
                 executions are not available in typical IoT
                 environments. As a consequence, the large corpus of
                 existing process analysis and mining techniques to
                 check and improve process executions cannot be applied.
                 In this work, we develop an interactive method guiding
                 the analysis of low-level IoT data with the goal of
                 detecting higher-level process activity executions. The
                 method is derived following the exploratory data
                 analysis of an IoT data set from a smart factory. We
                 propose analysis steps, sensor-actuator-activity
                 patterns, and the novel concept of activity signatures
                 that are applicable in many IoT domains. The method
                 shows to be valuable for the early stages of IoT data
                 analyses to build a ground truth based on domain
                 knowledge and decisions of the process analyst, which
                 can be used for automated activity detection in later
                 stages.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ahmed:2023:EED,
  author =       "Sheeraz Ahmed and Zahoor Ali Khan and Syed Muhammad
                 Mohsin and Shahid Latif and Sheraz Aslam and Hana
                 Mujlid and Muhammad Adil and Zeeshan Najam",
  title =        "Effective and Efficient {DDoS} Attack Detection Using
                 Deep Learning Algorithm, Multi-Layer Perceptron",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "76",
  day =          "15",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020076",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/76",
  abstract =     "Distributed denial of service (DDoS) attacks pose an
                 increasing threat to businesses and government
                 agencies. They harm internet businesses, limit access
                 to information and services, and damage corporate
                 brands. Attackers use application layer DDoS attacks
                 that are not easily detectable because of impersonating
                 authentic users. In this study, we address novel
                 application layer DDoS attacks by analyzing the
                 characteristics of incoming packets, including the size
                 of HTTP frame packets, the number of Internet Protocol
                 (IP) addresses sent, constant mappings of ports, and
                 the number of IP addresses using proxy IP. We analyzed
                 client behavior in public attacks using standard
                 datasets, the CTU-13 dataset, real weblogs (dataset)
                 from our organization, and experimentally created
                 datasets from DDoS attack tools: Slow Lairs, Hulk,
                 Golden Eyes, and Xerex. A multilayer perceptron (MLP),
                 a deep learning algorithm, is used to evaluate the
                 effectiveness of metrics-based attack detection.
                 Simulation results show that the proposed MLP
                 classification algorithm has an efficiency of 98.99\%
                 in detecting DDoS attacks. The performance of our
                 proposed technique provided the lowest value of false
                 positives of 2.11\% compared to conventional
                 classifiers, i.e., Na{\"\i}ve Bayes, Decision Stump,
                 Logistic Model Tree, Na{\"\i}ve Bayes Updateable,
                 Na{\"\i}ve Bayes Multinomial Text, AdaBoostM1,
                 Attribute Selected Classifier, Iterative Classifier,
                 and OneR.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bouarourou:2023:EMB,
  author =       "Soukaina Bouarourou and Abderrahim Zannou and El Habib
                 Nfaoui and Abdelhak Boulaalam",
  title =        "An Efficient Model-Based Clustering via Joint Multiple
                 Sink Placement for {WSNs}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "75",
  day =          "15",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020075",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/75",
  abstract =     "Wireless sensor networks consist of many restrictive
                 sensor nodes with limited abilities, including limited
                 power, low bandwidth and battery, small storage space,
                 and limited computational capacity. Sensor nodes
                 produce massive amounts of data that are then collected
                 and transferred to the sink via single or multihop
                 pathways. Since the nodes' abilities are limited,
                 ineffective data transmission across the nodes makes
                 the network unstable due to the rising data
                 transmission delay and the high consumption of energy.
                 Furthermore, sink location and sensor-to-sink routing
                 significantly impact network performance. Although
                 there are suggested solutions for this challenge, they
                 suffer from low-lifetime networks, high energy
                 consumption, and data transmission delay. Based on
                 these constrained capacities, clustering is a promising
                 technique for reducing the energy use of wireless
                 sensor networks, thus improving their performance. This
                 paper models the problem of multiple sink deployment
                 and sensor-to-sink routing using the clustering
                 technique to extend the lifetime of wireless sensor
                 networks. The proposed model determines the sink
                 placements and the most effective way to transmit data
                 from sensor nodes to the sink. First, we propose an
                 improved ant clustering algorithm to group nodes, and
                 we select the cluster head based on the chance of
                 picking factor. Second, we assign nodes to sinks that
                 are designated as data collectors. Third, we provide
                 optimal paths for nodes to relay the data to the sink
                 by maximizing the network's lifetime and improving data
                 flow. The results of simulation on a real network
                 dataset demonstrate that our proposal outperforms the
                 existing state-of-the-art approaches in terms of energy
                 consumption, network lifetime, data transmission delay,
                 and scalability.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2023:CSR,
  author =       "Yanxia Li and Yang Li",
  title =        "Collaborative Storage and Resolution Method between
                 Layers in Hierarchical {ICN} Name Resolution Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "74",
  day =          "13",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020074",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/74",
  abstract =     "Name resolution system is an important infrastructure
                 in Information Centric Networking (ICN) network
                 architecture of identifier--locator separation mode. In
                 the Local Name Resolution System (LNMRS), a
                 hierarchical name resolution system for
                 latency-sensitive scenarios; higher-level resolution
                 nodes serve more users and suffer more storage
                 pressure, which causes the problem of unbalanced
                 storage load between layers, and requires inter-layer
                 collaborative storage under the constraint of
                 deterministic service latency characteristics. In this
                 paper, we use the constraints required for inter-layer
                 collaborative resolution to construct an index neighbor
                 structure and perform collaborative storage based on
                 this structure. This method relieves storage pressure
                 on high-level resolution nodes. Experimental results
                 show that the increase of total storage load brought by
                 the proposed method is 57.1\% of that by MGreedy
                 algorithm, 8.1\% of that by Greedy algorithm, and 0.8\%
                 of that by the K-Mediod algorithm when relieving the
                 same storage load for high-level resolution nodes.
                 Meanwhile, deterministic service latency feature is
                 still sustained when our proposed method is used for
                 collaborative resolution.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zilli:2023:INW,
  author =       "Vit{\'o}ria Francesca Biasibetti Zilli and Cesar David
                 Paredes Crovato and Rodrigo da Rosa Righi and Rodrigo
                 Ivan Goytia Mejia and Giovani Pesenti and Dhananjay
                 Singh",
  title =        "{I4.0I}: a New Way to Rank How Involved a Company Is
                 in the {Industry 4.0} Era",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "73",
  day =          "13",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020073",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/73",
  abstract =     "Cloud, IoT, big data, and artificial intelligence are
                 currently very present in the industrial and academic
                 areas, being drivers of technological revolution. Such
                 concepts are closely related to Industry 4.0, which can
                 be defined as the idea of a flexible, technological,
                 and connected factory, encompassing the shop floor
                 itself and its relationship between workers, the chain
                 of supply, and final products. Some studies have
                 already been developed to quantify a company's level of
                 maturity within the scope of Industry 4.0. However,
                 there is a lack of a global and unique index that, by
                 receiving as input how many implemented technologies a
                 company has, enables its classification and therefore,
                 comparison with other companies of the same genre.
                 Thus, we present the I4.0I (Industry 4.0 Index), an
                 index that allows companies to measure how far they are
                 in Industry 4.0, enabling competitiveness between
                 factories and stimulating economic and technological
                 growth. To assess the method, companies in the
                 technology sector received and answered a questionnaire
                 in which they marked the technologies they used over
                 the years and the income obtained. The results were
                 used to compare the I4.0I with the profit measured in
                 the same period, proving that the greater the use of
                 technology, the greater the benefits for the company.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Anton-Sancho:2023:PUV,
  author =       "{\'A}lvaro Ant{\'o}n-Sancho and Pablo
                 Fern{\'a}ndez-Arias and Diego Vergara",
  title =        "Perception of the Use of Virtual Reality Didactic
                 Tools among Faculty in {Mexico}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "72",
  day =          "12",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020072",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/72",
  abstract =     "This paper develops descriptive quantitative research
                 of the assessments of virtual reality (VR) technology,
                 used as a didactic tool, by a sample of 712 university
                 professors in Mexico. For this purpose, a validated
                 Likert-type questionnaire was used as an instrument,
                 the responses to which were statistically analyzed. The
                 results obtained show that professors in Mexico report
                 low levels of digital skills, but high valuations of
                 VR. These ratings depend strongly on the professors'
                 area of knowledge. In this sense, the biggest gap is
                 between Engineering professors, who value VR better,
                 and Humanities professors, who value it worse. There
                 are also gender gaps and gaps due to the digital
                 generation of the participants in the assessments made,
                 whose behavior is also different according to the area
                 of knowledge. As a result, some recommendations are
                 provided to try to reduce the gaps found.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Stach:2023:DNO,
  author =       "Christoph Stach",
  title =        "Data Is the New Oil --- Sort of: a View on Why This
                 Comparison Is Misleading and Its Implications for
                 Modern Data Administration",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "71",
  day =          "12",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020071",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/71",
  abstract =     "Currently, data are often referred to as the oil of
                 the 21st century. This comparison is not only used to
                 express that the resource data are just as important
                 for the fourth industrial revolution as oil was for the
                 technological revolution in the late 19th century.
                 There are also further similarities between these two
                 valuable resources in terms of their handling. Both
                 must first be discovered and extracted from their
                 sources. Then, the raw materials must be cleaned,
                 preprocessed, and stored before they can finally be
                 delivered to consumers. Despite these undeniable
                 similarities, however, there are significant
                 differences between oil and data in all of these
                 processing steps, making data a resource that is
                 considerably more challenging to handle. For instance,
                 data sources, as well as the data themselves, are
                 heterogeneous, which means there is no
                 one-size-fits-all data acquisition solution.
                 Furthermore, data can be distorted by the source or by
                 third parties without being noticed, which affects both
                 quality and usability. Unlike oil, there is also no
                 uniform refinement process for data, as data
                 preparation should be tailored to the subsequent
                 consumers and their intended use cases. With regard to
                 storage, it has to be taken into account that data are
                 not consumed when they are processed or delivered to
                 consumers, which means that the data volume that has to
                 be managed is constantly growing. Finally, data may be
                 subject to special constraints in terms of
                 distribution, which may entail individual delivery
                 plans depending on the customer and their intended
                 purposes. Overall, it can be concluded that innovative
                 approaches are needed for handling the resource data
                 that address these inherent challenges. In this paper,
                 we therefore study and discuss the relevant
                 characteristics of data making them such a challenging
                 resource to handle. In order to enable appropriate data
                 provisioning, we introduce a holistic research concept
                 from data source to data sink that respects the
                 processing requirements of data producers as well as
                 the quality requirements of data consumers and,
                 moreover, ensures a trustworthy data administration.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ghosh:2023:IWS,
  author =       "Swarnendu Ghosh and Teresa Gon{\c{c}}alves and Nibaran
                 Das",
  title =        "{Im2Graph}: a Weakly Supervised Approach for
                 Generating Holistic Scene Graphs from Regional
                 Dependencies",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "70",
  day =          "10",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020070",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/70",
  abstract =     "Conceptual representations of images involving
                 descriptions of entities and their relations are often
                 represented using scene graphs. Such scene graphs can
                 express relational concepts by using sets of triplets
                 ``subject---predicate---object''. Instead of building
                 dedicated models for scene graph generation, our model
                 tends to extract the latent relational information
                 implicitly encoded in image captioning models. We
                 explored dependency parsing to build grammatically
                 sound parse trees from captions. We used detection
                 algorithms for the region propositions to generate
                 dense region-based concept graphs. These were optimally
                 combined using the approximate sub-graph isomorphism to
                 create holistic concept graphs for images. The major
                 advantages of this approach are threefold. Firstly, the
                 proposed graph generation module is completely
                 rule-based and, hence, adheres to the principles of
                 explainable artificial intelligence. Secondly, graph
                 generation can be used as plug-and-play along with any
                 region proposition and caption generation framework.
                 Finally, our results showed that we could generate rich
                 concept graphs without explicit graph-based
                 supervision.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ricci:2023:DMM,
  author =       "Marina Ricci and Alessandra Scarcelli and Michele
                 Fiorentino",
  title =        "Designing for the Metaverse: a Multidisciplinary
                 Laboratory in the Industrial Design Program",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "69",
  day =          "10",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020069",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/69",
  abstract =     "The design research and education landscapes are
                 changing. The widespread development and use of
                 technologies such as Mixed Reality (MR) and the
                 diffusion of Head-Mounted Displays (HMDs) available at
                 low cost are causing a shift in design education toward
                 the Metaverse. In this ever-changing scenario, there is
                 a need to rethink design and teaching methods. However,
                 scientific literature lacks the ability to provide
                 contributions that include MR technology education in
                 the industrial design program. We, therefore, present
                 an innovative laboratory with an integrated
                 multidisciplinary approach that starts from the
                 fundamentals of interaction design and aims to teach
                 students how to design next-generation MR interfaces
                 for the Metaverse. The lab combines theory and practice
                 within three courses: Information Design, Information
                 Systems, and Virtual Design and Simulation. Industrial
                 design students follow a precise multidisciplinary
                 method consisting of five steps, from state-of-the-art
                 analysis to the presentation of a final group design of
                 an MR user interface. Thus, we introduce a class case
                 study by presenting the outcomes of a semester project
                 in the field of household appliances. Evaluation of the
                 teaching method is conducted through a semi-structured
                 questionnaire. Preliminary results show positive
                 outcomes from students in terms of acceptance,
                 effectiveness, usefulness, efficiency, and satisfaction
                 with the teaching method adopted for the laboratory.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Han:2023:RRA,
  author =       "Lu Han and Xiaohong Huang and Dandan Li and Yong
                 Zhang",
  title =        "{RingFFL}: a Ring-Architecture-Based Fair Federated
                 Learning Framework",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "68",
  day =          "09",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020068",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib; Mon
                 Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/68",
  abstract =     "In the ring-architecture-based federated learning
                 framework, security and fairness are severely
                 compromised when dishonest clients abort the training
                 process after obtaining useful information. To solve
                 the problem, we propose a Ring- architecture-based F
                 air F ederated L earning framework called RingFFL, in
                 which we design a penalty mechanism for FL. Before the
                 training starts in each round, all clients that will
                 participate in the training pay deposits in a set order
                 and record the transactions on the blockchain to ensure
                 that they are not tampered with. Subsequently, the
                 clients perform the FL training process, and the
                 correctness of the models transmitted by the clients is
                 guaranteed by the HASH algorithm during the training
                 process. When all clients perform honestly, each client
                 can obtain the final model, and the number of digital
                 currencies in each client's wallet is kept constant;
                 otherwise, the deposits of clients who leave halfway
                 will be compensated to the clients who perform honestly
                 during the training process. In this way, through the
                 penalty mechanism, all clients either obtain the final
                 model or are compensated, thus ensuring the fairness of
                 federated learning. The security analysis and
                 experimental results show that RingFFL not only
                 guarantees the accuracy and security of the federated
                 learning model but also guarantees the fairness.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bagnoli:2023:SMK,
  author =       "Franco Bagnoli and Guido de Bonfioli Cavalcabo'",
  title =        "A Simple Model of Knowledge Scaffolding Applied to
                 {Wikipedia} Growth",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "67",
  day =          "06",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020067",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/67",
  abstract =     "We illustrate a simple model of knowledge scaffolding,
                 based on the process of building a corpus of knowledge,
                 each item of which is linked to ``previous'' ones. The
                 basic idea is that the relationships among the items of
                 corpus can be essentially drawn as an acyclic network,
                 in which topmost contributions are ``derived'' from
                 items at lower levels. When a new item is added to the
                 corpus, we impose a limit to the maximum unit increase
                 (i.e., ``jumps'') of knowledge. We analyzed the time
                 growth of the corpus (number of items) and the maximum
                 knowledge, both showing a power law. Another result was
                 that the number of ``holes'' in the knowledge corpus
                 always remains limited. Our model can be used as a
                 rough approximation to the asymptotic growth of
                 Wikipedia, and indeed, actual data show a certain
                 resemblance with our model. Assuming that the user base
                 is growing, at beginning, in an exponential way, one
                 can also recover the early phases of Wikipedia
                 growth.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Koryzis:2023:DTP,
  author =       "Dimitris Koryzis and Dionisis Margaris and Costas
                 Vassilakis and Konstantinos Kotis and Dimitris
                 Spiliotopoulos",
  title =        "Disruptive Technologies for Parliaments: a Literature
                 Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "66",
  day =          "05",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020066",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/66",
  abstract =     "Exploitation and use of disruptive technologies, such
                 as the Internet of Things, recommender systems, and
                 artificial intelligence, with an ambidextrous balance,
                 are a challenge, nowadays. Users of the technologies,
                 and stakeholders, could be part of a new organisational
                 model that affects business procedures and processes.
                 Additionally, the use of inclusive participatory
                 organisational models is essential for the effective
                 adoption of these technologies. Such models aim to
                 transform organisational structures, as well. Public
                 organisations, such as the parliament, could utilise
                 information systems' personalisation techniques. As
                 there are a lot of efforts to define the framework, the
                 methodology, the techniques, the platforms, and the
                 suitable models for digital technologies adoption in
                 public organisations, this paper aims to provide a
                 literature review for disruptive technology inclusive
                 use in parliaments. The review emphasises the
                 assessment of the applicability of the technologies,
                 their maturity and usefulness, user acceptance, their
                 performance, and their correlation to the adoption of
                 relevant innovative, inclusive organisational models.
                 It is argued that the efficient digital transformation
                 of democratic institutions, such as parliaments, with
                 the use of advanced e-governance tools and disruptive
                 technologies, requires strategic approaches for
                 adoption, acceptance, and inclusive service
                 adaptation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liu:2023:MSA,
  author =       "Fan Liu and Jiandong Fang",
  title =        "Multi-Scale Audio Spectrogram Transformer for
                 Classroom Teaching Interaction Recognition",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "65",
  day =          "02",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020065",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/65",
  abstract =     "Classroom interactivity is one of the important
                 metrics for assessing classrooms, and identifying
                 classroom interactivity through classroom image data is
                 limited by the interference of complex teaching
                 scenarios. However, audio data within the classroom are
                 characterized by significant student--teacher
                 interaction. This study proposes a multi-scale audio
                 spectrogram transformer (MAST) speech scene
                 classification algorithm and constructs a classroom
                 interactive audio dataset to achieve interactive
                 teacher--student recognition in the classroom teaching
                 process. First, the original speech signal is sampled
                 and pre-processed to generate a multi-channel
                 spectrogram, which enhances the representation of
                 features compared with single-channel features; Second,
                 in order to efficiently capture the long-range global
                 context of the audio spectrogram, the audio features
                 are globally modeled by the multi-head self-attention
                 mechanism of MAST, and the feature resolution is
                 reduced during feature extraction to continuously
                 enrich the layer-level features while reducing the
                 model complexity; Finally, a further combination with a
                 time-frequency enrichment module maps the final output
                 to a class feature map, enabling accurate audio
                 category recognition. The experimental comparison of
                 MAST is carried out on the public environment audio
                 dataset and the self-built classroom audio interaction
                 datasets. Compared with the previous state-of-the-art
                 methods on public datasets AudioSet and ESC-50, its
                 accuracy has been improved by 3\% and 5\%,
                 respectively, and the accuracy of the self-built
                 classroom audio interaction dataset has reached 92.1\%.
                 These results demonstrate the effectiveness of MAST in
                 the field of general audio classification and the smart
                 classroom domain.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ahmad:2023:SCC,
  author =       "Nafi Ahmad and Abdul Wahab and John Schormans and Ali
                 Adib Arnab",
  title =        "Significance of Cross-Correlated {QoS} Configurations
                 for Validating the Subjective and Objective {QoE} of
                 Cloud Gaming Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "64",
  day =          "02",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020064",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/64",
  abstract =     "In this paper, utilising real-internet traffic data,
                 we modified a popular network emulator to better
                 imitate real network traffic and studied its subjective
                 and objective implications on QoE for cloud-gaming
                 apps. Subjective QoE evaluation was then used to
                 compare cross-correlated QoS metric with the default
                 non-correlated emulator setup. Human test subjects
                 showed different correlated versus non-correlated QoS
                 parameters affects regarding cloud gaming QoE. Game-QoE
                 is influenced more by network degradation than video
                 QoE. To validate our subjective QoE study, we analysed
                 the experiment's video objectively. We tested how well
                 Full-Reference VQA measures subjective QoE. The
                 correlation between FR QoE and subjective MOS was
                 greater in non-correlated QoS than in correlated QoS
                 conditions. We also found that correlated scenarios had
                 more stuttering events compared to non-correlated
                 scenarios, resulting in lower game QoE.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Truyen:2023:VAR,
  author =       "Eddy Truyen and Hongjie Xie and Wouter Joosen",
  title =        "Vendor-Agnostic Reconfiguration of {Kubernetes}
                 Clusters in Cloud Federations",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "63",
  day =          "01",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020063",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/63",
  abstract =     "Kubernetes (K8s) defines standardized APIs for
                 container-based cluster orchestration such that it
                 becomes possible for application managers to deploy
                 their applications in a portable and interopable
                 manner. However, a practical problem arises when the
                 same application must be replicated in a distributed
                 fashion across different edge, fog and cloud sites;
                 namely, there will not exist a single K8s vendor that
                 is able to provision and manage K8s clusters across all
                 these sites. Hence, the problem of feature
                 incompatibility between different K8s vendors arises. A
                 large number of documented features in the open-source
                 distribution of K8s are optional features that are
                 turned off by default but can be activated by setting
                 specific combinations of parameters and plug-in
                 components in configuration manifests for the K8s
                 control plane and worker node agents. However, none of
                 these configuration manifests are standardized, giving
                 K8s vendors the freedom to hide the manifests behind a
                 single, more restricted, and proprietary customization
                 interface. Therefore, some optional K8s features cannot
                 be activated consistently across K8s vendors and
                 applications that require these features cannot be run
                 on those vendors. In this paper, we present a unified,
                 vendor-agnostic feature management approach for
                 consistently configuring optional K8s features across a
                 federation of clusters hosted by different Kubernetes
                 vendors. We describe vendor-agnostic reconfiguration
                 tactics that are already applied in industry and that
                 cover a wide range of optional K8s features. Based on
                 these tactics, we design and implement an autonomic
                 controller for declarative feature compatibility
                 management across a cluster federation. We found that
                 the features configured through our vendor-agnostic
                 approach have no impact on application performance when
                 compared with a cluster where the features are
                 configured using the configuration manifests of the
                 open-source K8s distribution. Moreover, the maximum
                 time to complete reconfiguration of a single feature is
                 within 100 seconds, which is 6 times faster than using
                 proprietary customization interfaces of mainstream K8s
                 vendors such as Google Kubernetes Engine. However,
                 there is a non-negligible disruption to running
                 applications when performing the reconfiguration to an
                 existing cluster; this disruption impact does not
                 appear using the proprietary customization methods of
                 the K8s vendors due to the use of rolling upgrade of
                 cluster nodes. Therefore, our approach is best applied
                 in the following three use cases: (i) when starting up
                 new K8s clusters, (ii) when optional K8s features of
                 existing clusters must be activated as quickly as
                 possibly and temporary disruption to running
                 applications can be tolerated or (iii) when proprietary
                 customization interfaces do not allow to activate the
                 desired optional feature.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alotaibi:2023:AML,
  author =       "Afnan Alotaibi and Murad A. Rassam",
  title =        "Adversarial Machine Learning Attacks against Intrusion
                 Detection Systems: a Survey on Strategies and Defense",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "62",
  day =          "31",
  month =        jan,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020062",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/62",
  abstract =     "Concerns about cybersecurity and attack methods have
                 risen in the information age. Many techniques are used
                 to detect or deter attacks, such as intrusion detection
                 systems (IDSs), that help achieve security goals, such
                 as detecting malicious attacks before they enter the
                 system and classifying them as malicious activities.
                 However, the IDS approaches have shortcomings in
                 misclassifying novel attacks or adapting to emerging
                 environments, affecting their accuracy and increasing
                 false alarms. To solve this problem, researchers have
                 recommended using machine learning approaches as
                 engines for IDSs to increase their efficacy.
                 Machine-learning techniques are supposed to
                 automatically detect the main distinctions between
                 normal and malicious data, even novel attacks, with
                 high accuracy. However, carefully designed adversarial
                 input perturbations during the training or testing
                 phases can significantly affect their predictions and
                 classifications. Adversarial machine learning (AML)
                 poses many cybersecurity threats in numerous sectors
                 that use machine-learning-based classification systems,
                 such as deceiving IDS to misclassify network packets.
                 Thus, this paper presents a survey of adversarial
                 machine-learning strategies and defenses. It starts by
                 highlighting various types of adversarial attacks that
                 can affect the IDS and then presents the defense
                 strategies to decrease or eliminate the influence of
                 these attacks. Finally, the gaps in the existing
                 literature and future research directions are
                 presented.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Avazov:2023:FFD,
  author =       "Kuldoshbay Avazov and An Eui Hyun and Alabdulwahab
                 Abrar Sami S and Azizbek Khaitov and Akmalbek
                 Bobomirzaevich Abdusalomov and Young Im Cho",
  title =        "Forest Fire Detection and Notification Method Based on
                 {AI} and {IoT} Approaches",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "61",
  day =          "31",
  month =        jan,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020061",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/61",
  abstract =     "There is a high risk of bushfire in spring and autumn,
                 when the air is dry. Do not bring any flammable
                 substances, such as matches or cigarettes. Cooking or
                 wood fires are permitted only in designated areas.
                 These are some of the regulations that are enforced
                 when hiking or going to a vegetated forest. However,
                 humans tend to disobey or disregard guidelines and the
                 law. Therefore, to preemptively stop people from
                 accidentally starting a fire, we created a technique
                 that will allow early fire detection and classification
                 to ensure the utmost safety of the living things in the
                 forest. Some relevant studies on forest fire detection
                 have been conducted in the past few years. However,
                 there are still insufficient studies on early fire
                 detection and notification systems for monitoring fire
                 disasters in real time using advanced approaches.
                 Therefore, we came up with a solution using the
                 convergence of the Internet of Things (IoT) and You
                 Only Look Once Version 5 (YOLOv5). The experimental
                 results show that IoT devices were able to validate
                 some of the falsely detected fires or undetected fires
                 that YOLOv5 reported. This report is recorded and sent
                 to the fire department for further verification and
                 validation. Finally, we compared the performance of our
                 method with those of recently reported fire detection
                 approaches employing widely used performance matrices
                 to test the achieved fire classification results.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mokrov:2023:PAC,
  author =       "Evgeni Mokrov and Konstantin Samouylov",
  title =        "Performance Assessment and Comparison of Deployment
                 Options for {5G} Millimeter Wave Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "60",
  day =          "31",
  month =        jan,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020060",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/60",
  abstract =     "The roll-outs of fifth-generation (5G) New Radio (NR)
                 systems operating in the millimeter-wave (mmWave)
                 frequency band are essential for satisfying IMT-2020
                 requirements set forth by ITU-R in terms of the data
                 rate at the access interface. To overcome
                 mmWave-specific propagation phenomena, a number of
                 radio access network densification options have been
                 proposed, including a conventional base station (BS) as
                 well as integrated access and backhaul (IAB) with
                 terrestrial and aerial IAB nodes. The aim of this paper
                 is to qualitatively and quantitatively compare the
                 proposed deployments using coverage, spectral
                 efficiency and BS density as the main metrics of
                 interest. To this end, we develop a model capturing the
                 specifics of various deployment options. Our numerical
                 results demonstrate that, while the implementation of
                 terrestrial relaying nodes potentially improves
                 coverage and spectral efficiency, aerial relays provide
                 the highest coverage, three times that of a direct link
                 connection, and also significantly reduce the required
                 BS density. The main benefit is provided by the link
                 between the BS and the aerial relay. However, gains are
                 highly dependent on a number of elements in antenna
                 arrays and targeted outage probability. The use of
                 terrestrial relays can be considered a natural
                 trade-off between coverage and the aggregate rate.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Maaradji:2023:SCM,
  author =       "Abderrahmane Maaradji and Hakim Hacid and Assia
                 Soukane",
  title =        "From Service Composition to {Mashup Editor}: a
                 Multiperspective Taxonomy",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "59",
  day =          "31",
  month =        jan,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020059",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/59",
  abstract =     "Service-oriented computing has become a popular area
                 of research, with a particular focus on service
                 composition. There have been many developments in this
                 field, such as new techniques for data engineering in
                 service description languages, protocols for
                 publication and discovery, the optimization of service
                 selection and scheduling, and the deployment and
                 monitoring of composed services. However, this
                 diversity of approaches and methodologies can make it
                 challenging to navigate between different proposed
                 solutions and identify research gaps. In order to
                 provide a clearer understanding of this body of work,
                 this paper presents a comprehensive framework for the
                 taxonomy of service composition approaches,
                 methodologies, and tools. This framework proposes a
                 structured view of different perspectives, such as
                 formal, semantic, and automatic approaches, with a
                 particular focus on the end-user's perspective and
                 tools such as Mashups.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ferreira:2023:OPT,
  author =       "Eduardo Ferreira and Pedro Sebasti{\~a}o and Francisco
                 Cercas and Carlos S{\'a} Costa and Am{\'e}rico
                 Correia",
  title =        "An Optimized Planning Tool for Microwave Terrestrial
                 and Satellite Link Design",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "58",
  day =          "31",
  month =        jan,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020058",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/58",
  abstract =     "Today, the internet is fundamental to social
                 inclusion. There are many people that live in remote
                 areas, and the only way to supply internet services is
                 through the use of microwave terrestrial and satellite
                 systems. Thus, it is important to have efficient tools
                 to design and optimize these systems. In this paper, a
                 tool with the objective to shorten the time spent in
                 the design process of microwave terrestrial and
                 satellite point-to-point links is presented. This tool
                 can be applied in academia by engineering students,
                 providing an extended analysis of many sections of a
                 link project design, as well as in professional
                 practice by telecommunication engineering departments,
                 presenting a concise step-by-step interactive design
                 process. This tool uses three-dimensional world
                 visualization, with the Cesium Application Programming
                 Interface (API), to display and analyze site-specific
                 characteristics that can disrupt the link's quality of
                 service (QoS). Using this visualization, two
                 ray-tracing algorithms were developed to analyze signal
                 diffraction and reflection mainly throughout
                 terrestrial links. Using this new algorithm, an
                 innovative process for signal diffraction and
                 reflection calculations was created. Using updated
                 standards provided by the International
                 Telecommunication Union Radiocommunication Sector
                 (ITU-R), the characteristics of the defined simulated
                 links could be predicted, thus providing the user with
                 the metrics of signal quality and system link budget.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Nekovee:2023:VET,
  author =       "Maziar Nekovee and Ferheen Ayaz",
  title =        "Vision, Enabling Technologies, and Scenarios for a
                 {6G}-Enabled {Internet of Verticals (6G-IoV)}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "57",
  day =          "30",
  month =        jan,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020057",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/57",
  abstract =     "5G is the critical mobile infrastructure required to
                 both enable and accelerate the full digital
                 transformation of vertical sectors. While the 5G for
                 vertical sectors is aiming at connectivity requirements
                 of specific verticals, such as manufacturing,
                 automotive and energy, we envisage that in the longer
                 term the expansion of wide area cellular connectivity
                 to these sectors will pave the way for a transformation
                 to a new Internet of Verticals (IoV) in the 6G era,
                 which we call 6G-IoV. In this paper, we describe our
                 vision of 6G-IoV and examine its emerging and future
                 architectural and networking enablers. We then
                 illustrate our vision by describing a number of future
                 scenarios of the 6G-IoV, namely the Internet of Cloud
                 Manufacturing accounting for around 25\% of digital
                 services and products, the Internet of Robotics to
                 cater the challenges of the growing number of robotics
                 and expected 7\% increase in usage over the coming
                 years and the Internet of Smart Energy Grids for
                 net-zero energy balance and shifting to 100\%
                 dependence on the renewables of energy generation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chen:2023:EEH,
  author =       "Yonghong Chen and Lei Xun and Shibing Zhang",
  title =        "The Energy Efficiency of Heterogeneous Cellular
                 Networks Based on the {Poisson} Hole Process",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "2",
  pages =        "56",
  day =          "30",
  month =        jan,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15020056",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Feb 27 09:26:59 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/2/56",
  abstract =     "In order to decrease energy consumption caused by the
                 dense deployment of pico base stations (PBSs) in
                 heterogeneous cellular networks (HetNets), this paper
                 first analyzes the energy efficiency (EE) of two-tier
                 HetNets and then proposes a method to maximize the
                 network EE by adjusting the PBS transmit power. The
                 two-tier HetNets are modeled by the Poisson point
                 process (PPP) and the Poisson hole process (PHP), and
                 then the coverage probability of the macro base station
                 (MBS) and the PBS in the two-tier HetNets is derived
                 based on the mean interference to signal ratio (MISR).
                 According to the user association probability, the
                 coverage probability of the PPP-PHP HetNets is
                 obtained. Then, the tractable expression of the average
                 achievable rate is deduced on the basis of the
                 relationship between the coverage probability and the
                 average achievable rate. Finally, the expression of EE
                 is derived and the EE optimization algorithm is
                 proposed based on the PBS transmit power. The
                 simulation results show that the PPP-PHP network is
                 superior to the PPP-PPP network in terms of coverage
                 probability and EE, and the network EE can be
                 effectively improved by setting an appropriate PBS
                 transmit power.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Cho:2023:AIB,
  author =       "Hsin-Hung Cho and Wei-Che Chien and Fan-Hsun Tseng and
                 Han-Chieh Chao",
  title =        "Artificial-Intelligence-Based Charger Deployment in
                 Wireless Rechargeable Sensor Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "117",
  day =          "22",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030117",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/117",
  abstract =     "To extend a network's lifetime, wireless rechargeable
                 sensor networks are promising solutions. Chargers can
                 be deployed to replenish energy for the sensors.
                 However, deployment cost will increase when the number
                 of chargers increases. Many metrics may affect the
                 final policy for charger deployment, such as distance,
                 the power requirement of the sensors and transmission
                 radius, which makes the charger deployment problem very
                 complex and difficult to solve. In this paper, we
                 propose an efficient method for determining the field
                 of interest (FoI) in which to find suitable candidate
                 positions of chargers with lower computational costs.
                 In addition, we designed four metaheuristic algorithms
                 to address the local optima problem. Since we know that
                 metaheuristic algorithms always require more
                 computational costs for escaping local optima, we
                 designed a new framework to reduce the searching space
                 effectively. The simulation results show that the
                 proposed method can achieve the best price--performance
                 ratio.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Emad-Ud-Din:2023:IOS,
  author =       "Muhammad Emad-Ud-Din and Ya Wang",
  title =        "Indoor Occupancy Sensing via Networked Nodes
                 (2012--2022): a Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "116",
  day =          "22",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030116",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/116",
  abstract =     "In the past decade, different sensing mechanisms and
                 algorithms have been developed to detect or estimate
                 indoor occupancy. One of the most recent advancements
                 is using networked sensor nodes to create a more
                 comprehensive occupancy detection system where multiple
                 sensors can identify human presence within more
                 expansive areas while delivering enhanced accuracy
                 compared to a system that relies on stand-alone sensor
                 nodes. The present work reviews the studies from 2012
                 to 2022 that use networked sensor nodes to detect
                 indoor occupancy, focusing on PIR-based sensors.
                 Methods are compared based on pivotal ADPs that play a
                 significant role in selecting an occupancy detection
                 system for applications such as Health and Safety or
                 occupant comfort. These parameters include accuracy,
                 information requirement, maximum sensor failure and
                 minimum observation rate, and feasible detection area.
                 We briefly describe the overview of occupancy detection
                 criteria used by each study and introduce a metric
                 called ``sensor node deployment density'' through our
                 analysis. This metric captures the strength of
                 network-level data filtering and fusion algorithms
                 found in the literature. It is hinged on the fact that
                 a robust occupancy estimation algorithm requires a
                 minimal number of nodes to estimate occupancy. This
                 review only focuses on the occupancy estimation models
                 for networked sensor nodes. It thus provides a
                 standardized insight into networked nodes' occupancy
                 sensing pipelines, which employ data fusion strategies,
                 network-level machine learning algorithms, and
                 occupancy estimation algorithms. This review thus helps
                 determine the suitability of the reviewed methods to a
                 standard set of application areas by analyzing their
                 gaps.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Serrano:2023:PNM,
  author =       "Salvatore Serrano and Marco Scarpa",
  title =        "A {Petri} Net Model for Cognitive Radio {Internet of
                 Things} Networks Exploiting {GSM} Bands",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "115",
  day =          "21",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030115",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/115",
  abstract =     "Quality of service (QoS) is a crucial requirement in
                 distributed applications. Internet of Things
                 architectures have become a widely used approach in
                 many application domains, from Industry 4.0 to smart
                 agriculture; thus, it is crucial to develop appropriate
                 methodologies for managing QoS in such contexts. In an
                 overcrowded spectrum scenario, cognitive radio
                 technology could be an effective methodology for
                 improving QoS requirements. In order to evaluate QoS in
                 the context of a cognitive radio Internet of Things
                 network, we propose a Petri net-based model that
                 evaluates the cognitive radio environment and operates
                 in a 200 kHz GSM/EDGE transponder band. The model is
                 quite flexible as it considers several circuit and
                 packet switching primary user network loads and
                 configurations and several secondary user types of
                 services (that involve semantic transparency or time
                 transparency); furthermore, it is able to take into
                 account mistakes of the spectrum sensing algorithm used
                 by secondary users. Specifically, we derive the
                 distribution of the response time perceived by the
                 secondary users, where it is then possible to obtain an
                 estimation of both the maximum throughput and jitter.
                 The proposed cognitive radio scenario considers a
                 secondary user synchronized access to the channel when
                 using the GSM/EDGE frame structure.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Shi:2023:RST,
  author =       "Qi Shi and Daheng Wang and Wen Chen and Jinpei Yu and
                 Weiting Zhou and Jun Zou and Guangzu Liu",
  title =        "Research on Spaceborne Target Detection Based on
                 {Yolov5} and Image Compression",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "114",
  day =          "19",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030114",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/datacompression.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/114",
  abstract =     "Satellite image compression technology plays an
                 important role in the development of space science. As
                 optical sensors on satellites become more
                 sophisticated, high-resolution and high-fidelity
                 satellite images will occupy more storage. This raises
                 the required transmission bandwidth and transmission
                 rate in the satellite--ground data transmission system.
                 In order to reduce the pressure from image transmission
                 on the data transmission system, a spaceborne target
                 detection system based on Yolov5 and a satellite image
                 compression transmission system is proposed in this
                 paper. It can reduce the pressure on the data
                 transmission system by detecting the object of interest
                 and deciding whether to transmit. An improved Yolov5
                 network is proposed to detect the small target on the
                 high-resolution satellite image. Simulation results
                 show that the improved Yolov5 network proposed in this
                 paper can detect specific targets in real satellite
                 images, including aircraft, ships, etc. At the same
                 time, image compression has little effect on target
                 detection, so detection complexity can be effectively
                 reduced and detection speed can be improved by
                 detecting the compressed images.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Federico:2023:CEA,
  author =       "Gemma {Di Federico} and Andrea Burattin",
  title =        "{CvAMoS} --- Event Abstraction Using Contextual
                 Information",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "113",
  day =          "18",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030113",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/113",
  abstract =     "Process mining analyzes events that are logged during
                 the execution of a process, with the aim of gathering
                 useful information and knowledge. Process discovery
                 algorithms derive process models that represent these
                 processes. The level of abstraction at which the
                 process model is represented is reflected in the
                 granularity of the event log. When a process is
                 captured by the usage of sensor systems, process
                 activities are recorded at the sensor-level in the form
                 of sensor readings, and are therefore too fine-grained
                 and non-explanatory. To increase the understandability
                 of the process model, events need to be abstracted into
                 higher-level activities that provide a more meaningful
                 representation of the process. The abstraction becomes
                 more relevant and challenging when the process involves
                 human behavior, as the flexible nature of human actions
                 can make it harder to identify and abstract meaningful
                 activities. This paper proposes CvAMoS, a trace-based
                 approach for event abstraction, which focuses on
                 identifying motifs while taking context into account. A
                 motif is a recurring sequence of events that represents
                 an activity that took place under specific
                 circumstances depicted by the context. Context
                 information is logged in the event log in the form of
                 environmental sensor readings (e.g., the temperature
                 and light sensors). The presented algorithm uses a
                 distance function to deal with the variability in the
                 execution of activities. The result is a set of
                 meaningful and interpretable motifs. The algorithm has
                 been tested on both synthetic and real datasets, and
                 compared to the state of the art. CvAMoS is implemented
                 as a Java application and the code is freely
                 available.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Schnell:2023:DSW,
  author =       "Karen Schnell and Kaushik Roy and Madhuri Siddula",
  title =        "A Descriptive Study of Webpage Designs for Posting
                 Privacy Policies for Different-Sized {US} Hospitals to
                 Create an Assessment Framework",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "112",
  day =          "17",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030112",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/112",
  abstract =     "In the United States, there are laws and standards
                 guiding how people should be informed about the use of
                 their private data. However, the challenge of
                 communicating these guidelines to the na{\"\i}ve user
                 is still at its peak. Research has shown that the
                 willingness to read privacy statements is influenced by
                 attitudes toward privacy risks and privacy benefits.
                 Many websites publish privacy policies somewhere on
                 their web pages, and it can be difficult to navigate to
                 them. In the healthcare field, research has found that
                 health information websites' key information is
                 presented poorly and inconsistently. For the policies
                 to be legally binding, a person must be able to find
                 them. In the healthcare industry, where sensitive data
                 are being collected, research on how a user navigates
                 to privacy policies for different size hospital
                 websites is limited. Studies exist about privacy
                 policies or website design and not both. This
                 descriptive study involved ascertaining commonalities
                 and differences among different-sized hospitals'
                 website designs for supporting privacy policies. A
                 foundation framework was created using Web Content
                 Accessibility Guidelines (WGAC) principles and the
                 literature review findings for evaluating practices for
                 website publishing of privacy policies. The results
                 demonstrated a very low variance in the website design
                 concepts employed by hospitals to publish their privacy
                 policy.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bajaj:2023:CDD,
  author =       "Ruhi Kiran Bajaj and Rebecca Mary Meiring and Fernando
                 Beltran",
  title =        "Co-Design, Development, and Evaluation of a Health
                 Monitoring Tool Using Smartwatch Data: A
                 Proof-of-Concept Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "111",
  day =          "17",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030111",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/111",
  abstract =     "Computational analysis and integration of smartwatch
                 data with Electronic Medical Records (EMR) present
                 potential uses in preventing, diagnosing, and managing
                 chronic diseases. One of the key requirements for the
                 successful clinical application of smartwatch data is
                 understanding healthcare professional (HCP)
                 perspectives on whether these devices can play a role
                 in preventive care. Gaining insights from the vast
                 amount of smartwatch data is a challenge for HCPs, thus
                 tools are needed to support HCPs when integrating
                 personalized health monitoring devices with EMR. This
                 study aimed to develop and evaluate an application
                 prototype, co-designed with HCPs and employing design
                 science research methodology and diffusion of
                 innovation frameworks to identify the potential for
                 clinical integration. A machine learning algorithm was
                 developed to detect possible health anomalies in
                 smartwatch data, and these were presented visually to
                 HCPs in a web-based platform. HCPs completed a
                 usability questionnaire to evaluate the prototype, and
                 over 60\% of HCPs scored positively on usability. This
                 preliminary study tested the proposed research to solve
                 the practical challenges of HCP in interpreting
                 smartwatch data before fully integrating smartwatches
                 into the EMR. The findings provide design directions
                 for future applications that use smartwatch data to
                 improve clinical decision-making and reduce HCP
                 workloads.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wu:2023:CAE,
  author =       "Zixiu Wu and Simone Balloccu and Vivek Kumar and Rim
                 Helaoui and Diego Reforgiato Recupero and Daniele
                 Riboni",
  title =        "Creation, Analysis and Evaluation of {AnnoMI}, a
                 Dataset of Expert-Annotated Counselling Dialogues",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "110",
  day =          "14",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030110",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/110",
  abstract =     "Research on the analysis of counselling conversations
                 through natural language processing methods has seen
                 remarkable growth in recent years. However, the
                 potential of this field is still greatly limited by the
                 lack of access to publicly available therapy dialogues,
                 especially those with expert annotations, but it has
                 been alleviated thanks to the recent release of AnnoMI,
                 the first publicly and freely available conversation
                 dataset of 133 faithfully transcribed and
                 expert-annotated demonstrations of high- and
                 low-quality motivational interviewing (MI)---an
                 effective therapy strategy that evokes client
                 motivation for positive change. In this work, we
                 introduce new expert-annotated utterance attributes to
                 AnnoMI and describe the entire data collection process
                 in more detail, including dialogue source selection,
                 transcription, annotation, and post-processing. Based
                 on the expert annotations on key MI aspects, we carry
                 out thorough analyses of AnnoMI with respect to
                 counselling-related properties on the utterance,
                 conversation, and corpus levels. Furthermore, we
                 introduce utterance-level prediction tasks with
                 potential real-world impacts and build baseline models.
                 Finally, we examine the performance of the models on
                 dialogues of different topics and probe the
                 generalisability of the models to unseen topics.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mangler:2023:DXE,
  author =       "Juergen Mangler and Joscha Gr{\"u}ger and Lukas
                 Malburg and Matthias Ehrendorfer and Yannis Bertrand
                 and Janik-Vasily Benzin and Stefanie Rinderle-Ma and
                 Estefania Serral Asensio and Ralph Bergmann",
  title =        "{DataStream} {XES} Extension: Embedding {IoT} Sensor
                 Data into Extensible Event Stream Logs",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "109",
  day =          "14",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030109",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/109",
  abstract =     "The Internet of Things (IoT) has been shown to be very
                 valuable for Business Process Management (BPM), for
                 example, to better track and control process
                 executions. While IoT actuators can automatically
                 trigger actions, IoT sensors can monitor the changes in
                 the environment and the humans involved in the
                 processes. These sensors produce large amounts of
                 discrete and continuous data streams, which hold the
                 key to understanding the quality of the executed
                 processes. However, to enable this understanding, it is
                 needed to have a joint representation of the data
                 generated by the process engine executing the process,
                 and the data generated by the IoT sensors. In this
                 paper, we present an extension of the event log
                 standard format XES called DataStream. DataStream
                 enables the connection of IoT data to process events,
                 preserving the full context required for data analysis,
                 even when scenarios or hardware artifacts are rapidly
                 changing. The DataStream extension is designed based on
                 a set of goals and evaluated by creating two datasets
                 for real-world scenarios from the
                 transportation/logistics and manufacturing domains.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sultana:2023:NHE,
  author =       "Habiba Sultana and A. H. M. Kamal and Gahangir Hossain
                 and Muhammad Ashad Kabir",
  title =        "A Novel Hybrid Edge Detection and {LBP} Code-Based
                 Robust Image Steganography Method",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "108",
  day =          "10",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030108",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/108",
  abstract =     "In digital image processing and steganography, images
                 are often described using edges and local binary
                 pattern (LBP) codes. By combining these two properties,
                 a novel hybrid image steganography method of secret
                 embedding is proposed in this paper. This method only
                 employs edge pixels that influence how well the novel
                 approach embeds data. To increase the quantity of
                 computed edge pixels, several edge detectors are
                 applied and hybridized using a logical OR operation. A
                 morphological dilation procedure in the hybridized edge
                 image is employed to this purpose. The least
                 significant bits (LSB) and all LBP codes are calculated
                 for edge pixels. Afterward, these LBP codes, LSBs, and
                 secret bits using an exclusive-OR operation are merged.
                 These resulting implanted bits are delivered to edge
                 pixels' LSBs. The experimental results show that the
                 suggested approach outperforms current strategies in
                 terms of measuring perceptual transparency, such as
                 peak signal-to-noise ratio (PSNR) and structural
                 similarity index (SSI). The embedding capacity per
                 tempered pixel in the proposed approach is also
                 substantial. Its embedding guidelines protect the
                 privacy of implanted data. The entropy, correlation
                 coefficient, cosine similarity, and pixel difference
                 histogram data show that our proposed method is more
                 resistant to various types of cyber-attacks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Capkovic:2023:DDI,
  author =       "Frantisek Capkovic",
  title =        "Dealing with Deadlocks in Industrial Multi Agent
                 Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "107",
  day =          "09",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030107",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/107",
  abstract =     "Automated Manufacturing Systems (AMS) consisting of
                 many cooperating devices incorporated into multiple
                 cooperating production lines, sharing common resources,
                 represent industrial Multi-Agent Systems (MAS).
                 Deadlocks may occur during operation of such MAS. It is
                 necessary to deal with deadlocks (more precisely said,
                 to prevent them) to ensure the correct behavior of AMS.
                 For this purpose, among other methods, methods based on
                 Petri nets (PN) are used too. Because AMS are very
                 often described by PN models, two PN-based methods will
                 be presented here, namely based on (i) PN place
                 invariants (P-invariants); and (ii) PN siphons and
                 traps. Intended final results of usage these methods is
                 finding a supervisor allowing a deadlock-free activity
                 of the global MAS. While the former method yields
                 results in analytical terms, latter one need
                 computation of siphons and traps.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Boumechaal:2023:CQQ,
  author =       "Hasna Boumechaal and Zizette Boufaida",
  title =        "Complex Queries for Querying Linked Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "106",
  day =          "09",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030106",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/106",
  abstract =     "Querying Linked Data is one of the most important
                 issues for the semantic web community today because it
                 requires the user to understand the structure and
                 vocabularies used in various data sources. Furthermore,
                 users must be familiar with the syntax of query
                 languages, such as SPARQL. However, because users are
                 accustomed to natural language-based search, novice
                 users may find it challenging to use these features. As
                 a result, new approaches for querying Linked Data
                 sources on the web with NL queries must be defined. In
                 this paper, we propose a novel system for converting
                 natural language queries into SPARQL queries to query
                 linked and heterogeneous semantic data on the web.
                 While most existing methods have focused on simple
                 queries and have ignored complex queries, the method
                 described in this work aims to handle various types of
                 NL queries, particularly complex queries containing
                 negation, numbers, superlatives, and comparative
                 adjectives. Three complementary strategies are used in
                 this context: (1) identifying the semantic relations
                 between query terms in order to understand the user's
                 needs; (2) mapping the NL terms to semantic entities;
                 and (3) constructing the query's valid triples based on
                 the different links used to describe the identified
                 entities in order to generate correct SPARQL queries.
                 The empirical evaluations show that the proposed system
                 is effective.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Andrade:2023:BBS,
  author =       "Daniel Andrade and Roberto Magueta and Ad{\~a}o Silva
                 and Paulo Marques",
  title =        "Beamforming Based on a {SSS} Angle Estimation
                 Algorithm for {5G} {NR} Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "105",
  day =          "09",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030105",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/105",
  abstract =     "The current 5G-NR standard includes the transmission
                 of multiple synchronization signal blocks (SSBs) in
                 different directions to be exploited in beamforming
                 techniques. However, choosing a pair of these beams
                 leads to performance degradation, mainly for the cases
                 where the transmit and receive beams are not aligned,
                 because it considers that only few fixed directions
                 among wide beams are established. Therefore, in this
                 article, we design a new 3GPP-standard- compliant beam
                 pair selection algorithm based on secondary
                 synchronization signal (SSS) angle estimation (BSAE)
                 that makes use of multiple synchronization signal
                 blocks (SSBs) to maximize the reference signal received
                 power (RSRP) value at the receiver. This optimization
                 is performed using the SSSs present in each SSB to
                 perform channel estimation in the digital domain.
                 Afterwards, the combination of those estimations is
                 used to perform equivalent channel propagation matrix
                 estimation without the analog processing effects.
                 Finally, through the estimated channel propagation
                 matrix, the angle that maximizes the RSRP is determined
                 to compute the most suitable beam. The proposed
                 algorithm was evaluated and compared with a
                 conventional beam pair selection algorithm. Ours has
                 better performance results. Furthermore, the proposed
                 algorithm achieved performance close to the optimal
                 performance, where all channel state information (CSI)
                 is available, emphasizing the interest of the proposed
                 approach for practical 5G mmWave mMIMO
                 implementations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Iqbal:2023:OTE,
  author =       "Mansoor Iqbal and Zahid Ullah and Izaz Ahmad Khan and
                 Sheraz Aslam and Haris Shaheer and Mujtaba Humayon and
                 Muhammad Asjad Salahuddin and Adeel Mehmood",
  title =        "Optimizing Task Execution: The Impact of Dynamic Time
                 Quantum and Priorities on Round {Robin} Scheduling",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "104",
  day =          "08",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030104",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/104",
  abstract =     "Task scheduling algorithms are crucial for optimizing
                 the utilization of computing resources. This work
                 proposes a unique approach for improving task execution
                 in real-time systems using an enhanced Round Robin
                 scheduling algorithm variant incorporating dynamic time
                 quantum and priority. The proposed algorithm adjusts
                 the time slice allocated to each task based on
                 execution time and priority, resulting in more
                 efficient resource utilization. We also prioritize
                 higher-priority tasks and execute them as soon as they
                 arrive in the ready queue, ensuring the timely
                 completion of critical tasks. We evaluate the
                 performance of our algorithm using a set of real-world
                 tasks and compare it with traditional Round Robin
                 scheduling. The results show that our proposed approach
                 significantly improves task execution time and resource
                 utilization compared to conventional Round Robin
                 scheduling. Our approach offers a promising solution
                 for optimizing task execution in real-time systems. The
                 combination of dynamic time quantum and priorities adds
                 a unique element to the existing literature in this
                 field.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alfian:2023:URF,
  author =       "Ganjar Alfian and Muhammad Syafrudin and Norma Latif
                 Fitriyani and Sahirul Alam and Dinar Nugroho Pratomo
                 and Lukman Subekti and Muhammad Qois Huzyan Octava and
                 Ninis Dyah Yulianingsih and Fransiskus Tatas Dwi Atmaji
                 and Filip Benes",
  title =        "Utilizing Random Forest with {iForest}-Based Outlier
                 Detection and {SMOTE} to Detect Movement and Direction
                 of {RFID} Tags",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "103",
  day =          "08",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030103",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/103",
  abstract =     "In recent years, radio frequency identification (RFID)
                 technology has been utilized to monitor product
                 movements within a supply chain in real time. By
                 utilizing RFID technology, the products can be tracked
                 automatically in real-time. However, the RFID cannot
                 detect the movement and direction of the tag. This
                 study investigates the performance of machine learning
                 (ML) algorithms to detect the movement and direction of
                 passive RFID tags. The dataset utilized in this study
                 was created by considering a variety of conceivable tag
                 motions and directions that may occur in actual
                 warehouse settings, such as going inside and out of the
                 gate, moving close to the gate, turning around, and
                 static tags. The statistical features are derived from
                 the received signal strength (RSS) and the timestamp of
                 tags. Our proposed model combined Isolation Forest
                 (iForest) outlier detection, Synthetic Minority Over
                 Sampling Technique (SMOTE) and Random Forest (RF) has
                 shown the highest accuracy up to 94.251\% as compared
                 to other ML models in detecting the movement and
                 direction of RFID tags. In addition, we demonstrated
                 the proposed classification model could be applied to a
                 web-based monitoring system, so that tagged products
                 that move in or out through a gate can be correctly
                 identified. This study is expected to improve the RFID
                 gate on detecting the status of products (being
                 received or delivered) automatically.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2023:IPA,
  author =       "Juan Wang and Jing Zhong and Jiangqi Li",
  title =        "{IoT}-Portrait: Automatically Identifying {IoT}
                 Devices via Transformer with Incremental Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "102",
  day =          "07",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030102",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/102",
  abstract =     "With the development of IoT, IoT devices have
                 proliferated. With the increasing demands of network
                 management and security evaluation, automatic
                 identification of IoT devices becomes necessary.
                 However, existing works require a lot of manual effort
                 and face the challenge of catastrophic forgetting. In
                 this paper, we propose IoT-Portrait, an automatic IoT
                 device identification framework based on a transformer
                 network. IoT-Portrait automatically acquires
                 information about IoT devices as labels and learns the
                 traffic behavior characteristics of devices through a
                 transformer neural network. Furthermore, for privacy
                 protection and overhead reasons, it is not easy to save
                 all past samples to retrain the classification model
                 when new devices join the network. Therefore, we use a
                 class incremental learning method to train the new
                 model to preserve old classes' features while learning
                 new devices' features. We implement a prototype of
                 IoT-Portrait based on our lab environment and
                 open-source database. Experimental results show that
                 IoT-Portrait achieves a high identification rate of up
                 to 99\% and is well resistant to catastrophic
                 forgetting with a negligible added cost both in memory
                 and time. It indicates that IoT-Portrait can classify
                 IoT devices effectively and continuously.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liang:2023:RAB,
  author =       "Haoming Liang and Jinze Du and Hongchen Zhang and Bing
                 Han and Yan Ma",
  title =        "Relational Action Bank with Semantic--Visual Attention
                 for Few-Shot Action Recognition",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "101",
  day =          "03",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030101",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/101",
  abstract =     "Recently, few-shot learning has attracted significant
                 attention in the field of video action recognition,
                 owing to its data-efficient learning paradigm. Despite
                 the encouraging progress, identifying ways to further
                 improve the few-shot learning performance by exploring
                 additional or auxiliary information for video action
                 recognition remains an ongoing challenge. To address
                 this problem, in this paper we make the first attempt
                 to propose a relational action bank with
                 semantic--visual attention for few-shot action
                 recognition. Specifically, we introduce a relational
                 action bank as the auxiliary library to assist the
                 network in understanding the actions in novel classes.
                 Meanwhile, the semantic--visual attention is devised to
                 adaptively capture the connections to the foregone
                 actions via both semantic correlation and visual
                 similarity. We extensively evaluate our approach via
                 two backbone models (ResNet-50 and C3D) on HMDB and
                 Kinetics datasets, and demonstrate that the proposed
                 model can obtain significantly better performance
                 compared against state-of-the-art methods. Notably, our
                 results demonstrate an average improvement of about
                 6.2\% when compared to the second-best method on the
                 Kinetics dataset.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Abikoye:2023:SCU,
  author =       "Oluwakemi Christiana Abikoye and Esau Taiwo Oladipupo
                 and Agbotiname Lucky Imoize and Joseph Bamidele
                 Awotunde and Cheng-Chi Lee and Chun-Ta Li",
  title =        "Securing Critical User Information over the {Internet
                 of Medical Things} Platforms Using a Hybrid
                 Cryptography Scheme",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "99",
  day =          "28",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030099",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/99",
  abstract =     "The application of the Internet of Medical Things
                 (IoMT) in medical systems has brought much ease in
                 discharging healthcare services by medical
                 practitioners. However, the security and privacy
                 preservation of critical user data remain the reason
                 the technology has not yet been fully maximized.
                 Undoubtedly, a secure IoMT model that preserves
                 individual users' privacy will enhance the wide
                 acceptability of IoMT technology. However, existing
                 works that have attempted to solve these privacy and
                 insecurity problems are not space-conservative,
                 computationally intensive, and also vulnerable to
                 security attacks. In this paper, an IoMT-based model
                 that conserves the privacy of the data, is less
                 computationally intensive, and is resistant to various
                 cryptanalysis attacks is proposed. Specifically, an
                 efficient privacy-preserving technique where an
                 efficient searching algorithm through encrypted data
                 was used and a hybrid cryptography algorithm that
                 combines the modification of the Caesar cipher with the
                 Elliptic Curve Diffie Hellman (ECDH) and Digital
                 Signature Algorithm (DSA) were projected to achieve
                 user data security and privacy preservation of the
                 patient. Furthermore, the modified algorithm can secure
                 messages during transmission, perform key exchanges
                 between clients and healthcare centres, and guarantee
                 user authentication by authorized healthcare centres.
                 The proposed IoMT model, leveraging the hybrid
                 cryptography algorithm, was analysed and compared
                 against different security attacks. The analysis
                 results revealed that the model is secure, preserves
                 the privacy of critical user information, and shows
                 robust resistance against different cryptanalysis
                 attacks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rangelov:2023:TIM,
  author =       "Denis Rangelov and Philipp L{\"a}mmel and Lisa Brunzel
                 and Stephan Borgert and Paul Darius and Nikolay
                 Tcholtchev and Michell Boerger",
  title =        "Towards an Integrated Methodology and Toolchain for
                 Machine Learning-Based Intrusion Detection in Urban
                 {IoT} Networks and Platforms",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "98",
  day =          "28",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030098",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/98",
  abstract =     "The constant increase in volume and wide variety of
                 available Internet of Things (IoT) devices leads to
                 highly diverse software and hardware stacks, which
                 opens new avenues for exploiting previously unknown
                 vulnerabilities. The ensuing risks are amplified by the
                 inherent IoT resource constraints both in terms of
                 performance and energy expenditure. At the same time,
                 IoT devices often generate or collect sensitive,
                 real-time data used in critical application scenarios
                 (e.g., health monitoring, transportation, smart energy,
                 etc.). All these factors combined make IoT networks a
                 primary target and potential victim of malicious
                 actors. In this paper, we presented a brief overview of
                 existing attacks and defense strategies and used this
                 as motivation for proposing an integrated methodology
                 for developing protection mechanisms for smart city IoT
                 networks. The goal of this work was to lay out a
                 theoretical plan and a corresponding pipeline of steps,
                 i.e., a development and implementation process, for the
                 design and application of cybersecurity solutions for
                 urban IoT networks. The end goal of following the
                 proposed process is the deployment and continuous
                 improvement of appropriate IoT security measures in
                 real-world urban IoT infrastructures. The application
                 of the methodology was exemplified on an
                 OMNET++-simulated scenario, which was developed in
                 collaboration with industrial partners and a
                 municipality.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Asif:2023:IBB,
  author =       "Rameez Asif and Syed Raheel Hassan and Gerard Parr",
  title =        "Integrating a Blockchain-Based Governance Framework
                 for Responsible {AI}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "97",
  day =          "28",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030097",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/97",
  abstract =     "This research paper reviews the potential of smart
                 contracts for responsible AI with a focus on
                 frameworks, hardware, energy efficiency, and
                 cyberattacks. Smart contracts are digital agreements
                 that are executed by a blockchain, and they have the
                 potential to revolutionize the way we conduct business
                 by increasing transparency and trust. When it comes to
                 responsible AI systems, smart contracts can play a
                 crucial role in ensuring that the terms and conditions
                 of the contract are fair and transparent as well as
                 that any automated decision-making is explainable and
                 auditable. Furthermore, the energy consumption of
                 blockchain networks has been a matter of concern; this
                 article explores the energy efficiency element of smart
                 contracts. Energy efficiency in smart contracts may be
                 enhanced by the use of techniques such as off-chain
                 processing and sharding. The study emphasises the need
                 for careful auditing and testing of smart contract code
                 in order to protect against cyberattacks along with the
                 use of secure libraries and frameworks to lessen the
                 likelihood of smart contract vulnerabilities.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Singh:2023:BEC,
  author =       "Raman Singh and Sean Sturley and Hitesh Tewari",
  title =        "Blockchain-Enabled {Chebyshev} Polynomial-Based Group
                 Authentication for Secure Communication in an {Internet
                 of Things} Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "96",
  day =          "28",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030096",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/96",
  abstract =     "The utilization of Internet of Things (IoT) devices in
                 various smart city and industrial applications is
                 growing rapidly. Within a trusted authority (TA), such
                 as an industry or smart city, all IoT devices are
                 closely monitored in a controlled infrastructure.
                 However, in cases where an IoT device from one TA needs
                 to communicate with another IoT device from a different
                 TA, the trust establishment between these devices
                 becomes extremely important. Obtaining a digital
                 certificate from a certificate authority for each IoT
                 device can be expensive. To solve this issue, a group
                 authentication framework is proposed that can establish
                 trust between group IoT devices owned by different
                 entities. The Chebyshev polynomial has many important
                 properties, semigroup is one of the most important.
                 These properties make the Chebyshev polynomial a good
                 candidate for the proposed group authentication
                 mechanism. The secure exchange of information between
                 trusted authorities is supported by Blockchain
                 technology. The proposed framework was implemented and
                 tested using Python and deployed on Blockchain using
                 Ethereum's Goerli's testnet. The results show that the
                 proposed framework can reasonably use Chebyshev
                 polynomials with degrees up to four digits in length.
                 The values of various parameters related to Blockchain
                 are also discussed to understand the usability of the
                 proposed framework.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ntafloukas:2023:VAA,
  author =       "Konstantinos Ntafloukas and Liliana Pasquale and
                 Beatriz Martinez-Pastor and Daniel P. McCrum",
  title =        "A Vulnerability Assessment Approach for Transportation
                 Networks Subjected to Cyber--Physical Attacks",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "100",
  day =          "28",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030100",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/100",
  abstract =     "Transportation networks are fundamental to the
                 efficient and safe functioning of modern societies. In
                 the past, physical and cyber space were treated as
                 isolated environments, resulting in transportation
                 network being considered vulnerable only to threats
                 from the physical space (e.g., natural hazards). The
                 integration of Internet of Things-based wireless sensor
                 networks into the sensing layer of critical
                 transportation infrastructure has resulted in
                 transportation networks becoming susceptible to
                 cyber--physical attacks due to the inherent
                 vulnerabilities of IoT devices. However, current
                 vulnerability assessment methods lack details related
                 to the integration of the cyber and physical space in
                 transportation networks. In this paper, we propose a
                 new vulnerability assessment approach for
                 transportation networks subjected to cyber--physical
                 attacks at the sensing layer. The novelty of the
                 approach used relies on the combination of the physical
                 and cyber space, using a Bayesian network attack graph
                 that enables the probabilistic modelling of
                 vulnerability states in both spaces. A new probability
                 indicator is proposed to enable the assignment of
                 probability scores to vulnerability states, considering
                 different attacker profile characteristics and control
                 barriers. A probability-based ranking table is
                 developed that details the most vulnerable nodes of the
                 graph. The vulnerability of the transportation network
                 is measured as a drop in network efficiency after the
                 removal of the highest probability-based ranked nodes.
                 We demonstrate the application of the approach by
                 studying the vulnerability of a transportation network
                 case study to a cyber--physical attack at the sensing
                 layer. Monte Carlo simulations and sensitivity analysis
                 are performed as methods to evaluate the results. The
                 results indicate that the vulnerability of the
                 transportation network depends to a large extent on the
                 successful exploitation of vulnerabilities, both in the
                 cyber and physical space. Additionally, we demonstrate
                 the usefulness of the proposed approach by comparing
                 the results with other currently available methods. The
                 approach is of interest to stakeholders who are
                 attempting to incorporate the cyber domain into the
                 vulnerability assessment procedures of their system.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Berardi:2023:WOT,
  author =       "Davide Berardi and Franco Callegati and Andrea Giovine
                 and Andrea Melis and Marco Prandini and Lorenzo
                 Rinieri",
  title =        "When Operation Technology Meets Information
                 Technology: Challenges and Opportunities",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "95",
  day =          "27",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030095",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/95",
  abstract =     "Industry 4.0 has revolutionized process innovation
                 while facilitating and encouraging many new
                 possibilities. The objective of Industry 4.0 is the
                 radical enhancement of productivity, a goal that
                 presupposes the integration of Operational Technology
                 (OT) networks with Information Technology (IT)
                 networks, which were hitherto isolated. This disruptive
                 approach is enabled by adopting several emerging
                 technologies in Enterprise processes. In this
                 manuscript, we discuss what we believe to be one of the
                 main challenges preventing the full employment of
                 Industry 4.0, namely, the integration of Operation
                 Technology networking and Information Technology
                 networking. We discuss the technical challenges
                 alongside the potential tools while providing a
                 state-of-the-art use case scenario. We showcase a
                 possible solution based on the Asset Administration
                 Shell approach, referring to the use case of camera
                 synchronization for collaborative tasks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rasool:2023:QCH,
  author =       "Raihan Ur Rasool and Hafiz Farooq Ahmad and Wajid
                 Rafique and Adnan Qayyum and Junaid Qadir and Zahid
                 Anwar",
  title =        "Quantum Computing for Healthcare: a Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "94",
  day =          "27",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030094",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/94",
  abstract =     "In recent years, the interdisciplinary field of
                 quantum computing has rapidly developed and garnered
                 substantial interest from both academia and industry
                 due to its ability to process information in
                 fundamentally different ways, leading to hitherto
                 unattainable computational capabilities. However,
                 despite its potential, the full extent of quantum
                 computing's impact on healthcare remains largely
                 unexplored. This survey paper presents the first
                 systematic analysis of the various capabilities of
                 quantum computing in enhancing healthcare systems, with
                 a focus on its potential to revolutionize
                 compute-intensive healthcare tasks such as drug
                 discovery, personalized medicine, DNA sequencing,
                 medical imaging, and operational optimization. Through
                 a comprehensive analysis of existing literature, we
                 have developed taxonomies across different dimensions,
                 including background and enabling technologies,
                 applications, requirements, architectures, security,
                 open issues, and future research directions, providing
                 a panoramic view of the quantum computing paradigm for
                 healthcare. Our survey aims to aid both new and
                 experienced researchers in quantum computing and
                 healthcare by helping them understand the current
                 research landscape, identifying potential opportunities
                 and challenges, and making informed decisions when
                 designing new architectures and applications for
                 quantum computing in healthcare.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Jiang:2023:DPM,
  author =       "Lili Jiang and Vicen{\c{c}} Torra",
  title =        "Data Protection and Multi-Database Data-Driven
                 Models",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "93",
  day =          "27",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030093",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/93",
  abstract =     "Anonymization and data masking have effects on
                 data-driven models. Different anonymization methods
                 have been developed to provide a good trade-off between
                 privacy guarantees and data utility. Nevertheless, the
                 effects of data protection (e.g., data microaggregation
                 and noise addition) on data integration and on
                 data-driven models (e.g., machine learning models)
                 built from these data are not known. In this paper, we
                 study how data protection affects data integration, and
                 the corresponding effects on the results of machine
                 learning models built from the outcome of the data
                 integration process. The experimental results show that
                 the levels of protection that prevent proper database
                 integration do not affect machine learning models that
                 learn from the integrated database to the same degree.
                 Concretely, our preliminary analysis and experiments
                 show that data protection techniques have a lower level
                 of impact on data integration than on machine learning
                 models.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{He:2023:GTB,
  author =       "Jingsha He and Yue Li and Nafei Zhu",
  title =        "A Game Theory-Based Model for the Dissemination of
                 Privacy Information in Online Social Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "92",
  day =          "27",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030092",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/92",
  abstract =     "Online social networks (OSNs) have experienced rapid
                 growth in recent years, and an increasing number of
                 people now use OSNs, such as Facebook and Twitter, to
                 share and spread information on a daily basis. As a
                 special type of information, user personal information
                 is also widely disseminated in such networks, posing
                 threats to user privacy. The study on privacy
                 information dissemination is thus useful for the
                 development of mechanisms and tools for the effective
                 protection of privacy information in OSNs. In this
                 paper, we propose to apply the game theory to establish
                 a sender--receiver game model and the Nash equilibrium
                 to describe the behavioral strategies of users in
                 disseminating privacy information. Factors that affect
                 the dissemination of privacy information are also
                 analyzed with two important aspects: intimacy and
                 popularity of the privacy-concerning subject.
                 Simulation experiments were conducted based on real
                 data sets from scale-free networks and real social
                 networks to compare and analyze the effectiveness of
                 the model. Results show that the proposed game theory
                 is applicable to the privacy information dissemination
                 model, which implements intimacy and popularity in the
                 modeling of the dissemination of privacy information in
                 OSNs. Both the impact of the macro-level OSNs and the
                 micro-relationships between users are evaluated on the
                 dissemination of privacy information, which provides a
                 new perspective for exploring the dissemination of
                 privacy information and facilitates the development of
                 effective mechanisms for privacy protection in OSNs.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hasslinger:2023:SAA,
  author =       "Gerhard Hasslinger and Konstantinos Ntougias and Frank
                 Hasslinger and Oliver Hohlfeld",
  title =        "Scope and Accuracy of Analytic and Approximate Results
                 for {FIFO}, Clock-Based and {LRU} Caching Performance",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "91",
  day =          "24",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030091",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/91",
  abstract =     "We evaluate analysis results and approximations for
                 the performance of basic caching methods, assuming
                 independent requests. Compared with simulative
                 evaluations, the analysis results are accurate, but
                 their computation is tractable only within a limited
                 scope. We compare the scalability of analytical FIFO
                 and LRU solutions including extensions for multisegment
                 caches and for caches with data of varying sizes. On
                 the other hand, approximations have been proposed for
                 the FIFO and LRU hit ratio. They are simple and
                 scalable, but their accuracy is confirmed mainly
                 through asymptotic behaviour only for large caches. We
                 derive bounds on the approximation errors in a detailed
                 worst-case study with a focus on small caches. The
                 approximations are extended to data of different sizes.
                 Then a fraction of unused cache space can add to the
                 deviations, which is estimated in order to improve the
                 solution.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kirikkayis:2023:BFM,
  author =       "Yusuf Kirikkayis and Florian Gallik and Michael Winter
                 and Manfred Reichert",
  title =        "{BPMNE4IoT}: a Framework for Modeling, Executing and
                 Monitoring {IoT}-Driven Processes",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "90",
  day =          "22",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030090",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/90",
  abstract =     "The Internet of Things (IoT) enables a variety of
                 smart applications, including smart home, smart
                 manufacturing, and smart city. By enhancing Business
                 Process Management Systems with IoT capabilities, the
                 execution and monitoring of business processes can be
                 significantly improved. Providing a holistic support
                 for modeling, executing and monitoring IoT-driven
                 processes, however, constitutes a challenge. Existing
                 process modeling and process execution languages, such
                 as BPMN 2.0, are unable to fully meet the IoT
                 characteristics (e.g., asynchronicity and parallelism)
                 of IoT-driven processes. In this article, we present
                 BPMNE4IoT---A holistic framework for modeling,
                 executing and monitoring IoT-driven processes. We
                 introduce various artifacts and events based on the
                 BPMN 2.0 metamodel that allow realizing the desired IoT
                 awareness of business processes. The framework is
                 evaluated along two real-world scenarios from two
                 different domains. Moreover, we present a user study
                 for comparing BPMNE4IoT and BPMN 2.0. In particular,
                 this study has confirmed that the BPMNE4IoT framework
                 facilitates the support of IoT-driven processes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2023:FWP,
  author =       "Sheng-Ming Wang and Wei-Min Cheng",
  title =        "Fast Way to Predict Parking Lots Availability: For
                 Shared Parking Lots Based on Dynamic Parking Fee
                 System",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "89",
  day =          "22",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030089",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/89",
  abstract =     "This study mainly focuses on the estimation
                 calculation of urban parking space. Urban parking has
                 always been a problem that plagues governments
                 worldwide. Due to limited parking space, if the parking
                 space is not controlled correctly, with the city's
                 development, the city will eventually face the result
                 that there is nowhere to park. In order to effectively
                 manage the urban parking problem, using the dynamic
                 parking fee pricing mechanism combined with the concept
                 of shared parking is an excellent way to alleviate the
                 parking problem, but how to quickly estimate the total
                 number of available parking spaces in the area is a big
                 problem. This study provides a fast parking space
                 estimation method and verifies the feasibility of this
                 estimation method through actual data from various
                 types of fields. This study also comprehensively
                 discusses the changing characteristics of parking space
                 data in multiple areas and possible data anomalies and
                 studies and explains the causes of data anomalies. The
                 study also concludes with a description of potential
                 applications of the predictive model in conjunction
                 with subsequent dynamic parking pricing mechanisms and
                 self-driving systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gebreyesus:2023:MLD,
  author =       "Yibrah Gebreyesus and Damian Dalton and Sebastian
                 Nixon and Davide {De Chiara} and Marta Chinnici",
  title =        "Machine Learning for Data Center Optimizations:
                 Feature Selection Using {Shapley Additive exPlanation
                 (SHAP)}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "3",
  pages =        "88",
  day =          "21",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15030088",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Mar 29 11:12:24 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/3/88",
  abstract =     "The need for artificial intelligence (AI) and machine
                 learning (ML) models to optimize data center (DC)
                 operations increases as the volume of operations
                 management data upsurges tremendously. These strategies
                 can assist operators in better understanding their DC
                 operations and help them make informed decisions
                 upfront to maintain service reliability and
                 availability. The strategies include developing models
                 that optimize energy efficiency, identifying
                 inefficient resource utilization and scheduling
                 policies, and predicting outages. In addition to model
                 hyperparameter tuning, feature subset selection (FSS)
                 is critical for identifying relevant features for
                 effectively modeling DC operations to provide insight
                 into the data, optimize model performance, and reduce
                 computational expenses. Hence, this paper introduces
                 the Shapley Additive exPlanation (SHAP) values method,
                 a class of additive feature attribution values for
                 identifying relevant features that is rarely discussed
                 in the literature. We compared its effectiveness with
                 several commonly used, importance-based feature
                 selection methods. The methods were tested on real DC
                 operations data streams obtained from the ENEA CRESCO6
                 cluster with 20,832 cores. To demonstrate the
                 effectiveness of SHAP compared to other methods, we
                 selected the top ten most important features from each
                 method, retrained the predictive models, and evaluated
                 their performance using the MAE, RMSE, and MPAE
                 evaluation criteria. The results presented in this
                 paper demonstrate that the predictive models trained
                 using features selected with the SHAP-assisted method
                 performed well, with a lower error and a reasonable
                 execution time compared to other methods.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Song:2023:PFP,
  author =       "Beibei Song and Dehua Zhou and Jiahe Wu and Xiaowei
                 Yuan and Yiming Zhu and Chuansheng Wang",
  title =        "Protecting Function Privacy and Input Privacy in the
                 Publicly Verifiable Outsourcing Computation of
                 Polynomial Functions",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "152",
  day =          "21",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040152",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/152",
  abstract =     "With the prevalence of cloud computing, the
                 outsourcing of computation has gained significant
                 attention. Clients with limited computing power often
                 outsource complex computing tasks to the cloud to save
                 on computing resources and costs. In outsourcing the
                 computation of functions, a function owner delegates a
                 cloud server to perform the function's computation on
                 the input received from the user. There are three
                 primary security concerns associated with this process:
                 protecting function privacy for the function owner,
                 protecting input privacy for the user and guaranteeing
                 that the cloud server performs the computation
                 correctly. Existing works have only addressed privately
                 verifiable outsourcing computation with privacy or
                 publicly verifiable outsourcing computation without
                 input privacy or function privacy. By using the
                 technologies of homomorphic encryption, proxy
                 re-encryption and verifiable computation, we propose
                 the first publicly verifiable outsourcing computation
                 scheme that achieves both input privacy and function
                 privacy for matrix functions, which can be extended to
                 arbitrary multivariate polynomial functions. We
                 additionally provide a faster privately verifiable
                 method. Moreover, the function owner retains control
                 over the function.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2023:DSE,
  author =       "Xu Wang and Bin Shi and Yili Fang",
  title =        "Distributed Systems for Emerging Computing: Platform
                 and Application",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "151",
  day =          "20",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040151",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/151",
  abstract =     "In recent years, the new computing paradigms such as
                 serverless computing, edge computing and
                 blockchain-based computing have attracted much
                 attention in both academia and industrial communities.
                 Distributed systems and applications play fundamental
                 roles in connecting the underlying computers, network
                 and devices for collaboration, as well as providing new
                 services for users. However, due to the increasing
                 complexity of the large-scale and dynamic heterogeneous
                 resource, and the new requirements and features, these
                 distributed systems and applications will face many
                 challenges in terms of their efficiency, flexibility
                 and algorithms. This editorial discusses the
                 state-of-the-art advancements in distributed systems
                 and applications for the emerging computing.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alaei:2023:TOD,
  author =       "Alireza Alaei and Ying Wang and Vinh Bui and Bela
                 Stantic",
  title =        "Target-Oriented Data Annotation for Emotion and
                 Sentiment Analysis in Tourism Related Social Media
                 Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "150",
  day =          "19",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040150",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/150",
  abstract =     "Social media have been a valuable data source for
                 studying people's opinions, intentions, and behaviours.
                 Such a data source incorporating advanced big data
                 analysis methods, such as machine-operated emotion and
                 sentiment analysis, will open unprecedented
                 opportunities for innovative data-driven destination
                 monitoring and management. However, a big challenge any
                 machine-operated text analysis method faces is the
                 ambiguity of the natural languages, which may cause an
                 expression to have different meanings in different
                 contexts. In this work, we address the ambiguity
                 challenge by proposing a context-aware dictionary-based
                 target-oriented emotion and sentiment analysis method
                 that incorporates inputs from both humans and machines
                 to introduce an alternative approach to measuring
                 emotions and sentiment in limited tourism-related data.
                 The study makes a methodological contribution by
                 creating a target dictionary specifically for tourism
                 sentiment analysis. To demonstrate the performance of
                 the proposed method, a case of target-oriented emotion
                 and sentiment analysis of posts from Twitter for the
                 Gold Coast of Australia as a tourist destination was
                 considered. The results suggest that Twitter data cover
                 a broad range of destination attributes and can be a
                 valuable source for comprehensive monitoring of tourist
                 experiences at a destination.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Paglialonga:2023:APS,
  author =       "Alessia Paglialonga and Rebecca Theal and Bruce Knox
                 and Robert Kyba and David Barber and Aziz Guergachi and
                 Karim Keshavjee",
  title =        "Applying Patient Segmentation Using Primary Care
                 Electronic Medical Records to Develop a Virtual
                 Peer-to-Peer Intervention for Patients with Type 2
                 Diabetes",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "149",
  day =          "14",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040149",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/149",
  abstract =     "The aim of this study was to design a virtual
                 peer-to-peer intervention for patients with type 2
                 diabetes (T2D) by grouping patients from specific
                 segments using data from primary care electronic
                 medical records (EMRs). Two opposing segments were
                 identified: patients living with diabetes who tend to
                 take several medications (``medication'' segment:
                 $\approx$32\%) and patients who do not take any
                 diabetes-specific medications (``lifestyle'' segment:
                 $\approx 15\%$). The remaining patients were from two
                 intermediate segments and exhibited medication-taking
                 behavior that placed them midway between the medication
                 and lifestyle segments. Patients were grouped into six
                 workshops (two workshops in each group: medication,
                 lifestyle, and mixed group), including individuals with
                 good and bad control of their disease. Measures of
                 attitudes, learning, and motivation were addressed
                 during and after the workshops. Results showed that
                 patients in the lifestyle segment were more interested
                 in T2D lifestyle control strategies, more satisfied
                 with their in-workshop learning experience, and more
                 motivated to set a goal than those in the medication
                 segment. These results suggest that the proposed
                 intervention may be more viable for patients in the
                 lifestyle segment and that EMR data may be used to
                 tailor behavioral interventions to specific patient
                 groups. Future research is needed to investigate
                 different segmentation approaches (e.g., using data
                 related to smoking, drinking, diet, and physical
                 activity) that could help tailor the intervention more
                 effectively.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Xu:2023:MDS,
  author =       "Yong Xu and Hong Ni and Xiaoyong Zhu",
  title =        "A Multipath Data-Scheduling Strategy Based on Path
                 Correlation for Information-Centric Networking",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "148",
  day =          "11",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040148",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/148",
  abstract =     "Information-Centric Networking (ICN) has
                 revolutionized the manner of content acquisition by
                 shifting the communication mode from host-centric to
                 information-centric. Considering the existing, large
                 amount of IP infrastructure in current networks, the
                 new ICN architecture is proposed to be compatible with
                 existing networks in order to reduce deployment cost.
                 However, due to compatibility with IP networks, ICN
                 data packets must be transmitted through the default
                 path provided by IP routing regulations, which also
                 limits the transmission efficiency and reliability of
                 ICN. In order to address this issue, this paper
                 introduces a multipath transmission method applied in
                 ICN which takes full advantage of the functions and
                 characteristics of ICN and builds multiple end-to-end
                 relay paths by using the ICN routers as relay nodes. We
                 then propose a relay-node-selection algorithm based on
                 path correlation to minimize the impact of overlapping
                 links. Moreover, we comprehensively calculate the path
                 state value by combining the round-trip time and packet
                 loss rate and propose a multipath data-scheduling
                 algorithm based on the path state value. Simulation
                 experiments show that the proposed method can maintain
                 high bandwidth utilization while reducing the number of
                 out-of-order packets.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fabre:2023:MGH,
  author =       "Renaud Fabre and Otmane Azeroual and Joachim
                 Sch{\"o}pfel and Patrice Bellot and Daniel Egret",
  title =        "A Multiverse Graph to Help Scientific Reasoning from
                 {Web} Usage: Interpretable Patterns of Assessor Shifts
                 in {GRAPHYP}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "147",
  day =          "10",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040147",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/147",
  abstract =     "The digital support for scientific reasoning presents
                 contrasting results. Bibliometric services are
                 improving, but not academic assessment; no service for
                 scholars relies on logs of web usage to base query
                 strategies for relevance judgments (or assessor
                 shifts). Our Scientific Knowledge Graph GRAPHYP
                 innovates with interpretable patterns of web usage,
                 providing scientific reasoning with conceptual
                 fingerprints and helping identify eligible hypotheses.
                 In a previous article, we showed how usage log data, in
                 the form of `documentary tracks', help determine
                 distinct cognitive communities (called adversarial
                 cliques) within sub-graphs. A typology of these
                 documentary tracks through a triplet of measurements
                 from logs (intensity, variety and attention) describes
                 the potential approaches to a (research) question.
                 GRAPHYP assists interpretation as a classifier, with
                 possibilistic graphical modeling. This paper shows what
                 this approach can bring to scientific reasoning; it
                 involves visualizing complete interpretable pathways,
                 in a multi-hop assessor shift, which users can then
                 explore toward the `best possible solution'---the one
                 that is most consistent with their hypotheses. Applying
                 the Leibnizian paradigm of scientific reasoning,
                 GRAPHYP highlights infinitesimal learning pathways, as
                 a `multiverse' geometric graph in modeling possible
                 search strategies answering research questions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Otta:2023:SSM,
  author =       "Soumya Prakash Otta and Subhrakanta Panda and Maanak
                 Gupta and Chittaranjan Hota",
  title =        "A Systematic Survey of Multi-Factor Authentication for
                 Cloud Infrastructure",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "146",
  day =          "10",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040146",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/146",
  abstract =     "The unauthorized usage of various services and
                 resources in cloud computing is something that must be
                 protected against. Authentication and access control
                 are the most significant concerns in cloud computing.
                 Several researchers in this field suggest numerous
                 approaches to enhance cloud authentication towards
                 robustness. User names and associated passwords have
                 been a common practice for long as Single Factor
                 Authentication. However, advancements in the speed of
                 computing and the usage of simple methods, starting
                 from the Brute Force technique to the implementation of
                 advanced and efficient cryptographic algorithms, have
                 posed several threats and vulnerabilities for
                 authentication systems, leading to the degradation of
                 their effectiveness. Multi-factor authentication has
                 emerged as a robust means of securing the cloud using
                 simultaneous and multiple means of authentication
                 factors. This employs multiple levels of cascaded
                 authentication checks. This paper covers an extensive
                 and systematic survey of various factors towards their
                 adoption and suitability for authentication for
                 multi-factor authentication mechanisms. The inference
                 drawn from the survey is in terms of arriving at a
                 unique authentication factor that does not require any
                 additional, specialized hardware or software for
                 multi-factor authentication. Such authentication also
                 uses the distinct biometric characteristics of the
                 concerned user in the process. This arrangement
                 augments the secured and robust user authentication
                 process. The mechanism is also assessed as an effective
                 means against impersonation attacks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{AlKhasawneh:2023:CAT,
  author =       "Mohammad {Al Khasawneh} and Abdel-Aziz Ahmad Sharabati
                 and Shafig Al-Haddad and Rania Al-Daher and Sarah
                 Hammouri and Sima Shaqman",
  title =        "Consumer's Attitude towards Display {Google Ads}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "145",
  day =          "07",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040145",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/145",
  abstract =     "The context of Display Google ads and its components
                 has significant importance to previous studies.
                 However, the full understanding of the variables that
                 influence both Display Google ads avoidance and
                 intention to click has not been thoroughly
                 acknowledged. Thus, this study aims to outline an
                 entire understanding of the different variables that
                 lead Display Google ads to be avoided or clicked on. A
                 detailed review of previous studies has been completed
                 to illustrate a thorough image of Display Google ads.
                 Accordingly, this study developed a theoretical model
                 combining four variables (Display Google ads' Prior
                 Experience, Originality, Relevance, and Credibility)
                 that lead to affecting Display Google ads' Avoidance
                 and Intention to Click, with one mediator (Consumer's
                 Attitude). A quantitative methodology has been
                 employed, in which an online survey has been used to
                 collect data, which were collected from 358
                 respondents, then coded against AMOS. The data analysis
                 results show that three independent variables
                 positively impact the intention to click; however,
                 credibility has the highest value, then relevance and
                 originality, consequently., while Display Google ads
                 prior experience had no impact on the intention to
                 click. Finally, the research concluded different
                 practical and theoretical implications, and future
                 potential research, and limitations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gazzan:2023:OED,
  author =       "Mazen Gazzan and Frederick T. Sheldon",
  title =        "Opportunities for Early Detection and Prediction of
                 Ransomware Attacks against Industrial Control Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "144",
  day =          "07",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040144",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/144",
  abstract =     "Industrial control systems (ICS) and supervisory
                 control and data acquisition (SCADA) systems, which
                 control critical infrastructure such as power plants
                 and water treatment facilities, have unique
                 characteristics that make them vulnerable to ransomware
                 attacks. These systems are often outdated and run on
                 proprietary software, making them difficult to protect
                 with traditional cybersecurity measures. The limited
                 visibility into these systems and the lack of effective
                 threat intelligence pose significant challenges to the
                 early detection and prediction of ransomware attacks.
                 Ransomware attacks on ICS and SCADA systems have become
                 a growing concern in recent years. These attacks can
                 cause significant disruptions to critical
                 infrastructure and result in significant financial
                 losses. Despite the increasing threat, the prediction
                 of ransomware attacks on ICS remains a significant
                 challenge for the cybersecurity community. This is due
                 to the unique characteristics of these systems,
                 including the use of proprietary software and limited
                 visibility into their operations. In this review paper,
                 we will examine the challenges associated with
                 predicting ransomware attacks on industrial systems and
                 the existing approaches for mitigating these risks. We
                 will also discuss the need for a multi-disciplinary
                 approach that involves a close collaboration between
                 the cybersecurity and ICS communities. We aim to
                 provide a comprehensive overview of the current state
                 of ransomware prediction on industrial systems and to
                 identify opportunities for future research and
                 development in this area.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Goncalves:2023:IGC,
  author =       "Ricardo Martins Gon{\c{c}}alves and Miguel Mira da
                 Silva and Paulo Rupino da Cunha",
  title =        "Implementing {GDPR}-Compliant Surveys Using
                 Blockchain",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "143",
  day =          "07",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040143",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/143",
  abstract =     "The immutability of data stored in a blockchain is a
                 crucial pillar of trust in this technology, which has
                 led to its increasing adoption in various use cases.
                 However, there are situations where the inability to
                 change or delete data may be illegal. European Union's
                 General Data Protection Regulation (GDPR)---applying to
                 any company processing personal data from European
                 citizens---explicitly entitles individuals to the right
                 to rectification and the right to be forgotten. In this
                 paper, we describe the design of a system to deploy and
                 process survey data in a GDPR-compliant manner. It
                 combines an Hyperledger Fabric blockchain to ensure
                 that data cannot be tampered with and InterPlanetary
                 File Systems (IPFS) for storage. With the proposed
                 arrangement, we reap several security benefits enabled
                 by blockchain's immutability without running afoul of
                 the regulations. Furthermore, the proof-of-concept is
                 generic and can easily be adapted to various domains.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Jamshidi:2023:FDD,
  author =       "Mohammad (Behdad) Jamshidi and Omid Moztarzadeh and
                 Alireza Jamshidi and Ahmed Abdelgawad and Ayman S.
                 El-Baz and Lukas Hauer",
  title =        "Future of Drug Discovery: The Synergy of Edge
                 Computing, {Internet of Medical Things}, and Deep
                 Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "142",
  day =          "07",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040142",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/142",
  abstract =     "The global spread of COVID-19 highlights the urgency
                 of quickly finding drugs and vaccines and suggests that
                 similar challenges will arise in the future. This
                 underscores the need for ongoing efforts to overcome
                 the obstacles involved in the development of potential
                 treatments. Although some progress has been made in the
                 use of Artificial Intelligence (AI) in drug discovery,
                 virologists, pharmaceutical companies, and investors
                 seek more long-term solutions and greater investment in
                 emerging technologies. One potential solution to aid in
                 the drug-development process is to combine the
                 capabilities of the Internet of Medical Things (IoMT),
                 edge computing (EC), and deep learning (DL). Some
                 practical frameworks and techniques utilizing EC, IoMT,
                 and DL have been proposed for the monitoring and
                 tracking of infected individuals or high-risk areas.
                 However, these technologies have not been widely
                 utilized in drug clinical trials. Given the
                 time-consuming nature of traditional drug- and
                 vaccine-development methods, there is a need for a new
                 AI-based platform that can revolutionize the industry.
                 One approach involves utilizing smartphones equipped
                 with medical sensors to collect and transmit real-time
                 physiological and healthcare information on
                 clinical-trial participants to the nearest edge nodes
                 (EN). This allows the verification of a vast amount of
                 medical data for a large number of individuals in a
                 short time frame, without the restrictions of latency,
                 bandwidth, or security constraints. The collected
                 information can be monitored by physicians and
                 researchers to assess a vaccine's performance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ocampo-Lopez:2023:PDL,
  author =       "Carlos Ocampo-L{\'o}pez and Oscar
                 Mu{\~n}oz-Bland{\'o}n and Leidy
                 Rend{\'o}n-Castrill{\'o}n and Margarita
                 Ram{\'\i}rez-Carmona",
  title =        "Post-Digital Learning for Rural Development: a Case
                 Study of {Open Biotec MOOCs} in {Colombia}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "141",
  day =          "06",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040141",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/141",
  abstract =     "This research presents an experience of post-digital
                 learning of biotechnology in rural areas in Colombia by
                 implementing a massive open online course (MOOC) for
                 biotechnology education called Open Biotec. The
                 objective was to improve Colombian rural development by
                 creating learning communities around five topics: waste
                 management, environmental biotechnology, bioprocesses,
                 alternative energies, and bio-entrepreneurship. The
                 study utilized various methods, including a
                 socioeconomic diagnosis of a subregion of the
                 department of Antioquia, Colombia, and the creation of
                 MOOCs using the Action Research methodology. The pilot
                 test of the training route in biotechnology involved
                 the progressive development of the MOOC courses that
                 comprise it. Around 918 students from rural areas were
                 trained, and statistical analysis showed that the
                 average grade of the students increased significantly
                 from 6.13 to 7.53 and the median from 6.15 to 8.00. The
                 study results demonstrate how the learning experience
                 designed in the Open Biotec MOOC increases the degree
                 of knowledge of students in this field of
                 biotechnology, offering an opportunity to establish
                 sustainable learning communities with participation and
                 collaborative action mediated by virtual tools. The
                 study concludes that rural education in Colombia could
                 be strengthened with a training strategy for rural
                 communities supported by MOOCs focused on the
                 responsible use of local biodiversity from a
                 biotechnological perspective.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Garcia-Delgado:2023:ETT,
  author =       "Miguel {\'A}ngel Garc{\'\i}a-Delgado and Sonia
                 Rodr{\'\i}guez-Cano and Vanesa Delgado-Benito and
                 Mar{\'\i}a Lozano-{\'A}lvarez",
  title =        "Emerging Technologies and Their Link to Digital
                 Competence in Teaching",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "140",
  day =          "05",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040140",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/140",
  abstract =     "The new educational reality requires teachers to have
                 a series of skills and competences that allow them to
                 improve the teaching--learning process and therefore
                 the quality of teaching, integrating technology and
                 emerging technologies. In order to assess the
                 competence level of teachers, a descriptive study was
                 designed, in which 101 teachers from different stages
                 and geographical locations in Spain took part and were
                 administered the DigCompEdu Check-in questionnaire. The
                 results show average levels of teachers' digital
                 competence (B1 and B2, particularly), and an incipient
                 use of emerging technologies by teachers, with less
                 than 50\% of the sample not using these technologies in
                 their daily classroom activities, although those who
                 show a higher level of digital competence are also
                 those who integrate them more in their daily work. The
                 results correspond with similar studies, corroborating
                 the average level of teachers' digital skills.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Romero:2023:TRA,
  author =       "Virginia M. Romero and Eduardo B. Fernandez",
  title =        "Towards a Reference Architecture for Cargo Ports",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "139",
  day =          "04",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040139",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/139",
  abstract =     "Cyber-Physical Systems (CPS) are physical systems
                 whose operations are coordinated, monitored, and
                 controlled by computing and communication functions.
                 These systems are typically heterogeneous, including
                 Internet of Things and information technology
                 subsystems, and can present a myriad of implementation
                 details, making them very complex systems. An important
                 type of CPS is a maritime container terminal (cargo
                 port), which is a facility where cargo containers are
                 transported between ships and land vehicles for onward
                 transportation and vice versa. A cargo port performs
                 four basic functions: receiving, storing, staging, and
                 loading for both import and export containers. We
                 present here process patterns that describe the
                 functional aspects of cargo ports and a pattern that
                 describes their structural properties (patterns are
                 encapsulated solutions to recurrent problems). These
                 patterns describe semantic aspects found in any cargo
                 port and can be adapted to describe other CPSs. We
                 decompose these process patterns into use cases that
                 describe their interactions with the system. We then
                 integrate the process patterns with structural patterns
                 to assemble a partial reference architecture (RA) that
                 shows the interactions of all the patterns while also
                 indicating the typical stakeholders found in all ports.
                 We validate the proposed reference architecture,
                 highlighting its theoretical and practical value.
                 Software and system designers of cargo ports need to
                 start from a conceptual and abstract view that is
                 subsequently refined to add more details. The use of
                 reference architectures and patterns is an effective
                 way to organize and describe the functional and
                 non-functional aspects of a system, as well as to unify
                 the design of all its aspects. This is, until now, the
                 only published RA for cargo ports, and it can be a
                 useful guideline for the designers of any type of cargo
                 port.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lancelot:2023:PEL,
  author =       "Jonathan Lancelot and Bhaskar P. Rimal and Edward M.
                 Dennis",
  title =        "Performance Evaluation of a Lane Correction Module
                 Stress Test: a Field Test of {Tesla Model 3}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "138",
  day =          "31",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040138",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/138",
  abstract =     "This paper is designed to explicate and analyze data
                 acquired from experimental field tests of a Tesla Model
                 3 lane correction module within the vehicle's Autopilot
                 Suite, a component of Tesla OS. The initial problem was
                 discovered during a nominal drive of the Tesla Model 3,
                 where after a random number of lane correction events,
                 the lane correction module shuts down, issues a visual
                 disable warning on the touchscreen, and control of the
                 vehicle is given to the driver until the next drive.
                 That development was considered problematic, as the
                 driver can be caught off guard or may be medically
                 disabled and unable to respond. During a controlled
                 stress test, a more severe issue was discovered. After
                 a random number of lane correction events, the lane
                 correction module shuts down without warning, then
                 stays activated after the test driver corrects the
                 vehicle's trajectory. This is considered a fatal error
                 in the system and adds a dangerous element to an
                 otherwise standard feature in a modern automotive
                 vehicle. The results established that the number of
                 events needed to trigger a fatal error without warning
                 is unpredictable. Our results also demonstrate that the
                 system is inconsistent.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhai:2023:CRD,
  author =       "Qiuhong Zhai and Wenhao Zhu and Xiaoyu Zhang and
                 Chenyun Liu",
  title =        "Contrastive Refinement for Dense Retrieval Inference
                 in the Open-Domain Question Answering Task",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "137",
  day =          "31",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040137",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/137",
  abstract =     "In recent years, dense retrieval has emerged as the
                 primary method for open-domain question-answering
                 (OpenQA). However, previous research often focused on
                 the query side, neglecting the importance of the
                 passage side. We believe that both the query and
                 passage sides are equally important and should be
                 considered for improved OpenQA performance. In this
                 paper, we propose a contrastive pseudo-labeled data
                 constructed around passages and queries separately. We
                 employ an improved pseudo-relevance feedback (PRF)
                 algorithm with a knowledge-filtering strategy to enrich
                 the semantic information in dense representations.
                 Additionally, we proposed an Auto Text Representation
                 Optimization Model (AOpt) to iteratively update the
                 dense representations. Experimental results demonstrate
                 that our methods effectively optimize dense
                 representations, making them more distinguishable in
                 dense retrieval, thus improving the OpenQA system's
                 overall performance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hasan:2023:EIC,
  author =       "Husam H. Hasan and Zainab T. Alisa",
  title =        "Effective {IoT} Congestion Control Algorithm",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "136",
  day =          "31",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040136",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/136",
  abstract =     "The Internet of Things (IoT) connects devices via the
                 Internet. Network congestion is one of the key problems
                 that has been identified by researchers in the IoT
                 field. When there is a huge number of IoT devices
                 connected to the internet, this creates network
                 congestion. Transfer control protocol is a transport
                 layer protocol that provides a reliable end-to-end
                 connection between two devices. Many Congestion Control
                 Algorithms have been proposed to solve network
                 congestion. However, there is no perfect solution to
                 this problem. This paper proposes an effective
                 loss-based Congestion Control Algorithm to effectively
                 adapt the congestion window in the IoT environment. It
                 uses simple experiment scenarios to test the algorithm
                 for wired and wireless channels and observes important
                 performance metrics: link utilization, inter-protocol
                 fairness, intra-protocol fairness and throughput. The
                 results are impressive, and the proposed algorithm is
                 shown to outperform other standard algorithms.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gkoulis:2023:TIE,
  author =       "Dimitris Gkoulis and Cleopatra Bardaki and George
                 Kousiouris and Mara Nikolaidou",
  title =        "Transforming {IoT} Events to Meaningful Business
                 Events on the Edge: Implementation for Smart Farming
                 Application",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "135",
  day =          "31",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040135",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/135",
  abstract =     "This paper focuses on Internet of Things (IoT)
                 architectures and knowledge generation out of streams
                 of events as the primary elements concerning the
                 creation of user-centric IoT services. We provide a
                 general, symmetrical IoT architecture, which enables
                 two-way bidirectional communication between things and
                 users within an application domain. We focus on two
                 main components of the architecture (i.e., Event Engine
                 and Process Engine) that handle event transformation by
                 implementing parametric Complex Event Processing (CEP).
                 More specifically, we describe and implement the
                 transformation cycle of events starting from raw IoT
                 data to their processing and transformation of events
                 for calculating information that we need in an
                 IoT-enabled application context. The implementation
                 includes a library of composite transformations
                 grouping the gradual and sequential steps for
                 transforming basic IoT events into business events,
                 which include ingestion, event splitting, and
                 calculation of measurements' average value. The
                 appropriateness and possibility of inclusion and
                 integration of the implementation in an IoT environment
                 are demonstrated by providing our implementation for a
                 smart farming application domain with four scenarios
                 that each reflect a user's requirements. Further, we
                 discuss the quality properties of each scenario.
                 Ultimately, we propose an IoT architecture and,
                 specifically, a parametric CEP model and implementation
                 for future researchers and practitioners who aspire to
                 build IoT applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Taha:2023:CSS,
  author =       "Ahmad Taha and Basel Barakat and Mohammad M. A. Taha
                 and Mahmoud A. Shawky and Chun Sing Lai and Sajjad
                 Hussain and Muhammad Zainul Abideen and Qammer H.
                 Abbasi",
  title =        "A Comparative Study of Single and Multi-Stage
                 Forecasting Algorithms for the Prediction of
                 Electricity Consumption Using a {UK-National Health
                 Service (NHS)} Hospital Dataset",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "134",
  day =          "31",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040134",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/134",
  abstract =     "Accurately looking into the future was a significantly
                 major challenge prior to the era of big data, but with
                 rapid advancements in the Internet of Things (IoT),
                 Artificial Intelligence (AI), and the data availability
                 around us, this has become relatively easier.
                 Nevertheless, in order to ensure high-accuracy
                 forecasting, it is crucial to consider suitable
                 algorithms and the impact of the extracted features.
                 This paper presents a framework to evaluate a total of
                 nine forecasting algorithms categorised into single and
                 multistage models, constructed from the Prophet,
                 Support Vector Regression (SVR), Long Short-Term Memory
                 (LSTM), and the Least Absolute Shrinkage and Selection
                 Operator (LASSO) approaches, applied to an electricity
                 demand dataset from an NHS hospital. The aim is to see
                 such techniques widely used in accurately predicting
                 energy consumption, limiting the negative impacts of
                 future waste on energy, and making a contribution
                 towards the 2050 net zero carbon target. The proposed
                 method accounts for patterns in demand and temperature
                 to accurately forecast consumption. The Coefficient of
                 Determination ( R2 ), Mean Absolute Error (MAE), and
                 Root Mean Square Error (RMSE) were used to evaluate the
                 algorithms' performance. The results show the
                 superiority of the Long Short-Term Memory (LSTM) model
                 and the multistage Facebook Prophet model, with R2
                 values of 87.20\% and 68.06\%, respectively.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Guan:2023:SBB,
  author =       "Yuting Guan and Junjiang He and Tao Li and Hui Zhao
                 and Baoqiang Ma",
  title =        "{SSQLi}: a Black-Box Adversarial Attack Method for
                 {SQL} Injection Based on Reinforcement Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "133",
  day =          "30",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040133",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/133",
  abstract =     "SQL injection is a highly detrimental web attack
                 technique that can result in significant data leakage
                 and compromise system integrity. To counteract the harm
                 caused by such attacks, researchers have devoted much
                 attention to the examination of SQL injection detection
                 techniques, which have progressed from traditional
                 signature-based detection methods to machine- and
                 deep-learning-based detection models. These detection
                 techniques have demonstrated promising results on
                 existing datasets; however, most studies have
                 overlooked the impact of adversarial attacks,
                 particularly black-box adversarial attacks, on
                 detection methods. This study addressed the
                 shortcomings of current SQL injection detection
                 techniques and proposed a reinforcement-learning-based
                 black-box adversarial attack method. The proposal
                 included an innovative vector transformation approach
                 for the original SQL injection payload, a comprehensive
                 attack-rule matrix, and a reinforcement-learning-based
                 method for the adaptive generation of adversarial
                 examples. Our approach was evaluated on existing web
                 application firewalls (WAF) and detection models based
                 on machine- and deep-learning methods, and the
                 generated adversarial examples successfully bypassed
                 the detection method at a rate of up to 97.39\%.
                 Furthermore, there was a substantial decrease in the
                 detection accuracy of the model after multiple attacks
                 had been carried out on the detection model via the
                 adversarial examples.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sousa-Vieira:2023:SCA,
  author =       "Mar{\'\i}a E. Sousa-Vieira and Manuel
                 Fern{\'a}ndez-Veiga",
  title =        "Study of Coded {ALOHA} with Multi-User Detection under
                 Heavy-Tailed and Correlated Arrivals",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "132",
  day =          "30",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040132",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/132",
  abstract =     "In this paper, we study via simulation the performance
                 of irregular repetition slotted ALOHA under
                 multi-packet detection and different patterns of the
                 load process. On the one hand, we model the arrival
                 process with a version of the M/G/ {\infty} process
                 able to exhibit a correlation structure decaying slowly
                 in time. Given the independence among frames in
                 frame-synchronous coded-slotted ALOHA (CSA), this
                 variation should only take effect on frame-asynchronous
                 CSA. On the other hand, we vary the marginal
                 distribution of the arrival process using discrete
                 versions of the Lognormal and Pareto distributions,
                 with the objective of investigating the influence of
                 the right tail. In this case, both techniques should be
                 affected by the change, albeit to a different degree.
                 Our results confirm these hypotheses and show that
                 these factors must be taken into account when designing
                 and analyzing these systems. In frameless operations,
                 both the shape of the packet arrivals tail distribution
                 and the existence of short-range and long-range
                 correlations strongly impact the packet loss ratio and
                 the average delay. Nevertheless, these effects emerge
                 only weakly in the case of frame-aligned operations,
                 because this enforces the system to introduce a delay
                 in the newly arrived packets (until the beginning of
                 the next frame), and implies that the backlog of
                 accumulated packets is the key quantity for calculating
                 the performance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Aria:2023:IFD,
  author =       "Reza Aria and Norm Archer and Moein Khanlari and
                 Bharat Shah",
  title =        "Influential Factors in the Design and Development of a
                 Sustainable {Web3\slash Metaverse} and Its
                 Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "131",
  day =          "30",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040131",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/131",
  abstract =     "This paper summarizes the work of many different
                 authors, industries, and countries by introducing
                 important and influential factors that will help in the
                 development, successful adoption, and sustainable use
                 of the Web3/metaverse and its applications. We
                 introduce a few important factors derived from the
                 current state-of-the-art literature, including four
                 essential elements including (1) appropriate
                 decentralization, (2) good user experience, (3)
                 appropriate translation and synchronization to the real
                 world, and (4) a viable economy, which are required for
                 appropriate implementation of a metaverse and its
                 applications. The future of Web3 is all about
                 decentralization, and blockchain can play a significant
                 part in the development of the Metaverse. This paper
                 also sheds light on some of the most relevant open
                 issues and challenges currently facing the
                 Web3/metaverse and its applications, with the hope that
                 this discourse will help to encourage the development
                 of appropriate solutions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bagui:2023:RIN,
  author =       "Sikha Bagui and Dustin Mink and Subhash Bagui and
                 Sakthivel Subramaniam and Daniel Wallace",
  title =        "Resampling Imbalanced Network Intrusion Datasets to
                 Identify Rare Attacks",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "130",
  day =          "29",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040130",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/130",
  abstract =     "This study, focusing on identifying rare attacks in
                 imbalanced network intrusion datasets, explored the
                 effect of using different ratios of oversampled to
                 undersampled data for binary classification. Two
                 designs were compared: random undersampling before
                 splitting the training and testing data and random
                 undersampling after splitting the training and testing
                 data. This study also examines how oversampling\slash
                 undersampling ratios affect random forest
                 classification rates in datasets with minority data or
                 rare attacks. The results suggest that random
                 undersampling before splitting gives better
                 classification rates; however, random undersampling
                 after oversampling with BSMOTE allows for the use of
                 lower ratios of oversampled data.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Xevgenis:2023:AZS,
  author =       "Michael Xevgenis and Dimitrios G. Kogias and
                 Panagiotis A. Karkazis and Helen C. Leligou",
  title =        "Addressing {ZSM} Security Issues with Blockchain
                 Technology",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "129",
  day =          "28",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040129",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/129",
  abstract =     "Undoubtedly, we are witnessing a new era of computer
                 networks that aspire to support modern demanding
                 applications by providing the highest Quality of
                 Experience (QoE) to the end user. Next Generations
                 Networks (NGNs) ensure that characteristics such as
                 ultra-low latency, high availability and wide service
                 coverage can be met across the network regardless of
                 the network infrastructure ownership. To accomplish
                 that, beyond the necessary improvements in the radio
                 propagation field, changes have been made in the core
                 network functions which are now characterized as
                 programmable, and software defined. Software Defined
                 Networks (SDNs) and Network Function Virtualization
                 (NFV) are the keystones of the NGNs flexibility. The
                 high expectations of NGNs' performance and the
                 continuous changes in the network conditions lead to
                 the development of new network management frameworks
                 that add elasticity and dynamicity and minimize human
                 intervention. ETSI (the European Standards
                 Organization) presents the Zero-touch Service
                 Management (ZSM) framework that uses hyped technologies
                 such as Artificial Intelligence (AI) and Machine
                 Learning (ML) to achieve full end-to-end automation of
                 the network services' management across one or many
                 different domains. Focusing on multi-domain network
                 service management, there are several security issues
                 identified by the standardization team which mostly
                 derive from the lack of trust among network providers.
                 In the present research, we explore the suitability of
                 blockchain technology adoption for facing these
                 security issues. Blockchain technology inherently
                 addresses security in trustless environments such as
                 the infrastructures defined by the ZSM team. Our
                 contribution is three-fold: (a) we define the
                 architecture of a multi-domain network infrastructure
                 that adopts the ZSM approach and integrates blockchain
                 functionality, (b) we explore the adoption of different
                 blockchain and distributed ledger technologies (DLT)
                 approaches to address ZSM security needs and (c) we
                 provide guidelines to prospective solution
                 designers\slash implementors on the detailed
                 requirements that this solution has to meet to maximize
                 the offered value.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wu:2023:NID,
  author =       "Kongpei Wu and Huiqin Qu and Conggui Huang",
  title =        "A Network Intrusion Detection Method Incorporating
                 {Bayesian} Attack Graph and Incremental Learning Part",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "128",
  day =          "28",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040128",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/128",
  abstract =     "For the current stage of complex and changing network
                 environments and correlated and synchronized
                 vulnerability attacks, this study first fuses attack
                 graph technology and Bayesian networks and constructs
                 Bayesian attack graphs to portray the correlation
                 relationships between vulnerabilities and discovering
                 attackers' intentions. Meanwhile, improving the
                 Bayesian attack graph is difficult because it is
                 difficult to achieve active updates and adapt to the
                 changing network environment and other problems. The
                 study proposed a detection method that integrated the
                 Bayesian attack graph and the XGBoost incremental
                 learning (IL) approach. Experiments showed that the IL
                 model had an accuracy of 0.951, an accuracy of 0.999, a
                 recall of 0.815, an F1 value of 0.898, and an Area
                 Under Curve (AUC) value of 0.907. The prediction
                 ability of this method was better than that of the base
                 model. Bayesian attack graphs fused with IL can detect
                 attacks in the network more efficiently and accurately,
                 so the probability of each node in the network system
                 being attacked can be updated in real time.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yang:2023:HIH,
  author =       "Xingyuan Yang and Jie Yuan and Hao Yang and Ya Kong
                 and Hao Zhang and Jinyu Zhao",
  title =        "A Highly Interactive Honeypot-Based Approach to
                 Network Threat Management",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "127",
  day =          "28",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040127",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/127",
  abstract =     "In this paper, considering the problem that the common
                 defensive means in the current cyber confrontation
                 often fall into disadvantage, honeypot technology is
                 adopted to turn reactive into proactive to deal with
                 the increasingly serious cyberspace security problem.
                 We address the issue of common defensive measures in
                 current cyber confrontations that frequently lead to
                 disadvantages. To tackle the progressively severe
                 cyberspace security problem, we propose the adoption of
                 honeypot technology to shift from a reactive to a
                 proactive approach. This system uses honeypot
                 technology for active defense, tempting attackers into
                 a predetermined sandbox to observe the attacker's
                 behavior and attack methods to better protect equipment
                 and information security. During the research, it was
                 found that due to the singularity of traditional
                 honeypots and the limitations of low-interactivity
                 honeypots, the application of honeypot technology has
                 difficulty in achieving the desired protective effect.
                 Therefore, the system adopts a highly interactive
                 honeypot and a modular design idea to distinguish the
                 honeypot environment from the central node of data
                 processing, so that the honeypot can obtain more
                 sufficient information and the honeypot technology can
                 be used more easily. By managing honeypots at the
                 central node, i.e., adding, deleting, and modifying
                 honeypots and other operations, it is easy to maintain
                 and upgrade the system, while reducing the difficulty
                 of using honeypots. The high-interactivity honeypot
                 technology not only attracts attackers into pre-set
                 sandboxes to observe their behavior and attack methods,
                 but also performs a variety of advanced functions, such
                 as network threat analysis, virtualization,
                 vulnerability perception, tracing reinforcement, and
                 camouflage detection. We have conducted a large number
                 of experimental comparisons and proven that our method
                 has significant advantages compared to traditional
                 honeypot technology and provides detailed data support.
                 Our research provides new ideas and effective methods
                 for network security protection.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lee:2023:VSS,
  author =       "Uddom Lee and Peng Jiang and Hongyi Wu and Chunsheng
                 Xin",
  title =        "View Synthesis with Scene Recognition for Cross-View
                 Image Localization",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "126",
  day =          "28",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040126",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/126",
  abstract =     "Image-based localization has been widely used for
                 autonomous vehicles, robotics, augmented reality, etc.,
                 and this is carried out by matching a query image taken
                 from a cell phone or vehicle dashcam to a large scale
                 of geo-tagged reference images, such as
                 satellite/aerial images or Google Street Views.
                 However, the problem remains challenging due to the
                 inconsistency between the query images and the
                 large-scale reference datasets regarding various light
                 and weather conditions. To tackle this issue, this work
                 proposes a novel view synthesis framework equipped with
                 deep generative models, which can merge the unique
                 features from the outdated reference dataset with
                 features from the images containing seasonal changes.
                 Our design features a unique scheme to ensure that the
                 synthesized images contain the important features from
                 both reference and patch images, covering seasonable
                 features and minimizing the gap for the image-based
                 localization tasks. The performance evaluation shows
                 that the proposed framework can synthesize the views in
                 various weather and lighting conditions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Keller:2023:BIU,
  author =       "Dami{\'a}n Keller and Azeema Yaseen and Joseph Timoney
                 and Sutirtha Chakraborty and Victor Lazzarini",
  title =        "Banging Interaction: a Ubimus-Design Strategy for the
                 Musical {Internet}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "125",
  day =          "27",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040125",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/125",
  abstract =     "We introduce a new perspective for musical interaction
                 tailored to a specific class of sonic resources: impact
                 sounds. Our work is informed by the field of ubiquitous
                 music (ubimus) and engages with the demands of artistic
                 practices. Through a series of deployments of a
                 low-cost and highly flexible network-based prototype,
                 the Dynamic Drum Collective, we exemplify the
                 limitations and specific contributions of banging
                 interaction. Three components of this new design
                 strategy---adaptive interaction, mid-air techniques and
                 timbre-led design---target the development of
                 creative-action metaphors that make use of resources
                 available in everyday settings. The techniques
                 involving the use of sonic gridworks yielded positive
                 outcomes. The subjects tended to choose sonic materials
                 that---when combined with their actions on the
                 prototype---approached a full rendition of the proposed
                 soundtrack. The results of the study highlighted the
                 subjects' reliance on visual feedback as a
                 non-exclusive strategy to handle both temporal
                 organization and collaboration. The results show a
                 methodological shift from device-centric and
                 instrumental-centric methods to designs that target the
                 dynamic relational properties of ubimus ecosystems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Samarnggoon:2023:DVW,
  author =       "Keattikorn Samarnggoon and Supara Grudpan and Noppon
                 Wongta and Konlawat Klaynak",
  title =        "Developing a Virtual World for an Open-House Event: a
                 Metaverse Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "124",
  day =          "27",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040124",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/124",
  abstract =     "The concept of a metaverse, a virtual world that
                 offers immersive experiences, has gained widespread
                 interest in recent years. Despite the hype, there is
                 still a gap in its practical application, especially in
                 the realm of education. This study presents the design
                 and implementation of a metaverse tailored to the needs
                 of education. The goal of this paper is to demonstrate
                 the feasibility of such a system and evaluate its
                 effectiveness. It is crucial to understand the
                 architecture and implementation of a metaverse to
                 effectively customise it for educational purposes. To
                 assess user experience, a field study was conducted,
                 collecting data through questionnaires and qualitative
                 feedback. The results show that users were pleased with
                 the features, player experience, and ease of use.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Trim:2023:IHV,
  author =       "Peter R. J. Trim and Yang-Im Lee and An Vu",
  title =        "Insights into How {Vietnamese} Retailers Utilize
                 Social Media to Facilitate Knowledge Creation through
                 the Process of Value Co-Creation",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "4",
  pages =        "123",
  day =          "26",
  month =        mar,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15040123",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Apr 28 07:04:49 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/4/123",
  abstract =     "Social media usage is a direct result of Internet
                 connectivity and is gaining increased prominence in
                 business-to-consumer (B2C), business-to-business (B2B),
                 and consumer-to-business (C2B) relationship building,
                 which is allowing marketers to devise and implement
                 digital marketing strategies that are perceived as
                 enhancing a customer's well-being. Through the process
                 of utilizing social media (SM) to share information
                 with consumers, marketers are affording themselves with
                 the concept of value co-creation and ensuring that the
                 development of knowledge is given priority. To explain
                 how this happens in an emerging economy, in-depth
                 personal interviews were undertaken with the owners of
                 five retail fashion companies in Vietnam. The findings
                 indicate that fashion retail companies in Vietnam are
                 deploying digital marketing strategies that deliver
                 perceived enhanced value to consumers through the
                 process of value co-creation. This highlights the
                 advantage of using SM in relation to increasing retail
                 staff's ability to convert information into usable
                 resources such as intelligence and knowledge. By
                 achieving knowledge conversion, retail staff fulfill
                 the role of `knowledge broker' and `knowledge
                 connector', and identify how organizational
                 intervention, such as new operating structures, can
                 help to deliver perceived enhanced value to
                 customers.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lightbody:2023:AIS,
  author =       "Dominic Lightbody and Duc-Minh Ngo and Andriy Temko
                 and Colin C. Murphy and Emanuel Popovici",
  title =        "Attacks on {IoT}: Side-Channel Power Acquisition
                 Framework for Intrusion Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "187",
  day =          "21",
  month =        may,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050187",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/187",
  abstract =     "This study proposes the wider use of non-intrusive
                 side-channel power data in cybersecurity for intrusion
                 detection. An in-depth analysis of side-channel IoT
                 power behaviour is performed on two well-known IoT
                 devices-a Raspberry Pi 3 model B and a DragonBoard
                 410c-operating under normal conditions and under
                 attack. Attacks from the categories of reconnaissance,
                 brute force and denial of service are applied, and the
                 side-channel power data of the IoT testbeds are then
                 studied in detail. These attacks are used together to
                 further compromise the IoT testbeds in a
                 ``capture-the-flag scenario'', where the attacker aims
                 to infiltrate the device and retrieve a secret file.
                 Some clear similarities in the side-channel power
                 signatures of these attacks can be seen across the two
                 devices. Furthermore, using the knowledge gained from
                 studying the features of these attacks individually and
                 the signatures witnessed in the ``capture the flag
                 scenario'', we show that security teams can reverse
                 engineer attacks applied to their system to achieve a
                 much greater understanding of the events that occurred
                 during a breach. While this study presents behaviour
                 signatures analysed visually, the acquired power series
                 datasets will be instrumental for future human-centred
                 AI-assisted intrusion detection.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ma:2023:DSB,
  author =       "Khai-Minh Ma and Duc-Hung Le and Cong-Kha Pham and
                 Trong-Thuc Hoang",
  title =        "Design of an {SoC} Based on 32-Bit {RISC-V} Processor
                 with Low-Latency Lightweight Cryptographic Cores in
                 {FPGA}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "186",
  day =          "19",
  month =        may,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050186",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/risc-v.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/186",
  abstract =     "The security of Internet of Things (IoTs) devices in
                 recent years has created interest in developing
                 implementations of lightweight cryptographic algorithms
                 for such systems. Additionally, open-source hardware
                 and field-programable gate arrays (FPGAs) are gaining
                 traction via newly developed tools, frameworks, and
                 HDLs. This enables new methods of creating hardware and
                 systems faster, more simply, and more efficiently. In
                 this paper, the implementation of a system-on-chip
                 (SoC) based on a 32-bit RISC-V processor with
                 lightweight cryptographic accelerator cores in FPGA and
                 an open-source integrating framework is presented. The
                 system consists of a 32-bit VexRiscv processor, written
                 in SpinalHDL, and lightweight cryptographic accelerator
                 cores for the PRINCE block cipher, the PRESENT-80 block
                 cipher, the ChaCha stream cipher, and the SHA3-512 hash
                 function, written in Verilog HDL and optimized for low
                 latency with fewer clock cycles. The primary aim of
                 this work was to develop a customized SoC platform with
                 a register-controlled bus suitable for integrating
                 lightweight cryptographic cores to become compact
                 embedded systems that require encryption
                 functionalities. Additionally, custom firmware was
                 developed to verify the functionality of the SoC with
                 all integrated accelerator cores, and to evaluate the
                 speed of cryptographic processing. The proposed system
                 was successfully implemented in a Xilinx Nexys4 DDR
                 FPGA development board. The resources of the system in
                 the FPGA were low with 11,830 LUTs and 9552 FFs. The
                 proposed system can be applicable to enhancing the
                 security of Internet of Things systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2023:CTA,
  author =       "Yufeng Li and Mengxiao Liu and Chenhong Cao and
                 Jiangtao Li",
  title =        "Communication-Traffic-Assisted Mining and Exploitation
                 of Buffer Overflow Vulnerabilities in {ADASs}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "185",
  day =          "18",
  month =        may,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050185",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/185",
  abstract =     "Advanced Driver Assistance Systems (ADASs) are crucial
                 components of intelligent vehicles, equipped with a
                 vast code base. To enhance the security of ADASs, it is
                 essential to mine their vulnerabilities and
                 corresponding exploitation methods. However, mining
                 buffer overflow (BOF) vulnerabilities in ADASs can be
                 challenging since their code and data are not publicly
                 available. In this study, we observed that ADAS devices
                 commonly utilize unencrypted protocols for module
                 communication, providing us with an opportunity to
                 locate input stream and buffer data operations more
                 efficiently. Based on the above observation, we
                 proposed a communication-traffic-assisted ADAS BOF
                 vulnerability mining and exploitation method. Our
                 method includes firmware extraction, a firmware and
                 system analysis, the locating of risk points with
                 communication traffic, validation, and exploitation. To
                 demonstrate the effectiveness of our proposed method,
                 we applied our method to several commercial ADAS
                 devices and successfully mined BOF vulnerabilities. By
                 exploiting these vulnerabilities, we executed the
                 corresponding commands and mapped the attack to the
                 physical world, showing the severity of these
                 vulnerabilities.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gao:2023:DRL,
  author =       "Siyu Gao and Yuchen Wang and Nan Feng and Zhongcheng
                 Wei and Jijun Zhao",
  title =        "Deep Reinforcement Learning-Based Video Offloading and
                 Resource Allocation in {NOMA}-Enabled Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "184",
  day =          "18",
  month =        may,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050184",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/184",
  abstract =     "With the proliferation of video surveillance system
                 deployment and related applications, real-time video
                 analysis is very critical to achieving intelligent
                 monitoring, autonomous driving, etc. Analyzing video
                 stream with high accuracy and low latency through the
                 traditional cloud computing represents a non-trivial
                 problem. In this paper, we propose a non-orthogonal
                 multiple access (NOMA)-based edge real-time video
                 analysis framework with one edge server (ES) and
                 multiple user equipments (UEs). A cost minimization
                 problem composed of delay, energy and accuracy is
                 formulated to improve the quality of experience (QoE)
                 of the UEs. In order to efficiently solve this problem,
                 we propose the joint video frame resolution scaling,
                 task offloading, and resource allocation algorithm
                 based on the Deep Q-Learning Network (JVFRS-TO-RA-DQN),
                 which effectively overcomes the sparsity of the
                 single-layer reward function and accelerates the
                 training convergence speed. JVFRS-TO-RA-DQN consists of
                 two DQN networks to reduce the curse of dimensionality,
                 which, respectively, select the offloading and resource
                 allocation action, as well as the resolution scaling
                 action. The experimental results show that
                 JVFRS-TO-RA-DQN can effectively reduce the cost of edge
                 computing and has better performance in terms of
                 convergence compared to other baseline schemes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kenyeres:2023:DAC,
  author =       "Martin Kenyeres and Jozef Kenyeres",
  title =        "Distributed Average Consensus Algorithms in
                 $d$-Regular Bipartite Graphs: Comparative Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "183",
  day =          "16",
  month =        may,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050183",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/183",
  abstract =     "Consensus-based data aggregation in d -regular
                 bipartite graphs poses a challenging task for the
                 scientific community since some of these algorithms
                 diverge in this critical graph topology. Nevertheless,
                 one can see a lack of scientific studies dealing with
                 this topic in the literature. Motivated by our recent
                 research concerned with this issue, we provide a
                 comparative study of frequently applied consensus
                 algorithms for distributed averaging in d -regular
                 bipartite graphs in this paper. More specifically, we
                 examine the performance of these algorithms with
                 bounded execution in this topology in order to identify
                 which algorithm can achieve the consensus despite no
                 reconfiguration and find the best-performing algorithm
                 in these graphs. In the experimental part, we apply the
                 number of iterations required for consensus to evaluate
                 the performance of the algorithms in randomly generated
                 regular bipartite graphs with various connectivities
                 and for three configurations of the applied stopping
                 criterion, allowing us to identify the optimal
                 distributed consensus algorithm for this graph
                 topology. Moreover, the obtained experimental results
                 presented in this paper are compared to other
                 scientific manuscripts where the analyzed algorithms
                 are examined in non-regular non-bipartite topologies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Taleb:2023:EMS,
  author =       "Anas Abu Taleb and Qasem Abu Al-Haija and Ammar Odeh",
  title =        "Efficient Mobile Sink Routing in Wireless Sensor
                 Networks Using Bipartite Graphs",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "182",
  day =          "14",
  month =        may,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050182",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/182",
  abstract =     "Wireless sensor networks (W.S.N.s) are a critical
                 research area with numerous practical applications.
                 W.S.N.s are utilized in real-life scenarios, including
                 environmental monitoring, healthcare, industrial
                 automation, smart homes, and agriculture. As W.S.N.s
                 advance and become more sophisticated, they offer
                 limitless opportunities for innovative solutions in
                 various fields. However, due to their unattended
                 nature, it is essential to develop strategies to
                 improve their performance without draining the battery
                 power of the sensor nodes, which is their most valuable
                 resource. This paper proposes a novel sink mobility
                 model based on constructing a bipartite graph from a
                 deployed wireless sensor network. The proposed model
                 uses bipartite graph properties to derive a controlled
                 mobility model for the mobile sink. As a result,
                 stationary nodes will be visited and planned to reduce
                 routing overhead and enhance the network's performance.
                 Using the bipartite graph's properties, the mobile sink
                 node can visit stationary sensor nodes in an optimal
                 way to collect data and transmit it to the base
                 station. We evaluated the proposed approach through
                 simulations using the NS-2 simulator to investigate the
                 performance of wireless sensor networks when adopting
                 this mobility model. Our results show that using the
                 proposed approach can significantly enhance the
                 performance of wireless sensor networks while
                 conserving the energy of the sensor nodes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Imoize:2023:OQS,
  author =       "Agbotiname Lucky Imoize and Friday Udeji and Joseph
                 Isabona and Cheng-Chi Lee",
  title =        "Optimizing the Quality of Service of Mobile Broadband
                 Networks for a Dense Urban Environment",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "181",
  day =          "12",
  month =        may,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050181",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/181",
  abstract =     "Mobile broadband (MBB) services in Lagos, Nigeria are
                 marred with poor signal quality and inconsistent user
                 experience, which can result in frustrated end-users
                 and lost revenue for service providers. With the
                 introduction of 5G, it is becoming more necessary for
                 4G LTE users to find ways of maximizing the technology
                 while they await the installation and implementation of
                 the new 5G networks. A comprehensive analysis of the
                 quality of 4G LTE MBB services in three different
                 locations in Lagos is performed. Minimal optimization
                 techniques using particle swarm optimization (PSO) are
                 used to propose solutions to the identified problems. A
                 methodology that involves data collection, statistical
                 analysis, and optimization techniques is adopted to
                 measure key performance indicators (KPIs) for MBB
                 services in the three locations: UNILAG, Ikorodu, and
                 Oniru VI. The measured KPIs include reference signal
                 received power (RSRP), reference signal received
                 quality (RSRQ), received signal strength indicator
                 (RSSI), and signal-to-noise ratio (SINR). Specific
                 statistical analysis was performed, and the mean,
                 standard deviation, skewness, and kurtosis were
                 calculated for the measured KPIs. Additionally, the
                 probability distribution functions for each KPI were
                 plotted to infer the quality of MBB services in each
                 location. Subsequently, the PSO algorithm was used to
                 optimize the KPIs in each location, and the results
                 were compared with the measured data to evaluate the
                 effectiveness of the optimization. Generally, the
                 optimization process results in an improvement in the
                 quality of service (QoS) in the investigated
                 environments. Findings also indicated that a single
                 KPI, such as RSRP, is insufficient for assessing the
                 quality of MBB services as perceived by end-users.
                 Therefore, multiple KPIs should be considered instead,
                 including RSRQ and RSSI. In order to improve MBB
                 performance in Lagos, recommendations require mapping
                 and replanning of network routes and hardware design.
                 Additionally, it is clear that there is a significant
                 difference in user experience between locations with
                 good and poor reception and that consistency in signal
                 values does not necessarily indicate a good user
                 experience. Therefore, this study provides valuable
                 insights and solutions for improving the quality of MBB
                 services in Lagos and can help service providers better
                 understand the needs and expectations of their end
                 users.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhu:2023:HTG,
  author =       "Wenhao Zhu and Xiaoyu Zhang and Qiuhong Zhai and
                 Chenyun Liu",
  title =        "A Hybrid Text Generation-Based Query Expansion Method
                 for Open-Domain Question Answering",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "180",
  day =          "12",
  month =        may,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050180",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/180",
  abstract =     "In the two-stage open-domain question answering
                 (OpenQA) systems, the retriever identifies a subset of
                 relevant passages, which the reader then uses to
                 extract or generate answers. However, the performance
                 of OpenQA systems is often hindered by issues such as
                 short and semantically ambiguous queries, making it
                 challenging for the retriever to find relevant passages
                 quickly. This paper introduces Hybrid Text
                 Generation-Based Query Expansion (HTGQE), an effective
                 method to improve retrieval efficiency. HTGQE combines
                 large language models with Pseudo-Relevance Feedback
                 techniques to enhance the input for generative models,
                 improving text generation speed and quality. Building
                 on this foundation, HTGQE employs multiple query
                 expansion generators, each trained to provide query
                 expansion contexts from distinct perspectives. This
                 enables the retriever to explore relevant passages from
                 various angles for complementary retrieval results. As
                 a result, under an extractive and generative QA setup,
                 HTGQE achieves promising results on both Natural
                 Questions (NQ) and TriviaQA (Trivia) datasets for
                 passage retrieval and reading tasks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hasan:2023:RDL,
  author =       "Md. Tarek Hasan and Md. Al Emran Hossain and Md.
                 Saddam Hossain Mukta and Arifa Akter and Mohiuddin
                 Ahmed and Salekul Islam",
  title =        "A Review on Deep-Learning-Based Cyberbullying
                 Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "179",
  day =          "11",
  month =        may,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050179",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/179",
  abstract =     "Bullying is described as an undesirable behavior by
                 others that harms an individual physically, mentally,
                 or socially. Cyberbullying is a virtual form (e.g.,
                 textual or image) of bullying or harassment, also known
                 as online bullying. Cyberbullying detection is a
                 pressing need in today's world, as the prevalence of
                 cyberbullying is continually growing, resulting in
                 mental health issues. Conventional machine learning
                 models were previously used to identify cyberbullying.
                 However, current research demonstrates that deep
                 learning surpasses traditional machine learning
                 algorithms in identifying cyberbullying for several
                 reasons, including handling extensive data, efficiently
                 classifying text and images, extracting features
                 automatically through hidden layers, and many others.
                 This paper reviews the existing surveys and identifies
                 the gaps in those studies. We also present a
                 deep-learning-based defense ecosystem for cyberbullying
                 detection, including data representation techniques and
                 different deep-learning-based models and frameworks. We
                 have critically analyzed the existing DL-based
                 cyberbullying detection techniques and identified their
                 significant contributions and the future research
                 directions they have presented. We have also summarized
                 the datasets being used, including the DL architecture
                 being used and the tasks that are accomplished for each
                 dataset. Finally, several challenges faced by the
                 existing researchers and the open issues to be
                 addressed in the future have been presented.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Falayi:2023:SDD,
  author =       "Ayodeji Falayi and Qianlong Wang and Weixian Liao and
                 Wei Yu",
  title =        "Survey of Distributed and Decentralized {IoT}
                 Securities: Approaches Using Deep Learning and
                 Blockchain Technology",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "178",
  day =          "11",
  month =        may,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050178",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/178",
  abstract =     "The Internet of Things (IoT) continues to attract
                 attention in the context of computational resource
                 growth. Various disciplines and fields have begun to
                 employ IoT integration technologies in order to enable
                 smart applications. The main difficulty in supporting
                 industrial development in this scenario involves
                 potential risk or malicious activities occurring in the
                 network. However, there are tensions that are difficult
                 to overcome at this stage in the development of IoT
                 technology. In this situation, the future of security
                 architecture development will involve enabling
                 automatic and smart protection systems. Due to the
                 vulnerability of current IoT devices, it is
                 insufficient to ensure system security by implementing
                 only traditional security tools such as encryption and
                 access control. Deep learning and blockchain technology
                 has now become crucial, as it provides distinct and
                 secure approaches to IoT network security. The aim of
                 this survey paper is to elaborate on the application of
                 deep learning and blockchain technology in the IoT to
                 ensure secure utility. We first provide an introduction
                 to the IoT, deep learning, and blockchain technology,
                 as well as a discussion of their respective security
                 features. We then outline the main obstacles and
                 problems of trusted IoT and how blockchain and deep
                 learning may be able to help. Next, we present the
                 future challenges in integrating deep learning and
                 blockchain technology into the IoT. Finally, as a
                 demonstration of the value of blockchain in
                 establishing trust, we provide a comparison between
                 conventional trust management methods and those based
                 on blockchain.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Marin:2023:BSB,
  author =       "Oana Marin and Tudor Cioara and Ionut Anghel",
  title =        "Blockchain Solution for Buildings' Multi-Energy
                 Flexibility Trading Using Multi-Token Standards",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "177",
  day =          "10",
  month =        may,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050177",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/177",
  abstract =     "Buildings can become a significant contributor to an
                 energy system's resilience if they are operated in a
                 coordinated manner to exploit their flexibility in
                 multi-carrier energy networks. However, research and
                 innovation activities are focused on single-carrier
                 optimization (i.e., electricity), aiming to achieve
                 Zero Energy Buildings, and miss the significant
                 flexibility that buildings may offer through
                 multi-energy coupling. In this paper, we propose to use
                 blockchain technology and ERC-1155 tokens to digitize
                 the heat and electrical energy flexibility of
                 buildings, transforming them into active flexibility
                 assets within integrated multi-energy grids, allowing
                 them to trade both heat and electricity within
                 community-level marketplaces. The solution increases
                 the level of interoperability and integration of the
                 buildings with community multi-energy grids and brings
                 advantages from a transactive perspective. It permits
                 digitizing multi-carrier energy using the same token
                 and a single transaction to transfer both types of
                 energy, processing transaction batches between the
                 sender and receiver addresses, and holding both
                 fungible and non-fungible tokens in smart contracts to
                 support energy markets' financial payments and energy
                 transactions' settlement. The results show the
                 potential of our solution to support buildings in
                 trading heat and electricity flexibility in the same
                 market session, increasing their interoperability with
                 energy markets while decreasing the transactional
                 overhead and gas consumption.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chang:2023:SUF,
  author =       "Sang-Yoon Chang and Kyungmin Park and Jonghyun Kim and
                 Jinoh Kim",
  title =        "Securing {UAV} Flying Base Station for Mobile
                 Networking: a Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "176",
  day =          "09",
  month =        may,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050176",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/176",
  abstract =     "A flying base station based on an unmanned aerial
                 vehicle (UAV) uses its mobility to extend its
                 connectivity coverage and improve its communication
                 channel quality to achieve a greater communication rate
                 and latency performances. While UAV flying base
                 stations have been used in emergency events in 5G
                 networking (sporadic and temporary), their use will
                 significantly increase in 6G networking, as 6G expects
                 reliable connectivity even in rural regions and
                 requires high-performance communication channels and
                 line-of-sight channels for millimeter wave (mmWave)
                 communications. Securing the integrity and availability
                 of the base station operations is critical because of
                 the users' increasing reliance on the connectivity
                 provided by the base stations, e.g., the mobile user
                 loses connectivity if the base station operation gets
                 disrupted. This paper identifies the security issues
                 and research gaps of flying base stations, focusing on
                 their unique properties, while building on the existing
                 research in wireless communications for stationary
                 ground base stations and embedded control for UAV
                 drones. More specifically, the flying base station's
                 user-dependent positioning, its battery-constrained
                 power, and the dynamic and distributed operations cause
                 vulnerabilities that are distinct from those in 5G and
                 previous-generation mobile networking with stationary
                 ground base stations. This paper reviews the relevant
                 security research from the perspectives of
                 communications (mobile computing, 5G networking, and
                 distributed computing) and embedded/control systems
                 (UAV vehicular positioning and battery control) and
                 then identifies the security gaps and new issues
                 emerging for flying base stations. Through this review
                 paper, we inform readers of flying base station
                 research, development, and standardization for future
                 mobile and 6G networking.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wadatkar:2023:MTV,
  author =       "Prachi V. Wadatkar and Rosario G. Garroppo and
                 Gianfranco Nencioni",
  title =        "{5G-MEC} Testbeds for {V2X} Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "175",
  day =          "09",
  month =        may,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050175",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/175",
  abstract =     "Fifth-generation (5G) mobile networks fulfill the
                 demands of critical applications, such as
                 Ultra-Reliable Low-Latency Communication (URLLC),
                 particularly in the automotive industry. Vehicular
                 communication requires low latency and high
                 computational capabilities at the network's edge. To
                 meet these requirements, ETSI standardized Multi-access
                 Edge Computing (MEC), which provides cloud computing
                 capabilities and addresses the need for low latency.
                 This paper presents a generalized overview for
                 implementing a 5G-MEC testbed for Vehicle-to-Everything
                 (V2X) applications, as well as the analysis of some
                 important testbeds and state-of-the-art implementations
                 based on their deployment scenario, 5G use cases, and
                 open source accessibility. The complexity of using the
                 testbeds is also discussed, and the challenges
                 researchers may face while replicating and deploying
                 them are highlighted. Finally, the paper summarizes the
                 tools used to build the testbeds and addresses open
                 issues related to implementing the testbeds.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Moustakidis:2023:PFT,
  author =       "Serafeim Moustakidis and Spyridon Plakias and Christos
                 Kokkotis and Themistoklis Tsatalas and Dimitrios
                 Tsaopoulos",
  title =        "Predicting Football Team Performance with Explainable
                 {AI}: Leveraging {SHAP} to Identify Key Team-Level
                 Performance Metrics",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "174",
  day =          "05",
  month =        may,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050174",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/174",
  abstract =     "Understanding the performance indicators that
                 contribute to the final score of a football match is
                 crucial for directing the training process towards
                 specific goals. This paper presents a pipeline for
                 identifying key team-level performance variables in
                 football using explainable ML techniques. The input
                 data includes various team-specific features such as
                 ball possession and pass behaviors, with the target
                 output being the average scoring performance of each
                 team over a season. The pipeline includes data
                 preprocessing, sequential forward feature selection,
                 model training, prediction, and explainability using
                 SHapley Additive exPlanations (SHAP). Results show that
                 14 variables have the greatest contribution to the
                 outcome of a match, with 12 having a positive effect
                 and 2 having a negative effect. The study also
                 identified the importance of certain performance
                 indicators, such as shots, chances, passing, and ball
                 possession, to the final score. This pipeline provides
                 valuable insights for coaches and sports analysts to
                 understand which aspects of a team's performance need
                 improvement and enable targeted interventions to
                 improve performance. The use of explainable ML
                 techniques allows for a deeper understanding of the
                 factors contributing to the predicted average team
                 score performance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Singh:2023:BEN,
  author =       "Raman Singh and Zeeshan Pervez and Hitesh Tewari",
  title =        "Blockchain-Enabled {NextGen} Service Architecture for
                 Mobile {Internet} Offload",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "173",
  day =          "05",
  month =        may,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050173",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/173",
  abstract =     "The amalgamation of heterogeneous generations of
                 mobile cellular networks around the globe has resulted
                 in diverse data speed experiences for end users. At
                 present, there are no defined mechanisms in place for
                 subscribers of a mobile network operator (MNO) to use
                 the services of third-party WiFi providers. MNOs also
                 have no standardized procedures to securely interact
                 with each other, and allow their subscribers to use
                 third-party services on a pay-as-you-go basis. This
                 paper proposes a blockchain-enabled offloading
                 framework that allows a subscriber of a mobile operator
                 to temporarily use another MNO or WiFi provider's
                 higher-speed network. A smart contract is employed to
                 allow diverse entities, such as MNOs, brokers and WiFi
                 providers, to automatically execute mutual agreements,
                 to enable the utilization of third-party infrastructure
                 in a secure and controlled manner. The proposed
                 framework is tested using Ethereum's testnet on the
                 Goerli network using Alchemy and Hardhat. The analysis
                 of the results obtained shows that the proposed
                 technique helps mobile operators to offer improved user
                 experience in the form of average speed and latency.
                 The experiments show that the average time taken to
                 deliver a 500 MB file is reduced from 10.23 s to 0.91 s
                 for the global average scenario, from 6.09 s to 0.50 s
                 for 5G, from 13.50 s to 0.50 s for 4G-LTE, from 41.11 s
                 to 0.49 s for 4G, and from 339.11 s to 0.49 s for the
                 3G scenario. The results also show that, with WiFi
                 offloading, users from all cellular generations can
                 enjoy a similar quality of services, because delivery
                 time ranges from 0.49 s to 0.91 s for offloaded
                 experiments whereas for the non-offloaded scenario it
                 ranges from 6.09 s to 339.11 s.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lei:2023:SPA,
  author =       "Kuncheng Lei and Zhenrong Zhang",
  title =        "System Performance Analysis of Sensor Networks for
                 {RF} Energy Harvesting and Information Transmission",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "172",
  day =          "30",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050172",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/172",
  abstract =     "This paper investigates the problem of RF energy
                 harvesting in wireless sensor networks, with the aim of
                 finding a suitable communication protocol by comparing
                 the performance of the system under different
                 protocols. The network is made up of two parts: first,
                 at the beginning of each timeslot, the sensor nodes
                 harvest energy from the base station (BS) and then send
                 packets to the BS using the harvested energy. For the
                 energy-harvesting part of the wireless sensor network,
                 we consider two methods: point-to-point and
                 multi-point-to-point energy harvesting. For each
                 method, we use two independent control protocols,
                 namely head harvesting energy of each timeslot (HHT)
                 and head harvesting energy of dedicated timeslot (HDT).
                 Additionally, for complex channel states, we derive the
                 cumulative distribution function (CDF) of packet
                 transmission time using selective combining (SC) and
                 maximum ratio combining (MRC) techniques. Analytical
                 expressions for system reliability and packet timeout
                 probability are obtained. At the same time, we also
                 utilize the Monte Carlo simulation method to simulate
                 our system and have analyzed both the numerical and
                 simulation solutions. Results show that the performance
                 of the HHT protocol is better than that of the HDT
                 protocol, and the MRC technology outperforms the SC
                 technology for the HHT protocol in terms of the
                 energy-harvesting efficiency coefficient, sensor
                 positions, transmit signal-to-noise ratio (SNR), and
                 length of energy harvesting time.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2023:DSS,
  author =       "Mian Wang and Cong'an Xu and Yun Lin and Zhiyi Lu and
                 Jinlong Sun and Guan Gui",
  title =        "A Distributed Sensor System Based on Cloud-Edge-End
                 Network for {Industrial Internet of Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "171",
  day =          "30",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050171",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/171",
  abstract =     "The Industrial Internet of Things (IIoT) refers to the
                 application of the IoT in the industrial field. The
                 development of fifth-generation (5G) communication
                 technology has accelerated the world's entry into the
                 era of the industrial revolution and has also promoted
                 the overall optimization of the IIoT. In the IIoT
                 environment, challenges such as complex operating
                 conditions and diverse data transmission have become
                 increasingly prominent. Therefore, studying how to
                 collect and process a large amount of real-time data
                 from various devices in a timely, efficient, and
                 reasonable manner is a significant problem. To address
                 these issues, we propose a three-level networking model
                 based on distributed sensor self-networking and cloud
                 server platforms for networking. This model can collect
                 monitoring data for a variety of industrial scenarios
                 that require data collection. It enables the processing
                 and storage of key information in a timely manner,
                 reduces data transmission and storage costs, and
                 improves data transmission reliability and efficiency.
                 Additionally, we have designed a feature fusion network
                 to further enhance the amount of feature information
                 and improve the accuracy of industrial data
                 recognition. The system also includes data
                 preprocessing and data visualization capabilities.
                 Finally, we discuss how to further preprocess and
                 visualize the collected dataset and provide a specific
                 algorithm analysis process using a large manipulator
                 dataset as an example.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alotaibi:2023:TSB,
  author =       "Fahad M. Alotaibi and Vassilios G. Vassilakis",
  title =        "Toward an {SDN}-Based {Web} Application Firewall:
                 Defending against {SQL} Injection Attacks",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "170",
  day =          "29",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050170",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/170",
  abstract =     "Web attacks pose a significant threat to enterprises,
                 as attackers often target web applications first.
                 Various solutions have been proposed to mitigate and
                 reduce the severity of these threats, such as web
                 application firewalls (WAFs). On the other hand,
                 software-defined networking (SDN) technology has
                 significantly improved network management and operation
                 by providing centralized control for network
                 administrators. In this work, we investigated the
                 possibility of using SDN to implement a firewall
                 capable of detecting and blocking web attacks. As a
                 proof of concept, we designed and implemented a WAF to
                 detect a known web attack, specifically SQL injection.
                 Our design utilized two detection methods: signatures
                 and regular expressions. The experimental results
                 demonstrate that the SDN controller can successfully
                 function as a WAF and detect SQL injection attacks.
                 Furthermore, we implemented and compared ModSecurity, a
                 traditional WAF, with our proposed SDN-based WAF. The
                 results reveal that our system is more efficient in
                 terms of TCP ACK latency, while ModSecurity exhibits a
                 slightly lower overhead on the controller.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sakurai:2023:BCD,
  author =       "Guilherme Yukio Sakurai and Jessica Fernandes Lopes
                 and Bruno Bogaz Zarpel{\~a}o and Sylvio Barbon Junior",
  title =        "Benchmarking Change Detector Algorithms from Different
                 Concept Drift Perspectives",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "169",
  day =          "29",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050169",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/169",
  abstract =     "The stream mining paradigm has become increasingly
                 popular due to the vast number of algorithms and
                 methodologies it provides to address the current
                 challenges of Internet of Things (IoT) and modern
                 machine learning systems. Change detection algorithms,
                 which focus on identifying drifts in the data
                 distribution during the operation of a machine learning
                 solution, are a crucial aspect of this paradigm.
                 However, selecting the best change detection method for
                 different types of concept drift can be challenging.
                 This work aimed to provide a benchmark for four drift
                 detection algorithms (EDDM, DDM, HDDMW, and HDDMA) for
                 abrupt, gradual, and incremental drift types. To shed
                 light on the capacity and possible trade-offs involved
                 in selecting a concept drift algorithm, we compare
                 their detection capability, detection time, and
                 detection delay. The experiments were carried out using
                 synthetic datasets, where various attributes, such as
                 stream size, the amount of drifts, and drift duration
                 can be controlled and manipulated on our generator of
                 synthetic stream. Our results show that HDDMW provides
                 the best trade-off among all performance indicators,
                 demonstrating superior consistency in detecting abrupt
                 drifts, but has suboptimal time consumption and a
                 limited ability to detect incremental drifts. However,
                 it outperforms other algorithms in detection delay for
                 both abrupt and gradual drifts with an efficient
                 detection performance and detection time performance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Duarte:2023:MAR,
  author =       "Rui P. Duarte and Carlos A. S. Cunha and Valter N. N.
                 Alves",
  title =        "Mobile Application for Real-Time Food Plan Management
                 for {Alzheimer} Patients through Design-Based
                 Research",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "168",
  day =          "29",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050168",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/168",
  abstract =     "Alzheimer's disease is a type of dementia that affects
                 many individuals, mainly in an older age group. Over
                 time, it leads to other diseases that affect their
                 autonomy and independence. The quality of food
                 ingestion is a way to mitigate the disease and preserve
                 the patient's well-being, which substantially impacts
                 their health. Many existing applications for food plan
                 management focus on the prescription of food plans but
                 do not provide feedback to the nutritionist on the real
                 amount of ingested calories. It makes these
                 applications inadequate for these diseases, where
                 monitoring and control are most important. This paper
                 proposed the design and development of a mobile
                 application to monitor and control the food plans of
                 Alzheimer's patients, focused on informal caregivers
                 and respective patients. It allows both the realistic
                 visualization of the food plans and users to adjust
                 their consumption and register extra meals and water
                 consumption. The interface design process comprises a
                 two-level approach: the user centered design
                 methodology that accounts for users' needs and
                 requirements and the user experience questionnaire to
                 measure user satisfaction. The results show that the
                 interface is intuitive, visually appealing, and easy to
                 use, adjusted for users that require a particular level
                 of understanding regarding specific subjects.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Benmoussa:2023:NBB,
  author =       "Ahmed Benmoussa and Chaker Abdelaziz Kerrache and
                 Carlos T. Calafate and Nasreddine Lagraa",
  title =        "{NDN-BDA}: a Blockchain-Based Decentralized Data
                 Authentication Mechanism for Vehicular Named Data
                 Networking",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "167",
  day =          "29",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050167",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/167",
  abstract =     "Named Data Networking (NDN) is an implementation of
                 Information-Centric Networking (ICN) that has emerged
                 as a promising candidate for the Future Internet
                 Architecture (FIA). In contrast to traditional
                 networking protocols, NDN's focus is on content, rather
                 than the source of the content. NDN enables name-based
                 routing and location-independent data retrieval, which
                 gives NDN the ability to support the highly dynamic
                 nature of mobile networks. Among other important
                 features, NDN integrates security mechanisms and
                 prioritizes protecting content over communication
                 channels through cryptographic signatures. However, the
                 data verification process that NDN employs may cause
                 significant delays, especially in mobile networks and
                 vehicular networks. This aspect makes it unsuitable for
                 time-critical and sensitive applications such as the
                 sharing of safety messages. Therefore, in this work, we
                 propose NDN-BDA, a blockchain-based decentralized
                 mechanism that provides a faster and more efficient
                 data authenticity mechanism for NDN-based vehicular
                 networks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mohammed:2023:FIA,
  author =       "Sarfaraz Ahmed Mohammed and Anca L. Ralescu",
  title =        "Future {Internet} Architectures on an Emerging Scale
                 --- a Systematic Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "166",
  day =          "29",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050166",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/166",
  abstract =     "Future Internet is a general term that is used to
                 refer to the study of new Internet architectures that
                 emphasize the advancements that are paving the way for
                 the next generation of internet. Today's internet has
                 become more complicated and arduous to manage due to
                 its increased traffic. This traffic is a result of the
                 transfer of 247 billion emails, the management of more
                 than a billion websites and 735 active top-level
                 domains, the viewing of at least one billion YouTube
                 videos per day (which is the source of main traffic),
                 and the uploading of more than 2.5 billion photos to
                 Facebook every year. The internet was never anticipated
                 to provide quality of service (QoS) support, but one
                 can have a best effort service that provides support
                 for video streams and downloaded media applications.
                 Therefore, the future architecture of the internet
                 becomes crucial. Furthermore, the internet as a service
                 has witnessed many evolving conflicts among its
                 stakeholders, leading to extensive research. This
                 article presents a systematic review of the internet's
                 evolution and discusses the ongoing research efforts
                 towards new internet architectures, as well as the
                 challenges that are faced in increasing the network's
                 performance and quality. Moreover, as part of these
                 anticipated future developments, this article draws
                 attention to the Metaverse, which combines the emerging
                 areas of augmented reality, virtual reality, mixed
                 reality, and extended reality, and is considered to be
                 the next frontier for the future internet. This article
                 examines the key role of the blockchain in organizing
                 and advancing the applications and services within the
                 Metaverse. It also discusses the potential benefits and
                 challenges of future internet research. Finally, the
                 article outlines certain directions for future internet
                 research, particularly in the context of utilizing
                 blockchains in the Metaverse.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Dimoulas:2023:TAW,
  author =       "Charalampos A. Dimoulas and Andreas Veglis",
  title =        "Theory and Applications of {Web 3.0} in the Media
                 Sector",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "165",
  day =          "28",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050165",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/165",
  abstract =     "We live in a digital era, with vast technological
                 advancements, which, among others, have a major impact
                 on the media domain. More specifically, progress in the
                 last two decades led to the end-to-end digitalization
                 of the media industry, resulting in a rapidly evolving
                 media landscape. In addition to news digitization,
                 User-Generated Content (UGC) is dominant in this new
                 environment, also fueled by Social Media, which has
                 become commonplace for news publishing, propagation,
                 consumption, and interactions. However, the exponential
                 increase in produced and distributed content, with the
                 multiplied growth in the number of plenary individuals
                 involved in the processes, created urgent needs and
                 challenges that need careful treatment. Hence,
                 intelligent processing and automation incorporated into
                 the Semantic Web vision, also known as Web 3.0, aim at
                 providing sophisticated data documentation, retrieval,
                 and management solutions to meet the demands of the new
                 digital world. Specifically, for the sensitive news and
                 media domains, necessities are created both at the
                 production and consumption ends, dealing with content
                 production and validation, as well as tools empowering
                 and engaging audiences (professionals and end users).
                 In this direction, state-of-the-art works studying news
                 detection, modeling, generation, recommendation,
                 evaluation, and utilization are included in the current
                 Special Issue, enlightening multiple contemporary
                 journalistic practices and media perspectives.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{vanderSchyff:2023:OPF,
  author =       "Karl van der Schyff and Greg Foster and Karen Renaud
                 and Stephen Flowerday",
  title =        "Online Privacy Fatigue: a Scoping Review and Research
                 Agenda",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "164",
  day =          "28",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050164",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/164",
  abstract =     "Online users are responsible for protecting their
                 online privacy themselves: the mantra is custodiat te
                 (protect yourself). Even so, there is a great deal of
                 evidence pointing to the fact that online users
                 generally do not act to preserve the privacy of their
                 personal information, consequently disclosing more than
                 they ought to and unwisely divulging sensitive
                 information. Such self-disclosure has many negative
                 consequences, including the invasion of privacy and
                 identity theft. This often points to a need for more
                 knowledge and awareness but does not explain why even
                 knowledgeable users fail to preserve their privacy. One
                 explanation for this phenomenon may be attributed to
                 online privacy fatigue. Given the importance of online
                 privacy and the lack of integrative online privacy
                 fatigue research, this scoping review aims to provide
                 researchers with an understanding of online privacy
                 fatigue, its antecedents and outcomes, as well as a
                 critical analysis of the methodological approaches
                 used. A scoping review based on the PRISMA-ScR
                 checklist was conducted. Only empirical studies
                 focusing on online privacy were included, with
                 nontechnological studies being excluded. All studies
                 had to be written in English. A search strategy
                 encompassing six electronic databases resulted in
                 eighteen eligible studies, and a backward search of the
                 references resulted in an additional five publications.
                 Of the 23 studies, the majority were quantitative
                 (74\%), with fewer than half being theory driven
                 (48\%). Privacy fatigue was mainly conceptualized as a
                 loss of control (74\% of studies). Five categories of
                 privacy fatigue antecedents were identified: privacy
                 risk, privacy control and management, knowledge and
                 information, individual differences, and privacy policy
                 characteristics. This study highlights the need for
                 greater attention to be paid to the methodological
                 design and theoretical underpinning of future research.
                 Quantitative studies should carefully consider the use
                 of CB-SEM or PLS-SEM, should aim to increase the sample
                 size, and should improve on analytical rigor. In
                 addition, to ensure that the field matures, future
                 studies should be underpinned by established
                 theoretical frameworks. This review reveals a notable
                 absence of privacy fatigue research when modeling the
                 influence of privacy threats and invasions and their
                 relationship with privacy burnout, privacy resignation,
                 and increased self-disclosure. In addition, this review
                 provides insight into theoretical and practical
                 research recommendations that future privacy fatigue
                 researchers should consider going forward.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Frattolillo:2023:WPS,
  author =       "Franco Frattolillo",
  title =        "Watermarking Protocols: a Short Guide for Beginners",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "163",
  day =          "28",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050163",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/163",
  abstract =     "Watermarking protocols, in conjunction with digital
                 watermarking technologies, make it possible to trace
                 back digital copyright infringers by identifying who
                 has legitimately purchased digital content and then
                 illegally shared it on the Internet. Although they can
                 act as an effective deterrent against copyright
                 violations, their adoption in the current web context
                 is made difficult due to unresolved usability and
                 performance issues. This paper aims at providing
                 researchers with the basics needed to design
                 watermarking protocols suited to the web context. It is
                 focused on two important aspects. The first concerns
                 the basic requirements that make a protocol usable by
                 both web users and content providers, whereas the
                 second concerns the security primitives and how they
                 have been used to implement the most relevant examples
                 of watermarking protocols documented in the literature.
                 In this way, researchers can rely on a quick guide to
                 getting started in the field of watermarking
                 protocols.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mourtzis:2023:FHM,
  author =       "Dimitris Mourtzis and John Angelopoulos and Nikos
                 Panopoulos",
  title =        "The Future of the Human--Machine Interface ({HMI}) in
                 {Society 5.0}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "162",
  day =          "27",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050162",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/162",
  abstract =     "The blending of human and mechanical capabilities has
                 become a reality in the realm of Industry 4.0.
                 Enterprises are encouraged to design frameworks capable
                 of harnessing the power of human and technological
                 resources to enhance the era of Artificial Intelligence
                 (AI). Over the past decade, AI technologies have
                 transformed the competitive landscape, particularly
                 during the pandemic. Consequently, the job market, at
                 an international level, is transforming towards the
                 integration of suitably skilled people in cutting edge
                 technologies, emphasizing the need to focus on the
                 upcoming super-smart society known as Society 5.0. The
                 concept of a Humachine builds on the notion that humans
                 and machines have a common future that capitalizes on
                 the strengths of both humans and machines. Therefore,
                 the aim of this paper is to identify the capabilities
                 and distinguishing characteristics of both humans and
                 machines, laying the groundwork for improving
                 human-machine interaction (HMI).",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Santos:2023:BBL,
  author =       "Andr{\'e} F. Santos and Jos{\'e} Marinho and Jorge
                 Bernardino",
  title =        "Blockchain-Based Loyalty Management System",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "161",
  day =          "27",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050161",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/161",
  abstract =     "Loyalty platforms are designed to increase customer
                 loyalty and thus increase consumers' attraction to
                 purchase. Although successful in increasing brand reach
                 and sales, these platforms fail to meet their primary
                 objective due to a lack of incentives and encouragement
                 for customers to return. Along with the problem in
                 originating sales, they bring excessive costs to brands
                 due to the maintenance and infrastructure required to
                 make the systems feasible. In that sense, recent
                 blockchain technology can help to overcome some of
                 these problems, providing capabilities such as smart
                 contracts, which have the potential to reinvent the way
                 loyalty systems work and solve current problems.
                 Although blockchain is a relatively new technology,
                 some brands are already investigating its usefulness
                 and rebuilding their loyalty systems. However, these
                 platforms are independent and linked directly to a
                 brand. Thus, there is a need for a generic platform
                 capable of creating and managing different loyalty
                 programs, regardless of the size of the business. This
                 paper explores the shortcomings of current loyalty
                 programs identified through the literature review, and
                 proposes a loyalty management system with blockchain
                 integration that allows any retailer to create and
                 manage their loyalty programs and have customers
                 interact directly with multiple programs in a single
                 application.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Delgado:2023:ELC,
  author =       "Francisco Delgado",
  title =        "Extending Learning and Collaboration in Quantum
                 Information with {Internet} Support: a Future
                 Perspective on Research Education beyond Boundaries,
                 Limitations, and Frontiers",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "160",
  day =          "26",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050160",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/160",
  abstract =     "Quantum information is an emerging scientific and
                 technological discipline attracting a growing number of
                 professionals from various related fields. Although it
                 can potentially serve as a valuable source of skilled
                 labor, the Internet provides a way to disseminate
                 information about education, opportunities, and
                 collaboration. In this work, we analyzed, through a
                 blended approach, the sustained effort over 12 years to
                 involve science and engineering students in research
                 education and collaboration, emphasizing the role
                 played by the Internet. Three main spaces have been
                 promoted, workshops, research stays, and a minor, all
                 successfully developed through distance education in
                 2021-2022, involving students from various locations in
                 Mexico and the United States. The success of these
                 efforts was measured by research-oriented indicators,
                 the number of participants, and their surveyed
                 opinions. The decisive inclusion of the Internet to
                 facilitate the blended approach has accelerated the
                 boost in human resources and research production.
                 During the COVID-19 pandemic, the Internet played a
                 crucial role in the digital transformation of this
                 research education initiative, leading to effective
                 educative and collaborative experiences in the ``New
                 Normal''.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Medeiros:2023:DAS,
  author =       "Eduardo Medeiros and Leonel Corado and Lu{\'\i}s Rato
                 and Paulo Quaresma and Pedro Salgueiro",
  title =        "Domain Adaptation Speech-to-Text for Low-Resource
                 {European} {Portuguese} Using Deep Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "159",
  day =          "24",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050159",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/159",
  abstract =     "Automatic speech recognition (ASR), commonly known as
                 speech-to-text, is the process of transcribing audio
                 recordings into text, i.e., transforming speech into
                 the respective sequence of words. This paper presents a
                 deep learning ASR system optimization and evaluation
                 for the European Portuguese language. We present a
                 pipeline composed of several stages for data
                 acquisition, analysis, pre-processing, model creation,
                 and evaluation. A transfer learning approach is
                 proposed considering an English language-optimized
                 model as starting point; a target composed of European
                 Portuguese; and the contribution to the transfer
                 process by a source from a different domain consisting
                 of a multiple-variant Portuguese language dataset,
                 essentially composed of Brazilian Portuguese. A domain
                 adaptation was investigated between European Portuguese
                 and mixed (mostly Brazilian) Portuguese. The proposed
                 optimization evaluation used the NVIDIA NeMo framework
                 implementing the QuartzNet15$ \times $5 architecture
                 based on 1D time-channel separable convolutions.
                 Following this transfer learning data-centric approach,
                 the model was optimized, achieving a state-of-the-art
                 word error rate (WER) of 0.0503.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2023:CST,
  author =       "Jinlong Wang and Dong Cui and Qiang Zhang",
  title =        "{Chinese} Short-Text Sentiment Prediction: a Study of
                 Progressive Prediction Techniques and Attentional
                 Fine-Tuning",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "158",
  day =          "23",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050158",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/158",
  abstract =     "With sentiment prediction technology, businesses can
                 quickly look at user reviews to find ways to improve
                 their products and services. We present the BertBilstm
                 Multiple Emotion Judgment (BBMEJ) model for
                 small-sample emotion prediction tasks to solve the
                 difficulties of short emotion identification datasets
                 and the high dataset annotation costs encountered by
                 small businesses. The BBMEJ model is suitable for many
                 datasets. When an insufficient quantity of relevant
                 datasets prevents the model from achieving the desired
                 training results, the prediction accuracy of the model
                 can be enhanced by fine-tuning it with additional
                 datasets prior to training. Due to the number of
                 parameters in the Bert model, fine-tuning requires a
                 lot of data, which drives up the cost of fine-tuning.
                 We present the Bert Tail Attention Fine-Tuning (BTAFT)
                 method to make fine-tuning work better. Our
                 experimental findings demonstrate that the BTAFT
                 fine-tuning approach performs better in terms of the
                 prediction effect than fine-tuning all parameters. Our
                 model obtains a small sample prediction accuracy of
                 0.636, which is better than the ideal baseline of
                 0.064. The Macro-F1 (F1) evaluation metrics
                 significantly exceed other models.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Weerasinghe:2023:TCB,
  author =       "Nuwan Weerasinghe and Muhammad Arslan Usman and
                 Chaminda Hewage and Eckhard Pfluegel and Christos
                 Politis",
  title =        "Threshold Cryptography-Based Secure
                 Vehicle-to-Everything ({V2X}) Communication in
                 {5G}-Enabled Intelligent Transportation Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "157",
  day =          "23",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050157",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/157",
  abstract =     "Implementing 5G-enabled Vehicle-to-Everything (V2X)
                 intelligent transportation systems presents a promising
                 opportunity to enhance road safety and traffic flow
                 while facilitating the integration of artificial
                 intelligence (AI) based solutions. Yet, security and
                 privacy concerns pose significant challenges that must
                 be addressed. Therefore, researchers have focused on
                 improving the security and integrity of vehicle data
                 sharing, with a particular emphasis on V2X application
                 layer security and privacy requirements. This is
                 crucial given that V2X networks can consist of vehicles
                 manufactured by different companies and registered in
                 various jurisdictions, which may only be within
                 communication range for a few seconds. Thus, it is
                 necessary to establish a trusting relationship between
                 vehicles quickly. The article proposes a threshold
                 cryptography-based key exchange protocol that meets the
                 key requirements for V2X data sharing and privacy,
                 including the rapid establishment of trust, the
                 maintenance of vehicle anonymity, and the provision of
                 secure messages. To evaluate the feasibility and
                 performance of the proposed protocol, a tailored
                 testbed that leverages the NS-3 network simulator, a
                 commercial 5G network, and public cloud infrastructure
                 is used. Overall, the proposed protocol provides a
                 potential solution for addressing security and privacy
                 concerns in V2X networks, which is essential for
                 successfully implementing and adopting this
                 technology.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tian:2023:RSP,
  author =       "Zhenyu Tian and Jiali You and Linlin Hu",
  title =        "A Reverse Shortest Path Tree-Based Multicast Joining
                 Node Selection Method",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "156",
  day =          "23",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050156",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/156",
  abstract =     "Network layer multicast is a powerful method for
                 transmitting data from sources to multiple group
                 members. When joining a multicast group, a group member
                 first sends a request to a designated router (DR).
                 Then, the DR selects a node in the existing multicast
                 tree (known as a multicast joining node, or MJN) to
                 establish a multicast distribution path from the MJN to
                 itself. The MJN selection method runs on the DR and has
                 a significant impact on the distribution of the
                 multicast tree, that directly affects the load
                 distribution in the network. However, the current MJN
                 selection method cannot effectively detect the load
                 status of the downlink multicast path in the case of
                 asymmetric routing, leading to network congestion and
                 limiting the number of multicast groups that the
                 network can accommodate (multicast capacity). To solve
                 this problem, we propose an MJN selection method based
                 on the reverse shortest path tree (RSPT). RSPT can
                 effectively detect the load status of downlink
                 multicast paths in case of routing asymmetry. Based on
                 the detection results of RSPT, DR can select the MJN
                 with the lowest path load to join the multicast tree.
                 Our experimental results indicate that compared to
                 existing multicast methods, our method has a lower cost
                 and delay, and can effectively balance the network load
                 in the case of asymmetric routing, increasing multicast
                 capacity by more than two times.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hernandez:2023:ADI,
  author =       "Luis Alberto Mart{\'\i}nez Hern{\'a}ndez and Ana
                 Lucila Sandoval Orozco and Luis Javier Garc{\'\i}a
                 Villalba",
  title =        "Analysis of Digital Information in Storage Devices
                 Using Supervised and Unsupervised Natural Language
                 Processing Techniques",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "155",
  day =          "23",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050155",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/155",
  abstract =     "Due to the advancement of technology, cybercrime has
                 increased considerably, making digital forensics
                 essential for any organisation. One of the most
                 critical challenges is to analyse and classify the
                 information on devices, identifying the relevant and
                 valuable data for a specific purpose. This phase of the
                 forensic process is one of the most complex and
                 time-consuming, and requires expert analysts to avoid
                 overlooking data relevant to the investigation.
                 Although tools exist today that can automate this
                 process, they will depend on how tightly their
                 parameters are tuned to the case study, and many lack
                 support for complex scenarios where language barriers
                 play an important role. Recent advances in machine
                 learning allow the creation of new architectures to
                 significantly increase the performance of information
                 analysis and perform the intelligent search process
                 automatically, reducing analysis time and identifying
                 relationships between files based on initial
                 parameters. In this paper, we present a bibliographic
                 review of artificial intelligence algorithms that allow
                 an exhaustive analysis of multimedia information
                 contained in removable devices in a forensic process,
                 using natural language processing and natural language
                 understanding techniques for the automatic
                 classification of documents in seized devices. Finally,
                 some of the open challenges technology developers face
                 when generating tools that use artificial intelligence
                 techniques to analyse the information contained in
                 documents on seized devices are reviewed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sada:2023:CAE,
  author =       "Abdelkarim {Ben Sada} and Abdenacer Naouri and Amar
                 Khelloufi and Sahraoui Dhelim and Huansheng Ning",
  title =        "A Context-Aware Edge Computing Framework for Smart
                 {Internet of Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "154",
  day =          "22",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050154",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/154",
  abstract =     "The data explosion caused by the rapid and widespread
                 use of IoT devices is placing tremendous pressure on
                 current communication, computing and storage resources.
                 In an ambient ubiquitous computing environment, taking
                 advantage of the context of the application scenario
                 can significantly improve the system performance of IoT
                 networks. Therefore, in this paper, we propose CONTESS,
                 a context-aware edge computing framework with selective
                 sensing that leverages the context information of the
                 sensed environment to improve its applicability to
                 smart IoT systems. CONTESS is composed of two parts:
                 context management, where context acquisition, modeling
                 and reasoning happens; and selective sensing, where
                 data selection happens. We demonstrate the capabilities
                 of CONTESS in the scenario of a parking management
                 system for a smart city environment. We implement
                 CONTESS using linked data and semantic web
                 technologies. We start by designing an OWL-based
                 ontology and then simulating the proposed scenario
                 using the OMNET++ network simulator along with the
                 Veins framework and SUMO traffic simulator. The results
                 show an improvement compared to traditional sensing
                 methods in both communication overhead and the
                 application results.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Papathanasiou:2023:MFP,
  author =       "Dimitris Papathanasiou and Konstantinos Demertzis and
                 Nikos Tziritas",
  title =        "Machine Failure Prediction Using Survival Analysis",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "5",
  pages =        "153",
  day =          "22",
  month =        apr,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15050153",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Jun 1 07:41:25 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/5/153",
  abstract =     "With the rapid growth of cloud computing and the
                 creation of large-scale systems such as IoT
                 environments, the failure of machines/devices and, by
                 extension, the systems that rely on them is a major
                 risk to their performance, usability, and the security
                 systems that support them. The need to predict such
                 anomalies in combination with the creation of
                 fault-tolerant systems to manage them is a key factor
                 for the development of safer and more stable systems.
                 In this work, a model consisting of survival analysis,
                 feature analysis/selection, and machine learning was
                 created, in order to predict machine failure. The
                 approach is based on the random survival forest model
                 and an architecture that aims to filter the features
                 that are of major importance to the cause of machine
                 failure. The objectives of this paper are to (1) Create
                 an efficient feature filtering mechanism, by combining
                 different methods of feature importance ranking, that
                 can remove the ``noise'' from the data and leave only
                 the relevant information. The filtering mechanism uses
                 the RadViz, COX, Rank2D, random survival forest feature
                 ranking, and recursive feature elimination, with each
                 of the methods used to achieve a different
                 understanding of the data. (2) Predict the machine
                 failure with a high degree of accuracy using the RSF
                 model, which is trained with optimal features. The
                 proposed method yields superior performance compared to
                 other similar models, with an impressive C-index
                 accuracy rate of approximately 97\%. The consistency of
                 the model's predictions makes it viable in large-scale
                 systems, where it can be used to improve the
                 performance and security of these systems while also
                 lowering their overall cost and longevity.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hurst:2023:DAM,
  author =       "William Hurst and Orestis Spyrou and Bedir
                 Tekinerdogan and Caspar Krampe",
  title =        "Digital Art and the Metaverse: Benefits and
                 Challenges",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "188--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060188",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/188",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Guidi:2023:NNR,
  author =       "Barbara Guidi and Andrea Michienzi",
  title =        "From {NFT 1.0} to {NFT 2.0}: a Review of the Evolution
                 of Non-Fungible Tokens",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "189--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060189",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/189",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Azeroual:2023:ESG,
  author =       "Otmane Azeroual and Renaud Fabre and Uta St{\"o}rl and
                 and Ruidong Qi",
  title =        "Elastic Stack and {GRAPHYP} Knowledge Graph of {Web}
                 Usage: a Win--Win Workflow for Semantic
                 Interoperability in Decision Making",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "190--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060190",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/190",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Patrickson:2023:DCD,
  author =       "Bronwin Patrickson and Mike Musker and Dan Thorpe and
                 Yasmin van Kasteren and Niranjan Bidargaddi",
  title =        "In-Depth Co-Design of Mental Health Monitoring
                 Technologies by People with Lived Experience",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "191--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060191",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/191",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Roumeliotis:2023:COA,
  author =       "Konstantinos I. Roumeliotis and Nikolaos D. Tselikas",
  title =        "{ChatGPT} and Open-{AI} Models: a Preliminary Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "192--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060192",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/192",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Majeed:2023:DLB,
  author =       "Abdul Majeed and Abdullah M. Alnajim and Athar Waseem
                 and Aleem Khaliq and Aqdas Naveed and Shabana Habib and
                 Muhammad Islam and Sheroz Khan",
  title =        "Deep Learning-Based Symptomizing Cyber Threats Using
                 Adaptive {5G} Shared Slice Security Approaches",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "193--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060193",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/193",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gao:2023:RDD,
  author =       "Han Gao and Zhangqin Huang and Xiaobo Zhang and
                 Huapeng Yang",
  title =        "Research and Design of a Decentralized
                 Edge-Computing-Assisted {LoRa} Gateway",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "194--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060194",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/194",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chen:2023:FCU,
  author =       "Renjie Chen and Nalini Ravishanker",
  title =        "Feature Construction Using Persistence Landscapes for
                 Clustering Noisy {IoT} Time Series",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "195--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060195",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/195",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wali:2023:TAI,
  author =       "Abdul Wali and Saipunidzam Mahamad and Suziah
                 Sulaiman",
  title =        "Task Automation Intelligent Agents: a Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "196--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060196",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/196",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhu:2023:HCW,
  author =       "Yiming Zhu and Dehua Zhou and Yuan Li and Beibei Song
                 and Chuansheng Wang",
  title =        "How Can We Achieve Query Keyword Frequency Analysis in
                 Privacy-Preserving Situations?",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "197--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060197",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/197",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Csirmaz:2023:SMF,
  author =       "Elod P. Csirmaz and Laszlo Csirmaz",
  title =        "Synchronizing Many Filesystems in Near Linear Time",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "198--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060198",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/198",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Musa:2023:DNN,
  author =       "Abubakar Ahmad Musa and Adamu Hussaini and Weixian
                 Liao and Fan Liang and Wei Yu",
  title =        "Deep Neural Networks for Spatial-Temporal
                 Cyber-Physical Systems: a Survey",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "199--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060199",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/199",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ismail:2023:SWS,
  author =       "Shereen Ismail and Diana W. Dawoud and Hassan Reza",
  title =        "Securing Wireless Sensor Networks Using Machine
                 Learning and Blockchain: a Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "200--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060200",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/200",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Pticek:2023:MAI,
  author =       "Martina Pticek and Jasminka Dobsa",
  title =        "Methods of Annotating and Identifying Metaphors in the
                 Field of Natural Language Processing",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "201--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060201",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/201",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Munoz:2023:PAD,
  author =       "Ernesto Cadena Mu{\~n}oz and Gustavo Chica Pedraza and
                 Rafael Cubillos-S{\'a}nchez and Alexander Aponte-Moreno
                 and M{\'o}nica Espinosa Buitrago",
  title =        "{PUE} Attack Detection by Using {DNN} and Entropy in
                 Cooperative Mobile Cognitive Radio Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "202--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060202",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/202",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{AlAsqah:2023:FLB,
  author =       "Muneerah {Al Asqah} and Tarek Moulahi",
  title =        "Federated Learning and Blockchain Integration for
                 Privacy Protection in the {Internet of Things}:
                 Challenges and Solutions",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "203--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060203",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/203",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ilie:2023:ADH,
  author =       "Dragos Ilie and H{\aa}kan Grahn and Lars Lundberg and
                 Alexander Westerhagen and Bo Granbom and Anders
                 H{\"o}{\"o}k",
  title =        "Avoiding Detection by Hostile Nodes in Airborne
                 Tactical Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "204--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060204",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/204",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Guo:2023:SSR,
  author =       "Yu Guo and Guigen Nie and Wenliang Gao and Mi Liao",
  title =        "{2D} Semantic Segmentation: Recent Developments and
                 Future Directions",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "205--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060205",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/205",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fic:2023:ADH,
  author =       "Pawe{\l} Fic and Adam Czornik and Piotr Rosikowski",
  title =        "Anomaly Detection for Hydraulic Power Units --- a Case
                 Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "206--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060206",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/206",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Pliatsios:2023:SSS,
  author =       "Antonios Pliatsios and Dimitrios Lymperis and Christos
                 Goumopoulos",
  title =        "{S2NetM}: a Semantic Social Network of Things
                 Middleware for Developing Smart and Collaborative
                 {IoT}-Based Solutions",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "207--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060207",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/207",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ahmed:2023:BSS,
  author =       "Khaled A. M. Ahmed and Sabry F. Saraya and John F.
                 Wanis and Amr M. T. Ali-Eldin",
  title =        "A Blockchain Self-Sovereign Identity for Open Banking
                 Secured by the {Customer}'s Banking Cards",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "208--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060208",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/208",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Xu:2023:DBM,
  author =       "Tongyang Xu and Yuan Liu and Zhaotai Ma and Yiqiang
                 Huang and Peng Liu",
  title =        "A {DQN}-Based Multi-Objective Participant Selection
                 for Efficient Federated Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "209--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060209",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/209",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Koirala:2023:EID,
  author =       "Ashish Koirala and Rabindra Bista and Joao C.
                 Ferreira",
  title =        "Enhancing {IoT} Device Security through Network Attack
                 Data Analysis Using Machine Learning Algorithms",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "210--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060210",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/210",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Pergantis:2023:SOA,
  author =       "Minas Pergantis and Iraklis Varlamis and Nikolaos
                 Grigorios Kanellopoulos and Andreas Giannakoulopoulos",
  title =        "Searching Online for Art and Culture: User Behavior
                 Analysis",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "211--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060211",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/211",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Si:2023:RBD,
  author =       "Honghao Si and Baoning Niu",
  title =        "Research on Blockchain Data Availability and Storage
                 Scalability",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "212--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060212",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/212",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bashir:2023:BBL,
  author =       "Syed Raza Bashir and Shaina Raza and Vojislav B.
                 Misic",
  title =        "{BERT4Loc}: {BERT} for Location-{POI} Recommender
                 System",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "213--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060213",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/213",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhu:2023:TAM,
  author =       "Jinting Zhu and Julian Jang-Jaccard and Amardeep Singh
                 and Paul A. Watters and Seyit Camtepe",
  title =        "Task-Aware Meta Learning-Based {Siamese} Neural
                 Network for Classifying Control Flow Obfuscated
                 Malware",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "214--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060214",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/214",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ou:2023:DCF,
  author =       "Yuanyou Ou and Baoning Niu",
  title =        "Dual-Channel Feature Enhanced Collaborative Filtering
                 Recommendation Algorithm",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "215--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060215",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/215",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sun:2023:MTA,
  author =       "Yiming Sun and Tatsuo Nakajima",
  title =        "Mitigating Technological Anxiety through the
                 Application of Natural Interaction in Mixed Reality
                 Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "216--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060216",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/216",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lehniger:2023:TWE,
  author =       "Kai Lehniger and Peter Langend{\"o}rfer",
  title =        "Through the Window: Exploitation and Countermeasures
                 of the {ESP32} Register Window Overflow",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "217--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060217",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/217",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gheyas:2023:OMD,
  author =       "Iffat Gheyas and Alessandro Raschella and Michael
                 Mackay",
  title =        "Optimal Meshing Degree Performance Analysis in a
                 {mmWave} {FWA} {5G} Network Deployment",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "218--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060218",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/218",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bushur:2023:NNE,
  author =       "Jacob Bushur and Chao Chen",
  title =        "Neural Network Exploration for Keyword Spotting on
                 Edge Devices",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "219--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060219",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/219",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Khan:2023:RDP,
  author =       "Imran Moez Khan and Andrew Thompson and Akram
                 Al-Hourani and Kandeepan Sithamparanathan and Wayne S.
                 T. Rowe",
  title =        "{RSSI} and Device Pose Fusion for Fingerprinting-Based
                 Indoor Smartphone Localization Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "6",
  pages =        "220--??",
  month =        jun,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15060220",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/6/220",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liotou:2023:CEA,
  author =       "Eirini Liotou and Dionysis Xenakis and Vasiliki
                 Georgara and Georgios Kourouniotis and Lazaros
                 Merakos",
  title =        "Cache-Enabled Adaptive Video Streaming: a {QoE}-Based
                 Evaluation Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "7",
  pages =        "221--??",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15070221",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/7/221",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yin:2023:BTT,
  author =       "Zhenzhong Yin and Bin Zhang",
  title =        "Bus Travel Time Prediction Based on the Similarity in
                 Drivers' Driving Styles",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "7",
  pages =        "222--??",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15070222",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/7/222",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Avanzato:2023:HDM,
  author =       "Roberta Avanzato and Francesco Beritelli and Alfio
                 Lombardo and Carmelo Ricci",
  title =        "Heart {DT}: Monitoring and Preventing Cardiac
                 Pathologies Using {AI} and {IoT} Sensors",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "7",
  pages =        "223--??",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15070223",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/7/223",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bocci:2023:SPC,
  author =       "Alessandro Bocci and Stefano Forti and Roberto
                 Guanciale and Gian-Luigi Ferrari and Antonio Brogi",
  title =        "Secure Partitioning of Cloud Applications, with Cost
                 Look-Ahead",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "7",
  pages =        "224--??",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15070224",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/7/224",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sone:2023:OST,
  author =       "Takuro Sone and Shin Kato and Ray Atarashi and Jin
                 Nakazato and Manabu Tsukada and Hiroshi Esaki",
  title =        "An Ontology for Spatio-Temporal Media Management and
                 an Interactive Application",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "7",
  pages =        "225--??",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15070225",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/7/225",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Haimed:2023:EMV,
  author =       "Ibrahim Bu Haimed and Marwan Albahar and Ali
                 Alzubaidi",
  title =        "Exploiting Misconfiguration Vulnerabilities in
                 {Microsoft}'s {Azure} Active Directory for Privilege
                 Escalation Attacks",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "7",
  pages =        "226--??",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15070226",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/7/226",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Villafuerte:2023:AIV,
  author =       "Naythan Villafuerte and Santiago Manzano and Paulina
                 Ayala and Marcelo V. Garc{\'\i}a",
  title =        "Artificial Intelligence in Virtual Telemedicine
                 Triage: a Respiratory Infection Diagnosis Tool with
                 Electronic Measuring Device",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "7",
  pages =        "227--??",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15070227",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/7/227",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{DellImmagine:2023:KDM,
  author =       "Giorgio Dell'Immagine and Jacopo Soldani and Antonio
                 Brogi",
  title =        "{KubeHound}: Detecting Microservices' Security Smells
                 in {Kubernetes} Deployments",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "7",
  pages =        "228--??",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15070228",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/7/228",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rudwan:2023:HFS,
  author =       "Mohammed Suleiman Mohammed Rudwan and Jean Vincent
                 Fonou-Dombeu",
  title =        "Hybridizing Fuzzy String Matching and Machine Learning
                 for Improved Ontology Alignment",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "7",
  pages =        "229--??",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15070229",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/string-matching.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/7/229",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Serina:2023:SAF,
  author =       "Lorenzo Serina and Luca Putelli and Alfonso Emilio
                 Gerevini and Ivan Serina",
  title =        "Synonyms, Antonyms and Factual Knowledge in {BERT}
                 Heads",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "7",
  pages =        "230--??",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15070230",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/7/230",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sufi:2023:NAB,
  author =       "Fahim Sufi",
  title =        "A New {AI}-Based Semantic Cyber Intelligence Agent",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "7",
  pages =        "231--??",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15070231",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/7/231",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Pinna:2023:ISA,
  author =       "Andrea Pinna and Maria Ilaria Lunesu and Stefano
                 Orr{\`u} and Roberto Tonelli",
  title =        "Investigation on Self-Admitted Technical Debt in
                 Open-Source Blockchain Projects",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "7",
  pages =        "232--??",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15070232",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/7/232",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Reis:2023:DCV,
  author =       "Manuel J. C. S. Reis",
  title =        "Developments of Computer Vision and Image Processing:
                 Methodologies and Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "7",
  pages =        "233--??",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15070233",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/7/233",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tang:2023:IVS,
  author =       "Xiangdong Tang and Fei Chen and Yunlong He",
  title =        "Intelligent Video Streaming at Network Edge: an
                 Attention-Based Multiagent Reinforcement Learning
                 Solution",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "7",
  pages =        "234--??",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15070234",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/7/234",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Karabila:2023:ECF,
  author =       "Ikram Karabila and Nossayba Darraz and Anas El-Ansari
                 and Nabil Alami and Mostafa {El Mallahi}",
  title =        "Enhancing Collaborative Filtering-Based Recommender
                 System Using Sentiment Analysis",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "7",
  pages =        "235--??",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15070235",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/7/235",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bagui:2023:UGE,
  author =       "Sikha S. Bagui and Dustin Mink and Subhash C. Bagui
                 and Michael Plain and Jadarius Hill and Marshall Elam",
  title =        "Using a Graph Engine to Visualize the Reconnaissance
                 Tactic of the {MITRE ATT\&CK} Framework from
                 {UWF-ZeekData22}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "7",
  pages =        "236--??",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15070236",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/7/236",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Battistoni:2023:CPS,
  author =       "Pietro Battistoni and Andrea Antonio Cantone and
                 Gerardo Martino and Valerio Passamano and Marco Romano
                 and Monica Sebillo and Giuliana Vitiello",
  title =        "A Cyber-Physical System for Wildfire Detection and
                 Firefighting",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "7",
  pages =        "237--??",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15070237",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/7/237",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Younes:2023:ADS,
  author =       "Maram Bani Younes",
  title =        "Assisting Drivers at Stop Signs in a Connected Vehicle
                 Environment",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "7",
  pages =        "238--??",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15070238",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/7/238",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Haralambous:2023:BSW,
  author =       "Yannis Haralambous and Philippe Lenca",
  title =        "Beyond the Semantic {Web}: Towards an Implicit
                 Pragmatic {Web} and a {Web} of Social Representations",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "7",
  pages =        "239--??",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15070239",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/7/239",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Cheng:2023:ATM,
  author =       "Bingbing Cheng and Jiao Wu",
  title =        "Acoustic {TDOA} Measurement and Accurate Indoor
                 Positioning for Smartphone",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "7",
  pages =        "240--??",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15070240",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/7/240",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mesbah:2023:AIS,
  author =       "Mohamed Mesbah and Mahmoud Said Elsayed and Anca Delia
                 Jurcut and Marianne Azer",
  title =        "Analysis of {ICS} and {SCADA} Systems Attacks Using
                 Honeypots",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "7",
  pages =        "241--??",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15070241",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/7/241",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Roka:2023:ODC,
  author =       "Rastislav R{\'o}ka",
  title =        "Optimization of the Decision Criterion for Increasing
                 the Bandwidth Utilization by Means of the Novel
                 Effective {DBA} Algorithm in {NG-PON2} Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "7",
  pages =        "242--??",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15070242",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/7/242",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{AlLail:2023:MLN,
  author =       "Mustafa {Al Lail} and Alejandro Garcia and Saul
                 Olivo",
  title =        "Machine Learning for Network Intrusion Detection --- a
                 Comparative Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "7",
  pages =        "243--??",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15070243",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/7/243",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Johnphill:2023:SHC,
  author =       "Obinna Johnphill and Ali Safaa Sadiq and Feras
                 Al-Obeidat and Haider Al-Khateeb and Mohammed Adam
                 Taheir and Omprakash Kaiwartya and Mohammed Ali",
  title =        "Self-Healing in Cyber-Physical Systems Using Machine
                 Learning: a Critical Analysis of Theories and Tools",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "7",
  pages =        "244--??",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15070244",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/7/244",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Phan:2023:ISM,
  author =       "Vu Hien Phan and Danh Phan Hong Pham and Tran Vu Pham
                 and Kashif Naseer Qureshi and Cuong Pham-Quoc",
  title =        "An {IoT} System and {MODIS} Images Enable Smart
                 Environmental Management for {Mekong Delta}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "7",
  pages =        "245--??",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15070245",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/7/245",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Aoyagi:2023:API,
  author =       "Shunji Aoyagi and Yuki Horie and Do Thi Thu Hien and
                 Thanh Duc Ngo and Duy-Dinh Le and Kien Nguyen and Hiroo
                 Sekiya",
  title =        "An Accurate Platform for Investigating {TCP}
                 Performance in {Wi-Fi} Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "7",
  pages =        "246--??",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15070246",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/7/246",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hu:2023:CMN,
  author =       "Yang Hu and Liangliang Gong and Xinyang Li and Hui Li
                 and Ruoxin Zhang and Rentao Gu",
  title =        "A Carrying Method for {5G} Network Slicing in Smart
                 Grid Communication Services Based on Neural Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "7",
  pages =        "247--??",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15070247",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/7/247",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bhurtel:2023:ULO,
  author =       "Manish Bhurtel and Danda B. Rawat",
  title =        "Unveiling the Landscape of Operating System
                 Vulnerabilities",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "7",
  pages =        "248--??",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15070248",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Aug 2 06:19:58 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/7/248",
  acknowledgement = ack-nhfb,
  fjournal =     "Future Internet",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Jadhav:2023:ITA,
  author =       "Hindavi Kishor Jadhav and Vinoth Babu Kumaravelu and
                 Arthi Murugadass and Agbotiname Lucky Imoize and
                 Poongundran Selvaprabhu and Arunkumar Chandrasekhar",
  title =        "Intelligent Transmit Antenna Selection Schemes for
                 High-Rate Fully Generalized Spatial Modulation",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "281",
  day =          "21",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080281",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/281",
  abstract =     "The sixth-generation (6G) network is supposed to
                 transmit significantly more data at much quicker rates
                 than existing networks while meeting severe energy
                 efficiency (EE) targets. The high-rate spatial
                 modulation (SM) methods can be used to deal with these
                 design metrics. SM uses transmit antenna selection
                 (TAS) practices to improve the EE of the network.
                 Although it is computationally intensive, free distance
                 optimized TAS (FD-TAS) is the best for performing the
                 average bit error rate (ABER). The present
                 investigation aims to examine the effectiveness of
                 various machine learning (ML)-assisted TAS practices,
                 such as support vector machine (SVM), na{\"\i}ve Bayes
                 (NB), K -nearest neighbor (KNN), and decision tree
                 (DT), to the small-scale multiple-input multiple-output
                 (MIMO)-based fully generalized spatial modulation
                 (FGSM) system. To the best of our knowledge, there is
                 no ML-based antenna selection schemes for high-rate
                 FGSM. SVM-based TAS schemes achieve {\sim}71.1\%
                 classification accuracy, outperforming all other
                 approaches. The ABER performance of each scheme is
                 evaluated using a higher constellation order, along
                 with various transmit antennas to achieve the target
                 ABER of {10$-$5}. By employing SVM for TAS, FGSM can
                 achieve a minimal gain of {\sim}2.2 dB over FGSM
                 without TAS (FGSM-NTAS). All TAS strategies based on ML
                 perform better than FGSM-NTAS.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Obonna:2023:DMM,
  author =       "Ugochukwu Onyekachi Obonna and Felix Kelechi Opara and
                 Christian Chidiebere Mbaocha and Jude-Kennedy Chibuzo
                 Obichere and Isdore Onyema Akwukwaegbu and Miriam
                 Mmesoma Amaefule and Cosmas Ifeanyi Nwakanma",
  title =        "Detection of Man-in-the-Middle ({MitM}) Cyber-Attacks
                 in Oil and Gas Process Control Networks Using Machine
                 Learning Algorithms",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "280",
  day =          "21",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080280",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/280",
  abstract =     "Recently, the process control network (PCN) of oil and
                 gas installation has been subjected to amorphous
                 cyber-attacks. Examples include the denial-of-service
                 (DoS), distributed denial-of-service (DDoS), and
                 man-in-the-middle (MitM) attacks, and this may have
                 largely been caused by the integration of open network
                 to operation technology (OT) as a result of low-cost
                 network expansion. The connection of OT to the internet
                 for firmware updates, third-party support, or the
                 intervention of vendors has exposed the industry to
                 attacks. The inability to detect these unpredictable
                 cyber-attacks exposes the PCN, and a successful attack
                 can lead to devastating effects. This paper reviews the
                 different forms of cyber-attacks in PCN of oil and gas
                 installations while proposing the use of machine
                 learning algorithms to monitor data exchanges between
                 the sensors, controllers, processes, and the final
                 control elements on the network to detect anomalies in
                 such data exchanges. Python 3.0 Libraries,
                 Deep-Learning Toolkit, MATLAB, and Allen Bradley
                 RSLogic 5000 PLC Emulator software were used in
                 simulating the process control. The outcomes of the
                 experiments show the reliability and functionality of
                 the different machine learning algorithms in detecting
                 these anomalies with significant precise attack
                 detections identified using tree algorithms (bagged or
                 coarse ) for man-in-the-middle (MitM) attacks while
                 taking note of accuracy-computation complexity
                 trade-offs.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Salam:2023:CBD,
  author =       "Abdu Salam and Qaisar Javaid and Masood Ahmad and
                 Ishtiaq Wahid and Muhammad Yeasir Arafat",
  title =        "Cluster-Based Data Aggregation in Flying Sensor
                 Networks Enabled {Internet of Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "279",
  day =          "20",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080279",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/279",
  abstract =     "Multiple unmanned aerial vehicles (UAVs) are organized
                 into clusters in a flying sensor network (FSNet) to
                 achieve scalability and prolong the network lifetime.
                 There are a variety of optimization schemes that can be
                 adapted to determine the cluster head (CH) and to form
                 stable and balanced clusters. Similarly, in FSNet,
                 duplicated data may be transmitted to the CHs when
                 multiple UAVs monitor activities in the vicinity where
                 an event of interest occurs. The communication of
                 duplicate data may consume more energy and bandwidth
                 than computation for data aggregation. This paper
                 proposes a honey-bee algorithm (HBA) to select the
                 optimal CH set and form stable and balanced clusters.
                 The modified HBA determines CHs based on the residual
                 energy, UAV degree, and relative mobility. To transmit
                 data, the UAV joins the nearest CH. The re-affiliation
                 rate decreases with the proposed stable clustering
                 procedure. Once the cluster is formed, ordinary UAVs
                 transmit data to their UAVs-CH. An aggregation method
                 based on dynamic programming is proposed to save energy
                 consumption and bandwidth. The data aggregation
                 procedure is applied at the cluster level to minimize
                 communication and save bandwidth and energy. Simulation
                 experiments validated the proposed scheme. The
                 simulation results are compared with recent
                 cluster-based data aggregation schemes. The results
                 show that our proposed scheme outperforms
                 state-of-the-art cluster-based data aggregation schemes
                 in FSNet.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mousa:2023:IDL,
  author =       "Amthal K. Mousa and Mohammed Najm Abdullah",
  title =        "An Improved Deep Learning Model for {DDoS} Detection
                 Based on Hybrid Stacked Autoencoder and Checkpoint
                 Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "278",
  day =          "19",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080278",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/278",
  abstract =     "The software defined network (SDN) collects network
                 traffic data and proactively manages networks. SDN's
                 programmability makes it excellent for developing
                 distributed applications, cybersecurity, and
                 decentralized network control in multitenant data
                 centers. This exceptional architecture is vulnerable to
                 security concerns, such as distributed denial of
                 service (DDoS) attacks. DDoS attacks can be very
                 serious due to the fact that they prevent authentic
                 users from accessing, temporarily or indefinitely,
                 resources they would normally expect to have. Moreover,
                 there are continuous efforts from attackers to produce
                 new techniques to avoid detection. Furthermore, many
                 existing DDoS detection methods now in use have a high
                 potential for producing false positives. This motivates
                 us to provide an overview of the research studies that
                 have already been conducted in this area and point out
                 the strengths and weaknesses of each of those
                 approaches. Hence, adopting an optimal detection method
                 is necessary to overcome these issues. Thus, it is
                 crucial to accurately detect abnormal flows to maintain
                 the availability and security of the network. In this
                 work, we propose hybrid deep learning algorithms, which
                 are the long short-term memory network (LSTM) and
                 convolutional neural network (CNN) with a stack
                 autoencoder for DDoS attack detection and checkpoint
                 network, which is a fault tolerance strategy for
                 long-running processes. The proposed approach is
                 trained and tested with the aid of two DDoS attack
                 datasets in the SDN environment: the DDoS attack SDN
                 dataset and Botnet dataset. The results show that the
                 proposed model achieves a very high accuracy, reaching
                 99.99\% in training, 99.92\% in validation, and 100\%
                 in precision, recall, and F1 score with the DDoS attack
                 SDN dataset. Also, it achieves 100\% in all metrics
                 with the Botnet dataset. Experimental results reveal
                 that our proposed model has a high feature extraction
                 ability and high performance in detecting attacks. All
                 performance metrics indicate that the proposed approach
                 is appropriate for a real-world flow detection
                 environment.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fragiadakis:2023:AML,
  author =       "George Fragiadakis and Evangelia Filiopoulou and
                 Christos Michalakelis and Thomas Kamalakis and Mara
                 Nikolaidou",
  title =        "Applying Machine Learning in Cloud Service Price
                 Prediction: The Case of {Amazon IaaS}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "277",
  day =          "19",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080277",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/277",
  abstract =     "When exploring alternative cloud solution designs, it
                 is important to also consider cost. Thus, having a
                 comprehensive view of the cloud market and future price
                 evolution allows well-informed decisions to choose
                 between alternatives. Cloud providers offer various
                 service types with different pricing policies.
                 Currently, infrastructure-as-a-Service (IaaS) is
                 considered the most mature cloud service, while
                 reserved instances, where virtual machines are reserved
                 for a fixed period of time, have the largest market
                 share. In this work, we employ a machine-learning
                 approach based on the CatBoost algorithm to explore a
                 price-prediction model for the reserve instance market.
                 The analysis is based on historical data provided by
                 Amazon Web Services from 2016 to 2022. Early results
                 demonstrate the machine-learning model's ability to
                 capture the underlying evolution patterns and predict
                 future trends. Findings suggest that prediction
                 accuracy is not improved by integrating data from older
                 time periods.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lymperis:2023:SPS,
  author =       "Dimitrios Lymperis and Christos Goumopoulos",
  title =        "{SEDIA}: A Platform for Semantically Enriched {IoT}
                 Data Integration and Development of Smart City
                 Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "276",
  day =          "18",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080276",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/276",
  abstract =     "The development of smart city applications often
                 encounters a variety of challenges. These include the
                 need to address complex requirements such as
                 integrating diverse data sources and incorporating
                 geographical data that reflect the physical urban
                 environment. Platforms designed for smart cities hold a
                 pivotal position in materializing these applications,
                 given that they offer a suite of high-level services,
                 which can be repurposed by developers. Although a
                 variety of platforms are available to aid the creation
                 of smart city applications, most fail to couple their
                 services with geographical data, do not offer the
                 ability to execute semantic queries on the available
                 data, and possess restrictions that could impede the
                 development process. This paper introduces SEDIA, a
                 platform for developing smart applications based on
                 diverse data sources, including geographical
                 information, to support a semantically enriched data
                 model for effective data analysis and integration. It
                 also discusses the efficacy of SEDIA in a
                 proof-of-concept smart city application related to air
                 quality monitoring. The platform utilizes ontology
                 classes and properties to semantically annotate
                 collected data, and the Neo4j graph database
                 facilitates the recognition of patterns and
                 relationships within the data. This research also
                 offers empirical data demonstrating the performance
                 evaluation of SEDIA. These contributions collectively
                 advance our understanding of semantically enriched data
                 integration within the realm of smart city
                 applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ray:2023:OWI,
  author =       "Partha Pratim Ray",
  title =        "An Overview of {WebAssembly} for {IoT}: Background,
                 Tools, State-of-the-Art, Challenges, and Future
                 Directions",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "275",
  day =          "18",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080275",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/275",
  abstract =     "This paper explores the relationship between two
                 emerging technologies, WebAssembly (Wasm) and the
                 Internet of Things (IoT). It examines the complementary
                 roles of these technologies and their impact on modern
                 web applications. First, it delves into the
                 capabilities of Wasm as a high-performance binary
                 format that allows developers to leverage low-level
                 languages for computationally intensive tasks. Second,
                 it seeks to explain why integration of IoT and Wasm is
                 important. Third, it discusses the strengths and
                 limitations of various tools and tool chains that are
                 crucial for Wasm development and implementation, with a
                 special focus on IoT. Fourth, it presents the
                 state-of-the-art with regard to advances that combine
                 both technologies. Fifth, it discusses key challenges
                 and provides future directions. Lastly, it provides an
                 in-depth elaboration of the future aspects of Wasm,
                 with a strong focus on IoT, concluding that IoT and
                 Wasm can provide developers with a versatile toolkit
                 that enables them to balance productivity and
                 performance in both web and non-web development
                 scenarios. The collaborative use of these technologies
                 opens up new possibilities for pushing the boundaries
                 of web application development in terms of
                 interactivity, security, portability, scalability, and
                 efficient computational capabilities. As web and
                 non-web embeddings continue to evolve, the integration
                 of IoT and Wasm will play a crucial role in shaping the
                 future of innovative application development. The key
                 findings of this extensive review work suggest that
                 existing tool sets can be easily conglomerated together
                 to form a new era in WebAssembly--IoT infrastructure
                 for low-power, energy-efficient, and secure edge--IoT
                 ecosystems with near-native execution speed.
                 Furthermore, the expansion of edge--IoT ecosystems can
                 be augmented with prospective cloud-side deployments.
                 However, there remains a strong need to more cohesively
                 advance the amalgamation of Wasm and IoT technologies
                 in the near future.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gonzalez:2023:LLV,
  author =       "Luis F. Gonzalez and Ivan Vidal and Francisco Valera
                 and Raul Martin and Dulce Artalejo",
  title =        "A Link-Layer Virtual Networking Solution for
                 Cloud-Native Network Function Virtualisation
                 Ecosystems: {L2S-M}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "274",
  day =          "17",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080274",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/274",
  abstract =     "Microservices have become promising candidates for the
                 deployment of network and vertical functions in the
                 fifth generation of mobile networks. However,
                 microservice platforms like Kubernetes use a flat
                 networking approach towards the connectivity of
                 virtualised workloads, which prevents the deployment of
                 network functions on isolated network segments (for
                 example, the components of an IP Telephony system or a
                 content distribution network). This paper presents
                 L2S-M, a solution that enables the connectivity of
                 Kubernetes microservices over isolated link-layer
                 virtual networks, regardless of the compute nodes where
                 workloads are actually deployed. L2S-M uses
                 software-defined networking (SDN) to fulfil this
                 purpose. Furthermore, the L2S-M design is flexible to
                 support the connectivity of Kubernetes workloads across
                 different Kubernetes clusters. We validate the
                 functional behaviour of our solution in a moderately
                 complex Smart Campus scenario, where L2S-M is used to
                 deploy a content distribution network, showing its
                 potential for the deployment of network services in
                 distributed and heterogeneous environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Coutinho:2023:EAD,
  author =       "Micael Coutinho and Jose A. Afonso and S{\'e}rgio F.
                 Lopes",
  title =        "An Efficient Adaptive Data-Link-Layer Architecture for
                 {LoRa} Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "273",
  day =          "17",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080273",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/273",
  abstract =     "LoRa is one of the most popular low-power wireless
                 network technologies for implementation of the Internet
                 of Things, with the advantage of providing long-range
                 communication, but lower data rates, when compared with
                 technologies such as Zigbee or Bluetooth. LoRa is a
                 single-channel physical layer technology on top of
                 which LoRaWAN implements a more complex multi-channel
                 network with enhanced functionalities, such as adaptive
                 data rate. However, LoRaWAN relies on expensive
                 hardware to support these functionalities. This paper
                 proposes a LoRa data-link-layer architecture based on a
                 multi-layer star network topology that adapts relevant
                 LoRa parameters for each end node dynamically taking
                 into account its link distance and quality in order to
                 balance communication range and energy consumption. The
                 developed solution is comprised of multiple components,
                 including a LoRa parameter calculator to help the user
                 to configure the network parameters, a contention-free
                 MAC protocol to avoid collisions, and an adaptive
                 spreading factor and transmission power mechanism.
                 These components work together to ensure a more
                 efficient use of the chosen ISM band and end node
                 resources, but with low-cost implementation and
                 operation requirements.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Stach:2023:SIS,
  author =       "Christoph Stach and Cl{\'e}mentine Gritti",
  title =        "Special Issue on Security and Privacy in Blockchains
                 and the {IoT} Volume {II}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "272",
  day =          "16",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080272",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/272",
  abstract =     "LoRa is one of the most popular low-power wireless
                 network technologies for implementation of the Internet
                 of Things, with the advantage of providing long-range
                 communication, but lower data rates, when compared with
                 technologies such as Zigbee or Bluetooth. LoRa is a
                 single-channel physical layer technology on top of
                 which LoRaWAN implements a more complex multi-channel
                 network with enhanced functionalities, such as adaptive
                 data rate. However, LoRaWAN relies on expensive
                 hardware to support these functionalities. This paper
                 proposes a LoRa data-link-layer architecture based on a
                 multi-layer star network topology that adapts relevant
                 LoRa parameters for each end node dynamically taking
                 into account its link distance and quality in order to
                 balance communication range and energy consumption. The
                 developed solution is comprised of multiple components,
                 including a LoRa parameter calculator to help the user
                 to configure the network parameters, a contention-free
                 MAC protocol to avoid collisions, and an adaptive
                 spreading factor and transmission power mechanism.
                 These components work together to ensure a more
                 efficient use of the chosen ISM band and end node
                 resources, but with low-cost implementation and
                 operation requirements.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rajawat:2023:QML,
  author =       "Anand Singh Rajawat and S. B. Goyal and Pradeep Bedi
                 and Tony Jan and Md Whaiduzzaman and Mukesh Prasad",
  title =        "Quantum Machine Learning for Security Assessment in
                 the {Internet of Medical Things (IoMT)}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "271",
  day =          "15",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080271",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/271",
  abstract =     "Internet of Medical Things (IoMT) is an ecosystem
                 composed of connected electronic items such as small
                 sensors/actuators and other cyber-physical devices
                 (CPDs) in medical services. When these devices are
                 linked together, they can support patients through
                 medical monitoring, analysis, and reporting in more
                 autonomous and intelligent ways. The IoMT devices;
                 however, often do not have sufficient computing
                 resources onboard for service and security assurance
                 while the medical services handle large quantities of
                 sensitive and private health-related data. This leads
                 to several research problems on how to improve security
                 in IoMT systems. This paper focuses on quantum machine
                 learning to assess security vulnerabilities in IoMT
                 systems. This paper provides a comprehensive review of
                 both traditional and quantum machine learning
                 techniques in IoMT vulnerability assessment. This paper
                 also proposes an innovative fused semi-supervised
                 learning model, which is compared to the
                 state-of-the-art traditional and quantum machine
                 learning in an extensive experiment. The experiment
                 shows the competitive performance of the proposed model
                 against the state-of-the-art models and also highlights
                 the usefulness of quantum machine learning in IoMT
                 security assessments and its future applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Askhedkar:2023:LCU,
  author =       "Anjali R. Askhedkar and Bharat S. Chaudhari and Maha
                 Abdelhaq and Raed Alsaqour and Rashid Saeed and Marco
                 Zennaro",
  title =        "{LoRa} Communication Using {TVWS} Frequencies: Range
                 and Data Rate",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "270",
  day =          "14",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080270",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/270",
  abstract =     "Low power wide area network (LPWAN) is a wireless
                 communication technology that offers large coverage,
                 low data rates, and low power consumption, making it a
                 suitable choice for the growing Internet of Things and
                 machine-to-machine communication applications. Long
                 range (LoRa), an LPWAN technology, has recently been
                 used in the industrial, scientific and medical (ISM)
                 band for various low-power wireless applications. The
                 coverage and data rate supported by these devices in
                 the ISM band is well-studied in the literature. In this
                 paper, we study the usage of TV white spaces (TVWS) for
                 LoRa transmissions to address the growing spectrum
                 demand. Additionally, the range and data rate of
                 TVWS-based LoRa, for different transmission parameter
                 values using different path-loss models and for various
                 scenarios such as free space, outdoor and indoor are
                 investigated. A path-loss model for TVWS-based LoRa is
                 also proposed and explored, and the evaluations show
                 that TVWS offers a longer range. This range and data
                 rate study would be useful for efficient network
                 planning and system design for TVWS-based LoRa
                 LPWANs.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Salah:2023:ENS,
  author =       "Zaher Salah and Esraa Abu Elsoud",
  title =        "Enhancing Network Security: A Machine Learning-Based
                 Approach for Detecting and Mitigating {Krack} and
                 {Kr00k} Attacks in {IEEE 802.11}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "269",
  day =          "14",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080269",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/269",
  abstract =     "The rise in internet users has brought with it the
                 impending threat of cybercrime as the Internet of
                 Things (IoT) increases and the introduction of 5G
                 technologies continues to transform our digital world.
                 It is now essential to protect communication networks
                 from illegal intrusions to guarantee data integrity and
                 user privacy. In this situation, machine learning
                 techniques used in data mining have proven to be
                 effective tools for constructing intrusion detection
                 systems (IDS) and improving their precision. We use the
                 well-known AWID3 dataset, a comprehensive collection of
                 wireless network traffic, to investigate the
                 effectiveness of machine learning in enhancing network
                 security. Our work primarily concentrates on Krack and
                 Kr00k attacks, which target the most recent and
                 dangerous flaws in IEEE 802.11 protocols. Through
                 diligent implementation, we were able to successfully
                 identify these threats using an IDS model that is based
                 on machine learning. Notably, the resilience of our
                 method was demonstrated by our ensemble classifier's
                 astounding 99\% success rate in detecting the Krack
                 attack. The effectiveness of our suggested remedy was
                 further demonstrated by the high accuracy rate of
                 96.7\% displayed by our neural network-based model in
                 recognizing instances of the Kr00k attack. Our research
                 shows the potential for considerably boosting network
                 security in the face of new threats by leveraging the
                 capabilities of machine learning and a diversified
                 dataset. Our findings open the door for stronger, more
                 proactive security measures to protect IEEE. 802.11
                 networks' integrity, resulting in a safer online
                 environment for all users.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Arici:2023:RWI,
  author =       "Nicola Arici and Alfonso Emilio Gerevini and Matteo
                 Olivato and Luca Putelli and Luca Sigalini and Ivan
                 Serina",
  title =        "Real-World Implementation and Integration of an
                 Automatic Scoring System for Workplace Safety Courses
                 in {Italian}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "268",
  day =          "12",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080268",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/268",
  abstract =     "Artificial Intelligence and Natural Language
                 Processing techniques can have a very significant
                 impact on the e-learning sector, with the introduction
                 of chatbots, automatic correctors, or scoring systems.
                 However, integrating such technologies into the
                 business environment in an effective way is not a
                 trivial operation, and it not only requires realising a
                 model with good predictive performance, but also it
                 requires the following: (i) a proper study of the task,
                 (ii) a data collection process, (iii) a real-world
                 evaluation of its utility. Moreover, it is also very
                 important to build an entire IT infrastructure that
                 connects the AI system with the company database, with
                 the human employees, the users, etc. In this work, we
                 present a real-world system, based on the
                 state-of-the-art BERT model, which implements an
                 automatic scoring system for open-ended questions
                 written in Italian. More specifically, these questions
                 pertain to the workplace safety courses which every
                 worker must attend by law, often via e-learning
                 platforms such as the one offered by Mega Italia Media.
                 This article describes how our system has been
                 designed, evaluated, and finally deployed for
                 commercial use with complete integration with the other
                 services provided by the company.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rajaei:2023:SPD,
  author =       "Mohammad Javad Rajaei and Qusay H. Mahmoud",
  title =        "A Survey on Pump and Dump Detection in the
                 Cryptocurrency Market Using Machine Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "267",
  day =          "11",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080267",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/267",
  abstract =     "The popularity of cryptocurrencies has skyrocketed in
                 recent years, with blockchain technologies enabling the
                 development of new digital assets. However, along with
                 their advantages, such as lower transaction costs,
                 increased security, and transactional transparency,
                 cryptocurrencies have also become susceptible to
                 various forms of market manipulation. The pump and dump
                 (P\&D) scheme is of significant concern among these
                 manipulation tactics. Despite the growing awareness of
                 P\&D activities in cryptocurrency markets, a
                 comprehensive survey is needed to explore the detection
                 methods. This paper aims to fill this gap by reviewing
                 the literature on P\&D detection in the cryptocurrency
                 world. This survey provides valuable insights into
                 detecting and classifying P\&D schemes in the
                 cryptocurrency market by analyzing the selected
                 studies, including their definitions and the taxonomies
                 of P\&D schemes, the methodologies employed, their
                 strengths and weaknesses, and the proposed solutions.
                 Presented here are insights that can guide future
                 research in this field and offer practical approaches
                 to combating P\&D manipulations in cryptocurrency
                 trading.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Iqbal:2023:ESC,
  author =       "Asad Iqbal and Muhammad Zubair and Muhammad Asghar
                 Khan and Insaf Ullah and Ghani Ur-Rehman and Alexey V.
                 Shvetsov and Fazal Noor",
  title =        "An Efficient and Secure Certificateless Aggregate
                 Signature Scheme for Vehicular Ad hoc Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "266",
  day =          "10",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080266",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/266",
  abstract =     "Vehicular ad hoc networks (VANETs) have become an
                 essential part of the intelligent transportation system
                 because they provide secure communication among
                 vehicles, enhance vehicle safety, and improve the
                 driving experience. However, due to the openness and
                 vulnerability of wireless networks, the participating
                 vehicles in a VANET system are prone to a variety of
                 cyberattacks. To secure the privacy of vehicles and
                 assure the authenticity, integrity, and nonrepudiation
                 of messages, numerous signature schemes have been
                 employed in the literature on VANETs. The majority of
                 these solutions, however, are either not fully secured
                 or entail high computational costs. To address the
                 above issues and to enable secure communication between
                 the vehicle and the roadside unit (RSU), we propose a
                 certificateless aggregate signature (CLAS) scheme based
                 on hyperelliptic curve cryptography (HECC). This scheme
                 enables participating vehicles to share their
                 identities with trusted authorities via an open
                 wireless channel without revealing their identities to
                 unauthorized participants. Another advantage of this
                 approach is its capacity to release the partial private
                 key to participating devices via an open wireless
                 channel while keeping its identity secret from any
                 other third parties. A provable security analysis
                 through the random oracle model (ROM), which relies on
                 the hyperelliptic curve discrete logarithm problem, is
                 performed, and we have proven that the proposed scheme
                 is unforgeable against Type 1 ( FGR1 ) and Type 2 (
                 FGR2 ) forgers. The proposed scheme is compared with
                 relevant schemes in terms of computational cost and
                 communication overhead, and the results demonstrate
                 that the proposed scheme is more efficient than the
                 existing schemes in maintaining high-security levels.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mukasine:2023:CAM,
  author =       "Angelique Mukasine and Louis Sibomana and Kayalvizhi
                 Jayavel and Kizito Nkurikiyeyezu and Eric Hitimana",
  title =        "Correlation Analysis Model of Environment Parameters
                 Using {IoT} Framework in a Biogas Energy Generation
                 Context",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "265",
  day =          "09",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080265",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/265",
  abstract =     "Recently, the significance and demand for biogas
                 energy has dramatically increased. However, biogas
                 operators lack automated and intelligent mechanisms to
                 produce optimization. The Internet of Things (IoT) and
                 Machine Learning (ML) have become key enablers for the
                 real-time monitoring of biogas production environments.
                 This paper aimed to implement an IoT framework to
                 gather environmental parameters for biogas generation.
                 In addition, data analysis was performed to assess the
                 effect of environmental parameters on biogas
                 production. The edge-based computing architecture was
                 designed comprising sensors, microcontrollers,
                 actuators, and data acquired for the cloud Mongo
                 database via MQTT protocol. Data were captured at a
                 home digester on a time-series basis for 30 days.
                 Further, Pearson distribution and multiple linear
                 regression models were explored to evaluate
                 environmental parameter effects on biogas production.
                 The constructed regression model was evaluated using R
                 2 metrics, and this was found to be 73.4\% of the
                 variability. From a correlation perspective, the
                 experimental result shows a strong correlation of
                 biogas production with an indoor temperature of 0.78
                 and a pH of 0.6. On the other hand, outdoor temperature
                 presented a moderated correlation of 0.4. This implies
                 that the model had a relatively good fit and could
                 effectively predict the biogas production process.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{GomezRomero-Borquez:2023:MEA,
  author =       "Jesus GomezRomero-Borquez and J. Alberto {Del
                 Puerto-Flores} and Carolina Del-Valle-Soto",
  title =        "Mapping {EEG} Alpha Activity: Assessing Concentration
                 Levels during Player Experience in Virtual Reality
                 Video Games",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "264",
  day =          "09",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080264",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/264",
  abstract =     "This work presents a study in which the cognitive
                 concentration levels of participants were evaluated
                 using electroencephalogram (EEG) measures while they
                 were playing three different categories of virtual
                 reality (VR) video games: Challenging Puzzlers, Casual
                 Games, and Exergames. Thirty-one voluntary participants
                 between the ages of 17 and 35 were recruited. EEG data
                 were processed to analyze the brain's electrical
                 activity in the alpha band. The values of power
                 spectral density (PSD) and individual alpha frequency
                 (IAF) of each participant were compared to detect
                 changes that could indicate a state of concentration.
                 Additionally, frontal alpha asymmetry (FAA) between the
                 left and right hemispheres of the brain was compared.
                 The results showed that the Exergame category of video
                 games elicited higher average cognitive concentration
                 in players, as indicated by the IAF and FAA values.
                 These findings contribute to understanding the
                 cognitive effects of VR video games and their
                 implications for designing and developing VR
                 experiences to enhance cognitive abilities.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{AlJawarneh:2023:EIH,
  author =       "Isam Mashhour {Al Jawarneh} and Luca Foschini and
                 Paolo Bellavista",
  title =        "Efficient Integration of Heterogeneous
                 Mobility-Pollution Big Data for Joint Analytics at
                 Scale with {QoS} Guarantees",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "263",
  day =          "07",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080263",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/263",
  abstract =     "Numerous real-life smart city application scenarios
                 require joint analytics on unified views of
                 georeferenced mobility data with environment contextual
                 data including pollution and meteorological data.
                 particularly, future urban planning requires
                 restricting vehicle access to specific areas of a city
                 to reduce the adverse effect of their engine combustion
                 emissions on the health of dwellers and cyclers.
                 Current editions of big spatial data management systems
                 do not come with over-the-counter support for similar
                 scenarios. To close this gap, in this paper, we show
                 the design and prototyping of a novel system we term as
                 EMDI for the enrichment of human and vehicle mobility
                 data with pollution information, thus enabling
                 integrated analytics on a unified view. Our system
                 supports a variety of queries including single
                 geo-statistics, such as `mean', and Top-N queries, in
                 addition to geo-visualization on the combined view. We
                 have tested our system with real big georeferenced
                 mobility and environmental data coming from the city of
                 Bologna in Italy. Our testing results show that our
                 system can be efficiently utilized for advanced
                 combined pollution-mobility analytics at a scale with
                 QoS guarantees. Specifically, a reduction in latency
                 that equals roughly 65\%, on average, is obtained by
                 using EMDI as opposed to the plain baseline, we also
                 obtain statistically significant accuracy results for
                 Top-N queries ranging roughly from 0.84 to 1 for both
                 Spearman and Pearson correlation coefficients depending
                 on the geo-encoding configurations, in addition to
                 significant single geo-statistics accuracy values
                 expressed using Mean Absolute Percentage Error on the
                 range from 0.00392 to 0.000195.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Al-Zubaidie:2023:ADL,
  author =       "Mishall Al-Zubaidie and Ghanima Sabr Shyaa",
  title =        "Applying Detection Leakage on Hybrid Cryptography to
                 Secure Transaction Information in E-Commerce Apps",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "262",
  day =          "01",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080262",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/262",
  abstract =     "Technology advancements have driven a boost in
                 electronic commerce use in the present day due to an
                 increase in demand processes, regardless of whether
                 goods, products, services, or payments are being bought
                 or sold. Various goods are purchased and sold online by
                 merchants ( M )s for large amounts of money.
                 Nonetheless, during the transmission of information via
                 electronic commerce, M s' information may be
                 compromised or attacked. In order to enhance the
                 security of e-commerce transaction data, particularly
                 sensitive M information, we have devised a protocol
                 that combines the Fernet (FER) algorithm with the
                 ElGamal (ELG) algorithm. Additionally, we have
                 integrated data leakage detection (DLD) technology to
                 verify the integrity of keys, encryptions, and
                 decryptions. The integration of these algorithms
                 ensures that electronic-commerce transactions are both
                 highly secure and efficiently processed. Our analysis
                 of the protocol's security and performance indicates
                 that it outperforms the algorithms used in previous
                 studies, providing superior levels of security and
                 performance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Nikolaidis:2023:TER,
  author =       "Fotis Nikolaidis and Moysis Symeonides and Demetris
                 Trihinas",
  title =        "Towards Efficient Resource Allocation for Federated
                 Learning in Virtualized Managed Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "261",
  day =          "31",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080261",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/261",
  abstract =     "Federated learning (FL) is a transformative approach
                 to Machine Learning that enables the training of a
                 shared model without transferring private data to a
                 central location. This decentralized training paradigm
                 has found particular applicability in edge computing,
                 where IoT devices and edge nodes often possess limited
                 computational power, network bandwidth, and energy
                 resources. While various techniques have been developed
                 to optimize the FL training process, an important
                 question remains unanswered: how should resources be
                 allocated in the training workflow? To address this
                 question, it is crucial to understand the nature of
                 these resources. In physical environments, the
                 allocation is typically performed at the node level,
                 with the entire node dedicated to executing a single
                 workload. In contrast, virtualized environments allow
                 for the dynamic partitioning of a node into
                 containerized units that can adapt to changing
                 workloads. Consequently, the new question that arises
                 is: how can a physical node be partitioned into virtual
                 resources to maximize the efficiency of the FL process?
                 To answer this, we investigate various resource
                 allocation methods that consider factors such as
                 computational and network capabilities, the complexity
                 of datasets, as well as the specific characteristics of
                 the FL workflow and ML backend. We explore two
                 scenarios: (i) running FL over a finite number of
                 testbed nodes and (ii) hosting multiple parallel FL
                 workflows on the same set of testbed nodes. Our
                 findings reveal that the default configurations of
                 state-of-the-art cloud orchestrators are sub-optimal
                 when orchestrating FL workflows. Additionally, we
                 demonstrate that different libraries and ML models
                 exhibit diverse computational footprints. Building upon
                 these insights, we discuss methods to mitigate
                 computational interferences and enhance the overall
                 performance of the FL pipeline execution.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bandi:2023:PGA,
  author =       "Ajay Bandi and Pydi Venkata Satya Ramesh Adapa and
                 Yudu Eswar Vinay Pratap Kumar Kuchi",
  title =        "The Power of Generative {AI}: A Review of
                 Requirements, Models, Input--Output Formats, Evaluation
                 Metrics, and Challenges",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "260",
  day =          "31",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080260",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/260",
  abstract =     "Generative artificial intelligence (AI) has emerged as
                 a powerful technology with numerous applications in
                 various domains. There is a need to identify the
                 requirements and evaluation metrics for generative AI
                 models designed for specific tasks. The purpose of the
                 research aims to investigate the fundamental aspects of
                 generative AI systems, including their requirements,
                 models, input--output formats, and evaluation metrics.
                 The study addresses key research questions and presents
                 comprehensive insights to guide researchers,
                 developers, and practitioners in the field. Firstly,
                 the requirements necessary for implementing generative
                 AI systems are examined and categorized into three
                 distinct categories: hardware, software, and user
                 experience. Furthermore, the study explores the
                 different types of generative AI models described in
                 the literature by presenting a taxonomy based on
                 architectural characteristics, such as variational
                 autoencoders (VAEs), generative adversarial networks
                 (GANs), diffusion models, transformers, language
                 models, normalizing flow models, and hybrid models. A
                 comprehensive classification of input and output
                 formats used in generative AI systems is also provided.
                 Moreover, the research proposes a classification system
                 based on output types and discusses commonly used
                 evaluation metrics in generative AI. The findings
                 contribute to advancements in the field, enabling
                 researchers, developers, and practitioners to
                 effectively implement and evaluate generative AI models
                 for various applications. The significance of the
                 research lies in understanding that generative AI
                 system requirements are crucial for effective planning,
                 design, and optimal performance. A taxonomy of models
                 aids in selecting suitable options and driving
                 advancements. Classifying input--output formats enables
                 leveraging diverse formats for customized systems,
                 while evaluation metrics establish standardized methods
                 to assess model quality and performance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Jain:2023:VGB,
  author =       "Shushant Kumar Jain and Rinkoo Bhatia and Neeraj
                 Shrivastava and Sharad Salunke and Mohammad Farukh
                 Hashmi and Neeraj Dhanraj Bokde",
  title =        "Virtual Grid-Based Routing for Query-Driven Wireless
                 Sensor Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "259",
  day =          "30",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080259",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/259",
  abstract =     "In the context of query-driven wireless sensor
                 networks (WSNs), a unique scenario arises where sensor
                 nodes are solicited by a base station, also known as a
                 sink, based on specific areas of interest (AoIs). Upon
                 receiving a query, designated sensor nodes are tasked
                 with transmitting their data to the sink. However, the
                 routing of these queries from the sink to the sensor
                 nodes becomes intricate when the sink is mobile. The
                 sink's movement after issuing a query can potentially
                 disrupt the performance of data delivery. To address
                 these challenges, we have proposed an innovative
                 approach called Query-driven Virtual Grid-based Routing
                 Protocol (VGRQ), aiming to enhance energy efficiency
                 and reduce data delivery delays. In VGRQ, we construct
                 a grid consisting of square-shaped virtual cells, with
                 the number of cells matching the count of sensor nodes.
                 Each cell designates a specific node as the cell header
                 (CH), and these CHs establish connections with each
                 other to form a chain-like structure. This chain serves
                 two primary purposes: sharing the mobile sink's
                 location information and facilitating the transmission
                 of queries to the AoI as well as data to the sink. By
                 employing the VGRQ approach, we seek to optimize the
                 performance of query-driven WSNs. It enhances energy
                 utilization and reduces data delivery delays.
                 Additionally, VGRQ results in {\SGMLasymp}10\% and
                 {\SGMLasymp}27\% improvement in energy consumption when
                 compared with QRRP and QDVGDD, respectively.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Jamroz:2023:OAS,
  author =       "Zainab Jamroz and Insaf Ullah and Bilal Hassan and
                 Noor Ul Amin and Muhammad Asghar Khan and Pascal Lorenz
                 and Nisreen Innab",
  title =        "An Optimal Authentication Scheme through Dual
                 Signature for the {Internet of Medical Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "258",
  day =          "30",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080258",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/258",
  abstract =     "The Internet of Medical Things (IoMT) overcomes the
                 flaws in the traditional healthcare system by enabling
                 remote administration, more effective use of resources,
                 and the mobility of medical devices to fulfil the
                 patient's needs. The IoMT makes it simple to review the
                 patient's cloud-based medical history in addition to
                 allowing the doctor to keep a close eye on the
                 patient's condition. However, any communication must be
                 secure and dependable due to the private nature of
                 patient medical records. In this paper, we proposed an
                 authentication method for the IoMT based on
                 hyperelliptic curves and featuring dual signatures. The
                 decreased key size of hyperelliptic curves makes the
                 proposed scheme efficient. Furthermore, security
                 validation analysis is performed with the help of the
                 formal verification tool called Scyther, which shows
                 that the proposed scheme is secure against several
                 types of attacks. A comparison of the proposed scheme's
                 computational and communication expenses with those of
                 existing schemes reveals its efficiency.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Adibi:2023:MFA,
  author =       "Sasan Adibi",
  title =        "The {mPOC} Framework: An Autonomous Outbreak
                 Prediction and Monitoring Platform Based on Wearable
                 {IoMT} Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "257",
  day =          "30",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080257",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/257",
  abstract =     "This paper presents the mHealth Predictive Outbreak
                 for COVID-19 (mPOC) framework, an autonomous platform
                 based on wearable Internet of Medical Things (IoMT)
                 devices for outbreak prediction and monitoring. It
                 utilizes real-time physiological and environmental data
                 to assess user risk. The framework incorporates the
                 analysis of psychological and user-centric data,
                 adopting a combination of top-down and bottom-up
                 approaches. The mPOC mechanism utilizes the
                 bidirectional Mobile Health (mHealth) Disaster Recovery
                 System (mDRS) and employs an intelligent algorithm to
                 calculate the Predictive Exposure Index (PEI) and
                 Deterioration Risk Index (DRI). These indices trigger
                 warnings to users based on adaptive threshold criteria
                 and provide updates to the Outbreak Tracking Center
                 (OTC). This paper provides a comprehensive description
                 and analysis of the framework's mechanisms and
                 algorithms, complemented by the performance accuracy
                 evaluation. By leveraging wearable IoMT devices, the
                 mPOC framework showcases its potential in disease
                 prevention and control during pandemics, offering
                 timely alerts and vital information to healthcare
                 professionals and individuals to mitigate outbreaks'
                 impact.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2023:FSR,
  author =       "Jinying Li and Ananda Maiti and Jiangang Fei",
  title =        "Features and Scope of Regulatory Technologies:
                 Challenges and Opportunities with {Industrial Internet
                 of Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "256",
  day =          "30",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080256",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/256",
  abstract =     "Regulatory Technology (RegTech) is an emerging set of
                 computing and network-based information systems and
                 practices intended to enhance and improve regulatory
                 compliance processes. Such technologies rely on
                 collecting exclusive information from the environment
                 and humans through automated Internet of Things (IoT)
                 sensors and self-reported data. The key enablers of
                 RegTech are the increased capabilities and reduced cost
                 of IoT and Artificial Intelligence (AI) technologies.
                 This article focuses on a survey of RegTech,
                 highlighting the recent developments in various
                 sectors. This work identifies the characteristics of
                 existing implementations of RegTech applications in the
                 financial industry. It examines the critical features
                 that non-financial industries such as agriculture must
                 address when using such technologies. We investigate
                 the suitability of existing technologies applied in
                 financial sectors to other industries and the potential
                 gaps to be filled between them in terms of designing
                 information systems for regulatory frameworks. This
                 includes identifying specific operational parameters
                 that are key differences between the financial and
                 non-financial sectors that can be supported with IoT
                 and AI technologies. These can be used by both
                 producers of goods and services and regulators who need
                 an affordable and efficient supervision method for
                 managing relevant organizations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kontopoulou:2023:RAV,
  author =       "Vaia I. Kontopoulou and Athanasios D. Panagopoulos and
                 Ioannis Kakkos and George K. Matsopoulos",
  title =        "A Review of {ARIMA} vs. Machine Learning Approaches
                 for Time Series Forecasting in Data Driven Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "255",
  day =          "30",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080255",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/255",
  abstract =     "In the broad scientific field of time series
                 forecasting, the ARIMA models and their variants have
                 been widely applied for half a century now due to their
                 mathematical simplicity and flexibility in application.
                 However, with the recent advances in the development
                 and efficient deployment of artificial intelligence
                 models and techniques, the view is rapidly changing,
                 with a shift towards machine and deep learning
                 approaches becoming apparent, even without a complete
                 evaluation of the superiority of the new approach over
                 the classic statistical algorithms. Our work
                 constitutes an extensive review of the published
                 scientific literature regarding the comparison of ARIMA
                 and machine learning algorithms applied to time series
                 forecasting problems, as well as the combination of
                 these two approaches in hybrid statistical-AI models in
                 a wide variety of data applications (finance, health,
                 weather, utilities, and network traffic prediction).
                 Our review has shown that the AI algorithms display
                 better prediction performance in most applications,
                 with a few notable exceptions analyzed in our
                 Discussion and Conclusions sections, while the hybrid
                 statistical-AI models steadily outperform their
                 individual parts, utilizing the best algorithmic
                 features of both worlds.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Patsias:2023:TAM,
  author =       "Vasilios Patsias and Petros Amanatidis and Dimitris
                 Karampatzakis and Thomas Lagkas and Kalliopi
                 Michalakopoulou and Alexandros Nikitas",
  title =        "Task Allocation Methods and Optimization Techniques in
                 Edge Computing: A Systematic Review of the Literature",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "254",
  day =          "28",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080254",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/254",
  abstract =     "Task allocation in edge computing refers to the
                 process of distributing tasks among the various nodes
                 in an edge computing network. The main challenges in
                 task allocation include determining the optimal
                 location for each task based on the requirements such
                 as processing power, storage, and network bandwidth,
                 and adapting to the dynamic nature of the network.
                 Different approaches for task allocation include
                 centralized, decentralized, hybrid, and machine
                 learning algorithms. Each approach has its strengths
                 and weaknesses and the choice of approach will depend
                 on the specific requirements of the application. In
                 more detail, the selection of the most optimal task
                 allocation methods depends on the edge computing
                 architecture and configuration type, like mobile edge
                 computing (MEC), cloud-edge, fog computing,
                 peer-to-peer edge computing, etc. Thus, task allocation
                 in edge computing is a complex, diverse, and
                 challenging problem that requires a balance of
                 trade-offs between multiple conflicting objectives such
                 as energy efficiency, data privacy, security, latency,
                 and quality of service (QoS). Recently, an increased
                 number of research studies have emerged regarding the
                 performance evaluation and optimization of task
                 allocation on edge devices. While several survey
                 articles have described the current state-of-the-art
                 task allocation methods, this work focuses on comparing
                 and contrasting different task allocation methods,
                 optimization algorithms, as well as the network types
                 that are most frequently used in edge computing
                 systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Simon:2023:CAH,
  author =       "Marek Simon and Ladislav Huraj and Nicolas B{\'u}cik",
  title =        "A Comparative Analysis of High Availability for
                 {Linux} Container Infrastructures",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "253",
  day =          "28",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080253",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/linux.bib;
                 https://www.math.utah.edu/pub/tex/bib/unix.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/253",
  abstract =     "In the current era of prevailing information
                 technology, the requirement for high availability and
                 reliability of various types of services is critical.
                 This paper focusses on the comparison and analysis of
                 different high-availability solutions for Linux
                 container environments. The objective was to identify
                 the strengths and weaknesses of each solution and to
                 determine the optimal container approach for common use
                 cases. Through a series of structured experiments,
                 basic performance metrics were collected, including
                 average service recovery time, average transfer rate,
                 and total number of failed calls. The container
                 platforms tested included Docker, Kubernetes, and
                 Proxmox. On the basis of a comprehensive evaluation, it
                 can be concluded that Docker with Docker Swarm is
                 generally the most effective high-availability solution
                 for commonly used Linux containers. Nevertheless, there
                 are specific scenarios in which Proxmox stands out, for
                 example, when fast data transfer is a priority or when
                 load balancing is not a critical requirement.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Jamshidi:2023:MMI,
  author =       "Mohammad (Behdad) Jamshidi and Arash Dehghaniyan Serej
                 and Alireza Jamshidi and Omid Moztarzadeh",
  title =        "The Meta-Metaverse: Ideation and Future Directions",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "8",
  pages =        "252",
  day =          "27",
  month =        jul,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15080252",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Aug 26 11:22:50 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/8/252",
  abstract =     "In the era of digitalization and artificial
                 intelligence (AI), the utilization of Metaverse
                 technology has become increasingly crucial. As the
                 world becomes more digitized, there is a pressing need
                 to effectively transfer real-world assets into the
                 digital realm and establish meaningful relationships
                 between them. However, existing approaches have shown
                 significant limitations in achieving this goal
                 comprehensively. To address this, this research
                 introduces an innovative methodology called the
                 Meta-Metaverse, which aims to enhance the immersive
                 experience and create realistic digital twins across
                 various domains such as biology, genetics, economy,
                 medicine, environment, gaming, digital twins, Internet
                 of Things, artificial intelligence, machine learning,
                 psychology, supply chain, social networking, smart
                 manufacturing, and politics. The multi-layered
                 structure of Metaverse platforms and digital twins
                 allows for greater flexibility and scalability,
                 offering valuable insights into the potential impact of
                 advancing science, technology, and the internet. This
                 article presents a detailed description of the proposed
                 methodology and its applications, highlighting its
                 potential to transform scientific research and inspire
                 groundbreaking ideas in science, medicine, and
                 technology.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Arachchige:2023:EBN,
  author =       "Kithmini Godewatte Arachchige and Philip Branch and
                 and Jason But",
  title =        "Evaluation of Blockchain Networks' Scalability
                 Limitations in Low-Powered {Internet of Things} ({IoT})
                 Sensor Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "317",
  day =          "21",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090317",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/317",
  abstract =     "With the development of Internet of Things (IoT)
                 technologies, industries such as healthcare have
                 started using low-powered sensor-based devices. Because
                 IoT devices are typically low-powered, they are
                 susceptible to cyber intrusions. As an emerging
                 information security solution, blockchain technology
                 has considerable potential for protecting low-powered
                 IoT end devices. Blockchain technology provides
                 promising security features such as cryptography, hash
                 functions, time stamps, and a distributed ledger
                 function. Therefore, blockchain technology can be a
                 robust security technology for securing IoT low-powered
                 devices. However, the integration of blockchain and IoT
                 technologies raises a number of research questions.
                 Scalability is one of the most significant. Blockchain'
                 scalability of low-powered sensor networks needs to be
                 evaluated to identify the practical application of both
                 technologies in low-powered sensor networks. In this
                 paper, we analyse the scalability limitations of three
                 commonly used blockchain algorithms running on
                 low-powered single-board computers communicating in a
                 wireless sensor network. We assess the scalability
                 limitations of three blockchain networks as we increase
                 the number of nodes. Our analysis shows considerable
                 scalability variations between three blockchain
                 networks. The results indicate that some blockchain
                 networks can have over 800 ms network latency and some
                 blockchain networks may use a bandwidth over 1600 Kbps.
                 This work will contribute to developing efficient
                 blockchain-based IoT sensor networks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ozadowicz:2023:TQE,
  author =       "Andrzej Ozadowicz",
  title =        "Technical, Qualitative and Energy Analysis of Wireless
                 Control Modules for Distributed Smart Home Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "316",
  day =          "20",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090316",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/316",
  abstract =     "Distributed smart home systems using wireless
                 communication are increasingly installed and operated
                 in households. Their popularity is due to the ease of
                 installation and configuration. This paper presents a
                 comprehensive technical, quality, and energy analysis
                 of several popular smart home modules. Specifically, it
                 focuses on verifying their power consumption levels,
                 both in standby and active mode, to assess their impact
                 on the energy efficiency of building installations.
                 This is an important aspect in the context of their
                 continuous operation, as well as in relation to the
                 relatively lower power of loads popular in buildings,
                 such as LED lighting. The author presents the results
                 of measurements carried out for seven different smart
                 home modules controlling seven different types of
                 loads. The analysis of the results shows a significant
                 share of home automation modules in the energy balance;
                 in particular, the appearance of reactive power
                 consumption due to the installation of smart home
                 modules is noteworthy. Bearing in mind all the threads
                 of the analysis and discussion of the results of
                 measurement experiments, a short SWOT analysis is
                 presented, with an indication of important issues in
                 the context of further development of smart systems and
                 the Internet of Things with wireless communication
                 interfaces, dedicated to home and building
                 applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Saffre:2023:FBS,
  author =       "Fabrice Saffre and Hanno Hildmann and Antti Anttonen",
  title =        "Force-Based Self-Organizing {MANET\slash FANET} with a
                 {UAV} Swarm",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "315",
  day =          "19",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090315",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/315",
  abstract =     "This paper introduces a novel distributed algorithm
                 designed to optimize the deployment of access points
                 within Mobile Ad Hoc Networks (MANETs) for better
                 service quality in infrastructure-less environments.
                 The algorithm operates based on local, independent
                 execution by each network node, thus ensuring a high
                 degree of scalability and adaptability to changing
                 network conditions. The primary focus is to match the
                 spatial distribution of access points with the
                 distribution of client devices while maintaining strong
                 connectivity to the network root. Using autonomous
                 decision-making and choreographed path-planning, this
                 algorithm bridges the gap between demand-responsive
                 network service provision and the maintenance of
                 crucial network connectivity links. The assessment of
                 the performance of this approach is motivated by using
                 numerical results generated by simulations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gorchakov:2023:APR,
  author =       "Artyom V. Gorchakov and Liliya A. Demidova and Peter
                 N. Sovietov",
  title =        "Analysis of Program Representations Based on Abstract
                 Syntax Trees and Higher-Order {Markov} Chains for
                 Source Code Classification Task",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "314",
  day =          "18",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090314",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/314",
  abstract =     "In this paper we consider the research and development
                 of classifiers that are trained to predict the task
                 solved by source code. Possible applications of such
                 task detection algorithms include method name
                 prediction, hardware--software partitioning,
                 programming standard violation detection, and semantic
                 code duplication search. We provide the comparative
                 analysis of modern approaches to source code
                 transformation into vector-based representations that
                 extend the variety of classification and clustering
                 algorithms that can be used for intelligent source code
                 analysis. These approaches include word2vec, code2vec,
                 first-order and second-order Markov chains constructed
                 from abstract syntax trees (AST), histograms of
                 assembly language instruction opcodes, and histograms
                 of AST node types. The vectors obtained with the
                 forementioned approaches are then used to train such
                 classification algorithms as k-nearest neighbor (KNN),
                 support vector machine (SVM), random forest (RF), and
                 multilayer perceptron (MLP). The obtained results show
                 that the use of program vectors based on first-order
                 AST-based Markov chains with an RF-based classifier
                 leads to the highest accuracy, precision, recall, and
                 F1 score. Increasing the order of Markov chains
                 considerably increases the dimensionality of a vector,
                 without any improvements in classifier quality, so we
                 assume that first-order Markov chains are best suitable
                 for real world applications. Additionally, the
                 experimental study shows that first-order AST-based
                 Markov chains are least sensitive to the used
                 classification algorithm.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mandarino:2023:PFD,
  author =       "Valerio Mandarino and Giuseppe Pappalardo and Emiliano
                 Tramontana",
  title =        "Proof of Flow: a Design Pattern for the Green Energy
                 Market",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "313",
  day =          "17",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090313",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/313",
  abstract =     "The increased penetration of Distributed Energy
                 Resources (DERs) in electricity markets has given rise
                 to a new category of energy players, called
                 Aggregators, whose role is to ensure fair remuneration
                 for energy supplied by DERs, and support the smooth
                 feeding of the intermittent energy produced into the
                 distribution network. This paper presents a software
                 solution, described as a design pattern, that governs
                 the interaction between an Aggregator and DERs,
                 leveraging blockchain technology to achieve a higher
                 degree of decentralization, data integrity and
                 security, through a properly designed,
                 blockchain-based, smart contract. Thus, the proposed
                 solution reduces the reliance on intermediaries acting
                 as authorities, while affording transparency,
                 efficiency and trust to the energy exchange process.
                 Thanks to the underlying blockchain properties,
                 generated events are easily observable and cannot be
                 forged or altered. However, blockchain technology has
                 inherent drawbacks, i.e., mainly the cost of storage
                 and execution, hence our solution provides additional
                 strategies for limiting blockchain usage, without
                 undermining its strengths. Moreover, the design of our
                 smart contract takes care of orchestrating the players,
                 and copes with their potential mutual disagreements,
                 which could arise from different measures of energy,
                 providing an automatic decision process to resolve such
                 disputes. The overall approach results in lower fees
                 for running smart contacts supporting energy players
                 and in a greater degree of fairness assurance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tosi:2023:ESI,
  author =       "Davide Tosi",
  title =        "Editorial for the Special Issue on {``Software
                 Engineering and Data Science''}, Volume {II}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "312",
  day =          "16",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090312",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/312",
  abstract =     "The increased penetration of Distributed Energy
                 Resources (DERs) in electricity markets has given rise
                 to a new category of energy players, called
                 Aggregators, whose role is to ensure fair remuneration
                 for energy supplied by DERs, and support the smooth
                 feeding of the intermittent energy produced into the
                 distribution network. This paper presents a software
                 solution, described as a design pattern, that governs
                 the interaction between an Aggregator and DERs,
                 leveraging blockchain technology to achieve a higher
                 degree of decentralization, data integrity and
                 security, through a properly designed,
                 blockchain-based, smart contract. Thus, the proposed
                 solution reduces the reliance on intermediaries acting
                 as authorities, while affording transparency,
                 efficiency and trust to the energy exchange process.
                 Thanks to the underlying blockchain properties,
                 generated events are easily observable and cannot be
                 forged or altered. However, blockchain technology has
                 inherent drawbacks, i.e., mainly the cost of storage
                 and execution, hence our solution provides additional
                 strategies for limiting blockchain usage, without
                 undermining its strengths. Moreover, the design of our
                 smart contract takes care of orchestrating the players,
                 and copes with their potential mutual disagreements,
                 which could arise from different measures of energy,
                 providing an automatic decision process to resolve such
                 disputes. The overall approach results in lower fees
                 for running smart contacts supporting energy players
                 and in a greater degree of fairness assurance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ghanem:2023:AST,
  author =       "Fahd A. Ghanem and M. C. Padma and Ramez Alkhatib",
  title =        "Automatic Short Text Summarization Techniques in
                 Social Media Platforms",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "311",
  day =          "13",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090311",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/311",
  abstract =     "The rapid expansion of social media platforms has
                 resulted in an unprecedented surge of short text
                 content being generated on a daily basis. Extracting
                 valuable insights and patterns from this vast volume of
                 textual data necessitates specialized techniques that
                 can effectively condense information while preserving
                 its core essence. In response to this challenge,
                 automatic short text summarization (ASTS) techniques
                 have emerged as a compelling solution, gaining
                 significant importance in their development. This paper
                 delves into the domain of summarizing short text on
                 social media, exploring various types of short text and
                 the associated challenges they present. It also
                 investigates the approaches employed to generate
                 concise and meaningful summaries. By providing a survey
                 of the latest methods and potential avenues for future
                 research, this paper contributes to the advancement of
                 ASTS in the ever-evolving landscape of social media
                 communication.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Aziz:2023:EHE,
  author =       "Rezak Aziz and Soumya Banerjee and Samia Bouzefrane
                 and Thinh Le Vinh",
  title =        "Exploring Homomorphic Encryption and Differential
                 Privacy Techniques towards Secure Federated Learning
                 Paradigm",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "310",
  day =          "13",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090310",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/310",
  abstract =     "The trend of the next generation of the internet has
                 already been scrutinized by top analytics enterprises.
                 According to Gartner investigations, it is predicted
                 that, by 2024, 75\% of the global population will have
                 their personal data covered under privacy regulations.
                 This alarming statistic necessitates the orchestration
                 of several security components to address the enormous
                 challenges posed by federated and distributed learning
                 environments. Federated learning (FL) is a promising
                 technique that allows multiple parties to
                 collaboratively train a model without sharing their
                 data. However, even though FL is seen as a
                 privacy-preserving distributed machine learning method,
                 recent works have demonstrated that FL is vulnerable to
                 some privacy attacks. Homomorphic encryption (HE) and
                 differential privacy (DP) are two promising techniques
                 that can be used to address these privacy concerns. HE
                 allows secure computations on encrypted data, while DP
                 provides strong privacy guarantees by adding noise to
                 the data. This paper first presents consistent attacks
                 on privacy in federated learning and then provides an
                 overview of HE and DP techniques for secure federated
                 learning in next-generation internet applications. It
                 discusses the strengths and weaknesses of these
                 techniques in different settings as described in the
                 literature, with a particular focus on the trade-off
                 between privacy and convergence, as well as the
                 computation overheads involved. The objective of this
                 paper is to analyze the challenges associated with each
                 technique and identify potential opportunities and
                 solutions for designing a more robust,
                 privacy-preserving federated learning framework.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tadj:2023:EID,
  author =       "Timothy Tadj and Reza Arablouei and Volkan Dedeoglu",
  title =        "On Evaluating {IoT} Data Trust via Machine Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "309",
  day =          "12",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090309",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/309",
  abstract =     "Data trust in IoT is crucial for safeguarding privacy,
                 security, reliable decision-making, user acceptance,
                 and complying with regulations. Various approaches
                 based on supervised or unsupervised machine learning
                 (ML) have recently been proposed for evaluating IoT
                 data trust. However, assessing their real-world
                 efficacy is hard mainly due to the lack of related
                 publicly available datasets that can be used for
                 benchmarking. Since obtaining such datasets is
                 challenging, we propose a data synthesis method, called
                 random walk infilling (RWI), to augment IoT time-series
                 datasets by synthesizing untrustworthy data from
                 existing trustworthy data. Thus, RWI enables us to
                 create labeled datasets that can be used to develop and
                 validate ML models for IoT data trust evaluation. We
                 also extract new features from IoT time-series sensor
                 data that effectively capture its autocorrelation as
                 well as its cross-correlation with the data of the
                 neighboring (peer) sensors. These features can be used
                 to learn ML models for recognizing the trustworthiness
                 of IoT sensor data. Equipped with our synthesized
                 ground-truth-labeled datasets and informative
                 correlation-based features, we conduct extensive
                 experiments to critically examine various approaches to
                 evaluating IoT data trust via ML. The results reveal
                 that commonly used ML-based approaches to IoT data
                 trust evaluation, which rely on unsupervised cluster
                 analysis to assign trust labels to unlabeled data,
                 perform poorly. This poor performance is due to the
                 underlying assumption that clustering provides reliable
                 labels for data trust, which is found to be untenable.
                 The results also indicate that ML models, when trained
                 on datasets augmented via RWI and using the proposed
                 features, generalize well to unseen data and surpass
                 existing related approaches. Moreover, we observe that
                 a semi-supervised ML approach that requires only about
                 10\% of the data labeled offers competitive performance
                 while being practically more appealing compared to the
                 fully supervised approaches. The related Python code
                 and data are available online.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Pelekoudas-Oikonomou:2023:PHF,
  author =       "Filippos Pelekoudas-Oikonomou and Jos{\'e} C. Ribeiro
                 and Georgios Mantas and Georgia Sakellari and Jonathan
                 Gonzalez",
  title =        "Prototyping a Hyperledger Fabric-Based Security
                 Architecture for {IoMT}-Based Health Monitoring
                 Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "308",
  day =          "11",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090308",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/308",
  abstract =     "The Internet of Medical Things (IoMT) has risen
                 significantly in recent years and has provided better
                 quality of life by enabling IoMT-based health
                 monitoring systems. Despite that fact, innovative
                 security mechanisms are required to meet the security
                 concerns of such systems effectively and efficiently.
                 Additionally, the industry and the research community
                 have anticipated that blockchain technology will be a
                 disruptive technology that will be able to be
                 integrated into innovative security solutions for IoMT
                 networks since it has the potential to play a big role
                 in: (a) enabling secure data transmission, (b) ensuring
                 IoMT device security, and (c) enabling tamper-proof
                 data storage. Therefore, the purpose of this research
                 work is to design a novel lightweight blockchain-based
                 security architecture for IoMT-based health monitoring
                 systems leveraging the features of the Hyperledger
                 Fabric (HF) Platform, its utilities. and its
                 lightweight blockchain nature in order to: (i) ensure
                 entity authentication, (ii) ensure data
                 confidentiality, and (iii) enable a more
                 energy-efficient blockchain-based security architecture
                 for IoMT-based health monitoring systems while
                 considering the limited resources of IoMT gateways.
                 While security mechanisms for IoT utilizing HF do
                 exist, to the best of our knowledge there is no
                 specific HF-based architecture for IoMT-based health
                 monitoring systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Aggarwal:2023:FLN,
  author =       "Shobhit Aggarwal and Asis Nasipuri",
  title =        "{FL-LoRaMAC}: a Novel Framework for Enabling On-Device
                 Learning for {LoRa}-Based {IoT} Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "307",
  day =          "10",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090307",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/307",
  abstract =     "The Internet of Things (IoT) enables us to gain access
                 to a wide range of data from the physical world that
                 can be analyzed for deriving critical state
                 information. In this regard, machine learning (ML) is a
                 valuable tool that can be used to develop models based
                 on observed physical data, leading to efficient
                 analytical decisions, including anomaly detection. In
                 this work, we address some key challenges for applying
                 ML in IoT applications that include maintaining privacy
                 considerations of user data that are needed for
                 developing ML models and minimizing the communication
                 cost for transmitting the data over the IoT network. We
                 consider a representative application of the anomaly
                 detection of ECG signals that are obtained from a set
                 of low-cost wearable sensors and transmitted to a
                 central server using LoRaWAN, which is a popular and
                 emerging low-power wide-area network (LPWAN)
                 technology. We present a novel framework utilizing
                 federated learning (FL) to preserve data privacy and
                 appropriate features for uplink and downlink
                 communications between the end devices and the gateway
                 to optimize the communication cost. Performance results
                 obtained from computer simulations demonstrate that the
                 proposed framework leads to a 98\% reduction in the
                 volume of data that is required to achieve the same
                 level of performance as in traditional centralized
                 ML.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Midolo:2023:ATS,
  author =       "Alessandro Midolo and Emiliano Tramontana",
  title =        "An Automatic Transformer from Sequential to Parallel
                 {Java} Code",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "306",
  day =          "08",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090306",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/java2020.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/306",
  abstract =     "Sequential programs can benefit from parallel
                 execution to improve their performance. When developing
                 a parallel application, several techniques are employed
                 to achieve the desired behavior: identifying parts that
                 can run in parallel, synchronizing access to shared
                 data, tuning performance, etc. Admittedly, manually
                 transforming a sequential application to make it
                 parallel can be tedious due to the large number of
                 lines of code to inspect, the possibility of errors
                 arising from inaccurate data dependence analysis
                 leading to unpredictable behavior, and inefficiencies
                 when the workload between parallel threads is
                 unbalanced. This paper proposes an automatic approach
                 that analyzes Java source code to identify method calls
                 that are suitable for parallel execution and transforms
                 them so that they run in another thread. The approach
                 is based on data dependence and control dependence
                 analyses to determine the execution flow and data
                 accessed. Based on the proposed method, a tool has been
                 developed to enhance applications by incorporating
                 parallelism, i.e., transforming suitable method calls
                 to execute on parallel threads, and synchronizing data
                 access where needed. The developed tool has been
                 extensively tested to verify the accuracy of its
                 analysis in finding parallel execution opportunities,
                 the correctness of the source code alterations, and the
                 resultant performance gain.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bucur:2023:EMJ,
  author =       "Vlad Bucur and Liviu-Cristian Miclea",
  title =        "Entering the Metaverse from the {JVM}: The State of
                 the Art, Challenges, and Research Areas of {JVM}-Based
                 {Web 3.0} Tools and Libraries",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "305",
  day =          "07",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090305",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/java2020.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/305",
  abstract =     "Web 3.0 is the basis on which the proposed metaverse,
                 a seamless virtual world enabled by computers and
                 interconnected devices, hopes to interact with its
                 users, but beyond the high-level project overview of
                 what Web 3.0 applications try to achieve, the
                 implementation is still down to low-level coding
                 details. This article aims to analyze the low-level
                 implementations of key components of Web 3.0 using a
                 variety of frameworks and tools as well as several
                 JVM-based languages. This paper breaks down the
                 low-level implementation of smart contracts and
                 semantic web principles using three frameworks, Corda
                 and Ethereum for smart contracts and Jeda for semantic
                 web, using both Scala and Java as implementing
                 languages all while highlighting differences and
                 similarities between the frameworks used.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tavakolian:2023:HRL,
  author =       "Alireza Tavakolian and Alireza Rezaee and Farshid
                 Hajati and Shahadat Uddin",
  title =        "Hospital Readmission and Length-of-Stay Prediction
                 Using an Optimized Hybrid Deep Model",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "304",
  day =          "06",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090304",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/304",
  abstract =     "Hospital readmission and length-of-stay predictions
                 provide information on how to manage hospital bed
                 capacity and the number of required staff, especially
                 during pandemics. We present a hybrid deep model called
                 the Genetic Algorithm-Optimized Convolutional Neural
                 Network (GAOCNN), with a unique preprocessing method to
                 predict hospital readmission and the length of stay
                 required for patients of various conditions. GAOCNN
                 uses one-dimensional convolutional layers to predict
                 hospital readmission and the length of stay. The
                 parameters of the layers are optimized via a genetic
                 algorithm. To show the performance of the proposed
                 model in patients with various conditions, we evaluate
                 the model under three healthcare datasets: the Diabetes
                 130-US hospitals dataset, the COVID-19 dataset, and the
                 MIMIC-III dataset. The diabetes 130-US hospitals
                 dataset has information on both readmission and the
                 length of stay, while the COVID-19 and MIMIC-III
                 datasets just include information on the length of
                 stay. Experimental results show that the proposed
                 model's accuracy for hospital readmission was 97.2\%
                 for diabetic patients. Furthermore, the accuracy of the
                 length-of-stay prediction was 89\%, 99.4\%, and 94.1\%
                 for the diabetic, COVID-19, and ICU patients,
                 respectively. These results confirm the superiority of
                 the proposed model compared to existing methods. Our
                 findings offer a platform for managing the healthcare
                 funds and resources for patients with various
                 diseases.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Malarczyk:2023:IRT,
  author =       "Mateusz Malarczyk and Grzegorz Kaczmarczyk and
                 Jaroslaw Szrek and Marcin Kaminski",
  title =        "{Internet of Robotic Things (IoRT)} and Metaheuristic
                 Optimization Techniques Applied for Wheel-Legged
                 Robot",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "303",
  day =          "06",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090303",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/303",
  abstract =     "This paper presents the operation of a remotely
                 controlled, wheel-legged robot. The developed Wi-Fi
                 connection framework is established on a popular ARM
                 microcontroller board. The implementation provides a
                 low-cost solution that is in congruence with the newest
                 industrial standards. Additionally, the problem of limb
                 structure and motor speed control is solved. The design
                 process of the mechanical structure is enhanced by a
                 nature-inspired metaheuristic optimization algorithm.
                 An FOC-based BLDC motor speed control strategy is
                 selected to guarantee dynamic operation of the drive.
                 The paper provides both the theoretical considerations
                 and the obtained prototype experimental results.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Peng:2023:HNO,
  author =       "Chao-Chung Peng and Yi-Ho Chen",
  title =        "A Hybrid Neural Ordinary Differential Equation Based
                 Digital Twin Modeling and Online Diagnosis for an
                 Industrial Cooling Fan",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "302",
  day =          "04",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090302",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/302",
  abstract =     "Digital twins can reflect the dynamical behavior of
                 the identified system, enabling self-diagnosis and
                 prediction in the digital world to optimize the
                 intelligent manufacturing process. One of the key
                 benefits of digital twins is the ability to provide
                 real-time data analysis during operation, which can
                 monitor the condition of the system and prognose the
                 failure. This allows manufacturers to resolve the
                 problem before it happens. However, most digital twins
                 are constructed using discrete-time models, which are
                 not able to describe the dynamics of the system across
                 different sampling frequencies. In addition, the high
                 computational complexity due to significant memory
                 storage and large model sizes makes digital twins
                 challenging for online diagnosis. To overcome these
                 issues, this paper proposes a novel structure for
                 creating the digital twins of cooling fan systems by
                 combining with neural ordinary differential equations
                 and physical dynamical differential equations.
                 Evaluated using the simulation data, the proposed
                 structure not only shows accurate modeling results
                 compared to other digital twins methods but also
                 requires fewer parameters and smaller model sizes. The
                 proposed approach has also been demonstrated using
                 experimental data and is robust in terms of measurement
                 noise, and it has proven to be an effective solution
                 for online diagnosis in the intelligent manufacturing
                 process.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chang:2023:WEH,
  author =       "Hsiao-Ching Chang and Hsing-Tsung Lin and Pi-Chung
                 Wang",
  title =        "Wireless Energy Harvesting for {Internet-of-Things}
                 Devices Using Directional Antennas",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "301",
  day =          "03",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090301",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/301",
  abstract =     "With the rapid development of the Internet of Things,
                 the number of wireless devices is increasing rapidly.
                 Because of the limited battery capacity, these devices
                 may suffer from the issue of power depletion. Radio
                 frequency (RF) energy harvesting technology can
                 wirelessly charge devices to prolong their lifespan.
                 With the technology of beamforming, the beams generated
                 by an antenna array can select the direction for
                 wireless charging. Although a good charging-time
                 schedule should be short, energy efficiency should also
                 be considered. In this work, we propose two algorithms
                 to optimize the time consumption for charging devices.
                 We first present a greedy algorithm to minimize the
                 total charging time. Then, a differential evolution
                 (DE) algorithm is proposed to minimize the energy
                 overflow and improve energy efficiency. The DE
                 algorithm can also gradually increase fully charged
                 devices. The experimental results show that both the
                 proposed greedy and DE algorithms can find a schedule
                 of a short charging time with the lowest energy
                 overflow. The DE algorithm can further improve the
                 performance of data transmission to promote the
                 feasibility of potential wireless sensing and charging
                 applications by reducing the number of fully charged
                 devices at the same time.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lan:2023:ACB,
  author =       "Chong Lan and Yongsheng Wang and Chengze Wang and
                 Shirong Song and Zheng Gong",
  title =        "Application of {ChatGPT}-Based Digital Human in
                 Animation Creation",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "300",
  day =          "02",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090300",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/300",
  abstract =     "Traditional 3D animation creation involves a process
                 of motion acquisition, dubbing, and mouth movement data
                 binding for each character. To streamline animation
                 creation, we propose combining artificial intelligence
                 (AI) with a motion capture system. This integration
                 aims to reduce the time, workload, and cost associated
                 with animation creation. By utilizing AI and natural
                 language processing, the characters can engage in
                 independent learning, generating their own responses
                 and interactions, thus moving away from the traditional
                 method of creating digital characters with pre-defined
                 behaviors. In this paper, we present an approach that
                 employs a digital person's animation environment. We
                 utilized Unity plug-ins to drive the character's mouth
                 Blendshape, synchronize the character's voice and mouth
                 movements in Unity, and connect the digital person to
                 an AI system. This integration enables AI-driven
                 language interactions within animation production.
                 Through experimentation, we evaluated the correctness
                 of the natural language interaction of the digital
                 human in the animated scene, the real-time
                 synchronization of mouth movements, the potential for
                 singularity in guiding users during digital human
                 animation creation, and its ability to guide user
                 interactions through its own thought process.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Castillo-Soria:2023:PRA,
  author =       "Francisco R. Castillo-Soria and J. Alberto {Del
                 Puerto-Flores} and Cesar A. Azurdia-Meza and Vinoth
                 Babu Kumaravelu and Jorge Sim{\'o}n and Carlos A.
                 Gutierrez",
  title =        "Precoding for {RIS}-Assisted Multi-User {MIMO-DQSM}
                 Transmission Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "299",
  day =          "02",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090299",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/299",
  abstract =     "This paper presents two precoding techniques for a
                 reconfigurable intelligent surface (RIS)-assisted
                 multi-user (MU) multiple-input multiple-output (MIMO)
                 double quadrature spatial modulation (DQSM) downlink
                 transmission system. Instead of being applied at the
                 remote RIS, the phase shift vector is applied at the
                 base station (BS) by using a double precoding stage.
                 Results show that the proposed RIS-MU-MIMO-DQSM system
                 has gains of up to 17 dB in terms of bit error rate
                 (BER) and a reduction in detection complexity of 51\%
                 when compared with the conventional MU-MIMO system
                 based on quadrature amplitude modulation (QAM).
                 Compared with a similar system based on amplify and
                 forward (AF) relay-assisted technique, the proposed
                 system has a gain of up to 18 dB in terms of BER under
                 the same conditions and parameters.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhang:2023:IUN,
  author =       "Weijie Zhang and Lanping Zhang and Xixi Zhang and Yu
                 Wang and Pengfei Liu and Guan Gui",
  title =        "Intelligent Unsupervised Network Traffic
                 Classification Method Using Adversarial Training and
                 Deep Clustering for Secure {Internet of Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "298",
  day =          "01",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090298",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/298",
  abstract =     "Network traffic classification (NTC) has attracted
                 great attention in many applications such as secure
                 communications, intrusion detection systems. The
                 existing NTC methods based on supervised learning rely
                 on sufficient labeled datasets in the training phase,
                 but for most traffic datasets, it is difficult to
                 obtain label information in practical applications.
                 Although unsupervised learning does not rely on labels,
                 its classification accuracy is not high, and the number
                 of data classes is difficult to determine. This paper
                 proposes an unsupervised NTC method based on
                 adversarial training and deep clustering with improved
                 network traffic classification (NTC) and lower
                 computational complexity in comparison with the
                 traditional clustering algorithms. Here, the training
                 process does not require data labels, which greatly
                 reduce the computational complexity of the network
                 traffic classification through pretraining. In the
                 pretraining stage, an autoencoder (AE) is used to
                 reduce the dimension of features and reduce the
                 complexity of the initial high-dimensional network
                 traffic data features. Moreover, we employ the
                 adversarial training model and a deep clustering
                 structure to further optimize the extracted features.
                 The experimental results show that our proposed method
                 has robust performance, with a multiclassification
                 accuracy of 92.2\%, which is suitable for
                 classification with a large number of unlabeled data in
                 actual application scenarios. This paper only focuses
                 on breakthroughs in the algorithm stage, and future
                 work can be focused on the deployment and adaptation in
                 practical environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Safarov:2023:ELB,
  author =       "Furkat Safarov and Mainak Basak and Rashid Nasimov and
                 Akmalbek Abdusalomov and Young Im Cho",
  title =        "Explainable Lightweight Block Attention Module
                 Framework for Network-Based {IoT} Attack Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "297",
  day =          "01",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090297",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/297",
  abstract =     "In the rapidly evolving landscape of internet usage,
                 ensuring robust cybersecurity measures has become a
                 paramount concern across diverse fields. Among the
                 numerous cyber threats, denial of service (DoS) and
                 distributed denial of service (DDoS) attacks pose
                 significant risks, as they can render websites and
                 servers inaccessible to their intended users.
                 Conventional intrusion detection methods encounter
                 substantial challenges in effectively identifying and
                 mitigating these attacks due to their widespread
                 nature, intricate patterns, and computational
                 complexities. However, by harnessing the power of deep
                 learning-based techniques, our proposed dense
                 channel-spatial attention model exhibits exceptional
                 accuracy in detecting and classifying DoS and DDoS
                 attacks. The successful implementation of our proposed
                 framework addresses the challenges posed by imbalanced
                 data and exhibits its potential for real-world
                 applications. By leveraging the dense channel-spatial
                 attention mechanism, our model can precisely identify
                 and classify DoS and DDoS attacks, bolstering the
                 cybersecurity defenses of websites and servers. The
                 high accuracy rates achieved across different datasets
                 reinforce the robustness of our approach, underscoring
                 its efficacy in enhancing intrusion detection
                 capabilities. As a result, our framework holds promise
                 in bolstering cybersecurity measures in real-world
                 scenarios, contributing to the ongoing efforts to
                 safeguard against cyber threats in an increasingly
                 interconnected digital landscape. Comparative analysis
                 with current intrusion detection methods reveals the
                 superior performance of our model. We achieved accuracy
                 rates of 99.38\%, 99.26\%, and 99.43\% for Bot-IoT,
                 CICIDS2017, and UNSW\_NB15 datasets, respectively.
                 These remarkable results demonstrate the capability of
                 our approach to accurately detect and classify various
                 types of DoS and DDoS assaults. By leveraging the
                 inherent strengths of deep learning, such as pattern
                 recognition and feature extraction, our model
                 effectively overcomes the limitations of traditional
                 methods, enhancing the accuracy and efficiency of
                 intrusion detection systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Anastasakis:2023:FFR,
  author =       "Zacharias Anastasakis and Terpsichori-Helen
                 Velivassaki and Artemis Voulkidis and Stavroula Bourou
                 and Konstantinos Psychogyios and Dimitrios Skias and
                 and Theodore Zahariadis",
  title =        "{FREDY}: Federated Resilience Enhanced with
                 Differential Privacy",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "296",
  day =          "01",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090296",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/296",
  abstract =     "Federated Learning is identified as a reliable
                 technique for distributed training of ML models.
                 Specifically, a set of dispersed nodes may collaborate
                 through a federation in producing a jointly trained ML
                 model without disclosing their data to each other. Each
                 node performs local model training and then shares its
                 trained model weights with a server node, usually
                 called Aggregator in federated learning, as it
                 aggregates the trained weights and then sends them back
                 to its clients for another round of local training.
                 Despite the data protection and security that FL
                 provides to each client, there are still well-studied
                 attacks such as membership inference attacks that can
                 detect potential vulnerabilities of the FL system and
                 thus expose sensitive data. In this paper, in order to
                 prevent this kind of attack and address private data
                 leakage, we introduce FREDY, a differential private
                 federated learning framework that enables knowledge
                 transfer from private data. Particularly, our approach
                 has a teachers--student scheme. Each teacher model is
                 trained on sensitive, disjoint data in a federated
                 manner, and the student model is trained on the most
                 voted predictions of the teachers on public unlabeled
                 data which are noisy aggregated in order to guarantee
                 the privacy of each teacher's sensitive data. Only the
                 student model is publicly accessible as the teacher
                 models contain sensitive information. We show that our
                 proposed approach guarantees the privacy of sensitive
                 data against model inference attacks while it combines
                 the federated learning settings for the model training
                 procedures.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mrvelj:2023:FVF,
  author =       "Stefica Mrvelj and Marko Matulin",
  title =        "{FLAME-VQA}: a Fuzzy Logic-Based Model for High Frame
                 Rate Video Quality Assessment",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "295",
  day =          "01",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090295",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/295",
  abstract =     "In the quest to optimize user experience, network, and
                 service, providers continually seek to deliver
                 high-quality content tailored to individual
                 preferences. However, predicting user perception of
                 quality remains a challenging task, given the
                 subjective nature of human perception and the plethora
                 of technical attributes that contribute to the overall
                 viewing experience. Thus, we introduce a Fuzzy
                 Logic-bAsed ModEl for Video Quality Assessment
                 (FLAME-VQA), leveraging the LIVE-YT-HFR database
                 containing 480 video sequences and subjective ratings
                 of their quality from 85 test subjects. The proposed
                 model addresses the challenges of assessing user
                 perception by capturing the intricacies of individual
                 preferences and video attributes using fuzzy logic. It
                 operates with four input parameters: video frame rate,
                 compression rate, and spatio-temporal information. The
                 Spearman Rank--Order Correlation Coefficient (SROCC)
                 and Pearson Correlation Coefficient (PCC) show a high
                 correlation between the output and the ground truth.
                 For the training, test, and complete dataset, SROCC
                 equals 0.8977, 0.8455, and 0.8961, respectively, while
                 PCC equals 0.9096, 0.8632, and 0.9086, respectively.
                 The model outperforms comparative models tested on the
                 same dataset.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2023:ATC,
  author =       "Yang Wang",
  title =        "Advances Techniques in Computer Vision and
                 Multimedia",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "294",
  day =          "01",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090294",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/294",
  abstract =     "In the quest to optimize user experience, network, and
                 service, providers continually seek to deliver
                 high-quality content tailored to individual
                 preferences. However, predicting user perception of
                 quality remains a challenging task, given the
                 subjective nature of human perception and the plethora
                 of technical attributes that contribute to the overall
                 viewing experience. Thus, we introduce a Fuzzy
                 Logic-bAsed ModEl for Video Quality Assessment
                 (FLAME-VQA), leveraging the LIVE-YT-HFR database
                 containing 480 video sequences and subjective ratings
                 of their quality from 85 test subjects. The proposed
                 model addresses the challenges of assessing user
                 perception by capturing the intricacies of individual
                 preferences and video attributes using fuzzy logic. It
                 operates with four input parameters: video frame rate,
                 compression rate, and spatio-temporal information. The
                 Spearman Rank--Order Correlation Coefficient (SROCC)
                 and Pearson Correlation Coefficient (PCC) show a high
                 correlation between the output and the ground truth.
                 For the training, test, and complete dataset, SROCC
                 equals 0.8977, 0.8455, and 0.8961, respectively, while
                 PCC equals 0.9096, 0.8632, and 0.9086, respectively.
                 The model outperforms comparative models tested on the
                 same dataset.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bidry:2023:ELB,
  author =       "Mahmoud Bidry and Abdellah Ouaguid and Mohamed
                 Hanine",
  title =        "Enhancing E-Learning with Blockchain: Characteristics,
                 Projects, and Emerging Trends",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "293",
  day =          "28",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090293",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/293",
  abstract =     "Blockchain represents a decentralized and distributed
                 ledger technology, ensuring transparent and secure
                 transaction recording across networks. This innovative
                 technology offers several benefits, including increased
                 security, trust, and transparency, making it suitable
                 for a wide range of applications. In the last few
                 years, there has been a growing interest in
                 investigating the potential of Blockchain technology to
                 enhance diverse fields, such as e-learning. In this
                 research, we undertook a systematic literature review
                 to explore the potential of Blockchain technology in
                 enhancing the e-learning domain. Our research focused
                 on four main questions: (1) What potential
                 characteristics of Blockchain can contribute to
                 enhancing e-learning? (2) What are the existing
                 Blockchain projects dedicated to e-learning? (3) What
                 are the limitations of existing projects? (4) What are
                 the future trends in Blockchain-related research that
                 will impact e-learning? The results showed that
                 Blockchain technology has several characteristics that
                 could benefit e-learning. We also discussed
                 immutability, transparency, decentralization, security,
                 and traceability. We also identified several existing
                 Blockchain projects dedicated to e-learning and
                 discussed their potential to revolutionize learning by
                 providing more transparency, security, and
                 effectiveness. However, our research also revealed many
                 limitations and challenges that could be addressed to
                 achieve Blockchain technology's potential in
                 e-learning.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Priyadarshini:2023:AST,
  author =       "Ishaani Priyadarshini",
  title =        "Autism Screening in Toddlers and Adults Using Deep
                 Learning and Fair {AI} Techniques",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "292",
  day =          "28",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090292",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/292",
  abstract =     "Autism spectrum disorder (ASD) has been associated
                 with conditions like depression, anxiety, epilepsy,
                 etc., due to its impact on an individual's educational,
                 social, and employment. Since diagnosis is challenging
                 and there is no cure, the goal is to maximize an
                 individual's ability by reducing the symptoms, and
                 early diagnosis plays a role in improving behavior and
                 language development. In this paper, an autism
                 screening analysis for toddlers and adults has been
                 performed using fair AI (feature engineering, SMOTE,
                 optimizations, etc.) and deep learning methods. The
                 analysis considers traditional deep learning methods
                 like Multilayer Perceptron (MLP), Artificial Neural
                 Networks (ANN), Convolutional Neural Networks (CNN),
                 and Long Short-Term Memory (LSTM), and also proposes
                 two hybrid deep learning models, i.e., CNN--LSTM with
                 Particle Swarm Optimization (PSO), and a CNN model
                 combined with Gated Recurrent Units (GRU--CNN). The
                 models have been validated using multiple performance
                 metrics, and the analysis confirms that the proposed
                 models perform better than the traditional models.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Al-Hamid:2023:NSB,
  author =       "Duaa Zuhair Al-Hamid and Pejman A. Karegar and Peter
                 Han Joo Chong",
  title =        "A Novel {SDWSN}-Based Testbed for {IoT} Smart
                 Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "291",
  day =          "28",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090291",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/291",
  abstract =     "Wireless sensor network (WSN) environment monitoring
                 and smart city applications present challenges for
                 maintaining network connectivity when, for example,
                 dynamic events occur. Such applications can benefit
                 from recent technologies such as software-defined
                 networks (SDNs) and network virtualization to support
                 network flexibility and offer validation for a physical
                 network. This paper aims to present a testbed-based,
                 software-defined wireless sensor network (SDWSN) for
                 IoT applications with a focus on promoting the approach
                 of virtual network testing and analysis prior to
                 physical network implementation to monitor and repair
                 any network failures. Herein, physical network
                 implementation employing hardware boards such as Texas
                 Instruments CC2538 (TI CC2538) and TI CC1352R sensor
                 nodes is presented and designed based on virtual WSN-
                 based clustering for stationary and dynamic networks
                 use cases. The key performance indicators such as
                 evaluating node (such as a gateway node to the
                 Internet) connection capability based on packet drop
                 and energy consumption virtually and physically are
                 discussed. According to the test findings, the proposed
                 software-defined physical network benefited from
                 ``prior-to-implementation'' analysis via
                 virtualization, as the performance of both virtual and
                 physical networks is comparable.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kochetkova:2023:STM,
  author =       "Irina Kochetkova and Anna Kushchazli and Sofia
                 Burtseva and Andrey Gorshenin",
  title =        "Short-Term Mobile Network Traffic Forecasting Using
                 Seasonal {ARIMA} and {Holt--Winters} Models",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "290",
  day =          "28",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090290",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/290",
  abstract =     "Fifth-generation (5G) networks require efficient radio
                 resource management (RRM) which should dynamically
                 adapt to the current network load and user needs.
                 Monitoring and forecasting network performance
                 requirements and metrics helps with this task. One of
                 the parameters that highly influences radio resource
                 management is the profile of user traffic generated by
                 various 5G applications. Forecasting such mobile
                 network profiles helps with numerous RRM tasks such as
                 network slicing and load balancing. In this paper, we
                 analyze a dataset from a mobile network operator in
                 Portugal that contains information about volumes of
                 traffic in download and upload directions in one-hour
                 time slots. We apply two statistical models for
                 forecasting download and upload traffic profiles,
                 namely, seasonal autoregressive integrated moving
                 average (SARIMA) and Holt-Winters models. We
                 demonstrate that both models are suitable for
                 forecasting mobile network traffic. Nevertheless, the
                 SARIMA model is more appropriate for download traffic
                 (e.g., MAPE [mean absolute percentage error] of 11.2\%
                 vs. 15\% for Holt-Winters), while the Holt-Winters
                 model is better suited for upload traffic (e.g., MAPE
                 of 4.17\% vs. 9.9\% for SARIMA and Holt-Winters,
                 respectively).",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Carvajal-Rodriguez:2023:PPA,
  author =       "Jorge Carvajal-Rodriguez and Marco Morales and
                 Christian Tipantu{\~n}a",
  title =        "{3D} Path Planning Algorithms in {UAV}-Enabled
                 Communications Systems: a Mapping Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "289",
  day =          "27",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090289",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/289",
  abstract =     "Unmanned Aerial Vehicles (UAVs) equipped with
                 communication technologies have gained significant
                 attention as a promising solution for providing
                 wireless connectivity in remote, disaster-stricken
                 areas lacking communication infrastructure. However,
                 enabling UAVs to provide communications (e.g., UAVs
                 acting as flying base stations) in real scenarios
                 requires the integration of various technologies and
                 algorithms. In particular 3D path planning algorithms
                 are crucial in determining the optimal path free of
                 obstacles so that UAVs in isolation or forming networks
                 can provide wireless coverage in a specific region.
                 Considering that most of the existing proposals in the
                 literature only address path planning in a 2D
                 environment, this paper systematically studies existing
                 path-planning solutions in UAVs in a 3D environment in
                 which optimization models (optimal and heuristics) have
                 been applied. This paper analyzes 37 articles selected
                 from 631 documents from a search in the Scopus
                 database. This paper also presents an overview of
                 UAV-enabled communications systems, the research
                 questions, and the methodology for the systematic
                 mapping study. In the end, this paper provides
                 information about the objectives to be minimized or
                 maximized, the optimization variables used, and the
                 algorithmic strategies employed to solve the 3D path
                 planning problem.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{ONeill:2023:SMC,
  author =       "Vyas O'Neill and Ben Soh",
  title =        "Spot Market Cloud Orchestration Using Task-Based
                 Redundancy and Dynamic Costing",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "9",
  pages =        "288",
  day =          "27",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15090288",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Thu Sep 28 13:55:47 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/9/288",
  abstract =     "Cloud computing has become ubiquitous in the
                 enterprise environment as its on-demand model realizes
                 technical and economic benefits for users. Cloud users
                 demand a level of reliability, availability, and
                 quality of service. Improvements to reliability
                 generally come at the cost of additional replication.
                 Existing approaches have focused on the replication of
                 virtual environments as a method of improving the
                 reliability of cloud services. As cloud systems move
                 towards microservices-based architectures, a more
                 granular approach to replication is now possible. In
                 this paper, we propose a cloud orchestration approach
                 that balances the potential cost of failure with the
                 spot market running cost, optimizing the resource usage
                 of the cloud system. We present the results of
                 empirical testing we carried out using a simulator to
                 compare the outcome of our proposed approach to a
                 control algorithm based on a static reliability
                 requirement. Our empirical testing showed an
                 improvement of between 37\% and 72\% in total cost over
                 the control, depending on the specific characteristics
                 of the cloud models tested. We thus propose that in
                 clouds where the cost of failure can be reasonably
                 approximated, our approach may be used to optimize the
                 cloud redundancy configuration to achieve a lower total
                 cost.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Thakur:2023:CAI,
  author =       "Nirmalya Thakur and Kesha A. Patel and Audrey Poon and
                 Rishika Shah and Nazif Azizi and Changhee Han",
  title =        "A Comprehensive Analysis and Investigation of the
                 Public Discourse on {Twitter} about Exoskeletons from
                 2017 to 2023",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "10",
  pages =        "346",
  day =          "22",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15100346",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 3 09:03:57 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/10/346",
  abstract =     "Exoskeletons have emerged as a vital technology in the
                 last decade and a half, with diverse use cases in
                 different domains. Even though several works related to
                 the analysis of Tweets about emerging technologies
                 exist, none of those works have focused on the analysis
                 of Tweets about exoskeletons. The work of this paper
                 aims to address this research gap by presenting
                 multiple novel findings from a comprehensive analysis
                 of about 150,000 Tweets about exoskeletons posted
                 between May 2017 and May 2023. First, findings from
                 temporal analysis of these Tweets reveal the specific
                 months per year when a significantly higher volume of
                 Tweets was posted and the time windows when the highest
                 number of Tweets, the lowest number of Tweets, Tweets
                 with the highest number of hashtags, and Tweets with
                 the highest number of user mentions were posted.
                 Second, the paper shows that there are statistically
                 significant correlations between the number of Tweets
                 posted per hour and the different characteristics of
                 these Tweets. Third, the paper presents a multiple
                 linear regression model to predict the number of Tweets
                 posted per hour in terms of these characteristics of
                 Tweets. The R 2 score of this model was observed to be
                 0.9540. Fourth, the paper reports that the 10 most
                 popular hashtags were \#exoskeleton, \#robotics, \#iot,
                 \#technology, \#tech, \#innovation, \#ai, \#sci,
                 \#construction and \#news. Fifth, sentiment analysis of
                 these Tweets was performed, and the results show that
                 the percentages of positive, neutral, and negative
                 Tweets were 46.8\%, 33.1\%, and 20.1\%, respectively.
                 To add to this, in the Tweets that did not express a
                 neutral sentiment, the sentiment of surprise was the
                 most common sentiment. It was followed by sentiments of
                 joy, disgust, sadness, fear, and anger, respectively.
                 Furthermore, hashtag-specific sentiment analysis
                 revealed several novel insights. For instance, for
                 almost all the months in 2022, the usage of \#ai in
                 Tweets about exoskeletons was mainly associated with a
                 positive sentiment. Sixth, lexicon-based approaches
                 were used to detect possibly sarcastic Tweets and
                 Tweets that contained news, and the results are
                 presented. Finally, a comparison of positive Tweets,
                 negative Tweets, neutral Tweets, possibly sarcastic
                 Tweets, and Tweets that contained news is presented in
                 terms of the different characteristic properties of
                 these Tweets. The findings reveal multiple novel
                 insights related to the similarities, variations, and
                 trends of character count, hashtag usage, and user
                 mentions in such Tweets during this time range.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ferilli:2023:GDB,
  author =       "Stefano Ferilli and Eleonora Bernasconi and Davide {Di
                 Pierro} and Domenico Redavid",
  title =        "A Graph {DB}-Based Solution for Semantic Technologies
                 in the Future {Internet}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "10",
  pages =        "345",
  day =          "20",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15100345",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 3 09:03:57 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/10/345",
  abstract =     "With the progressive improvements in the power,
                 effectiveness, and reliability of AI solutions, more
                 and more critical human problems are being handled by
                 automated AI-based tools and systems. For more complex
                 or particularly critical applications, the level of
                 knowledge, not just information, must be handled by
                 systems where explicit relationships among objects are
                 represented and processed. For this purpose, the
                 knowledge representation branch of AI proposes
                 Knowledge Graphs, widely used in the Semantic Web,
                 where different online applications may interact by
                 understanding the meaning of the data they process and
                 exchange. This paper describes a framework and online
                 platform for the Internet-based knowledge graph
                 definition, population, and exploitation based on the
                 LPG graph model. Its main advantages are its efficiency
                 and representational power and the wide range of
                 functions that it provides to its users beyond
                 traditional Semantic Web reasoning: network analysis,
                 data mining, multistrategy reasoning, and knowledge
                 browsing. Still, it can also be mapped onto the SW.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Koulianos:2023:BTS,
  author =       "Athanasios Koulianos and Antonios Litke",
  title =        "Blockchain Technology for Secure Communication and
                 Formation Control in Smart Drone Swarms",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "10",
  pages =        "344",
  day =          "19",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15100344",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 3 09:03:57 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/10/344",
  abstract =     "Today, intelligent drone technology is rapidly
                 expanding, particularly in the defense industry. A
                 swarm of drones can communicate, share data, and make
                 the best decisions on their own. Drone swarms can
                 swiftly and effectively carry out missions like
                 surveillance, reconnaissance, and rescue operations,
                 without exposing military troops to hostile conditions.
                 However, there are still significant problems that need
                 to be resolved. One of them is to protect
                 communications on these systems from threat actors. In
                 this paper, we use blockchain technology as a defense
                 mechanism against such issues. Drones can communicate
                 data safely, without the need for a centralized
                 authority (ground station), when using a blockchain to
                 facilitate communication between them in a
                 leader--follower hierarchy structure. Solidity has been
                 used to create a compact, lightweight, and effective
                 smart contract that automates the process of choosing a
                 position in a certain swarm formation structure.
                 Additionally, a mechanism for electing a new leader is
                 proposed. The effectiveness of the presented model is
                 assessed through a simulation that makes use of a DApp
                 we created and Gazebo software. The purpose of this
                 work is to develop a reliable and secure UAV swarm
                 communication system that will enable widespread global
                 adoption by numerous sectors.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{AlQahtani:2023:TOC,
  author =       "Salman Ali AlQahtani",
  title =        "Towards an Optimal Cloud-Based Resource Management
                 Framework for Next-Generation {Internet} with
                 Multi-Slice Capabilities",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "10",
  pages =        "343",
  day =          "19",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15100343",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 3 09:03:57 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/10/343",
  abstract =     "With the advent of 5G networks, the demand for
                 improved mobile broadband, massive machine-type
                 communication, and ultra-reliable, low-latency
                 communication has surged, enabling a wide array of new
                 applications. A key enabling technology in 5G networks
                 is network slicing, which allows the creation of
                 multiple virtual networks to support various use cases
                 on a unified physical network. However, the limited
                 availability of radio resources in the 5G cloud-Radio
                 Access Network (C-RAN) and the ever-increasing data
                 traffic volume necessitate efficient resource
                 allocation algorithms to ensure quality of service
                 (QoS) for each network slice. This paper proposes an
                 Adaptive Slice Allocation (ASA) mechanism for the 5G
                 C-RAN, designed to dynamically allocate resources and
                 adapt to changing network conditions and traffic delay
                 tolerances. The ASA system incorporates slice admission
                 control and dynamic resource allocation to maximize
                 network resource efficiency while meeting the QoS
                 requirements of each slice. Through extensive
                 simulations, we evaluate the ASA system's performance
                 in terms of resource consumption, average waiting time,
                 and total blocking probability. Comparative analysis
                 with a popular static slice allocation (SSA) approach
                 demonstrates the superiority of the ASA system in
                 achieving a balanced utilization of system resources,
                 maintaining slice isolation, and provisioning QoS. The
                 results highlight the effectiveness of the proposed ASA
                 mechanism in optimizing future internet connectivity
                 within the context of 5G C-RAN, paving the way for
                 enhanced network performance and improved user
                 experiences.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Spiekermann:2023:CNF,
  author =       "Daniel Spiekermann and J{\"o}rg Keller",
  title =        "Challenges of Network Forensic Investigation in Fog
                 and Edge Computing",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "10",
  pages =        "342",
  day =          "18",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15100342",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 3 09:03:57 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/10/342",
  abstract =     "While network forensics has matured over the decades
                 and even made progress in the last 10 years when
                 deployed in virtual networks, network forensics in fog
                 and edge computing is still not progressed to that
                 level despite the now widespread use of these
                 paradigms. By using an approach similar to software
                 testing, i.e., a mixture of systematic and experience,
                 we analyze obstacles specific to forensics in fog and
                 edge computing such as spatial dispersion and possibly
                 incomplete recordings, and derive how far these
                 obstacles can be overcome by adapting processes and
                 techniques from other branches of network forensics,
                 and how new solutions could look otherwise. In
                 addition, we present a discussion of open problems of
                 network forensics in fog and edge environments and
                 discusses the challenges for an investigator.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gratsos:2023:KAD,
  author =       "Konstantinos Gratsos and Stefanos Ougiaroglou and
                 Dionisis Margaris",
  title =        "{kClusterHub}: an {AutoML}-Driven Tool for Effortless
                 Partition-Based Clustering over Varied Data Types",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "10",
  pages =        "341",
  day =          "18",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15100341",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 3 09:03:57 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/10/341",
  abstract =     "Partition-based clustering is widely applied over
                 diverse domains. Researchers and practitioners from
                 various scientific disciplines engage with
                 partition-based algorithms relying on specialized
                 software or programming libraries. Addressing the need
                 to bridge the knowledge gap associated with these
                 tools, this paper introduces kClusterHub, an
                 AutoML-driven web tool that simplifies the execution of
                 partition-based clustering over numerical, categorical
                 and mixed data types, while facilitating the
                 identification of the optimal number of clusters, using
                 the elbow method. Through automatic feature analysis,
                 kClusterHub selects the most appropriate algorithm from
                 the trio of k-means, k-modes, and k-prototypes. By
                 empowering users to seamlessly upload datasets and
                 select features, kClusterHub selects the algorithm,
                 provides the elbow graph, recommends the optimal number
                 of clusters, executes clustering, and presents the
                 cluster assignment, through tabular representations and
                 exploratory plots. Therefore, kClusterHub reduces the
                 need for specialized software and programming skills,
                 making clustering more accessible to non-experts. For
                 further enhancing its utility, kClusterHub integrates a
                 REST API to support the programmatic execution of
                 cluster analysis. The paper concludes with an
                 evaluation of kClusterHub's usability via the System
                 Usability Scale and CPU performance experiments. The
                 results emerge that kClusterHub is a streamlined,
                 efficient and user-friendly AutoML-inspired tool for
                 cluster analysis.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kuantama:2023:FWB,
  author =       "Endrowednes Kuantama and Avishkar Seth and Alice James
                 and Yihao Zhang",
  title =        "Flying Watchdog-Based Guard Patrol with Check Point
                 Data Verification",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "10",
  pages =        "340",
  day =          "16",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15100340",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 3 09:03:57 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/10/340",
  abstract =     "The effectiveness of human security-based guard patrol
                 systems often faces challenges related to the
                 consistency of perimeter checks regarding timing and
                 patterns. Some solutions use autonomous drones for
                 monitoring assistance but primarily optimize their
                 camera-based object detection capabilities for
                 favorable lighting conditions. This research introduces
                 an innovative approach to address these limitations---a
                 flying watchdog designed to augment patrol operations
                 with predetermined flight patterns, enabling checkpoint
                 identification and position verification through
                 vision-based methods. The system has a laser-based data
                 transmitter to relay real-time location and timing
                 information to a receiver. The proposed system consists
                 of drone and ground checkpoints with distinctive shapes
                 and colored lights, further enhanced by solar panels
                 serving as laser data receivers. The result
                 demonstrates the drone's ability to detect four white
                 dot LEDs with square configurations at distances
                 ranging from 18 to 20 m, even under deficient light
                 conditions based on the OpenCV detection algorithm.
                 Notably, the study underscores the significance of
                 achieving an even distribution of light shapes to
                 mitigate light scattering effects on readings while
                 also confirming that ambient light levels up to a
                 maximum of 390 Lux have no adverse impact on the
                 performance of the sensing device.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bayu:2023:RLA,
  author =       "Teguh Indra Bayu and Yung-Fa Huang and Jeang-Kuo
                 Chen",
  title =        "Reinforcement Learning Approach for Adaptive {C-V2X}
                 Resource Management",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "10",
  pages =        "339",
  day =          "15",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15100339",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 3 09:03:57 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/10/339",
  abstract =     "The modulation coding scheme (MCS) index is the
                 essential configuration parameter in cellular
                 vehicle-to-everything (C-V2X) communication. As
                 referenced by the 3rd Generation Partnership Project
                 (3GPP), the MCS index will dictate the transport block
                 size (TBS) index, which will affect the size of
                 transport blocks and the number of physical resource
                 blocks. These numbers are crucial in the C-V2X resource
                 management since it is also bound to the transmission
                 power used in the system. To the authors' knowledge,
                 this particular area of research has not been
                 previously investigated. Ultimately, this research
                 establishes the fundamental principles for future
                 studies seeking to use the MCS adaptability in many
                 contexts. In this work, we proposed the application of
                 the reinforcement learning (RL) algorithm, as we used
                 the Q-learning approach to adaptively change the MCS
                 index according to the current environmental states.
                 The simulation results showed that our proposed RL
                 approach outperformed the static MCS index and was able
                 to attain stability in a short number of events.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2023:FDQ,
  author =       "Meng Li and Jiqiang Liu and Yeping Yang",
  title =        "Financial Data Quality Evaluation Method Based on
                 Multiple Linear Regression",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "10",
  pages =        "338",
  day =          "14",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15100338",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 3 09:03:57 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/10/338",
  abstract =     "With the rapid growth of customer data in financial
                 institutions, such as trusts, issues of data quality
                 have become increasingly prominent. The main challenge
                 lies in constructing an effective evaluation method
                 that ensures accurate and efficient assessment of
                 customer data quality when dealing with massive
                 customer data. In this paper, we construct a data
                 quality evaluation index system based on the analytic
                 hierarchy process through a comprehensive investigation
                 of existing research on data quality. Then, redundant
                 features are filtered based on the Shapley value, and
                 the multiple linear regression model is employed to
                 adjust the weight of different indices. Finally, a case
                 study of the customer and institution information of a
                 trust institution is conducted. The results demonstrate
                 that the utilization of completeness, accuracy,
                 timeliness, consistency, uniqueness, and compliance to
                 establish a quality evaluation index system proves
                 instrumental in conducting extensive and in-depth
                 research on data quality measurement dimensions.
                 Additionally, the data quality evaluation approach
                 based on multiple linear regression facilitates the
                 batch scoring of data, and the incorporation of the
                 Shapley value facilitates the elimination of invalid
                 features. This enables the intelligent evaluation of
                 large-scale data quality for financial data.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Shen:2023:ECB,
  author =       "Tsu-Chuan Shen and Edward T.-H. Chu",
  title =        "Edge-Computing-Based People-Counting System for
                 Elevators Using {MobileNet}--Single-Stage Object
                 Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "10",
  pages =        "337",
  day =          "14",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15100337",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 3 09:03:57 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/10/337",
  abstract =     "Existing elevator systems lack the ability to display
                 the number of people waiting on each floor and inside
                 the elevator. This causes an inconvenience as users
                 cannot tell if they should wait or seek alternatives,
                 leading to unnecessary time wastage. In this work, we
                 adopted edge computing by running the
                 MobileNet--Single-Stage Object Detection (SSD)
                 algorithm on edge devices to recognize the number of
                 people inside an elevator and waiting on each floor. To
                 ensure the accuracy of people counting, we fine-tuned
                 the SSD parameters, such as the recognition frequency
                 and confidence thresholds, and utilized the line of
                 interest (LOI) counting strategy for people counting.
                 In our experiment, we deployed four NVIDIA Jetson Nano
                 boards in a four-floor building as edge devices to
                 count people when they entered specific areas. The
                 counting results, such as the number of people waiting
                 on each floor and inside the elevator, were provided to
                 users through a web app. Our experimental results
                 demonstrate that the proposed method achieved an
                 average accuracy of 85\% for people counting.
                 Furthermore, when comparing it to sending all images
                 back to a remote server for people counting, the
                 execution time required for edge computing was shorter,
                 without compromising the accuracy significantly.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lozic:2023:FFC,
  author =       "Edisa Lozi{\'c} and Benjamin Stular",
  title =        "Fluent but Not Factual: a Comparative Analysis of
                 {ChatGPT} and Other {AI} Chatbots' Proficiency and
                 Originality in Scientific Writing for Humanities",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "10",
  pages =        "336",
  day =          "13",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15100336",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 3 09:03:57 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/10/336",
  abstract =     "Historically, mastery of writing was deemed essential
                 to human progress. However, recent advances in
                 generative AI have marked an inflection point in this
                 narrative, including for scientific writing. This
                 article provides a comprehensive analysis of the
                 capabilities and limitations of six AI chatbots in
                 scholarly writing in the humanities and archaeology.
                 The methodology was based on tagging AI-generated
                 content for quantitative accuracy and qualitative
                 precision by human experts. Quantitative accuracy
                 assessed the factual correctness in a manner similar to
                 grading students, while qualitative precision gauged
                 the scientific contribution similar to reviewing a
                 scientific article. In the quantitative test, ChatGPT-4
                 scored near the passing grade ({-5}) whereas
                 ChatGPT-3.5 ({-18}), Bing ({-21}) and Bard ({-31}) were
                 not far behind. Claude 2 ({-75}) and Aria ({-80})
                 scored much lower. In the qualitative test, all AI
                 chatbots, but especially ChatGPT-4, demonstrated
                 proficiency in recombining existing knowledge, but all
                 failed to generate original scientific content. As a
                 side note, our results suggest that with ChatGPT-4, the
                 size of large language models has reached a plateau.
                 Furthermore, this paper underscores the intricate and
                 recursive nature of human research. This process of
                 transforming raw data into refined knowledge is
                 computationally irreducible, highlighting the
                 challenges AI chatbots face in emulating human
                 originality in scientific writing. Our results apply to
                 the state of affairs in the third quarter of 2023. In
                 conclusion, while large language models have
                 revolutionised content generation, their ability to
                 produce original scientific contributions in the
                 humanities remains limited. We expect this to change in
                 the near future as current large language model-based
                 AI chatbots evolve into large language model-powered
                 software.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gonzalez-Franco:2023:CSL,
  author =       "Joan D. Gonzalez-Franco and Jorge E. Preciado-Velasco
                 and Jose E. Lozano-Rizk and Raul Rivera-Rodriguez and
                 Jorge Torres-Rodriguez and Miguel A. Alonso-Arevalo",
  title =        "Comparison of Supervised Learning Algorithms on a {5G}
                 Dataset Reduced via Principal Component Analysis
                 ({PCA})",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "10",
  pages =        "335",
  day =          "11",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15100335",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 3 09:03:57 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/10/335",
  abstract =     "Improving the quality of service (QoS) and meeting
                 service level agreements (SLAs) are critical objectives
                 in next-generation networks. This article presents a
                 study on applying supervised learning (SL) algorithms
                 in a 5G/B5G service dataset after being subjected to a
                 principal component analysis (PCA). The study objective
                 is to evaluate if the reduction of the dimensionality
                 of the dataset via PCA affects the predictive capacity
                 of the SL algorithms. A machine learning (ML) scheme
                 proposed in a previous article used the same algorithms
                 and parameters, which allows for a fair comparison with
                 the results obtained in this work. We searched the best
                 hyperparameters for each SL algorithm, and the
                 simulation results indicate that the support vector
                 machine (SVM) algorithm obtained a precision of 98\%
                 and a F1 score of 98.1\%. We concluded that the
                 findings of this study hold significance for research
                 in the field of next-generation networks, which involve
                 a wide range of input parameters and can benefit from
                 the application of principal component analysis (PCA)
                 on the performance of QoS and maintaining the SLA.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Singh:2023:OMT,
  author =       "Satyanand Singh and Joanna Rosak-Szyrocka and
                 Istv{\'a}n Drot{\'a}r and Xavier Fernando",
  title =        "{Oceania}'s {5G} Multi-Tier Fixed Wireless Access
                 {Link}'s Long-Term Resilience and Feasibility
                 Analysis",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "10",
  pages =        "334",
  day =          "10",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15100334",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 3 09:03:57 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/10/334",
  abstract =     "Information and communications technologies play a
                 vital role in achieving the Sustainable Development
                 Goals (SDGs) and bridging the gap between developed and
                 developing countries. However, various socioeconomic
                 factors adversely impact the deployment of digital
                 infrastructure, such as 5G networks, in the countries
                 of Oceania. The high-speed broadband fifth-generation
                 cellular network (5G) will improve the quality of
                 service for growing mobile users and the massive
                 Internet of Things (IoT). It will also provide
                 ultra-low-latency services required by smart city
                 applications. This study investigates the planning
                 process for a 5G radio access network incorporating
                 sub-6 GHz macro-remote radio units (MRRUs) and mmWave
                 micro-remote radio units (mRRUs). We carefully define
                 an optimization problem for 5G network planning,
                 considering the characteristics of urban macro-cells
                 (UMa) and urban micro-cells (UMi) with appropriate
                 channel models and link budgets. We determine the
                 minimum number of MRRUs and mRRUs that can be installed
                 in each area while meeting coverage and user traffic
                 requirements. This will ensure adequate broadband
                 low-latency network coverage with micro-cells instead
                 of macro-cells. This study evaluates the technical
                 feasibility analysis of combining terrestrial and
                 airborne networks to provide 5G coverage in Oceania,
                 with a special emphasis on Fiji.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Elwy:2023:DDS,
  author =       "Fatema Elwy and Raafat Aburukba and A. R. Al-Ali and
                 Ahmad {Al Nabulsi} and Alaa Tarek and Ameen Ayub and
                 and Mariam Elsayeh",
  title =        "Data-Driven Safe Deliveries: The Synergy of {IoT} and
                 Machine Learning in Shared Mobility",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "10",
  pages =        "333",
  day =          "10",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15100333",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 3 09:03:57 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/10/333",
  abstract =     "Shared mobility is one of the smart city applications
                 in which traditional individually owned vehicles are
                 transformed into shared and distributed ownership.
                 Ensuring the safety of both drivers and riders is a
                 fundamental requirement in shared mobility. This work
                 aims to design and implement an adequate framework for
                 shared mobility within the context of a smart city. The
                 characteristics of shared mobility are identified,
                 leading to the proposal of an effective solution for
                 real-time data collection, tracking, and automated
                 decisions focusing on safety. Driver and rider safety
                 is considered by identifying dangerous driving
                 behaviors and the prompt response to accidents.
                 Furthermore, a trip log is recorded to identify the
                 reasons behind the accident. A prototype implementation
                 is presented to validate the proposed framework for a
                 delivery service using motorbikes. The results
                 demonstrate the scalability of the proposed design and
                 the integration of the overall system to enhance the
                 rider's safety using machine learning techniques. The
                 machine learning approach identifies dangerous driving
                 behaviors with an accuracy of 91.59\% using the
                 decision tree approach when compared against the
                 support vector machine and K-nearest neighbor
                 approaches.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Khoei:2023:MLM,
  author =       "Tala Talaei Khoei and Naima Kaabouch",
  title =        "Machine Learning: Models, Challenges, and Research
                 Directions",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "10",
  pages =        "332",
  day =          "09",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15100332",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 3 09:03:57 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/10/332",
  abstract =     "Machine learning techniques have emerged as a
                 transformative force, revolutionizing various
                 application domains, particularly cybersecurity. The
                 development of optimal machine learning applications
                 requires the integration of multiple processes, such as
                 data pre-processing, model selection, and parameter
                 optimization. While existing surveys have shed light on
                 these techniques, they have mainly focused on specific
                 application domains. A notable gap that exists in
                 current studies is the lack of a comprehensive overview
                 of machine learning architecture and its essential
                 phases in the cybersecurity field. To address this gap,
                 this survey provides a holistic review of current
                 studies in machine learning, covering techniques
                 applicable to any domain. Models are classified into
                 four categories: supervised, semi-supervised,
                 unsupervised, and reinforcement learning. Each of these
                 categories and their models are described. In addition,
                 the survey discusses the current progress related to
                 data pre-processing and hyperparameter tuning
                 techniques. Moreover, this survey identifies and
                 reviews the research gaps and key challenges that the
                 cybersecurity field faces. By analyzing these gaps, we
                 propose some promising research directions for the
                 future. Ultimately, this survey aims to serve as a
                 valuable resource for researchers interested in
                 learning about machine learning, providing them with
                 insights to foster innovation and progress across
                 diverse application domains.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Abdelreheim:2023:POR,
  author =       "Marwa Abdelreheim and Taysir Hassan A. Soliman and
                 Friederike Klan",
  title =        "A Personalized Ontology Recommendation System to
                 Effectively Support Ontology Development by Reuse",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "10",
  pages =        "331",
  day =          "07",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15100331",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 3 09:03:57 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/10/331",
  abstract =     "The profusion of existing ontologies in different
                 domains has made reusing ontologies a best practice
                 when developing new ontologies. The ontology reuse
                 process reduces the expensive cost of developing a new
                 ontology, in terms of time and effort, and supports
                 semantic interoperability. Existing ontology
                 development tools do not assist in the recommendation
                 of ontologies or their concepts to be reused. Also,
                 existing ontology recommendation tools could suggest
                 whole ontologies covering a set of input keywords
                 without referring to which parts of them (e.g.,
                 concepts) can be reused. In this paper, we propose an
                 effective ontology recommendation system that helps the
                 user in the iterative development and reuse of
                 ontologies. The system allows the user to provide
                 explicit preferences about the new ontology, and
                 iteratively guides the user to parts from existing
                 ontologies which match his preferences for reuse.
                 Finally, we developed a prototype of our ontology
                 recommendation system and conducted a user-based
                 evaluation to assess the effectiveness of our
                 approach.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Grigaliunas:2023:LTE,
  author =       "Sarunas Grigaliunas and Michael Schmidt and Rasa
                 Bruzgiene and Panayiota Smyrli and Vladislav Bidikov",
  title =        "Leveraging Taxonomical Engineering for Security
                 Baseline Compliance in International Regulatory
                 Frameworks",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "10",
  pages =        "330",
  day =          "07",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15100330",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 3 09:03:57 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/10/330",
  abstract =     "A surge in successful Information Security (IS)
                 breaches targeting Research and Education (R\&E)
                 institutions highlights a pressing need for enhanced
                 protection. Addressing this, a consortium of European
                 National Research and Education Network (NREN)
                 organizations has developed a unified IS framework.
                 This paper aims to introduce the Security Baseline for
                 NRENs and a security maturity model tailored for R\&E
                 entities, derived from established security best
                 practices to meet the specific needs of NRENs,
                 universities, and various research institutions. The
                 models currently in existence do not possess a system
                 to smoothly correlate varying requirement tiers with
                 distinct user groups or scenarios, baseline standards,
                 and existing legislative actions. This segmentation
                 poses a significant hurdle to the community's capacity
                 to guarantee consistency, congruency, and thorough
                 compliance with a cohesive array of security standards
                 and regulations. By employing taxonomical engineering
                 principles, a mapping of baseline requirements to other
                 security frameworks and regulations has been
                 established. This reveals a correlation across most
                 regulations impacting R\&E institutions and uncovers an
                 overlap in the high-level requirements, which is
                 beneficial for the implementation of multiple
                 standards. Consequently, organizations can
                 systematically compare diverse security requirements,
                 pinpoint gaps in their strategy, and formulate a
                 roadmap to bolster their security initiatives.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kabashkin:2023:EES,
  author =       "Igor Kabashkin",
  title =        "End-to-End Service Availability in Heterogeneous
                 Multi-Tier Cloud--Fog--Edge Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "10",
  pages =        "329",
  day =          "06",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15100329",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 3 09:03:57 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/10/329",
  abstract =     "With the evolution towards the interconnected future
                 internet spanning satellites, aerial systems,
                 terrestrial infrastructure, and oceanic networks,
                 availability modeling becomes imperative to ensure
                 reliable service. This paper presents a methodology to
                 assess end-to-end availability in complex multi-tiered
                 architectures using a Markov model tailored to the
                 unique characteristics of cloud, fog, edge, and IoT
                 layers. By quantifying individual tier reliability and
                 combinations thereof, the approach enables setting
                 availability targets during the design and evaluation
                 of operational systems. In the paper, a methodology is
                 proposed to construct a Markov model for the
                 reliability of discrete tiers and end-to-end service
                 availability in heterogeneous multi-tier
                 cloud--fog--edge networks, and the model is
                 demonstrated through numerical examples assessing
                 availability in multi-tier networks. The numerical
                 examples demonstrate the adaptability of the model to
                 various topologies from conventional three-tier to
                 arbitrary multi-level architectures. As connectivity
                 becomes ubiquitous across heterogeneous devices and
                 networks, the proposed approach and availability
                 modeling provide an effective tool for reinforcing the
                 future internet's fault tolerance and service
                 quality.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Luczak:2023:EMC,
  author =       "Lukasz Piotr Luczak and Przemys{\l}aw Ignaciuk and
                 Micha{\l} Morawski",
  title =        "Evaluating {MPTCP} Congestion Control Algorithms:
                 Implications for Streaming in Open {Internet}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "10",
  pages =        "328",
  day =          "04",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15100328",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 3 09:03:57 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/10/328",
  abstract =     "In today's digital era, the demand for uninterrupted
                 and efficient data streaming is paramount across
                 various sectors, from entertainment to industrial
                 automation. While the traditional single-path solutions
                 often fell short in ensuring rapid and consistent data
                 transfers, Multipath TCP (MPTCP) emerges as a promising
                 alternative, enabling simultaneous data transfer across
                 multiple network paths. The efficacy of MPTCP, however,
                 hinges on the choice of appropriate congestion control
                 (CC) algorithms. Addressing the present knowledge gap,
                 this research provides a thorough evaluation of key
                 MPTCP CC algorithms in the context of streaming
                 applications in open Internet environments. Our
                 findings reveal that BALIA stands out as the most
                 suitable choice for MPTCP streaming, adeptly balancing
                 waiting time, throughput, and Head-of-Line blocking
                 reduction. Conversely, the wVegas algorithm, with its
                 delay-centric approach, proves less adequate for
                 multipath streaming. This study underscores the
                 imperative to fine-tune MPTCP for streaming
                 applications, at the same time offering insights for
                 future development areas and innovations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yu:2023:MMS,
  author =       "Yong Yu and Shudong Chen and Rong Du and Da Tong and
                 Hao Xu and Shuai Chen",
  title =        "{MSEN}: a Multi-Scale Evolutionary Network for
                 Modeling the Evolution of Temporal Knowledge Graphs",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "10",
  pages =        "327",
  day =          "30",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15100327",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 3 09:03:57 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/10/327",
  abstract =     "Temporal knowledge graphs play an increasingly
                 prominent role in scenarios such as social networks,
                 finance, and smart cities. As such, research on
                 temporal knowledge graphs continues to deepen. In
                 particular, research on temporal knowledge graph
                 reasoning holds great significance, as it can provide
                 abundant knowledge for downstream tasks such as
                 question answering and recommendation systems. Current
                 reasoning research focuses primarily on interpolation
                 and extrapolation. Extrapolation research aims to
                 predict the likelihood of events occurring in future
                 timestamps. Historical events are crucial for
                 predicting future events. However, existing models
                 struggle to fully capture the evolutionary
                 characteristics of historical knowledge graphs. This
                 paper proposes a multi-scale evolutionary network
                 (MSEN) model that leverages Hierarchical Transfer aware
                 Graph Neural Network (HT-GNN) in a local memory encoder
                 to aggregate rich structural semantics from each
                 timestamp's knowledge graph. It also utilizes Time
                 Related Graph Neural Network (TR-GNN) in a global
                 memory encoder to model temporal-semantic dependencies
                 of entities across the global knowledge graph, mining
                 global evolutionary patterns. The model integrates
                 information from both encoders to generate entity
                 embeddings for predicting future events. The proposed
                 MSEN model demonstrates strong performance compared to
                 several baselines on typical benchmark datasets.
                 Results show MSEN achieves the highest prediction
                 accuracy.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Szabo:2023:NAW,
  author =       "Zolt{\'a}n Szab{\'o} and Vilmos Bilicki",
  title =        "A New Approach to {Web} Application Security:
                 Utilizing {GPT} Language Models for Source Code
                 Inspection",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "10",
  pages =        "326",
  day =          "28",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15100326",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 3 09:03:57 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/10/326",
  abstract =     "Due to the proliferation of large language models
                 (LLMs) and their widespread use in applications such as
                 ChatGPT, there has been a significant increase in
                 interest in AI over the past year. Multiple researchers
                 have raised the question: how will AI be applied and in
                 what areas? Programming, including the generation,
                 interpretation, analysis, and documentation of static
                 program code based on prompts is one of the most
                 promising fields. With the GPT API, we have explored a
                 new aspect of this: static analysis of the source code
                 of front-end applications at the endpoints of the data
                 path. Our focus was the detection of the CWE-653
                 vulnerability---inadequately isolated sensitive code
                 segments that could lead to unauthorized access or data
                 leakage. This type of vulnerability detection consists
                 of the detection of code segments dealing with
                 sensitive data and the categorization of the isolation
                 and protection levels of those segments that were
                 previously not feasible without human intervention.
                 However, we believed that the interpretive capabilities
                 of GPT models could be explored to create a set of
                 prompts to detect these cases on a file-by-file basis
                 for the applications under study, and the efficiency of
                 the method could pave the way for additional analysis
                 tasks that were previously unavailable for automation.
                 In the introduction to our paper, we characterize in
                 detail the problem space of vulnerability and weakness
                 detection, the challenges of the domain, and the
                 advances that have been achieved in similarly complex
                 areas using GPT or other LLMs. Then, we present our
                 methodology, which includes our classification of
                 sensitive data and protection levels. This is followed
                 by the process of preprocessing, analyzing, and
                 evaluating static code. This was achieved through a
                 series of GPT prompts containing parts of static source
                 code, utilizing few-shot examples and chain-of-thought
                 techniques that detected sensitive code segments and
                 mapped the complex code base into manageable JSON
                 structures.Finally, we present our findings and
                 evaluation of the open source project analysis,
                 comparing the results of the GPT-based pipelines with
                 manual evaluations, highlighting that the field yields
                 a high research value. The results show a vulnerability
                 detection rate for this particular type of model of
                 88.76\%, among others.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lockett:2023:IIM,
  author =       "Adam Lockett and Ioannis Chalkias and Cagatay Yucel
                 and Jane Henriksen-Bulmer and Vasilis Katos",
  title =        "Investigating {IPTV} Malware in the Wild",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "10",
  pages =        "325",
  day =          "28",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15100325",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 3 09:03:57 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/10/325",
  abstract =     "Technologies providing copyright-infringing IPTV
                 content are commonly used as an illegal alternative to
                 legal IPTV subscriptions and services, as they usually
                 have lower monetary costs and can be more convenient
                 for users who follow content from different sources.
                 These infringing IPTV technologies may include
                 websites, software, software add-ons, and physical
                 set-top boxes. Due to the free or low cost of illegal
                 IPTV technologies, illicit IPTV content providers will
                 often resort to intrusive advertising, scams, and the
                 distribution of malware to increase their revenue. We
                 developed an automated solution for collecting and
                 analysing malware from illegal IPTV technologies and
                 used it to analyse a sample of illicit IPTV websites,
                 application (app) stores, and software. Our results
                 show that our IPTV Technologies Malware Analysis
                 Framework (IITMAF) classified 32 of the 60 sample URLs
                 tested as malicious compared to running the same test
                 using publicly available online antivirus solutions,
                 which only detected 23 of the 60 sample URLs as
                 malicious. Moreover, the IITMAF also detected malicious
                 URLs and files from 31 of the sample's websites, one of
                 which had reported ransomware behaviour.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Cheimonidis:2023:DRA,
  author =       "Pavlos Cheimonidis and Konstantinos Rantos",
  title =        "Dynamic Risk Assessment in Cybersecurity: a Systematic
                 Literature Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "10",
  pages =        "324",
  day =          "28",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15100324",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 3 09:03:57 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/10/324",
  abstract =     "Traditional information security risk assessment (RA)
                 methodologies and standards, adopted by information
                 security management systems and frameworks as a
                 foundation stone towards robust environments, face many
                 difficulties in modern environments where the threat
                 landscape changes rapidly and new vulnerabilities are
                 being discovered. In order to overcome this problem,
                 dynamic risk assessment (DRA) models have been proposed
                 to continuously and dynamically assess risks to
                 organisational operations in (near) real time. The aim
                 of this work is to analyse the current state of DRA
                 models that have been proposed for cybersecurity,
                 through a systematic literature review. The screening
                 process led us to study 50 DRA models, categorised
                 based on the respective primary analysis methods they
                 used. The study provides insights into the key
                 characteristics of these models, including the maturity
                 level of the examined models, the domain or application
                 area in which these models flourish, and the
                 information they utilise in order to produce results.
                 The aim of this work is to answer critical research
                 questions regarding the development of dynamic risk
                 assessment methodologies and provide insights on the
                 already developed methods as well as future research
                 directions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chen:2023:TGK,
  author =       "Chin-Yi Chen and Jih-Jeng Huang",
  title =        "Temporal-Guided Knowledge Graph-Enhanced Graph
                 Convolutional Network for Personalized Movie
                 Recommendation Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "10",
  pages =        "323",
  day =          "28",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15100323",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 3 09:03:57 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/10/323",
  abstract =     "Traditional movie recommendation systems are
                 increasingly falling short in the contemporary
                 landscape of abundant information and evolving user
                 behaviors. This study introduced the temporal knowledge
                 graph recommender system (TKGRS), a ground-breaking
                 algorithm that addresses the limitations of existing
                 models. TKGRS uniquely integrates graph convolutional
                 networks (GCNs), matrix factorization, and temporal
                 decay factors to offer a robust and dynamic
                 recommendation mechanism. The algorithm's architecture
                 comprises an initial embedding layer for identifying
                 the user and item, followed by a GCN layer for a
                 nuanced understanding of the relationships and fully
                 connected layers for prediction. A temporal decay
                 factor is also used to give weightage to recent
                 user--item interactions. Empirical validation using the
                 MovieLens 100K, 1M, and Douban datasets showed that
                 TKGRS outperformed the state-of-the-art models
                 according to the evaluation metrics, i.e., RMSE and
                 MAE. This innovative approach sets a new standard in
                 movie recommendation systems and opens avenues for
                 future research in advanced graph algorithms and
                 machine learning techniques.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chung:2023:AEH,
  author =       "Yao-Liang Chung",
  title =        "Application of an Effective Hierarchical
                 Deep-Learning-Based Object Detection Model Integrated
                 with Image-Processing Techniques for Detecting Speed
                 Limit Signs, Rockfalls, Potholes, and Car Crashes",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "10",
  pages =        "322",
  day =          "28",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15100322",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 3 09:03:57 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/10/322",
  abstract =     "Against the backdrop of rising road traffic accident
                 rates, measures to prevent road traffic accidents have
                 always been a pressing issue in Taiwan. Road traffic
                 accidents are mostly caused by speeding and roadway
                 obstacles, especially in the form of rockfalls,
                 potholes, and car crashes (involving damaged cars and
                 overturned cars). To address this, it was necessary to
                 design a real-time detection system that could detect
                 speed limit signs, rockfalls, potholes, and car
                 crashes, which would alert drivers to make timely
                 decisions in the event of an emergency, thereby
                 preventing secondary car crashes. This system would
                 also be useful for alerting the relevant authorities,
                 enabling a rapid response to the situation. In this
                 study, a hierarchical deep-learning-based object
                 detection model is proposed based on You Only Look Once
                 v7 (YOLOv7) and mask region-based convolutional neural
                 network (Mask R-CNN) algorithms. In the first level,
                 YOLOv7 identifies speed limit signs and rockfalls,
                 potholes, and car crashes. In the second level, Mask
                 R-CNN subdivides the speed limit signs into nine
                 categories (30, 40, 50, 60, 70, 80, 90, 100, and 110
                 km/h). The images used in this study consisted of
                 screen captures of dashcam footage as well as images
                 obtained from the Tsinghua-Tencent 100K dataset, Google
                 Street View, and Google Images searches. During model
                 training, we employed Gaussian noise and image rotation
                 to simulate poor weather conditions as well as
                 obscured, slanted, or twisted objects. Canny edge
                 detection was used to enhance the contours of the
                 detected objects and accentuate their features. The
                 combined use of these image-processing techniques
                 effectively increased the quantity and variety of
                 images in the training set. During model testing, we
                 evaluated the model's performance based on its mean
                 average precision (mAP). The experimental results
                 showed that the mAP of our proposed model was 8.6
                 percentage points higher than that of the YOLOv7
                 model---a significant improvement in the overall
                 accuracy of the model. In addition, we tested the model
                 using videos showing different scenarios that had not
                 been used in the training process, finding the model to
                 have a rapid response time and a lower overall mean
                 error rate. To summarize, the proposed model is a good
                 candidate for road safety detection.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mohammed:2023:EFA,
  author =       "Medina Ayta Mohammed and Carmen De-Pablos-Heredero and
                 and Jos{\'e} Luis Montes Botella",
  title =        "Exploring the Factors Affecting Countries' Adoption of
                 Blockchain-Enabled Central Bank Digital Currencies",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "10",
  pages =        "321",
  day =          "28",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15100321",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 3 09:03:57 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/10/321",
  abstract =     "Central bank-issued digital currencies have sparked
                 significant interest and are currently the subject of
                 extensive research, owing to their potential for rapid
                 settlement, low fees, accessibility, and automated
                 monetary policies. However, central bank digital
                 currencies are still in their infancy and the levels of
                 adoption vary significantly between nations, with a few
                 countries seeing widespread adoption. We used partial
                 least squares structural equation modeling to
                 investigate the nonlinear relationship between key
                 national development indicators and central bank
                 digital deployment across 67 countries. We explore the
                 technological, environmental, legal, and economic
                 factors that affect central bank digital currency
                 adoption by country. We found a statistically
                 significant and positive correlation between countries'
                 central bank digital currency adoption status and a
                 country's level of democracy and public confidence in
                 governance, and a negative association between
                 regulatory quality and income inequality. There was no
                 significant association between countries' central bank
                 digital currency adoption status and their level of
                 network readiness, foreign exchange reserves, and
                 sustainable development goal rank. Thus, we posit that
                 a country that is highly democratic and has good
                 governance adopts central bank digital currencies more
                 readily than others. Based on our findings, we
                 suggested areas for additional research and highlighted
                 policy considerations related to the wider adoption of
                 central bank digital currency.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chen:2023:MAJ,
  author =       "Dechuan Chen and Jin Li and Jianwei Hu and Xingang
                 Zhang and Shuai Zhang",
  title =        "Multi-Antenna Jammer-Assisted Secure Short Packet
                 Communications in {IoT} Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "10",
  pages =        "320",
  day =          "26",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15100320",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 3 09:03:57 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/10/320",
  abstract =     "In this work, we exploit a multi-antenna cooperative
                 jammer to enable secure short packet communications in
                 Internet of Things (IoT) networks. Specifically, we
                 propose three jamming schemes to combat eavesdropping,
                 i.e., the zero forcing beamforming (ZFB) scheme,
                 null-space artificial noise (NAN) scheme, and transmit
                 antenna selection (TAS) scheme. Assuming Rayleigh
                 fading, we derive new closed-form approximations for
                 the secrecy throughput with finite blocklength coding.
                 To gain further insights, we also analyze the
                 asymptotic performance of the secrecy throughput in the
                 case of infinite blocklength. Furthermore, we
                 investigate the optimization problem in terms of
                 maximizing the secrecy throughput with the latency and
                 reliability constraints to determine the optimal
                 blocklength. Simulation results validate the accuracy
                 of the approximations and evaluate the impact of key
                 parameters such as the jamming power and the number of
                 antennas at the jammer on the secrecy throughput.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Borghesi:2023:MNF,
  author =       "Michela Borghesi and Cristian Zambelli and Rino
                 Micheloni and Stefano Bonnini",
  title =        "Modeling {3D} {NAND} Flash with Nonparametric
                 Inference on Regression Coefficients for Reliable
                 Solid-State Storage",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "10",
  pages =        "319",
  day =          "26",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15100319",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 3 09:03:57 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/10/319",
  abstract =     "Solid-state drives represent the preferred backbone
                 storage solution thanks to their low latency and high
                 throughput capabilities compared to mechanical hard
                 disk drives. The performance of a drive is intertwined
                 with the reliability of the memories; hence, modeling
                 their reliability is an important task to be performed
                 as a support for storage system designers. In the
                 literature, storage developers devise dedicated
                 parametric statistical approaches to model the
                 evolution of the memory's error distribution through
                 well-known statistical frameworks. Some of these
                 well-founded reliability models have a deep connection
                 with the 3D NAND flash technology. In fact, the more
                 precise and accurate the model, the less the
                 probability of incurring storage performance slowdowns.
                 In this work, to avoid some limitations of the
                 parametric methods, a non-parametric approach to test
                 the model goodness-of-fit based on combined permutation
                 tests is carried out. The results show that the
                 electrical characterization of different memory blocks
                 and pages tested provides an FBC feature that can be
                 well-modeled using a multiple regression analysis.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gazzan:2023:EML,
  author =       "Mazen Gazzan and Frederick T. Sheldon",
  title =        "An Enhanced Minimax Loss Function Technique in
                 Generative Adversarial Network for Ransomware Behavior
                 Prediction",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "10",
  pages =        "318",
  day =          "22",
  month =        sep,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15100318",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Nov 3 09:03:57 MDT 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/10/318",
  abstract =     "Recent ransomware attacks threaten not only personal
                 files but also critical infrastructure like smart
                 grids, necessitating early detection before encryption
                 occurs. Current methods, reliant on pre-encryption
                 data, suffer from insufficient and rapidly outdated
                 attack patterns, despite efforts to focus on select
                 features. Such an approach assumes that the same
                 features remain unchanged. This approach proves
                 ineffective due to the polymorphic and metamorphic
                 characteristics of ransomware, which generate unique
                 attack patterns for each new target, particularly in
                 the pre-encryption phase where evasiveness is
                 prioritized. As a result, the selected features quickly
                 become obsolete. Therefore, this study proposes an
                 enhanced Bi-Gradual Minimax (BGM) loss function for the
                 Generative Adversarial Network (GAN) Algorithm that
                 compensates for the attack patterns insufficiency to
                 represents the polymorphic behavior at the earlier
                 phases of the ransomware lifecycle. Unlike existing
                 GAN-based models, the BGM-GAN gradually minimizes the
                 maximum loss of the generator and discriminator in the
                 network. This allows the generator to create artificial
                 patterns that resemble the pre-encryption data
                 distribution. The generator is used to craft evasive
                 adversarial patterns and add them to the original data.
                 Then, the generator and discriminator compete to
                 optimize their weights during the training phase such
                 that the generator produces realistic attack patterns,
                 while the discriminator endeavors to distinguish
                 between the real and crafted patterns. The experimental
                 results show that the proposed BGM-GAN reached maximum
                 accuracy of 0.98, recall (0.96), and a minimum false
                 positive rate (0.14) which all outperform those
                 obtained by the existing works. The application of
                 BGM-GAN can be extended to early detect malware and
                 other types of attacks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Utomo:2023:FAT,
  author =       "Sapdo Utomo and Adarsh Rouniyar and Hsiu-Chun Hsu and
                 and Pao-Ann Hsiung",
  title =        "Federated Adversarial Training Strategies for
                 Achieving Privacy and Security in Sustainable Smart
                 City Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "11",
  pages =        "371",
  day =          "20",
  month =        nov,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15110371",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/11/371",
  abstract =     "Smart city applications that request sensitive user
                 information necessitate a comprehensive data privacy
                 solution. Federated learning (FL), also known as
                 privacy by design, is a new paradigm in machine
                 learning (ML). However, FL models are susceptible to
                 adversarial attacks, similar to other AI models. In
                 this paper, we propose federated adversarial training
                 (FAT) strategies to generate robust global models that
                 are resistant to adversarial attacks. We apply two
                 adversarial attack methods, projected gradient descent
                 (PGD) and the fast gradient sign method (FGSM), to our
                 air pollution dataset to generate adversarial samples.
                 We then evaluate the effectiveness of our FAT
                 strategies in defending against these attacks. Our
                 experiments show that FGSM-based adversarial attacks
                 have a negligible impact on the accuracy of global
                 models, while PGD-based attacks are more effective.
                 However, we also show that our FAT strategies can make
                 global models robust enough to withstand even PGD-based
                 attacks. For example, the accuracy of our FAT-PGD and
                 FL-mixed-PGD models is 81.13\% and 82.60\%,
                 respectively, compared to 91.34\% for the baseline FL
                 model. This represents a reduction in accuracy of 10\%,
                 but this could be potentially mitigated by using a more
                 complex and larger model. Our results demonstrate that
                 FAT can enhance the security and privacy of sustainable
                 smart city applications. We also show that it is
                 possible to train robust global models from modest
                 datasets per client, which challenges the conventional
                 wisdom that adversarial training requires massive
                 datasets.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Badidi:2023:EAE,
  author =       "Elarbi Badidi",
  title =        "Edge {AI} for Early Detection of Chronic Diseases and
                 the Spread of Infectious Diseases: Opportunities,
                 Challenges, and Future Directions",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "11",
  pages =        "370",
  day =          "18",
  month =        nov,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15110370",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/11/370",
  abstract =     "Edge AI, an interdisciplinary technology that enables
                 distributed intelligence with edge devices, is quickly
                 becoming a critical component in early health
                 prediction. Edge AI encompasses data analytics and
                 artificial intelligence (AI) using machine learning,
                 deep learning, and federated learning models deployed
                 and executed at the edge of the network, far from
                 centralized data centers. AI enables the careful
                 analysis of large datasets derived from multiple
                 sources, including electronic health records, wearable
                 devices, and demographic information, making it
                 possible to identify intricate patterns and predict a
                 person's future health. Federated learning, a novel
                 approach in AI, further enhances this prediction by
                 enabling collaborative training of AI models on
                 distributed edge devices while maintaining privacy.
                 Using edge computing, data can be processed and
                 analyzed locally, reducing latency and enabling instant
                 decision making. This article reviews the role of Edge
                 AI in early health prediction and highlights its
                 potential to improve public health. Topics covered
                 include the use of AI algorithms for early detection of
                 chronic diseases such as diabetes and cancer and the
                 use of edge computing in wearable devices to detect the
                 spread of infectious diseases. In addition to
                 discussing the challenges and limitations of Edge AI in
                 early health prediction, this article emphasizes future
                 research directions to address these concerns and the
                 integration with existing healthcare systems and
                 explore the full potential of these technologies in
                 improving public health.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wu:2023:MUC,
  author =       "Qianqian Wu and Qiang Liu and Zefan Wu and Jiye
                 Zhang",
  title =        "Maximizing {UAV} Coverage in Maritime Wireless
                 Networks: a Multiagent Reinforcement Learning
                 Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "11",
  pages =        "369",
  day =          "16",
  month =        nov,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15110369",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/11/369",
  abstract =     "In the field of ocean data monitoring, collaborative
                 control and path planning of unmanned aerial vehicles
                 (UAVs) are essential for improving data collection
                 efficiency and quality. In this study, we focus on how
                 to utilize multiple UAVs to efficiently cover the
                 target area in ocean data monitoring tasks. First, we
                 propose a multiagent deep reinforcement learning
                 (DRL)-based path-planning method for multiple UAVs to
                 perform efficient coverage tasks in a target area in
                 the field of ocean data monitoring. Additionally, the
                 traditional Multi-Agent Twin Delayed Deep Deterministic
                 policy gradient (MATD3) algorithm only considers the
                 current state of the agents, leading to poor
                 performance in path planning. To address this issue, we
                 introduce an improved MATD3 algorithm with the
                 integration of a stacked long short-term memory
                 (S-LSTM) network to incorporate the historical
                 interaction information and environmental changes among
                 agents. Finally, the experimental results demonstrate
                 that the proposed MATD3-Stacked\_LSTM algorithm can
                 effectively improve the efficiency and practicality of
                 UAV path planning by achieving a high coverage rate of
                 the target area and reducing the redundant coverage
                 rate among UAVs compared with two other advanced DRL
                 algorithms.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gori:2023:GSM,
  author =       "Giacomo Gori and Lorenzo Rinieri and Amir {Al Sadi}
                 and Andrea Melis and Franco Callegati and Marco
                 Prandini",
  title =        "{GRAPH4}: a Security Monitoring Architecture Based on
                 Data Plane Anomaly Detection Metrics Calculated over
                 Attack Graphs",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "11",
  pages =        "368",
  day =          "15",
  month =        nov,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15110368",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/11/368",
  abstract =     "The correct and efficient measurement of security
                 properties is key to the deployment of effective
                 cyberspace protection strategies. In this work, we
                 propose GRAPH4, which is a system that combines
                 different security metrics to design an attack
                 detection approach that leverages the advantages of
                 modern network architectures. GRAPH4 makes use of
                 attack graphs that are generated by the control plane
                 to extract a view of the network components requiring
                 monitoring, which is based on the specific attack that
                 must be detected and on the knowledge of the complete
                 network layout. It enables an efficient distribution of
                 security metrics tasks between the control plane and
                 the data plane. The attack graph is translated into
                 network rules that are subsequently installed in
                 programmable nodes in order to enable alerting and
                 detecting network anomalies at a line rate. By
                 leveraging data plane programmability and security
                 metric scores, GRAPH4 enables timely responses to
                 unforeseen conditions while optimizing resource
                 allocation and enhancing proactive defense. This paper
                 details the architecture of GRAPH4, and it provides an
                 evaluation of the performance gains it can achieve.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Badshah:2023:TEI,
  author =       "Afzal Badshah and Ghani Ur Rehman and Haleem Farman
                 and Anwar Ghani and Shahid Sultan and Muhammad Zubair
                 and Moustafa M. Nasralla",
  title =        "Transforming Educational Institutions: Harnessing the
                 Power of {Internet of Things}, Cloud, and Fog
                 Computing",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "11",
  pages =        "367",
  day =          "13",
  month =        nov,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15110367",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/11/367",
  abstract =     "The Internet of Things (IoT), cloud, and fog computing
                 are now a reality and have become the vision of the
                 smart world. Self-directed learning approaches, their
                 tools, and smart spaces are transforming traditional
                 institutions into smart institutions. This transition
                 has a positive impact on learner engagement,
                 motivation, attendance, and advanced learning outcomes.
                 In developing countries, there are many barriers to
                 quality education, such as inadequate implementation of
                 standard operating procedures, lack of involvement from
                 learners and parents, and lack of transparent
                 performance measurement for both institutions and
                 students. These issues need to be addressed to ensure
                 further growth and improvement. This study explored the
                 use of smart technologies (IoT, fog, and cloud
                 computing) to address challenges in student learning
                 and administrative tasks. A novel framework (a
                 five-element smart institution framework) is proposed
                 to connect administrators, teachers, parents, and
                 students using smart technologies to improve
                 attendance, pedagogy, and evaluation. The results
                 showed significant increases in student attendance and
                 homework progress, along with improvements in annual
                 results, student discipline, and teacher/parent
                 engagement.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liaqat:2023:DCP,
  author =       "Rao Muzamal Liaqat and Philip Branch and Jason But",
  title =        "Design Considerations and Performance Evaluation of
                 Gossip Routing in {LoRa}-Based Linear Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "11",
  pages =        "366",
  day =          "11",
  month =        nov,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15110366",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/11/366",
  abstract =     "Linear networks (sometimes called chain-type networks)
                 occur frequently in Internet of Things (IoT)
                 applications, where sensors or actuators are deployed
                 along pipelines, roads, railways, mines, and
                 international borders. LoRa, short for Long Range, is
                 an increasingly important technology for the IoT with
                 great potential for linear networking. Despite its
                 potential, limited research has explored LoRa's
                 implementation in such networks. In this paper, we
                 addressed two important issues related to LoRa linear
                 networks. The first is contention, when multiple nodes
                 attempt to access a shared channel. Although originally
                 designed to deal with interference, LoRa's technique of
                 synchronisation with a transmission node permits a
                 novel approach to contention, which we explored. The
                 second issue revolves around routing, where linear
                 networks permit simpler strategies, in contrast to the
                 common routing complexities of mesh networks. We
                 present gossip routing as a very lightweight approach
                 to routing. All our evaluations were carried out using
                 real equipment by developing real networks. We
                 constructed networks of up to three hops in length and
                 up to three nodes in width. We carried out experiments
                 looking at contention and routing. We demonstrate using
                 the novel approach that we could achieve up to 98\%
                 throughput. We compared its performance considering
                 collocated scenarios that achieved 84\% and 89\%
                 throughputby using relay widths of two and three at
                 each hop, respectively. Lastly, we demonstrate the
                 effectiveness of gossip routing by using various
                 transmission probabilities. We noticed high performance
                 up to 98\% throughputat Tprob = 0.90 and Tprob = 0.80
                 by employing two and three active relay nodes,
                 respectively. The experimental result showed that, at
                 Tprob = 0.40, it achieved an average performance of
                 62.8\% and 73.77\% by using two and three active relay
                 nodes, respectively. We concluded that LoRa is an
                 excellent technology for Internet of Things
                 applications where sensors and actuators are deployed
                 in an approximately linear fashion.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{AlSalem:2023:AIW,
  author =       "Thanaa Saad AlSalem and Majed Aadi AlShamari",
  title =        "Assessing Interactive {Web}-Based Systems Using
                 Behavioral Measurement Techniques",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "11",
  pages =        "365",
  day =          "11",
  month =        nov,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15110365",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/11/365",
  abstract =     "Nowadays, e-commerce websites have become part of
                 people's daily lives; therefore, it has become
                 necessary to seek help in assessing and improving the
                 usability of the services of e-commerce websites.
                 Essentially, usability studies offer significant
                 information about users' assessment and perceptions of
                 satisfaction, effectiveness, and efficiency of online
                 services. This research investigated the usability of
                 two e-commerce web-sites in Saudi Arabia and compared
                 the effectiveness of different behavioral measurement
                 techniques, such as heuristic evaluation, usability
                 testing, and eye-tracking. In particular, this research
                 selected the Extra and Jarir e-commerce websites in
                 Saudi Arabia based on a combined approach of criteria
                 and ranking. This research followed an experimental
                 approach in which both qualitative and quantitative
                 approaches were employed to collect and analyze the
                 data. Each of the behavioral measurement techniques
                 identified usability issues ranging from cosmetic to
                 catastrophic issues. It is worth mentioning that the
                 heuristic evaluation by experts provided both the
                 majority of the issues and identified the most severe
                 usability issues compared to the number of issues
                 identified by both usability testing and eye-tracking
                 combined. Usability testing provided fewer problems,
                 most of which had already been identified by the
                 experts. Eye-tracking provided critical information
                 regarding the page design and element placements and
                 revealed certain user behavior patterns that indicated
                 certain usability problems. Overall, the research
                 findings appeared useful to user experience (UX) and
                 user interface (UI) designers to consider the provided
                 recommendations to enhance the usability of e-commerce
                 websites.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yuan:2023:SAC,
  author =       "Ye Yuan and Wang Wang and Guangze Wen and Zikun Zheng
                 and Zhemin Zhuang",
  title =        "Sentiment Analysis of {Chinese} Product Reviews Based
                 on Fusion of {DUAL}-Channel {BiLSTM} and
                 Self-Attention",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "11",
  pages =        "364",
  day =          "10",
  month =        nov,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15110364",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/11/364",
  abstract =     "Product reviews provide crucial information for both
                 consumers and businesses, offering insights needed
                 before purchasing a product or service. However,
                 existing sentiment analysis methods, especially for
                 Chinese language, struggle to effectively capture
                 contextual information due to the complex semantics,
                 multiple sentiment polarities, and long-term
                 dependencies between words. In this paper, we propose a
                 sentiment classification method based on the BiLSTM
                 algorithm to address these challenges in natural
                 language processing. Self-Attention-CNN BiLSTM
                 (SAC-BiLSTM) leverages dual channels to extract
                 features from both character-level embeddings and
                 word-level embeddings. It combines BiLSTM and
                 Self-Attention mechanisms for feature extraction and
                 weight allocation, aiming to overcome the limitations
                 in mining contextual information. Experiments were
                 conducted on the onlineshopping10cats dataset, which is
                 a standard corpus of e-commerce shopping reviews
                 available in the ChineseNlpCorpus 2018. The
                 experimental results demonstrate the effectiveness of
                 our proposed algorithm, with Recall, Precision, and F1
                 scores reaching 0.9409, 0.9369, and 0.9404,
                 respectively.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Skondras:2023:GSR,
  author =       "Panagiotis Skondras and Panagiotis Zervas and Giannis
                 Tzimas",
  title =        "Generating Synthetic Resume Data with Large Language
                 Models for Enhanced Job Description Classification",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "11",
  pages =        "363",
  day =          "09",
  month =        nov,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15110363",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/11/363",
  abstract =     "In this article, we investigate the potential of
                 synthetic resumes as a means for the rapid generation
                 of training data and their effectiveness in data
                 augmentation, especially in categories marked by sparse
                 samples. The widespread implementation of machine
                 learning algorithms in natural language processing
                 (NLP) has notably streamlined the resume classification
                 process, delivering time and cost efficiencies for
                 hiring organizations. However, the performance of these
                 algorithms depends on the abundance of training data.
                 While selecting the right model architecture is
                 essential, it is also crucial to ensure the
                 availability of a robust, well-curated dataset. For
                 many categories in the job market, data sparsity
                 remains a challenge. To deal with this challenge, we
                 employed the OpenAI API to generate both structured and
                 unstructured resumes tailored to specific criteria.
                 These synthetically generated resumes were cleaned,
                 preprocessed and then utilized to train two distinct
                 models: a transformer model (BERT) and a feedforward
                 neural network (FFNN) that incorporated Universal
                 Sentence Encoder 4 (USE4) embeddings. While both models
                 were evaluated on the multiclass classification task of
                 resumes, when trained on an augmented dataset
                 containing 60 percent real data (from Indeed website)
                 and 40 percent synthetic data from ChatGPT, the
                 transformer model presented exceptional accuracy. The
                 FFNN, albeit predictably, achieved lower accuracy.
                 These findings highlight the value of augmented
                 real-world data with ChatGPT-generated synthetic
                 resumes, especially in the context of limited training
                 data. The suitability of the BERT model for such
                 classification tasks further reinforces this
                 narrative.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Shaibu:2023:PPL,
  author =       "Farouq E. Shaibu and Elizabeth N. Onwuka and Nathaniel
                 Salawu and Stephen S. Oyewobi and Karim Djouani and
                 Adnan M. Abu-Mahfouz",
  title =        "Performance of Path Loss Models over Mid-Band and
                 High-Band Channels for {5G} Communication Networks: a
                 Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "11",
  pages =        "362",
  day =          "07",
  month =        nov,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15110362",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/11/362",
  abstract =     "The rapid development of 5G communication networks has
                 ushered in a new era of high-speed, low-latency
                 wireless connectivity, as well as the enabling of
                 transformative technologies. However, a crucial aspect
                 of ensuring reliable communication is the accurate
                 modeling of path loss, as it directly impacts signal
                 coverage, interference, and overall network efficiency.
                 This review paper critically assesses the performance
                 of path loss models in mid-band and high-band
                 frequencies and examines their effectiveness in
                 addressing the challenges of 5G deployment. In this
                 paper, we first present the summary of the background,
                 highlighting the increasing demand for high-quality
                 wireless connectivity and the unique characteristics of
                 mid-band (1--6 GHz) and high-band ({$>$6} GHz)
                 frequencies in the 5G spectrum. The methodology
                 comprehensively reviews some of the existing path loss
                 models, considering both empirical and machine learning
                 approaches. We analyze the strengths and weaknesses of
                 these models, considering factors such as urban and
                 suburban environments and indoor scenarios. The results
                 highlight the significant advancements in path loss
                 modeling for mid-band and high-band 5G channels. In
                 terms of prediction accuracy and computing
                 effectiveness, machine learning models performed better
                 than empirical models in both mid-band and high-band
                 frequency spectra. As a result, they might be suggested
                 as an alternative yet promising approach to predicting
                 path loss in these bands. We consider the results of
                 this review to be promising, as they provide network
                 operators and researchers with valuable insights into
                 the state-of-the-art path loss models for mid-band and
                 high-band 5G channels. Future work suggests tuning an
                 ensemble machine learning model to enhance a stable
                 empirical model with multiple parameters to develop a
                 hybrid path loss model for the mid-band frequency
                 spectrum.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sun:2023:IPP,
  author =       "Nigang Sun and Chenyang Zhu and Yuanyi Zhang and
                 Yining Liu",
  title =        "An Identity Privacy-Preserving Scheme against Insider
                 Logistics Data Leakage Based on One-Time-Use Accounts",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "11",
  pages =        "361",
  day =          "05",
  month =        nov,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15110361",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/11/361",
  abstract =     "Digital transformation of the logistics industry
                 triggered by the widespread use of Internet of Things
                 (IoT) technology has prompted a significant revolution
                 in logistics companies, further bringing huge dividends
                 to society. However, the concurrent accelerated growth
                 of logistics companies also significantly hinders the
                 safeguarding of individual privacy. Digital identity
                 has ascended to having the status of a prevalent
                 privacy-protection solution, principally due to its
                 efficacy in mitigating privacy compromises. However,
                 the extant schemes fall short of addressing the issue
                 of privacy breaches engendered by insider maleficence.
                 This paper proposes an innovative identity
                 privacy-preserving scheme aimed at addressing the
                 quandary of internal data breaches. In this scheme, the
                 identity provider furnishes one-time-use accounts for
                 logistics users, thereby obviating the protracted
                 retention of logistics data within the internal
                 database. The scheme also employs ciphertext policy
                 attribute-based encryption (CP-ABE) to encrypt address
                 nodes, wherein the access privileges accorded to
                 logistics companies are circumscribed. Therefore,
                 internal logistics staff have to secure unequivocal
                 authorization from users prior to accessing
                 identity-specific data and privacy protection of user
                 information is also concomitantly strengthened.
                 Crucially, this scheme ameliorates internal privacy
                 concerns, rendering it infeasible for internal
                 interlopers to correlate the users' authentic
                 identities with their digital wallets. Finally, the
                 effectiveness and reliability of the scheme are
                 demonstrated through simulation experiments and
                 discussions of security.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liao:2023:IBF,
  author =       "Wei-Shun Liao and Ou Zhao and Keren Li and Hikaru
                 Kawasaki and Takeshi Matsumura",
  title =        "Implementation of In-Band Full-Duplex Using Software
                 Defined Radio with Adaptive Filter-Based
                 Self-Interference Cancellation",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "11",
  pages =        "360",
  day =          "03",
  month =        nov,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15110360",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/11/360",
  abstract =     "For next generation wireless communication systems,
                 high throughput, low latency, and large user
                 accommodation are popular and important required
                 characteristics. To achieve these requirements for next
                 generation wireless communication systems, an in-band
                 full-duplex (IBFD) communication system is one of the
                 possible candidate technologies. However, to realize
                 IBFD systems, there is an essential problem that there
                 exists a large self-interference (SI) due to the
                 simultaneous signal transmission and reception in the
                 IBFD systems. Therefore, to implement the IBFD system,
                 it is necessary to realize a series of effective SI
                 cancellation processes. In this study, we implemented a
                 prototype of SI cancellation processes with our
                 designed antenna, analog circuit, and digital
                 cancellation function using an adaptive filter. For
                 system implementation, we introduce software-defined
                 radio (SDR) devices in this study. By using SDR
                 devices, which can be customized by users, the
                 evaluations of complicated wireless access systems like
                 IBFD can be realized easily. Besides the validation
                 stage of system practicality, the system development
                 can be more effective by using SDR devices. Therefore,
                 we utilize SDR devices to implement the proposed IBFD
                 system and conduct experiments to evaluate its
                 performance. The results show that the SI cancellation
                 effect can reach nearly 100 dB with $10^{-3}$ order
                 bit error rate (BER) after signal demodulation. From
                 the experiment results, it can be seen obviously that
                 the implemented prototype can effectively cancel the
                 large amount of SI and obtain satisfied digital
                 demodulation results, which validates the effectiveness
                 of the developed system.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Poltronieri:2023:RLV,
  author =       "Filippo Poltronieri and Cesare Stefanelli and Mauro
                 Tortonesi and Mattia Zaccarini",
  title =        "Reinforcement Learning vs. Computational Intelligence:
                 Comparing Service Management Approaches for the Cloud
                 Continuum",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "11",
  pages =        "359",
  day =          "31",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15110359",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/11/359",
  abstract =     "Modern computing environments, thanks to the advent of
                 enabling technologies such as Multi-access Edge
                 Computing (MEC), effectively represent a Cloud
                 Continuum, a capillary network of computing resources
                 that extend from the Edge of the network to the Cloud,
                 which enables a dynamic and adaptive service fabric.
                 Efficiently coordinating resource allocation,
                 exploitation, and management in the Cloud Continuum
                 represents quite a challenge, which has stimulated
                 researchers to investigate innovative solutions based
                 on smart techniques such as Reinforcement Learning and
                 Computational Intelligence. In this paper, we make a
                 comparison of different optimization algorithms and a
                 first investigation of how they can perform in this
                 kind of scenario. Specifically, this comparison
                 included the Deep Q-Network, Proximal Policy
                 Optimization, Genetic Algorithms, Particle Swarm
                 Optimization, Quantum-inspired Particle Swarm
                 Optimization, Multi-Swarm Particle Optimization, and
                 the Grey-Wolf Optimizer. We demonstrate how all
                 approaches can solve the service management problem
                 with similar performance---with a different sample
                 efficiency---if a high number of samples can be
                 evaluated for training and optimization. Finally, we
                 show that, if the scenario conditions change,
                 Deep-Reinforcement-Learning-based approaches can
                 exploit the experience built during training to adapt
                 service allocation according to the modified
                 conditions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ridolfi:2023:IEF,
  author =       "Lorenzo Ridolfi and David Naseh and Swapnil Sadashiv
                 Shinde and Daniele Tarchi",
  title =        "Implementation and Evaluation of a Federated Learning
                 Framework on {Raspberry PI} Platforms for {IoT} {6G}
                 Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "11",
  pages =        "358",
  day =          "31",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15110358",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/11/358",
  abstract =     "With the advent of 6G technology, the proliferation of
                 interconnected devices necessitates a robust, fully
                 connected intelligence network. Federated Learning (FL)
                 stands as a key distributed learning technique, showing
                 promise in recent advancements. However, the
                 integration of novel Internet of Things (IoT)
                 applications and virtualization technologies has
                 introduced diverse and heterogeneous devices into
                 wireless networks. This diversity encompasses
                 variations in computation, communication, storage
                 resources, training data, and communication modes among
                 connected nodes. In this context, our study presents a
                 pivotal contribution by analyzing and implementing FL
                 processes tailored for 6G standards. Our work defines a
                 practical FL platform, employing Raspberry Pi devices
                 and virtual machines as client nodes, with a Windows PC
                 serving as a parameter server. We tackle the image
                 classification challenge, implementing the FL model via
                 PyTorch, augmented by the specialized FL library,
                 Flower. Notably, our analysis delves into the impact of
                 computational resources, data availability, and heating
                 issues across heterogeneous device sets. Additionally,
                 we address knowledge transfer and employ pre-trained
                 networks in our FL performance evaluation. This
                 research underscores the indispensable role of
                 artificial intelligence in IoT scenarios within the 6G
                 landscape, providing a comprehensive framework for FL
                 implementation across diverse and heterogeneous
                 devices.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Cai:2023:TSF,
  author =       "Weihong Cai and Fengxi Duan",
  title =        "Task Scheduling for Federated Learning in Edge Cloud
                 Computing Environments by Using Adaptive-Greedy Dingo
                 Optimization Algorithm and Binary Salp Swarm
                 Algorithm",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "11",
  pages =        "357",
  day =          "30",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15110357",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/11/357",
  abstract =     "With the development of computationally intensive
                 applications, the demand for edge cloud computing
                 systems has increased, creating significant challenges
                 for edge cloud computing networks. In this paper, we
                 consider a simple three-tier computational model for
                 multiuser mobile edge computing (MEC) and introduce two
                 major problems of task scheduling for federated
                 learning in MEC environments: (1) the transmission
                 power allocation (PA) problem, and (2) the dual
                 decision-making problems of joint request offloading
                 and computational resource scheduling (JRORS). At the
                 same time, we factor in server pricing and task
                 completion, in order to improve the user-friendliness
                 and fairness in scheduling decisions. The solving of
                 these problems simultaneously ensures both scheduling
                 efficiency and system quality of service (QoS), to
                 achieve a balance between efficiency and user
                 satisfaction. Then, we propose an adaptive greedy dingo
                 optimization algorithm (AGDOA) based on greedy policies
                 and parameter adaptation to solve the PA problem and
                 construct a binary salp swarm algorithm (BSSA) that
                 introduces binary coding to solve the discrete JRORS
                 problem. Finally, simulations were conducted to verify
                 the better performance compared to the traditional
                 algorithms. The proposed algorithm improved the
                 convergence speed of the algorithm in terms of
                 scheduling efficiency, improved the system response
                 rate, and found solutions with a lower energy
                 consumption. In addition, the search results had a
                 higher fairness and system welfare in terms of system
                 quality of service.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Qahtani:2023:MAC,
  author =       "Elham {Al Qahtani} and Yousra Javed and Sarah Tabassum
                 and Lipsarani Sahoo and Mohamed Shehab",
  title =        "Managing Access to Confidential Documents: a Case
                 Study of an Email Security Tool",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "11",
  pages =        "356",
  day =          "28",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15110356",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/11/356",
  abstract =     "User adoption and usage of end-to-end encryption tools
                 is an ongoing research topic. A subset of such tools
                 allows users to encrypt confidential emails, as well as
                 manage their access control using features such as the
                 expiration time, disabling forwarding, persistent
                 protection, and watermarking. Previous studies have
                 suggested that protective attitudes and behaviors could
                 improve the adoption of new security technologies.
                 Therefore, we conducted a user study on 19 participants
                 to understand their perceptions of an email security
                 tool and how they use it to manage access control to
                 confidential information such as medical, tax, and
                 employee information if sent via email. Our results
                 showed that the participants' first impression upon
                 receiving an end-to-end encrypted email was that it
                 looked suspicious, especially when received from an
                 unknown person. After the participants were informed
                 about the importance of the investigated tool, they
                 were comfortable sharing medical, tax, and employee
                 information via this tool. Regarding access control
                 management of the three types of confidential
                 information, the expiration time and disabling
                 forwarding were most useful for the participants in
                 preventing unauthorized and continued access. While the
                 participants did not understand how the persistent
                 protection feature worked, many still chose to use it,
                 assuming it provided some extra layer of protection to
                 confidential information and prevented unauthorized
                 access. Watermarking was the least useful feature for
                 the participants, as many were unsure of its usage. Our
                 participants were concerned about data leaks from
                 recipients' devices if they set a longer expiration
                 date, such as a year. We provide the practical
                 implications of our findings.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kyriakos:2023:BIT,
  author =       "Christos Kyriakos and Manolis Vavalis",
  title =        "Business Intelligence through Machine Learning from
                 Satellite Remote Sensing Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "11",
  pages =        "355",
  day =          "27",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15110355",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/11/355",
  abstract =     "Several cities have been greatly affected by economic
                 crisis, unregulated gentrification, and the pandemic,
                 resulting in increased vacancy rates. Abandoned
                 buildings have various negative implications on their
                 neighborhoods, including an increased chance of fire
                 and crime and a drastic reduction in their monetary
                 value. This paper focuses on the use of satellite data
                 and machine learning to provide insights for businesses
                 and policymakers within Greece and beyond. Our
                 objective is two-fold: to provide a comprehensive
                 literature review on recent results concerning the
                 opportunities offered by satellite images for business
                 intelligence and to design and implement an open-source
                 software system for the detection of abandoned or
                 disused buildings based on nighttime lights and
                 built-up area indices. Our preliminary experimentation
                 provides promising results that can be used for
                 location intelligence and beyond.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{ElGaabouri:2023:SLR,
  author =       "Ismail {El Gaabouri} and Mohamed Senhadji and Mostafa
                 Belkasmi and Brahim {El Bhiri}",
  title =        "A Systematic Literature Review on Authentication and
                 Threat Challenges on {RFID} Based {NFC} Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "11",
  pages =        "354",
  day =          "27",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15110354",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/11/354",
  abstract =     "The Internet of Things (IoT) concept is tremendously
                 applied in our current daily lives. The IoT involves
                 Radio Frequency Identification (RFID) as a part of the
                 infrastructure that helps with the data gathering from
                 different types of sensors. In general, security
                 worries have increased significantly as these types of
                 technologies have become more common. For this reason,
                 manifold realizations and studies have been carried out
                 to address this matter. In this work, we tried to
                 provide a thorough analysis of the cryptography-based
                 solutions for RFID cards (MIFARE cards as a case study)
                 by performing a Systematic Literature Review (SLR) to
                 deliver the up-to-date trends and outlooks on this
                 topic.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Baras:2023:IEM,
  author =       "Nikolaos Baras and Antonios Chatzisavvas and Dimitris
                 Ziouzios and Ioannis Vanidis and Minas Dasygenis",
  title =        "Improving the Efficiency of Modern Warehouses Using
                 Smart Battery Placement",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "11",
  pages =        "353",
  day =          "26",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15110353",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/11/353",
  abstract =     "In the ever-evolving landscape of warehousing, the
                 integration of unmanned ground vehicles (UGVs) has
                 profoundly revolutionized operational efficiency.
                 Despite this advancement, a key determinant of UGV
                 productivity remains its energy management and battery
                 placement strategies. While many studies explored
                 optimizing the pathways within warehouses and
                 determining ideal power station locales, there remains
                 a gap in addressing the dynamic needs of
                 energy-efficient UGVs operating in tandem. The current
                 literature largely focuses on static designs, often
                 overlooking the challenges of multi-UGV scenarios. This
                 paper introduces a novel algorithm based on affinity
                 propagation (AP) for smart battery and charging station
                 placement in modern warehouses. The idea of the
                 proposed algorithm is to divide the initial area into
                 multiple sub-areas based on their traffic, and then
                 identify the optimal battery location within each
                 sub-area. A salient feature of this algorithm is its
                 adeptness at determining the most strategic battery
                 station placements, emphasizing uninterrupted
                 operations and minimized downtimes. Through extensive
                 evaluations in a synthesized realistic setting, our
                 results underscore the algorithm's proficiency in
                 devising enhanced solutions within feasible time
                 constraints, paving the way for more energy-efficient
                 and cohesive UGV-driven warehouse systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yu:2023:LAS,
  author =       "Liangkun Yu and Xiang Sun and Rana Albelaihi and Chen
                 Yi",
  title =        "Latency-Aware Semi-Synchronous Client Selection and
                 Model Aggregation for Wireless Federated Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "11",
  pages =        "352",
  day =          "26",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15110352",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/11/352",
  abstract =     "Federated learning (FL) is a collaborative
                 machine-learning (ML) framework particularly suited for
                 ML models requiring numerous training samples, such as
                 Convolutional Neural Networks (CNNs), Recurrent Neural
                 Networks (RNNs), and Random Forest, in the context of
                 various applications, e.g., next-word prediction and
                 eHealth. FL involves various clients participating in
                 the training process by uploading their local models to
                 an FL server in each global iteration. The server
                 aggregates these models to update a global model. The
                 traditional FL process may encounter bottlenecks, known
                 as the straggler problem, where slower clients delay
                 the overall training time. This paper introduces the
                 Latency-awarE Semi-synchronous client Selection and
                 mOdel aggregation for federated learNing (LESSON)
                 method. LESSON allows clients to participate at
                 different frequencies: faster clients contribute more
                 frequently, therefore mitigating the straggler problem
                 and expediting convergence. Moreover, LESSON provides a
                 tunable trade-off between model accuracy and
                 convergence rate by setting varying deadlines.
                 Simulation results show that LESSON outperforms two
                 baseline methods, namely FedAvg and FedCS, in terms of
                 convergence speed and maintains higher model accuracy
                 compared to FedCS.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lim:2023:NRM,
  author =       "Shueh-Ting Lim and Lee-Yeng Ong and Meng-Chew Leow",
  title =        "New {RFI} Model for Behavioral Audience Segmentation
                 in {Wi-Fi} Advertising System",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "11",
  pages =        "351",
  day =          "26",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15110351",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/11/351",
  abstract =     "In this technological era, businesses tend to place
                 advertisements via the medium of Wi-Fi advertising to
                 expose their brands and products to the public. Wi-Fi
                 advertising offers a platform for businesses to
                 leverage their marketing strategies to achieve desired
                 goals, provided they have a thorough understanding of
                 their audience's behaviors. This paper aims to
                 formulate a new RFI (recency, frequency, and interest)
                 model that is able to analyze the behavior of the
                 audience towards the advertisement. The audience's
                 interest is measured based on the relationship between
                 their total view duration on an advertisement and its
                 corresponding overall click received. With the help of
                 a clustering algorithm to perform the dynamic
                 segmentation, the patterns of the audience behaviors
                 are then being interpreted by segmenting the audience
                 based on their engagement behaviors. In the
                 experiments, two different Wi-Fi advertising attributes
                 are tested to prove the new RFI model is applicable to
                 effectively interpret the audience engagement behaviors
                 with the proposed dynamic characteristics range table.
                 The weak and strongly engaged behavioral
                 characteristics of the segmented behavioral patterns of
                 the audience, such as in a one-time audience, are
                 interpreted successfully with the
                 dynamic-characteristics range table.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Francia:2023:DMC,
  author =       "Alberto Francia and Stefano Mariani and Giuseppe
                 Adduce and Sandro Vecchiarelli and Franco Zambonelli",
  title =        "Digital Management of Competencies in {Web 3.0}: The
                 {C-Box\reg} Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "11",
  pages =        "350",
  day =          "26",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15110350",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/11/350",
  abstract =     "Management of competencies is a crucial concern for
                 both learners and workers as well as for training
                 institutions and companies. For the former, it allows
                 users to track and certify the acquired skills to apply
                 for positions; for the latter, it enables better
                 organisation of business processes. However, currently,
                 most software systems for competency management adopted
                 by the industry are either organisation-centric or
                 centralised: that is, they either lock-in students and
                 employees wishing to export their competencies
                 elsewhere, or they require users' trust and for users
                 to give up privacy (to store their personal data) while
                 being prone to faults. In this paper, we propose a
                 user-centric, fully decentralised competency management
                 system enabling verifiable, secure, and robust
                 management of competencies digitalised as Open Badges
                 via notarization on a public blockchain. This way,
                 whoever acquires the competence or achievement retains
                 full control over it and can disclose his/her own
                 digital certifications only when needed and to the
                 extent required, migrate them across storage platforms,
                 and let anyone verify the integrity and validity of
                 such certifications independently of any centralised
                 organisation. The proposed solution is based on C-Box
                 {\reg}, an existing application for the management of
                 digital competencies that has been improved to fully
                 support models, standards, and technologies of the
                 so-called Web 3.0 vision---a global effort by major web
                 organisations to ``give the web back to the people'',
                 pushing for maximum decentralisation of control and
                 user-centric data ownership.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Paasche:2023:FSA,
  author =       "Simon Paasche and Sven Groppe",
  title =        "A Finite State Automaton for Green Data Validation in
                 a Real-World Smart Manufacturing Environment with
                 Special Regard to Time-Outs and Overtaking",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "11",
  pages =        "349",
  day =          "26",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15110349",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/11/349",
  abstract =     "Since data are the gold of modern business, companies
                 put a huge effort into collecting internal and external
                 information, such as process, supply chain, or customer
                 data. To leverage the full potential of gathered
                 information, data have to be free of errors and
                 corruptions. Thus, the impacts of data quality and data
                 validation approaches become more and more relevant. At
                 the same time, the impact of information and
                 communication technologies has been increasing for
                 several years. This leads to increasing energy
                 consumption and the associated emission of
                 climate-damaging gases such as carbon dioxide (CO 2 ).
                 Since these gases cause serious problems (e.g., climate
                 change) and lead to climate targets not being met, it
                 is a major goal for companies to become climate
                 neutral. Our work focuses on quality aspects in smart
                 manufacturing lines and presents a finite automaton to
                 validate an incoming stream of manufacturing data.
                 Through this process, we aim to achieve a sustainable
                 use of manufacturing resources. In the course of this
                 work, we aim to investigate possibilities to implement
                 data validation in resource-saving ways. Our automaton
                 enables the detection of errors in a continuous data
                 stream and reports discrepancies directly. By making
                 inconsistencies visible and annotating affected data
                 sets, we are able to increase the overall data quality.
                 Further, we build up a fast feedback loop, allowing us
                 to quickly intervene and remove sources of
                 interference. Through this fast feedback, we expect a
                 lower consumption of material resources on the one hand
                 because we can intervene in case of error and optimize
                 our processes. On the other hand, our automaton
                 decreases the immaterial resources needed, such as the
                 required energy consumption for data validation, due to
                 more efficient validation steps. We achieve the more
                 efficient validation steps by the already-mentioned
                 automaton structure. Furthermore, we reduce the
                 response time through additional recognition of
                 overtaking data records. In addition, we implement an
                 improved check for complex inconsistencies. Our
                 experimental results show that we are able to
                 significantly reduce memory usage and thus decrease the
                 energy consumption for our data validation task.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Serodio:2023:ESI,
  author =       "Carlos Ser{\^o}dio and Jos{\'e} Cunha and Guillermo
                 Candela and Santiago Rodriguez and Xos{\'e} Ram{\'o}n
                 Sousa and Frederico Branco",
  title =        "The {6G} Ecosystem as Support for {IoE} and Private
                 Networks: Vision, Requirements, and Challenges",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "11",
  pages =        "348",
  day =          "25",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15110348",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/11/348",
  abstract =     "The emergence of the sixth generation of cellular
                 systems (6G) signals a transformative era and ecosystem
                 for mobile communications, driven by demands from
                 technologies like the internet of everything (IoE), V2X
                 communications, and factory automation. To support this
                 connectivity, mission-critical applications are
                 emerging with challenging network requirements. The
                 primary goals of 6G include providing sophisticated and
                 high-quality services, extremely reliable and
                 further-enhanced mobile broadband (feMBB), low-latency
                 communication (ERLLC), long-distance and high-mobility
                 communications (LDHMC), ultra-massive machine-type
                 communications (umMTC), extremely low-power
                 communications (ELPC), holographic communications, and
                 quality of experience (QoE), grounded in incorporating
                 massive broad-bandwidth machine-type (mBBMT), mobile
                 broad-bandwidth and low-latency (MBBLL), and massive
                 low-latency machine-type (mLLMT) communications. In
                 attaining its objectives, 6G faces challenges that
                 demand inventive solutions, incorporating AI,
                 softwarization, cloudification, virtualization, and
                 slicing features. Technologies like network function
                 virtualization (NFV), network slicing, and
                 software-defined networking (SDN) play pivotal roles in
                 this integration, which facilitates efficient resource
                 utilization, responsive service provisioning, expanded
                 coverage, enhanced network reliability, increased
                 capacity, densification, heightened availability,
                 safety, security, and reduced energy consumption. It
                 presents innovative network infrastructure concepts,
                 such as resource-as-a-service (RaaS) and
                 infrastructure-as-a-service (IaaS), featuring
                 management and service orchestration mechanisms. This
                 includes nomadic networks, AI-aware networking
                 strategies, and dynamic management of diverse network
                 resources. This paper provides an in-depth survey of
                 the wireless evolution leading to 6G networks,
                 addressing future issues and challenges associated with
                 6G technology to support V2X environments considering
                 presenting + challenges in architecture, spectrum, air
                 interface, reliability, availability, density,
                 flexibility, mobility, and security.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kljaic:2023:OCC,
  author =       "Zdenko Kljai{\'c} and Danijel Pavkovi{\'c} and Mihael
                 Cipek and Maja Trstenjak and Tomislav Josip
                 Mlinari{\'c} and Mladen Niksi{\'c}",
  title =        "An Overview of Current Challenges and Emerging
                 Technologies to Facilitate Increased Energy Efficiency,
                 Safety, and Sustainability of Railway Transport",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "11",
  pages =        "347",
  day =          "25",
  month =        oct,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15110347",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/11/347",
  abstract =     "This article presents a review of cutting-edge
                 technologies poised to shape the future of railway
                 transportation systems, focusing on enhancing their
                 intelligence, safety, and environmental sustainability.
                 It illustrates key aspects of the
                 energy-transport-information/communication system nexus
                 as a framework for future railway systems development.
                 Initially, we provide a review of the existing
                 challenges within the realm of railway transportation.
                 Subsequently, we delve into the realm of emerging
                 propulsion technologies, which are pivotal for ensuring
                 the sustainability of transportation. These include
                 innovative solutions such as alternative fuel-based
                 systems, hydrogen fuel cells, and energy storage
                 technologies geared towards harnessing kinetic energy
                 and facilitating power transfer. In the following
                 section, we turn our attention to emerging information
                 and telecommunication systems, including Long-Term
                 Evolution (LTE) and fifth generation New Radio (5G NR)
                 networks tailored for railway applications.
                 Additionally, we delve into the integral role played by
                 the Industrial Internet of Things (Industrial IoT) in
                 this evolving landscape. Concluding our analysis, we
                 examine the integration of information and
                 communication technologies and remote sensor networks
                 within the context of Industry 4.0. This leveraging of
                 information pertaining to transportation infrastructure
                 promises to bolster energy efficiency, safety, and
                 resilience in the transportation ecosystem.
                 Furthermore, we examine the significance of the smart
                 grid in the realm of railway transport, along with the
                 indispensable resources required to bring forth the
                 vision of energy-smart railways.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Nguyen:2023:HHE,
  author =       "Duy Tung Khanh Nguyen and Dung Hoang Duong and Willy
                 Susilo and Yang-Wai Chow and The Anh Ta",
  title =        "{HeFUN}: Homomorphic Encryption for Unconstrained
                 Secure Neural Network Inference",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "407",
  day =          "18",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120407",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/407",
  abstract =     "Homomorphic encryption (HE) has emerged as a pivotal
                 technology for secure neural network inference (SNNI),
                 offering privacy-preserving computations on encrypted
                 data. Despite active developments in this field,
                 HE-based SNNI frameworks are impeded by three inherent
                 limitations. Firstly, they cannot evaluate non-linear
                 functions such as ReLU, the most widely adopted
                 activation function in neural networks. Secondly, the
                 permitted number of homomorphic operations on
                 ciphertexts is bounded, consequently limiting the depth
                 of neural networks that can be evaluated. Thirdly, the
                 computational overhead associated with HE is
                 prohibitively high, particularly for deep neural
                 networks. In this paper, we introduce a novel paradigm
                 designed to address the three limitations of HE-based
                 SNNI. Our approach is an interactive approach that is
                 solely based on HE, called iLHE. Utilizing the idea of
                 iLHE, we present two protocols: ReLU, which facilitates
                 the direct evaluation of the ReLU function on encrypted
                 data, tackling the first limitation, and HeRefresh,
                 which extends the feasible depth of neural network
                 computations and mitigates the computational overhead,
                 thereby addressing the second and third limitations.
                 Based on HeReLU and HeRefresh protocols, we build a new
                 framework for SNNI, named HeFUN. We prove that our
                 protocols and the HeFUN framework are secure in the
                 semi-honest security model. Empirical evaluations
                 demonstrate that HeFUN surpasses current HE-based SNNI
                 frameworks in multiple aspects, including security,
                 accuracy, the number of communication rounds, and
                 inference latency. Specifically, for a convolutional
                 neural network with four layers on the MNIST dataset,
                 HeFUN achieves 99.16\% accuracy with an inference
                 latency of 1.501 s, surpassing the popular HE-based
                 framework CryptoNets proposed by Gilad-Bachrach, which
                 achieves 98.52\% accuracy with an inference latency of
                 3.479 s.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ogata:2023:DSA,
  author =       "Keigo Ogata and Satoshi Fujita",
  title =        "Decentralized Storage with Access Control and Data
                 Persistence for e-Book Stores",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "406",
  day =          "18",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120406",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/406",
  abstract =     "The e-book services we use today have a serious
                 drawback in that we will no longer be able to read the
                 books we have purchased when the service is terminated.
                 One way to solve this problem is to build a
                 decentralized system that does not depend on a specific
                 company or organization by combining smart contracts
                 running on the Ethereum blockchain and distributed
                 storage such as an IPFS. However, a simple combination
                 of existing technologies does not make the stored
                 e-book data persistent, so the risk of purchased
                 e-books becoming unreadable remains. In this paper, we
                 propose a decentralized distributed storage called
                 d-book-repository, which has both access management
                 function and data durability for purchased e-books.
                 This system uses NFTs as access rights to realize
                 strict access control by preventing clients who do not
                 have NFTs from downloading e-book data. In addition,
                 e-book data stored on storage nodes in the distributed
                 storage is divided into shards using Reed--Solomon
                 codes, and each storage node stores only a single
                 shard, thereby preventing the creation of nodes that
                 can restore the entire content from locally stored
                 data. The storage of each shard is not handled by a
                 single node but by a group of nodes, and the shard is
                 propagated to all nodes in the group using the gossip
                 protocol, where erasure codes are utilized to increase
                 the resilience against node departure. Furthermore, an
                 incentive mechanism to encourage participation as a
                 storage node is implemented using smart contracts. We
                 built a prototype of the proposed system on AWS and
                 evaluated its performance. The results showed that both
                 downloading and uploading 100 MB of e-book data
                 (equivalent to one comic book) were completed within 10
                 s using an instance type of m5.xlarge. This value is
                 only 1.3 s longer for downloading and 2.2 s longer for
                 uploading than the time required for a simple
                 download/upload without access control, confirming that
                 the overhead associated with the proposed method is
                 sufficiently small.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Adeke:2023:SNT,
  author =       "James Msughter Adeke and Guangjie Liu and Junjie Zhao
                 and Nannan Wu and Hafsat Muhammad Bashir",
  title =        "Securing Network Traffic Classification Models against
                 Adversarial Examples Using Derived Variables",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "405",
  day =          "16",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120405",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/405",
  abstract =     "Machine learning (ML) models are essential to securing
                 communication networks. However, these models are
                 vulnerable to adversarial examples (AEs), in which
                 malicious inputs are modified by adversaries to produce
                 the desired output. Adversarial training is an
                 effective defense method against such attacks but
                 relies on access to a substantial number of AEs, a
                 prerequisite that entails significant computational
                 resources and the inherent limitation of poor
                 performance on clean data. To address these problems,
                 this study proposes a novel approach to improve the
                 robustness of ML-based network traffic classification
                 models by integrating derived variables (DVars) into
                 training. Unlike adversarial training, our approach
                 focuses on enhancing training using DVars, introducing
                 randomness into the input data. DVars are generated
                 from the baseline dataset and significantly improve the
                 resilience of the model to AEs. To evaluate the
                 effectiveness of DVars, experiments were conducted
                 using the CSE-CIC-IDS2018 dataset and three
                 state-of-the-art ML-based models: decision tree (DT),
                 random forest (RF), and k-neighbors (KNN). The results
                 show that DVars can improve the accuracy of KNN under
                 attack from 0.45\% to 0.84\% for low-intensity attacks
                 and from 0.32\% to 0.66\% for high-intensity attacks.
                 Furthermore, both DT and RF achieve a significant
                 increase in accuracy when subjected to attack of
                 different intensity. Moreover, DVars are
                 computationally efficient, scalable, and do not require
                 access to AEs.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Panwar:2023:BAE,
  author =       "Arvind Panwar and Manju Khari and Sanjay Misra and
                 Urvashi Sugandh",
  title =        "Blockchain in Agriculture to Ensure Trust,
                 Effectiveness, and Traceability from Farm Fields to
                 Groceries",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "404",
  day =          "16",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120404",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/404",
  abstract =     "Despite its status as one of the most ancient sectors
                 worldwide, agriculture continues to be a fundamental
                 cornerstone of the global economy. Nevertheless, it
                 faces obstacles such as a lack of trust, difficulties
                 in tracking, and inefficiencies in managing the supply
                 chain. This article examines the potential of
                 blockchain technology (BCT) to alter the agricultural
                 industry by providing a decentralized, transparent, and
                 unchangeable solution to meet the difficulties it
                 faces. The initial discussion provides an overview of
                 the challenges encountered by the agricultural
                 industry, followed by a thorough analysis of BCT,
                 highlighting its potential advantages. Following that,
                 the article explores other agricultural uses for
                 blockchain technology, such as managing supply chains,
                 verifying products, and processing payments. In
                 addition, this paper examines the constraints and
                 challenges related to the use of blockchain technology
                 in agriculture, including issues such as scalability,
                 legal frameworks, and interoperability. This paper
                 highlights the potential of BCT to transform the
                 agricultural industry by offering a transparent and
                 secure platform for managing the supply chain.
                 Nevertheless, it emphasizes the need for involving
                 stakeholders, having clear legislation, and possessing
                 technical skills in order to achieve effective
                 implementation. This work utilizes a systematic
                 literature review using the PRISMA technique and
                 applies meta-analysis as the research methodology,
                 enabling a thorough investigation of the present
                 information available. The results emphasize the
                 significant and positive effect of BCT on agriculture,
                 emphasizing the need for cooperative endeavors among
                 governments, industry pioneers, and technology
                 specialists to encourage its extensive implementation
                 and contribute to the advancement of a sustainable and
                 resilient food system.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alsamiri:2023:FLI,
  author =       "Jadil Alsamiri and Khalid Alsubhi",
  title =        "Federated Learning for Intrusion Detection Systems in
                 {Internet} of Vehicles: a General Taxonomy,
                 Applications, and Future Directions",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "403",
  day =          "14",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120403",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/403",
  abstract =     "In recent years, the Internet of Vehicles (IoV) has
                 garnered significant attention from researchers and
                 automotive industry professionals due to its expanding
                 range of applications and services aimed at enhancing
                 road safety and driver/passenger comfort. However, the
                 massive amount of data spread across this network makes
                 securing it challenging. The IoV network generates,
                 collects, and processes vast amounts of valuable and
                 sensitive data that intruders can manipulate. An
                 intrusion detection system (IDS) is the most typical
                 method to protect such networks. An IDS monitors
                 activity on the road to detect any sign of a security
                 threat and generates an alert if a security anomaly is
                 detected. Applying machine learning methods to large
                 datasets helps detect anomalies, which can be utilized
                 to discover potential intrusions. However, traditional
                 centralized learning algorithms require gathering data
                 from end devices and centralizing it for training on a
                 single device. Vehicle makers and owners may not
                 readily share the sensitive data necessary for training
                 the models. Granting a single device access to enormous
                 volumes of personal information raises significant
                 privacy concerns, as any system-related problems could
                 result in massive data leaks. To alleviate these
                 problems, more secure options, such as Federated
                 Learning (FL), must be explored. A decentralized
                 machine learning technique, FL allows model training on
                 client devices while maintaining user data privacy.
                 Although FL for IDS has made significant progress, to
                 our knowledge, there has been no comprehensive survey
                 specifically dedicated to exploring the applications of
                 FL for IDS in the IoV environment, similar to
                 successful systems research in deep learning. To
                 address this gap, we undertake a well-organized
                 literature review on IDSs based on FL in an IoV
                 environment. We introduce a general taxonomy to
                 describe the FL systems to ensure a coherent structure
                 and guide future research. Additionally, we identify
                 the relevant state of the art in FL-based intrusion
                 detection within the IoV domain, covering the years
                 from FL's inception in 2016 through 2023. Finally, we
                 identify challenges and future research directions
                 based on the existing literature.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Nkemeni:2023:ECR,
  author =       "Valery Nkemeni and Fabien Mieyeville and Pierre
                 Tsafack",
  title =        "Energy Consumption Reduction in Wireless Sensor
                 Network-Based Water Pipeline Monitoring Systems via
                 Energy Conservation Techniques",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "402",
  day =          "14",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120402",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/402",
  abstract =     "In wireless sensor network-based water pipeline
                 monitoring (WWPM) systems, a vital requirement emerges:
                 the achievement of low energy consumption. This primary
                 goal arises from the fundamental necessity to ensure
                 the sustained operability of sensor nodes over extended
                 durations, all without the need for frequent battery
                 replacement. Given that sensor nodes in such
                 applications are typically battery-powered and often
                 physically inaccessible, maximizing energy efficiency
                 by minimizing unnecessary energy consumption is of
                 vital importance. This paper presents an experimental
                 study that investigates the impact of a hybrid
                 technique, incorporating distributed computing,
                 hierarchical sensing, and duty cycling, on the energy
                 consumption of a sensor node in prolonging the lifespan
                 of a WWPM system. A custom sensor node is designed
                 using the ESP32 MCU and nRF24L01+ transceiver.
                 Hierarchical sensing is implemented through the use of
                 LSM9DS1 and ADXL344 accelerometers, distributed
                 computing through the implementation of a distributed
                 Kalman filter, and duty cycling through the
                 implementation of interrupt-enabled sleep/wakeup
                 functionality. The experimental results reveal that
                 combining distributed computing, hierarchical sensing
                 and duty cycling reduces energy consumption by a factor
                 of eight compared to the lone implementation of
                 distributed computing.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Spyrou:2023:DDS,
  author =       "Evangelos D. Spyrou and Ioannis Tsoulos and
                 Chrysostomos Stylios",
  title =        "Distributed Denial of Service Classification for
                 Software-Defined Networking Using Grammatical
                 Evolution",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "401",
  day =          "13",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120401",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/401",
  abstract =     "Software-Defined Networking (SDN) stands as a pivotal
                 paradigm in network implementation, exerting a profound
                 influence on the trajectory of technological
                 advancement. The critical role of security within SDN
                 cannot be overstated, with distributed denial of
                 service (DDoS) emerging as a particularly disruptive
                 threat, capable of causing large-scale disruptions.
                 DDoS operates by generating malicious traffic that
                 mimics normal network activity, leading to service
                 disruptions. It becomes imperative to deploy mechanisms
                 capable of distinguishing between benign and malicious
                 traffic, serving as the initial line of defense against
                 DDoS challenges. In addressing this concern, we propose
                 the utilization of traffic classification as a
                 foundational strategy for combatting DDoS. By
                 categorizing traffic into malicious and normal streams,
                 we establish a crucial first step in the development of
                 effective DDoS mitigation strategies. The deleterious
                 effects of DDoS extend to the point of potentially
                 overwhelming networked servers, resulting in service
                 failures and SDN server downtimes. To investigate and
                 address this issue, our research employs a dataset
                 encompassing both benign and malicious traffic within
                 the SDN environment. A set of 23 features is harnessed
                 for classification purposes, forming the basis for a
                 comprehensive analysis and the development of robust
                 defense mechanisms against DDoS in SDN. Initially, we
                 compare GenClass with three common classification
                 methods, namely the Bayes, K-Nearest Neighbours (KNN),
                 and Random Forest methods. The proposed solution
                 improves the average class error, demonstrating 6.58\%
                 error as opposed to the Bayes method error of 32.59\%,
                 KNN error of 18.45\%, and Random Forest error of
                 30.70\%. Moreover, we utilize classification procedures
                 based on three methods based on grammatical evolution,
                 which are applied to the aforementioned data. In
                 particular, in terms of average class error, GenClass
                 exhibits 6.58\%, while NNC and FC2GEN exhibit average
                 class errors of 12.51\% and 15.86\%, respectively.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wu:2023:SBB,
  author =       "Lang Wu and Weijian Ruan and Jinhui Hu and Yaobin He",
  title =        "A Survey on Blockchain-Based Federated Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "400",
  day =          "12",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120400",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/400",
  abstract =     "Federated learning (FL) and blockchains exhibit
                 significant commonality, complementarity, and alignment
                 in various aspects, such as application domains,
                 architectural features, and privacy protection
                 mechanisms. In recent years, there have been notable
                 advancements in combining these two technologies,
                 particularly in data privacy protection, data sharing
                 incentives, and computational performance. Although
                 there are some surveys on blockchain-based federated
                 learning (BFL), these surveys predominantly focus on
                 the BFL framework and its classifications, yet lack
                 in-depth analyses of the pivotal issues addressed by
                 BFL. This work aims to assist researchers in
                 understanding the latest research achievements and
                 development directions in the integration of FL with
                 blockchains. Firstly, we introduced the relevant
                 research in FL and blockchain technology and
                 highlighted the existing shortcomings of FL. Next, we
                 conducted a comparative analysis of existing BFL
                 frameworks, delving into the significant problems in
                 the realm of FL that the combination of blockchain and
                 FL addresses. Finally, we summarized the application
                 prospects of BFL technology in various domains such as
                 the Internet of Things, Industrial Internet of Things,
                 Internet of Vehicles, and healthcare services, as well
                 as the challenges that need to be addressed and future
                 research directions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ravi:2023:AGI,
  author =       "Niranjan Ravi and Mohamed El-Sharkawy",
  title =        "Addressing the Gaps of {IoU} Loss in {3D} Object
                 Detection with {IIoU}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "399",
  day =          "11",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120399",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/399",
  abstract =     "Three-dimensional object detection involves estimating
                 the dimensions, orientations, and locations of 3D
                 bounding boxes. Intersection of Union (IoU) loss
                 measures the overlap between predicted 3D box and
                 ground truth 3D bounding boxes. The localization task
                 uses smooth-L1 loss with IoU to estimate the object's
                 location, and the classification task identifies the
                 object/class category inside each 3D bounding box.
                 Localization suffers a performance gap in cases where
                 the predicted and ground truth boxes overlap
                 significantly less or do not overlap, indicating the
                 boxes are far away, and in scenarios where the boxes
                 are inclusive. Existing axis-aligned IoU losses suffer
                 performance drop in cases of rotated 3D bounding boxes.
                 This research addresses the shortcomings in bounding
                 box regression problems of 3D object detection by
                 introducing an Improved Intersection Over Union (IIoU)
                 loss. The proposed loss function's performance is
                 experimented on LiDAR-based and Camera-LiDAR-based
                 fusion methods using the KITTI dataset.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ali:2023:ETN,
  author =       "Shrouk A. Ali and Shaimaa Ahmed Elsaid and Abdelhamied
                 A. Ateya and Mohammed ElAffendi and Ahmed A. Abd
                 El-Latif",
  title =        "Enabling Technologies for Next-Generation Smart
                 Cities: a Comprehensive Review and Research
                 Directions",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "398",
  day =          "09",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120398",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/398",
  abstract =     "The concept of smart cities, which aim to enhance the
                 quality of urban life through innovative technologies
                 and policies, has gained significant momentum in recent
                 years. As we approach the era of next-generation smart
                 cities, it becomes crucial to explore the key enabling
                 technologies that will shape their development. This
                 work reviews the leading technologies driving the
                 future of smart cities. The work begins by introducing
                 the main requirements of different smart city
                 applications; then, the enabling technologies are
                 presented. This work highlights the transformative
                 potential of the Internet of things (IoT) to facilitate
                 data collection and analysis to improve urban
                 infrastructure and services. As a complementary
                 technology, distributed edge computing brings
                 computational power closer to devices, reducing the
                 reliance on centralized data centers. Another key
                 technology is virtualization, which optimizes resource
                 utilization, enabling multiple virtual environments to
                 run efficiently on shared hardware. Software-defined
                 networking (SDN) emerges as a pivotal technology that
                 brings flexibility and scalability to smart city
                 networks, allowing for dynamic network management and
                 resource allocation. Artificial intelligence (AI) is
                 another approach for managing smart cities by enabling
                 predictive analytics, automation, and smart decision
                 making based on vast amounts of data. Lastly, the
                 blockchain is introduced as a promising approach for
                 smart cities to achieve the required security. The
                 review concludes by identifying potential research
                 directions to address the challenges and complexities
                 brought about by integrating these key enabling
                 technologies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hernandez-Suarez:2023:MAI,
  author =       "Aldo Hernandez-Suarez and Gabriel Sanchez-Perez and
                 Linda Karina Toscano-Medina and Hector Manuel
                 Perez-Meana and Jose Portillo-Portillo and Jesus
                 Olivares-Mercado",
  title =        "Methodological Approach for Identifying {Websites}
                 with Infringing Content via Text Transformers and Dense
                 Neural Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "397",
  day =          "09",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120397",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/397",
  abstract =     "The rapid evolution of the Internet of Everything
                 (IoE) has significantly enhanced global connectivity
                 and multimedia content sharing, simultaneously
                 escalating the unauthorized distribution of multimedia
                 content, posing risks to intellectual property rights.
                 In 2022 alone, about 130 billion accesses to
                 potentially non-compliant websites were recorded,
                 underscoring the challenges for industries reliant on
                 copyright-protected assets. Amidst prevailing
                 uncertainties and the need for technical and
                 AI-integrated solutions, this study introduces two
                 pivotal contributions. First, it establishes a novel
                 taxonomy aimed at safeguarding and identifying
                 IoE-based content infringements. Second, it proposes an
                 innovative architecture combining IoE components with
                 automated sensors to compile a dataset reflective of
                 potential copyright breaches. This dataset is analyzed
                 using a Bidirectional Encoder Representations from
                 Transformers-based advanced Natural Language Processing
                 (NLP) algorithm, further fine-tuned by a dense neural
                 network (DNN), achieving a remarkable 98.71\% accuracy
                 in pinpointing websites that violate copyright.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gomez:2023:PPF,
  author =       "Javier Gomez and Jose Jaime Camacho-Escoto and Luis
                 Orozco-Barbosa and Diego Rodriguez-Torres",
  title =        "{PROFEE}: a Probabilistic-Feedback Based Speed Rate
                 Adaption for {IEEE 802.11bc}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "396",
  day =          "09",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120396",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/396",
  abstract =     "WiFi is a widely used wireless technology for data
                 transmission. WiFi can also play a crucial role in
                 simultaneously broadcasting content to multiple devices
                 in multimedia transmission for venues such as
                 classrooms, theaters, and stadiums, etc. Broadcasting
                 allows for the efficient dissemination of information
                 to all devices connected to the network, and it becomes
                 crucial to ensure that the WiFi network has sufficient
                 capacity to transmit broadcast multimedia content
                 without interruptions or delays. However, using WiFi
                 for broadcasting presents challenges that can impact
                 user experience, specifically the difficulty of
                 obtaining real-time feedback from potentially hundreds
                 or thousands of users due to potential collisions of
                 feedback messages. This work focuses on providing
                 accurate feedback to the Access Point about the
                 percentage of users not receiving broadcast traffic
                 correctly so it can adjust its Modulation and Coding
                 Scheme (MCS) while transmitting broadcast multimedia
                 content to many users. The proposed method is comprised
                 of two sequential algorithms. In order to reduce the
                 probability of a collision after transmitting each
                 message, an algorithm searches for the best probability
                 value for users to transmit ACK/NACK messages,
                 depending on whether messages are received correctly or
                 not. This feedback allows the Access Point to estimate
                 the number of STAs correctly/incorrectly receiving the
                 messages being transmitted. A second algorithm uses
                 this estimation so the Access Point can select the best
                 MCS while maintaining the percentage of users not
                 receiving broadcast content correctly within acceptable
                 margins, thus providing users with the best possible
                 content quality. We implemented the proposed method in
                 the ns-3 simulator, and the results show it yields
                 quick, reliable feedback to the Access Point that was
                 then able to adjust to the best possible MCS in only a
                 few seconds, regardless of the user density and
                 dimensions of the scenario.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2023:LGB,
  author =       "Zuopeng Li and Hengshuai Ju and Zepeng Ren",
  title =        "A Learning Game-Based Approach to Task-Dependent Edge
                 Resource Allocation",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "395",
  day =          "07",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120395",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/395",
  abstract =     "The existing research on dependent task offloading and
                 resource allocation assumes that edge servers can
                 provide computational and communication resources free
                 of charge. This paper proposes a two-stage resource
                 allocation method to address this issue. In the first
                 stage, users incentivize edge servers to provide
                 resources. We formulate the incentive problem in this
                 stage as a multivariate Stackelberg game, which takes
                 into account both computational and communication
                 resources. In addition, we also analyze the uniqueness
                 of the Stackelberg equilibrium under information
                 sharing conditions. Considering the privacy issues of
                 the participants, the research is extended to scenarios
                 without information sharing, where the multivariable
                 game problem is modeled as a partially observable
                 Markov decision process (POMDP). In order to obtain the
                 optimal incentive decision in this scenario, a
                 reinforcement learning algorithm based on the learning
                 game is designed. In the second stage, we propose a
                 greedy-based deep reinforcement learning algorithm that
                 is aimed at minimizing task execution time by
                 optimizing resource and task allocation strategies.
                 Finally, the simulation results demonstrate that the
                 algorithm designed for non-information sharing
                 scenarios can effectively approximate the theoretical
                 Stackelberg equilibrium, and its performance is found
                 to be better than that of the other three benchmark
                 methods. After the allocation of resources and
                 sub-tasks by the greedy-based deep reinforcement
                 learning algorithm, the execution delay of the
                 dependent task is significantly lower than that in
                 local processing.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sabatucci:2023:EDP,
  author =       "Luca Sabatucci and Agnese Augello and Giuseppe
                 Caggianese and Luigi Gallo",
  title =        "Envisioning Digital Practices in the Metaverse: a
                 Methodological Perspective",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "394",
  day =          "06",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120394",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/394",
  abstract =     "Researchers are exploring methods that exploit digital
                 twins as all-purpose abstractions for sophisticated
                 modelling and simulation, bringing elements of the real
                 world into the virtual realm. Digital twins are
                 essential elements of the digital transformation of
                 society, which mostly benefit manufacturing, smart
                 cities, healthcare contexts, and in general systems
                 that include humans in the loop. As the metaverse
                 concept continues to evolve, the line separating the
                 virtual and the real will progressively fade away.
                 Considering the metaverse's goal to emulate our social
                 reality, it becomes essential to examine the aspects
                 that characterise real-world interaction practices and
                 explicitly model both physical and social contexts.
                 While the unfolding metaverse may reshape these
                 practices in distinct ways from their real-world
                 counterparts, our position is that it is essential to
                 incorporate social theories into the modelling
                 processes of digital twins within the metaverse. In
                 this work, we discuss our perspective by introducing a
                 digital practice model inspired by the theory of social
                 practice. We illustrate this model by exploiting the
                 scenario of a virtual grocery shop designed to help
                 older adults reduce their social isolation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Poleto:2023:ISA,
  author =       "Thiago Poleto and Thyago Celso Cavalcante Nepomuceno
                 and Victor Diogho Heuer de Carvalho and Ligiane
                 Cristina Braga de Oliveira Friaes and Rodrigo Cleiton
                 Paiva de Oliveira and Ciro Jos{\'e} Jardim Figueiredo",
  title =        "Information Security Applications in Smart Cities: a
                 Bibliometric Analysis of Emerging Research",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "393",
  day =          "01",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120393",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/393",
  abstract =     "This paper aims to analyze the intellectual structure
                 and research fronts in application information security
                 in smart cities to identify research boundaries,
                 trends, and new opportunities in the area. It applies
                 bibliometric analyses to identify the main authors and
                 their influences on information security and the smart
                 city area. Moreover, this analysis focuses on journals
                 indexed in Scopus databases. The results indicate that
                 there is an opportunity for further advances in the
                 adoption of information security policies in government
                 institutions. Moreover, the production indicators
                 presented herein are useful for the planning and
                 implementation of information security policies and the
                 knowledge of the scientific community about smart
                 cities. The bibliometric analysis provides support for
                 the visualization of the leading research technical
                 collaboration networks among authors, co-authors,
                 countries, and research areas. The methodology offers a
                 broader view of the application information security in
                 smart city areas and makes it possible to assist new
                 research that may contribute to further advances. The
                 smart cities topic has been receiving much attention in
                 recent years, but to the best of our knowledge, there
                 is no research on reporting new possibilities for
                 advances. Therefore, this article may contribute to an
                 emerging body of literature that explores the nature of
                 application information security and smart cities
                 research productivity to assist researchers in better
                 understanding the current emerging of the area.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lopez-Ardao:2023:RAI,
  author =       "Jos{\'e} Carlos L{\'o}pez-Ardao and Miguel
                 Rodr{\'\i}guez-P{\'e}rez and Sergio
                 Herrer{\'\i}a-Alonso",
  title =        "Recent Advances in Information-Centric Networks
                 ({ICNs})",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "392",
  day =          "01",
  month =        dec,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120392",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/392",
  abstract =     "This paper aims to analyze the intellectual structure
                 and research fronts in application information security
                 in smart cities to identify research boundaries,
                 trends, and new opportunities in the area. It applies
                 bibliometric analyses to identify the main authors and
                 their influences on information security and the smart
                 city area. Moreover, this analysis focuses on journals
                 indexed in Scopus databases. The results indicate that
                 there is an opportunity for further advances in the
                 adoption of information security policies in government
                 institutions. Moreover, the production indicators
                 presented herein are useful for the planning and
                 implementation of information security policies and the
                 knowledge of the scientific community about smart
                 cities. The bibliometric analysis provides support for
                 the visualization of the leading research technical
                 collaboration networks among authors, co-authors,
                 countries, and research areas. The methodology offers a
                 broader view of the application information security in
                 smart city areas and makes it possible to assist new
                 research that may contribute to further advances. The
                 smart cities topic has been receiving much attention in
                 recent years, but to the best of our knowledge, there
                 is no research on reporting new possibilities for
                 advances. Therefore, this article may contribute to an
                 emerging body of literature that explores the nature of
                 application information security and smart cities
                 research productivity to assist researchers in better
                 understanding the current emerging of the area.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Pashazadeh:2023:CSE,
  author =       "Ali Pashazadeh and Giovanni Nardini and Giovanni
                 Stea",
  title =        "A Comprehensive Survey Exploring the Multifaceted
                 Interplay between Mobile Edge Computing and Vehicular
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "391",
  day =          "30",
  month =        nov,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120391",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/391",
  abstract =     "In recent years, the need for computation-intensive
                 applications in mobile networks requiring more storage,
                 powerful processors, and real-time responses has risen
                 substantially. Vehicular networks play an important
                 role in this ecosystem, as they must support multiple
                 services, such as traffic monitoring or sharing of data
                 involving different aspects of the vehicular traffic.
                 Moreover, new resource-hungry applications have been
                 envisaged, such as autonomous driving or in-cruise
                 entertainment, hence making the demand for computation
                 and storage resources one of the most important
                 challenges in vehicular networks. In this context,
                 Mobile Edge Computing (MEC) has become the key
                 technology to handle these problems by providing
                 cloud-like capabilities at the edge of mobile networks
                 to support delay-sensitive and computation-intensive
                 tasks. In the meantime, researchers have envisaged use
                 of onboard vehicle resources to extend the computing
                 capabilities of MEC systems. This paper presents a
                 comprehensive review of the most recent works related
                 to MEC-assisted vehicular networks, as well as
                 vehicle-assisted MEC systems. We illustrate the MEC
                 system architecture and discuss its deployment in
                 vehicular environments, as well as the key technologies
                 to realize this integration. After that, we review the
                 recent literature by identifying three different areas,
                 i.e.: (i) MEC providing additional resources to
                 vehicles (e.g., for task offloading); (ii) MEC enabling
                 innovative vehicular applications (e.g., platooning),
                 and (iii) vehicular networks providing additional
                 resources to MEC systems. Finally, we discuss open
                 challenges and future research directions, addressing
                 the possible interplays between MEC systems and
                 vehicular networks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gao:2023:IBE,
  author =       "Lei Gao and Xiaoyong Zhu",
  title =        "{ICN}-Based Enhanced Content Delivery for {CDN}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "390",
  day =          "30",
  month =        nov,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120390",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/390",
  abstract =     "With the rapid growth of internet traffic, the
                 traditional host-to-host TCP/IP architecture is subject
                 to many service limitations faced with content-oriented
                 applications. Various novel network architectures have
                 been proposed to solve these limitations, among which
                 Information-Centric Networking (ICN) is one of the most
                 prominent. ICN features the decoupling of content
                 (service) from the physical devices storing (providing)
                 it through location-independent naming, and offers
                 inherent enhancement to network performance, such as
                 multicast and in-network caching. ICN in-network
                 caching has been extensively studied, and we believe
                 that it may also be the main incentive for ISPs to
                 deploy ICN. A CDN (content delivery network) is a
                 typical content-oriented network paradigm that aims to
                 provide the fast delivery of content. In this paper, we
                 leverage the advantages of the in-network caching of
                 ICN to enhance the content delivery efficiency of CDN
                 by integrating ICN as a service. First, we present our
                 design of a content delivery network enhanced with ICN,
                 called IECDN. Additionally, we formulate a mathematical
                 model to optimize the performance of our proposed
                 design and conduct a series of evaluations. The results
                 indicate that our proposed design provides significant
                 performance gains while reducing bandwidth consumption
                 and shows better resilience to traffic surge.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ren:2023:KDB,
  author =       "Yingying Ren and Ryan D. Restivo and Wenkai Tan and
                 Jian Wang and Yongxin Liu and Bin Jiang and Huihui Wang
                 and Houbing Song",
  title =        "Knowledge Distillation-Based {GPS} Spoofing Detection
                 for Small {UAV}",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "389",
  day =          "30",
  month =        nov,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120389",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/389",
  abstract =     "As a core component of small unmanned aerial vehicles
                 (UAVs), GPS is playing a critical role in providing
                 localization for UAV navigation. UAVs are an important
                 factor in the large-scale deployment of the Internet of
                 Things (IoT) and cyber--physical systems (CPS).
                 However, GPS is vulnerable to spoofing attacks that can
                 mislead a UAV to fly into a sensitive area and threaten
                 public safety and private security. The conventional
                 spoofing detection methods need too much overhead,
                 which stops efficient detection from working in a
                 computation-constrained UAV and provides an efficient
                 response to attacks. In this paper, we propose a novel
                 approach to obtain a lightweight detection model in the
                 UAV system so that GPS spoofing attacks can be detected
                 from a long distance. With long-short term memory
                 (LSTM), we propose a lightweight detection model on the
                 ground control stations, and then we distill it into a
                 compact size that is able to run in the control system
                 of the UAV with knowledge distillation. The
                 experimental results show that our lightweight
                 detection algorithm runs in UAV systems reliably and
                 can achieve good performance in GPS spoofing
                 detection.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Severino:2023:PHN,
  author =       "Ricardo Severino and Jos{\'e} Sim{\~a}o and Nuno Datia
                 and Ant{\'o}nio Serrador",
  title =        "Protecting Hybrid {ITS} Networks: a Comprehensive
                 Security Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "388",
  day =          "30",
  month =        nov,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120388",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/388",
  abstract =     "Cooperative intelligent transport systems (C-ITS)
                 continue to be developed to enhance transportation
                 safety and sustainability. However, the communication
                 of vehicle-to-everything (V2X) systems is inherently
                 open, leading to vulnerabilities that attackers can
                 exploit. This represents a threat to all road users, as
                 security failures can lead to privacy violations or
                 even fatalities. Moreover, a high fatality rate is
                 correlated with soft-mobility road users. Therefore,
                 when developing C-ITS systems, it is important to
                 broaden the focus beyond connected vehicles to include
                 soft-mobility users and legacy vehicles. This work
                 presents a new approach developed in the context of
                 emerging hybrid networks, combining intelligent
                 transport systems operating in 5.9 GHz (ITS-G5) and
                 radio-mobile cellular technologies. Two protocols were
                 implemented and evaluated to introduce security
                 guarantees (such as privacy and integrity) in
                 communications within the developed C-ITS hybrid
                 environment. As a result, this work securely integrates
                 G5-connected ITS stations and soft-mobility users
                 through a smartphone application via cellular networks.
                 Commercial equipment was used for this goal, including
                 on-board and roadside units. Computational,
                 transmission and end-to-end latency were used to assess
                 the system's performance. Implemented protocols
                 introduce an additional 11\% end-to-end latency in
                 hybrid communications. Moreover, workflows employing
                 hybrid communications impose, on average, an extra
                 28.29 ms of end-to-end latency. The proposal shows
                 promise, as it reaches end-to-end times below the
                 latency requirements imposed in most C-ITS use cases.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fouzar:2023:SVC,
  author =       "Youcef Fouzar and Ahmed Lakhssassi and Ramakrishna
                 Mundugar",
  title =        "Secure Video Communication Using Multi-Equation
                 Multi-Key Hybrid Cryptography",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "387",
  day =          "29",
  month =        nov,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120387",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/387",
  abstract =     "The safeguarding of intellectual property and
                 maintaining privacy for video content are closely
                 linked to the effectiveness of security protocols
                 employed in internet streaming platforms. The
                 inadequate implementation of security measures by
                 content providers has resulted in security breaches
                 within entertainment applications, hence causing a
                 reduction in the client base. This research aimed to
                 enhance the security measures employed for video
                 content by implementing a multi-key approach for
                 encryption and decryption processes. The aforementioned
                 objective was successfully accomplished through the use
                 of hybrid methodologies, the production of dynamic
                 keys, and the implementation of user-attribute-based
                 techniques. The main aim of the study was to improve
                 the security measures associated with the process of
                 generating video material. The proposed methodology
                 integrates a system of mathematical equations and a
                 pseudorandom key within its execution. This novel
                 approach significantly augments the degree of security
                 the encryption mechanism provides. The proposed
                 methodology utilises a set of mathematical equations
                 that are randomly employed to achieve encryption. Using
                 a random selection procedure contributes to the overall
                 enhancement of the system's security. The suggested
                 methodology entails the division of the video into
                 smaller entities known as chunks. Following this, every
                 segment is subjected to encryption using unique keys
                 that are produced dynamically in real-time. The
                 proposed methodology is executed via Android platforms.
                 The transmitter application is tasked with the
                 responsibility of facilitating the streaming of the
                 video content, whereas the receiver application serves
                 the purpose of presenting the video to the user. A
                 careful study was conducted to compare and contrast the
                 suggested method with other similar methods that were
                 already in use. The results of the study strongly
                 support the safety and dependability of the procedure
                 that was made available.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ashraf:2023:LPP,
  author =       "Zeeshan Ashraf and Zahid Mahmood and Muddesar Iqbal",
  title =        "Lightweight Privacy-Preserving Remote User
                 Authentication and Key Agreement Protocol for
                 Next-Generation {IoT}-Based Smart Healthcare",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "386",
  day =          "29",
  month =        nov,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120386",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/386",
  abstract =     "The advancement and innovations in wireless
                 communication technologies including the Internet of
                 Things have massively changed the paradigms of
                 health-based services. In particular, during the
                 COVID-19 pandemic, the trends of working from home have
                 been promoted. Wireless body area network technology
                 frameworks help sufferers in remotely obtaining
                 scientific remedies from physicians through the
                 Internet without paying a visit to the clinics. IoT
                 sensor nodes are incorporated into the clinical device
                 to allow health workers to consult the patients'
                 fitness conditions in real time. Insecure wireless
                 communication channels make unauthorized access to
                 fitness-related records and manipulation of IoT sensor
                 nodes attached to the patient's bodies possible, as a
                 result of security flaws. As a result, IoT-enabled
                 devices are threatened by a number of well-known
                 attacks, including impersonation, replay,
                 man-in-the-middle, and denial-of-service assaults.
                 Modern authentication schemes do solve these issues,
                 but they frequently involve challenging mathematical
                 concepts that raise processing and transmission costs.
                 In this paper, we propose a lightweight, secure, and
                 efficient symmetric key exchange algorithm and remote
                 user authentication scheme. Our research proposal
                 presents a successful privacy-protecting method for
                 remote users and provides protection against known
                 attacks. When compared to conventional options, this
                 technique significantly reduces calculation costs by up
                 to 37.68\% and transmission costs by up to 32.55\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liu:2023:TRC,
  author =       "Hongyu Liu and Hong Ni and Rui Han",
  title =        "A Transmission Rate Control Method for Active
                 Congestion Reduction Based on Network Node Bandwidth
                 Allocation",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "385",
  day =          "29",
  month =        nov,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120385",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/385",
  abstract =     "The control of transmission rates is currently a major
                 topic in network research, as it plays a significant
                 role in determining network performance. Traditional
                 network design principles suggest that network nodes
                 should only be responsible for forwarding data, while
                 the sending node should manage control. However,
                 sending nodes often lack information about network
                 resources and must use slow-start algorithms to
                 increase the transmission rate, potentially leading to
                 wasted bandwidth and network congestion. Furthermore,
                 incorrect judgments about network congestion by sending
                 nodes may further reduce network throughput. The
                 emergence of new Internet architectures, such as
                 information-centric networks (ICNn), has empowered
                 network nodes with more capabilities, including
                 computation and caching. This paper proposes a method
                 for transmission rate control that actively avoids
                 congestion through network node bandwidth allocation.
                 The sending, network, and receiving nodes each
                 calculate the available transmission rate, and the
                 sending node negotiates with the other nodes through a
                 rate negotiation message to obtain the maximum
                 transmission rate possible given the current state of
                 the network. The network nodes notify the sending node
                 to adjust the transmission rate to adapt to changes in
                 the network through a rate adjustment message.
                 Simulation experiments show that the proposed method is
                 better than traditional methods in reducing network
                 congestion, providing a stable transmission rate,
                 increasing the network throughput capacity, and
                 improving performance in high-latency and
                 high-bandwidth networks. Additionally, the proposed
                 transmission rate control method is fairer than
                 traditional methods.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kobza:2023:EBE,
  author =       "Ondrej Kobza and David Herel and Jan Cuhel and Tommaso
                 Gargiani and Jan Pichl and Petr Marek and Jakub Konrad
                 and Jan Sedivy",
  title =        "Enhancements in {BlenderBot 3}: Expanding Beyond a
                 Singular Model Governance and Boosting Generational
                 Performance",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "384",
  day =          "28",
  month =        nov,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120384",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/384",
  abstract =     "This paper provides a pioneering examination and
                 enhancement of generative chat models, with a specific
                 focus on the BlenderBot 3 model. Through meticulous
                 interaction with a diverse set of human participants,
                 we dissected the fundamental components of these
                 models, unveiling several deficiencies, including
                 long-term memory and entity recognition. Leveraging
                 these insights, we engineered refined, streamlined
                 iterations, culminating in a chatbot that transcends
                 the capabilities of all existing models. Our work
                 follows Occam's razor principle and proves that, for
                 tasks with relatively low complexity, using large
                 overparameterized models instead of smaller ones does
                 not bring significant benefits but increases latency,
                 which may result in a lowered overall user experience.
                 In upholding our commitment to transparency and the
                 progression of shared knowledge, we have made our
                 improved model universally accessible through
                 open-source distribution.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gkonis:2023:SIE,
  author =       "Panagiotis Gkonis and Anastasios Giannopoulos and
                 Panagiotis Trakadas and Xavi Masip-Bruin and Francesco
                 D'Andria",
  title =        "A Survey on {IoT}-Edge-Cloud Continuum Systems:
                 Status, Challenges, Use Cases, and Open Issues",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "383",
  day =          "28",
  month =        nov,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120383",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/383",
  abstract =     "The rapid growth in the number of interconnected
                 devices on the Internet (referred to as the Internet of
                 Things---IoT), along with the huge volume of data that
                 are exchanged and processed, has created a new
                 landscape in network design and operation. Due to the
                 limited battery size and computational capabilities of
                 IoT nodes, data processing usually takes place on
                 external devices. Since latency minimization is a key
                 concept in modern-era networks, edge servers that are
                 in close proximity to IoT nodes gather and process
                 related data, while in some cases data offloading in
                 the cloud might have to take place. The interconnection
                 of a vast number of heterogeneous IoT devices with the
                 edge servers and the cloud, where the IoT, edge, and
                 cloud converge to form a computing continuum, is also
                 known as the IoT-edge-cloud (IEC) continuum. Several
                 key challenges are associated with this new computing
                 systems' architectural approach, including (i) the
                 design of connection and programming protocols aimed at
                 properly manipulating a huge number of heterogeneous
                 devices over diverse infrastructures; (ii) the design
                 of efficient task offloading algorithms aimed at
                 optimizing services execution; (iii) the support for
                 security and privacy enhancements during data transfer
                 to deal with the existent and even unforeseen attacks
                 and threats landscape; (iv) scalability, flexibility,
                 and reliability guarantees to face the expected
                 mobility for IoT systems; and (v) the design of optimal
                 resource allocation mechanisms to make the most out of
                 the available resources. These challenges will become
                 even more significant towards the new era of
                 sixth-generation (6G) networks, which will be based on
                 the integration of various cutting-edge heterogeneous
                 technologies. Therefore, the goal of this survey paper
                 is to present all recent developments in the field of
                 IEC continuum systems, with respect to the
                 aforementioned deployment challenges. In the same
                 context, potential limitations and future challenges
                 are highlighted as well. Finally, indicative use cases
                 are also presented from an IEC continuum perspective.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Marin:2023:RBT,
  author =       "Oana Marin and Tudor Cioara and Liana Toderean and Dan
                 Mitrea and Ionut Anghel",
  title =        "Review of Blockchain Tokens Creation and Valuation",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "382",
  day =          "27",
  month =        nov,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120382",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/382",
  abstract =     "Blockchain and tokens are relatively new research
                 areas insufficiently explored from both technical and
                 economic perspectives. Even though tokens provide
                 benefits such as easier market access, increased
                 liquidity, lower transaction costs, and automated
                 transactional process, their valuation and price
                 determination are still challenging due to factors such
                 as a lack of intrinsic value, volatility, and
                 regulation making trading risky. In this paper, we
                 address this knowledge gap by reviewing the existing
                 literature on token creation and valuation to identify
                 and document the factors affecting their valuation,
                 investment, and founding, as well as the most promising
                 domains of applicability. The study follows the PRISMA
                 methodology and uses the Web of Science database,
                 defining clear research questions and objective
                 inclusion criteria for the articles. We discuss token
                 technical development, including creating, issuing, and
                 managing tokens on an Ethereum blockchain using smart
                 contracts. The study revealed several key factors that
                 significantly impact the field of tokenomics: demand
                 and supply, social incentives, market conditions,
                 macroeconomics, collective behavior, speculation, and
                 inclusion in index funds. The most relevant use cases
                 of blockchain and tokens are related to the
                 digitization of virtual and physical assets,
                 accountability, and traceability usual in smart grids
                 or supply chains management, social governance, and art
                 and gamification including metaverse.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Nadal:2023:MSD,
  author =       "Laia Nadal and Mumtaz Ali and Francisco Javier
                 V{\'\i}lchez and Josep Maria F{\`a}brega and Michela
                 Svaluto Moreolo",
  title =        "The Multiband over Spatial Division Multiplexing
                 Sliceable Transceiver for Future Optical Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "381",
  day =          "27",
  month =        nov,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120381",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/381",
  abstract =     "In the last 15 years, global data traffic has been
                 doubling approximately every 2--3 years, and there is a
                 strong indication that this pattern will persist.
                 Hence, also driven by the emergence of new applications
                 and services expected within the 6G era, new
                 transmission systems and technologies should be
                 investigated to enhance network capacity and achieve
                 increased bandwidth, improved spectral efficiency, and
                 greater flexibility to effectively accommodate all the
                 expected data traffic. In this paper, an innovative
                 transmission solution based on multiband (MB) over
                 spatial division multiplexing (SDM) sliceable
                 bandwidth/bitrate variable transceiver (S-BVT) is
                 implemented and assessed in relation to the provision
                 of sustainable capacity scaling. MB transmission
                 (S+C+L) over 25.4 km of 19-cores multicore fibre (MCF)
                 is experimentally assessed and demonstrated achieving
                 an aggregated capacity of 119.1 Gb/s at 4.62 $ \times $
                 $10^{-3}$ bit error rate (BER). The proposed modular
                 sliceable transceiver architecture arises as a suitable
                 option towards achieving 500 Tb/s per fibre
                 transmission, by further enabling more slices covering
                 all the available S+C+L spectra and the 19 cores of the
                 MCF.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Musa:2023:ORA,
  author =       "Abubakar Ahmad Musa and Adamu Hussaini and Cheng Qian
                 and Yifan Guo and Wei Yu",
  title =        "Open Radio Access Networks for Smart {IoT} Systems:
                 State of Art and Future Directions",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "380",
  day =          "27",
  month =        nov,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120380",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/380",
  abstract =     "The Internet of Things (IoT) constitutes a vast
                 network comprising various components such as physical
                 devices, vehicles, buildings, and other items equipped
                 with sensors, actuators, and software. These components
                 are interconnected, facilitating the collection and
                 exchange of copious data across networked
                 communications. IoT empowers extensive monitoring and
                 control over a myriad of objects, enabling them to
                 gather and disseminate data that bolster applications,
                 thereby enhancing the system's capacity for informed
                 decision making, environmental surveillance, and
                 autonomous inter-object interaction, all without the
                 need for direct human involvement. These systems have
                 achieved seamless connectivity requirements using the
                 next-generation wireless network infrastructures (5G,
                 6G, etc.), while their diverse reliability and quality
                 of service (QoS) requirements across various domains
                 require more efficient solutions. Open RAN (O-RAN),
                 i.e., open radio open access network (RAN), promotes
                 flexibility and intelligence in the next-generation
                 RAN. This article reviews the applications of O-RAN in
                 supporting the next-generation smart world IoT systems
                 by conducting a thorough survey. We propose a generic
                 problem space, which consists of (i) IoT Systems:
                 transportation, industry, healthcare, and energy; (ii)
                 targets: reliable communication, real-time analytics,
                 fault tolerance, interoperability, and integration; and
                 (iii) artificial intelligence and machine learning
                 (AI/ML): reinforcement learning (RL), deep neural
                 networks (DNNs), etc. Furthermore, we outline future
                 research directions concerning robust and scalable
                 solutions, interoperability and standardization,
                 privacy, and security. We present a taxonomy to unveil
                 the security threats to emerge from the O-RAN-assisted
                 IoT systems and the feasible directions to move this
                 research forward.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Marin-Vega:2023:ERX,
  author =       "Humberto Mar{\'\i}n-Vega and Giner Alor-Hern{\'a}ndez
                 and Maritza Bustos-L{\'o}pez and Ignacio
                 L{\'o}pez-Mart{\'\i}nez and Norma Leticia
                 Hern{\'a}ndez-Chaparro",
  title =        "Extended Reality ({XR}) Engines for Developing
                 Gamified Apps and Serious Games: a Scoping Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "379",
  day =          "27",
  month =        nov,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120379",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/379",
  abstract =     "Extended Reality (XR) is an emerging technology that
                 enables enhanced interaction between the real world and
                 virtual environments. In this study, we conduct a
                 scoping review of XR engines for developing gamified
                 apps and serious games. Our study revolves around four
                 aspects: (1) existing XR game engines, (2) their
                 primary features, (3) supported serious game
                 attributes, and (4) supported learning activities. We
                 used the Preferred Reporting Items for Systematic
                 Reviews and Meta-Analyses (PRISMA) model to conduct the
                 scoping review, which included 40 primary studies
                 published between 2019 and 2023. Our findings help us
                 understand how current XR engines support the
                 development of XR-enriched serious games and gamified
                 apps for specific learning activities. Additionally,
                 based on our findings, we suggest a set of
                 pre-established game attributes that could be commonly
                 supported by all XR game engines across the different
                 game categories proposed by Lameras. Hence, this
                 scoping review can help developers (1) select important
                 game attributes for their new games and (2) choose the
                 game engine that provides the most support to these
                 attributes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mangi:2023:SMC,
  author =       "Fawad Ali Mangi and Guoxin Su and Minjie Zhang",
  title =        "Statistical Model Checking in Process Mining: a
                 Comprehensive Approach to Analyse Stochastic
                 Processes",
  journal =      j-FUTURE-INTERNET,
  volume =       "15",
  number =       "12",
  pages =        "378",
  day =          "26",
  month =        nov,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi15120378",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Dec 23 05:04:14 MST 2023",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/15/12/378",
  abstract =     "The study of business process analysis and
                 optimisation has attracted significant scholarly
                 interest in the recent past, due to its integral role
                 in boosting organisational performance. A specific area
                 of focus within this broader research field is process
                 mining (PM). Its purpose is to extract knowledge and
                 insights from event logs maintained by information
                 systems, thereby discovering process models and
                 identifying process-related issues. On the other hand,
                 statistical model checking (SMC) is a verification
                 technique used to analyse and validate properties of
                 stochastic systems that employs statistical methods and
                 random sampling to estimate the likelihood of a
                 property being satisfied. In a seamless business
                 setting, it is essential to validate and verify process
                 models. The objective of this paper is to apply the SMC
                 technique in process mining for the verification and
                 validation of process models with stochastic behaviour
                 and large state space, where probabilistic model
                 checking is not feasible. We propose a novel
                 methodology in this research direction that integrates
                 SMC and PM by formally modelling discovered and
                 replayed process models and apply statistical methods
                 to estimate the results. The methodology facilitates an
                 automated and proficient evaluation of the extent to
                 which a process model aligns with user requirements and
                 assists in selecting the optimal model. We demonstrate
                 the effectiveness of our methodology with a case study
                 of a loan application process performed in a financial
                 institution that deals with loan applications submitted
                 by customers. The case study highlights our
                 methodology's capability to identify the performance
                 constraints of various process models and aid
                 enhancement efforts.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ramzan:2024:BCB,
  author =       "Muhammad Sher Ramzan and Anees Asghar and Ata Ullah
                 and Fawaz Alsolami and Iftikhar Ahmad",
  title =        "A Bee Colony-Based Optimized Searching Mechanism in
                 the {Internet of Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "35",
  day =          "22",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010035",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/35",
  abstract =     "The Internet of Things (IoT) consists of complex and
                 dynamically aggregated elements or smart entities that
                 need decentralized supervision for data exchanging
                 throughout different networks. The artificial bee
                 colony (ABC) is utilized in optimization problems for
                 the big data in IoT, cloud and central repositories.
                 The main limitation during the searching mechanism is
                 that every single food site is compared with every
                 other food site to find the best solution in the
                 neighboring regions. In this way, an extensive number
                 of redundant comparisons are required, which results in
                 a slower convergence rate, greater time consumption and
                 increased delays. This paper presents a solution to
                 optimize search operations with an enhanced ABC (E-ABC)
                 approach. The proposed algorithm compares the best food
                 sites with neighboring sites to exclude poor sources.
                 It achieves an efficient mechanism, where the number of
                 redundant comparisons is decreased during the searching
                 mechanism of the employed bee phase and the onlooker
                 bee phase. The proposed algorithm is implemented in a
                 replication scenario to validate its performance in
                 terms of the mean objective function values for
                 different functions, as well as the probability of
                 availability and the response time. The results prove
                 the superiority of the E-ABC in contrast to its
                 counterparts.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liu:2024:IIH,
  author =       "Jui-Chuan Liu and Heng-Xiao Chi and Ching-Chun Chang
                 and Chin-Chen Chang",
  title =        "An Innovative Information Hiding Scheme Based on
                 Block-Wise Pixel Reordering",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "34",
  day =          "22",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010034",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/34",
  abstract =     "Information has been uploaded and downloaded through
                 the Internet, day in and day out, ever since we
                 immersed ourselves in the Internet. Data security has
                 become an area demanding high attention, and one of the
                 most efficient techniques for protecting data is data
                 hiding. In recent studies, it has been shown that the
                 indices of a codebook can be reordered to hide secret
                 bits. The hiding capacity of the codeword index
                 reordering scheme increases when the size of the
                 codebook increases. Since the codewords in the codebook
                 are not modified, the visual performance of compressed
                 images is retained. We propose a novel scheme making
                 use of the fundamental principle of the codeword index
                 reordering technique to hide secret data in encrypted
                 images. By observing our experimental results, we can
                 see that the obtained embedding capacity of 197,888 is
                 larger than other state-of-the-art schemes. Secret data
                 can be extracted when a receiver owns a data hiding
                 key, and the image can be recovered when a receiver
                 owns an encryption key.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Daousis:2024:OPS,
  author =       "Spyridon Daousis and Nikolaos Peladarinos and
                 Vasileios Cheimaras and Panagiotis Papageorgas and
                 Dimitrios D. Piromalis and Radu Adrian Munteanu",
  title =        "Overview of Protocols and Standards for Wireless
                 Sensor Networks in Critical Infrastructures",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "33",
  day =          "21",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010033",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/33",
  abstract =     "This paper highlights the crucial role of wireless
                 sensor networks (WSNs) in the surveillance and
                 administration of critical infrastructures (CIs),
                 contributing to their reliability, security, and
                 operational efficiency. It starts by detailing the
                 international significance and structural aspects of
                 these infrastructures, mentions the market tension in
                 recent years in the gradual development of wireless
                 networks for industrial applications, and proceeds to
                 categorize WSNs and examine the protocols and standards
                 of WSNs in demanding environments like critical
                 infrastructures, drawing on the recent literature. This
                 review concentrates on the protocols and standards
                 utilized in WSNs for critical infrastructures, and it
                 concludes by identifying a notable gap in the
                 literature concerning quality standards for equipment
                 used in such infrastructures.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Khazane:2024:HRM,
  author =       "Hassan Khazane and Mohammed Ridouani and Fatima
                 Salahdine and Naima Kaabouch",
  title =        "A Holistic Review of Machine Learning Adversarial
                 Attacks in {IoT} Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "32",
  day =          "19",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010032",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/32",
  abstract =     "With the rapid advancements and notable achievements
                 across various application domains, Machine Learning
                 (ML) has become a vital element within the Internet of
                 Things (IoT) ecosystem. Among these use cases is IoT
                 security, where numerous systems are deployed to
                 identify or thwart attacks, including intrusion
                 detection systems (IDSs), malware detection systems
                 (MDSs), and device identification systems (DISs).
                 Machine Learning-based (ML-based) IoT security systems
                 can fulfill several security objectives, including
                 detecting attacks, authenticating users before they
                 gain access to the system, and categorizing suspicious
                 activities. Nevertheless, ML faces numerous challenges,
                 such as those resulting from the emergence of
                 adversarial attacks crafted to mislead classifiers.
                 This paper provides a comprehensive review of the body
                 of knowledge about adversarial attacks and defense
                 mechanisms, with a particular focus on three prominent
                 IoT security systems: IDSs, MDSs, and DISs. The paper
                 starts by establishing a taxonomy of adversarial
                 attacks within the context of IoT. Then, various
                 methodologies employed in the generation of adversarial
                 attacks are described and classified within a
                 two-dimensional framework. Additionally, we describe
                 existing countermeasures for enhancing IoT security
                 against adversarial attacks. Finally, we explore the
                 most recent literature on the vulnerability of three
                 ML-based IoT security systems to adversarial attacks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fan:2024:IPS,
  author =       "Zhengyang Fan and Wanru Li and Kathryn Blackmond
                 Laskey and Kuo-Chu Chang",
  title =        "Investigation of Phishing Susceptibility with
                 Explainable Artificial Intelligence",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "31",
  day =          "17",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010031",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/31",
  abstract =     "Phishing attacks represent a significant and growing
                 threat in the digital world, affecting individuals and
                 organizations globally. Understanding the various
                 factors that influence susceptibility to phishing is
                 essential for developing more effective strategies to
                 combat this pervasive cybersecurity challenge. Machine
                 learning has become a prevalent method in the study of
                 phishing susceptibility. Most studies in this area have
                 taken one of two approaches: either they explore
                 statistical associations between various factors and
                 susceptibility, or they use complex models such as deep
                 neural networks to predict phishing behavior. However,
                 these approaches have limitations in terms of providing
                 practical insights for individuals to avoid future
                 phishing attacks and delivering personalized
                 explanations regarding their susceptibility to
                 phishing. In this paper, we propose a machine-learning
                 approach that leverages explainable artificial
                 intelligence techniques to examine the influence of
                 human and demographic factors on susceptibility to
                 phishing attacks. The machine learning model yielded an
                 accuracy of 78\%, with a recall of 71\%, and a
                 precision of 57\%. Our analysis reveals that
                 psychological factors such as impulsivity and
                 conscientiousness, as well as appropriate online
                 security habits, significantly affect an individual's
                 susceptibility to phishing attacks. Furthermore, our
                 individualized case-by-case approach offers
                 personalized recommendations on mitigating the risk of
                 falling prey to phishing exploits, considering the
                 specific circumstances of each individual.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Qu:2024:ISF,
  author =       "Jiantao Qu and Chunyu Qi and He Meng",
  title =        "An Imbalanced Sequence Feature Extraction Approach for
                 the Detection of {LTE-R} Cells with Degraded
                 Communication Performance",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "30",
  day =          "16",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010030",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/30",
  abstract =     "Within the Shuo Huang Railway Company (Suning, China )
                 the long-term evolution for railways (LTE-R) network
                 carries core wireless communication services for
                 trains. The communication performance of LTE-R cells
                 directly affects the operational safety of the trains.
                 Therefore, this paper proposes a novel detection method
                 for LTE-R cells with degraded communication
                 performance. Considering that the number of LTE-R cells
                 with degraded communication performance and that of
                 normal cells are extremely imbalanced and that the
                 communication performance indicator data for each cell
                 are sequence data, we propose a feature extraction
                 neural network structure for imbalanced sequences,
                 based on shapelet transformation and a convolutional
                 neural network (CNN). Then, to train the network, we
                 set the optimization objective based on the Fisher
                 criterion. Finally, using a two-stage training method,
                 we obtain a neural network model that can distinguish
                 LTE-R cells with degraded communication performance
                 from normal cells at the feature level. Experiments on
                 a real-world dataset show that the proposed method can
                 realize the accurate detection of LTE-R cells with
                 degraded communication performance and has high
                 practical application value.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ivanov:2024:CLM,
  author =       "Valeriy Ivanov and Maxim Tereshonok",
  title =        "Cross-Layer Methods for Ad Hoc Networks --- Review and
                 Classification",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "29",
  day =          "16",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010029",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/29",
  abstract =     "The OSI model used to be a common network model for
                 years. In the case of ad hoc networks with dynamic
                 topology and difficult radio communications conditions,
                 gradual departure is happening from the classical kind
                 of OSI network model with a clear delineation of layers
                 (physical, channel, network, transport, application) to
                 the cross-layer approach. The layers of the network
                 model in ad hoc networks strongly influence each other.
                 Thus, the cross-layer approach can improve the
                 performance of an ad hoc network by jointly developing
                 protocols using interaction and collaborative
                 optimization of multiple layers. The existing
                 cross-layer methods classification is too complicated
                 because it is based on the whole manifold of network
                 model layer combinations, regardless of their
                 importance. In this work, we review ad hoc network
                 cross-layer methods, propose a new useful
                 classification of cross-layer methods, and show future
                 research directions in the development of ad hoc
                 network cross-layer methods. The proposed
                 classification can help to simplify the goal-oriented
                 cross-layer protocol development.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{DeMedeiros:2024:CCA,
  author =       "Kyle DeMedeiros and Chan Young Koh and Abdeltawab
                 Hendawi",
  title =        "Clustering on the {Chicago Array of} Things: Spotting
                 Anomalies in the {Internet of Things} Records",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "28",
  day =          "16",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010028",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/28",
  abstract =     "The Chicago Array of Things (AoT) is a robust dataset
                 taken from over 100 nodes over four years. Each node
                 contains over a dozen sensors. The array contains a
                 series of Internet of Things (IoT) devices with
                 multiple heterogeneous sensors connected to a
                 processing and storage backbone to collect data from
                 across Chicago, IL, USA. The data collected include
                 meteorological data such as temperature, humidity, and
                 heat, as well as chemical data like CO 2 concentration,
                 PM2.5, and light intensity. The AoT sensor network is
                 one of the largest open IoT systems available for
                 researchers to utilize its data. Anomaly detection (AD)
                 in IoT and sensor networks is an important tool to
                 ensure that the ever-growing IoT ecosystem is protected
                 from faulty data and sensors, as well as from attacking
                 threats. Interestingly, an in-depth analysis of the
                 Chicago AoT for anomaly detection is rare. Here, we
                 study the viability of the Chicago AoT dataset to be
                 used in anomaly detection by utilizing clustering
                 techniques. We utilized K-Means, DBSCAN, and
                 Hierarchical DBSCAN (H-DBSCAN) to determine the
                 viability of labeling an unlabeled dataset at the
                 sensor level. The results show that the clustering
                 algorithm best suited for this task varies based on the
                 density of the anomalous readings and the variability
                 of the data points being clustered; however, at the
                 sensor level, the K-Means algorithm, though simple, is
                 better suited for the task of determining specific,
                 at-a-glance anomalies than the more complex DBSCAN and
                 HDBSCAN algorithms, though it comes with drawbacks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Feng:2024:SFC,
  author =       "Xu Feng and Mengyang He and Lei Zhuang and Yanrui Song
                 and Rumeng Peng",
  title =        "Service Function Chain Deployment Algorithm Based on
                 Deep Reinforcement Learning in Space--Air--Ground
                 Integrated Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "27",
  day =          "16",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010027",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/27",
  abstract =     "SAGIN is formed by the fusion of ground networks and
                 aircraft networks. It breaks through the limitation of
                 communication, which cannot cover the whole world,
                 bringing new opportunities for network communication in
                 remote areas. However, many heterogeneous devices in
                 SAGIN pose significant challenges in terms of
                 end-to-end resource management, and the limited
                 regional heterogeneous resources also threaten the QoS
                 for users. In this regard, this paper proposes a
                 hierarchical resource management structure for SAGIN,
                 named SAGIN-MEC, based on a SDN, NFV, and MEC, aiming
                 to facilitate the systematic management of
                 heterogeneous network resources. Furthermore, to
                 minimize the operator deployment costs while ensuring
                 the QoS, this paper formulates a resource scheduling
                 optimization model tailored to SAGIN scenarios to
                 minimize energy consumption. Additionally, we propose a
                 deployment algorithm, named DRL-G, which is based on
                 heuristics and DRL, aiming to allocate heterogeneous
                 network resources within SAGIN effectively.
                 Experimental results showed that SAGIN-MEC can reduce
                 the end-to-end delay by 6--15 ms compared to the
                 terrestrial edge network, and compared to other
                 algorithms, the DRL-G algorithm can improve the service
                 request reception rate by up to 20\%. In terms of
                 energy consumption, it reduces the average energy
                 consumption by 4.4\% compared to the PG algorithm.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Moreno-Cabanillas:2024:DCS,
  author =       "Andrea Moreno-Cabanillas and Elizabet Castillero-Ostio
                 and Antonio Castillo-Esparcia",
  title =        "Digital Communication and Social Organizations: an
                 Evaluation of the Communication Strategies of the
                 Most-Valued {NGOs} Worldwide",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "26",
  day =          "13",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010026",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/26",
  abstract =     "The communication of organizations with their
                 audiences has undergone changes thanks to the Internet.
                 Non-Governmental Organizations (NGOs), as influential
                 groups, are no exception, as much of their activism
                 takes place through grassroots digital lobbying. The
                 consolidation of Web 2.0 has not only provided social
                 organizations with a new and powerful tool for
                 disseminating information but also brought about
                 significant changes in the relationship between
                 nonprofit organizations and their diverse audiences.
                 This has facilitated and improved interaction between
                 them. The purpose of this article is to analyze the
                 level of interactivity implemented on the websites of
                 leading NGOs worldwide and their presence on social
                 networks, with the aim of assessing whether these
                 influential groups are moving towards more dialogic
                 systems in relation to their audience. The results
                 reveal that NGOs have a high degree of interactivity in
                 the tools used to present and disseminate information
                 on their websites. However, not all maintain the same
                 level of interactivity in the resources available for
                 interaction with Internet users, as very few have high
                 interactivity regarding bidirectional resources. It was
                 concluded that international non-governmental
                 organizations still suffer from certain shortcomings in
                 the strategic management of digital communication on
                 their web platforms, while, on the other hand, a strong
                 presence can be noted on the most-popular social
                 networks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tseng:2024:CTD,
  author =       "Chinyang Henry Tseng and Woei-Jiunn Tsaur and Yueh-Mao
                 Shen",
  title =        "Classification Tendency Difference Index Model for
                 Feature Selection and Extraction in Wireless Intrusion
                 Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "25",
  day =          "12",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010025",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/25",
  abstract =     "In detecting large-scale attacks, deep neural networks
                 (DNNs) are an effective approach based on high-quality
                 training data samples. Feature selection and feature
                 extraction are the primary approaches for data quality
                 enhancement for high-accuracy intrusion detection.
                 However, their enhancement root causes usually present
                 weak relationships to the differences between normal
                 and attack behaviors in the data samples. Thus, we
                 propose a Classification Tendency Difference Index
                 (CTDI) model for feature selection and extraction in
                 intrusion detection. The CTDI model consists of three
                 indexes: Classification Tendency Frequency Difference
                 (CTFD), Classification Tendency Membership Difference
                 (CTMD), and Classification Tendency Distance Difference
                 (CTDD). In the dataset, each feature has many feature
                 values (FVs). In each FV, the normal and attack samples
                 indicate the FV classification tendency, and CTDI shows
                 the classification tendency differences between the
                 normal and attack samples. CTFD is the frequency
                 difference between the normal and attack samples. By
                 employing fuzzy C means (FCM) to establish the normal
                 and attack clusters, CTMD is the membership difference
                 between the clusters, and CTDD is the distance
                 difference between the cluster centers. CTDI calculates
                 the index score in each FV and summarizes the scores of
                 all FVs in the feature as the feature score for each of
                 the three indexes. CTDI adopts an Auto Encoder for
                 feature extraction to generate new features from the
                 dataset and calculate the three index scores for the
                 new features. CTDI sorts the original and new features
                 for each of the three indexes to select the best
                 features. The selected CTDI features indicate the best
                 classification tendency differences between normal and
                 attack samples. The experiment results demonstrate that
                 the CTDI features achieve better detection accuracy as
                 classified by DNN for the Aegean WiFi Intrusion Dataset
                 than their related works, and the detection
                 enhancements are based on the improved classification
                 tendency differences in the CTDI features.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rasheed:2024:BBI,
  author =       "Sana Rasheed and Soulla Louca",
  title =        "Blockchain-Based Implementation of National Census as
                 a Supplementary Instrument for Enhanced Transparency,
                 Accountability, Privacy, and Security",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "24",
  day =          "11",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010024",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/24",
  abstract =     "A national population census is instrumental in
                 offering a holistic view of a country's progress,
                 directly influencing policy formulation and strategic
                 planning. Potential flaws in the census system can have
                 detrimental impacts on national development. Our prior
                 research has pinpointed various deficiencies in current
                 census methodologies, including inadequate population
                 coverage, racial and ethnic discrimination, and
                 challenges related to data privacy, security, and
                 distribution. This study aims to address the ``missing
                 persons'' challenge in the national census population
                 and housing system. The integration of blockchain
                 technology emerges as a promising solution for
                 addressing these identified issues, enhancing the
                 integrity and efficacy of census processes. Building
                 upon our earlier research which examined the national
                 census system of Pakistan, we propose an architecture
                 design incorporating Hyperledger Fabric, performing
                 system sizing for the entire nation count. The
                 Blockchain-Based Implementation of National Census as a
                 Supplementary Instrument for Enhanced Transparency,
                 Accountability, Privacy, and Security (BINC-TAPS) seeks
                 to provide a robust, transparent, scalable, immutable,
                 and tamper-proof solution for conducting national
                 population and housing censuses, while also fostering
                 socio-economic advancements. This paper presents a
                 comprehensive overview of our research, with a primary
                 focus on the implementation of the blockchain-based
                 proposed solution, including prototype testing and the
                 resulting outcomes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Galis:2024:FSI,
  author =       "Alex Galis",
  title =        "Future Sustainable {Internet} Energy-Defined
                 Networking",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "23",
  day =          "09",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010023",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/23",
  abstract =     "This paper presents a comprehensive set of design
                 methods for making future Internet networking fully
                 energy-aware and sustainably minimizing and managing
                 the energy footprint. It includes (a) 41 energy-aware
                 design methods, grouped into Service Operations
                 Support, Management Operations Support, Compute
                 Operations Support, Connectivity/Forwarding Operations
                 Support, Traffic Engineering Methods, Architectural
                 Support for Energy Instrumentation, and Network
                 Configuration; (b) energy consumption models and energy
                 metrics are identified and specified. It specifies the
                 requirements for energy-defined network compliance,
                 which include energy-measurable network devices with
                 the support of several control messages: registration,
                 discovery, provisioning, discharge, monitoring,
                 synchronization, flooding, performance, and pushback.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Elkhodr:2024:NSI,
  author =       "Mahmoud Elkhodr and Samiya Khan and Ergun Gide",
  title =        "A Novel Semantic {IoT} Middleware for Secure Data
                 Management: Blockchain and {AI}-Driven Context
                 Awareness",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "22",
  day =          "07",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010022",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/22",
  abstract =     "In the modern digital landscape of the Internet of
                 Things (IoT), data interoperability and heterogeneity
                 present critical challenges, particularly with the
                 increasing complexity of IoT systems and networks.
                 Addressing these challenges, while ensuring data
                 security and user trust, is pivotal. This paper
                 proposes a novel Semantic IoT Middleware (SIM) for
                 healthcare. The architecture of this middleware
                 comprises the following main processes: data
                 generation, semantic annotation, security encryption,
                 and semantic operations. The data generation module
                 facilitates seamless data and event sourcing, while the
                 Semantic Annotation Component assigns structured
                 vocabulary for uniformity. SIM adopts blockchain
                 technology to provide enhanced data security, and its
                 layered approach ensures robust interoperability and
                 intuitive user-centric operations for IoT systems. The
                 security encryption module offers data protection, and
                 the semantic operations module underpins data
                 processing and integration. A distinctive feature of
                 this middleware is its proficiency in service
                 integration, leveraging semantic descriptions augmented
                 by user feedback. Additionally, SIM integrates
                 artificial intelligence (AI) feedback mechanisms to
                 continuously refine and optimise the middleware's
                 operational efficiency.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ali:2024:CSA,
  author =       "G. G. Md. Nawaz Ali and Mohammad Nazmus Sadat and Md
                 Suruz Miah and Sameer Ahmed Sharief and Yun Wang",
  title =        "A Comprehensive Study and Analysis of the Third
                 Generation Partnership {Project}'s {5G} New Radio for
                 Vehicle-to-Everything Communication",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "21",
  day =          "06",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010021",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/21",
  abstract =     "Recently, the Third Generation Partnership Project
                 (3GPP) introduced new radio (NR) technology for
                 vehicle-to-everything (V2X) communication to enable
                 delay-sensitive and bandwidth-hungry applications in
                 vehicular communication. The NR system is strategically
                 crafted to complement the existing long-term evolution
                 (LTE) cellular-vehicle-to-everything (C-V2X)
                 infrastructure, particularly to support advanced
                 services such as the operation of automated vehicles.
                 It is widely anticipated that the fifth-generation (5G)
                 NR system will surpass LTE C-V2X in terms of achieving
                 superior performance in scenarios characterized by high
                 throughput, low latency, and enhanced reliability,
                 especially in the context of congested traffic
                 conditions and a diverse range of vehicular
                 applications. This article will provide a comprehensive
                 literature review on vehicular communications from
                 dedicated short-range communication (DSRC) to NR V2X.
                 Subsequently, it delves into a detailed examination of
                 the challenges and opportunities inherent in NR V2X
                 technology. Finally, we proceed to elucidate the
                 process of creating and analyzing an open-source 5G NR
                 V2X module in network simulation-3 (ns-3) and then
                 demonstrate the NR V2X performance in terms of
                 different key performance indicators implemented
                 through diverse operational scenarios.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liu:2024:JBF,
  author =       "Lidong Liu and Shidang Li and Mingsheng Wei and
                 Jinsong Xu and Bencheng Yu",
  title =        "Joint Beam-Forming Optimization for
                 Active-{RIS}-Assisted {Internet-of-Things} Networks
                 with {SWIPT}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "20",
  day =          "06",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010020",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/20",
  abstract =     "Network energy resources are limited in communication
                 systems, which may cause energy shortages in mobile
                 devices at the user end. Active Reconfigurable
                 Intelligent Surfaces (A-RIS) not only have phase
                 modulation properties but also enhance the signal
                 strength; thus, they are expected to solve the energy
                 shortage problem experience at the user end in 6G
                 communications. In this paper, a resource allocation
                 algorithm for maximizing the sum of harvested energy is
                 proposed for an active RIS-assisted Simultaneous
                 Wireless Information and Power Transfer (SWIPT) system
                 to solve the problem of low performance of harvested
                 energy for users due to multiplicative fading. First,
                 in the active RIS-assisted SWIPT system using a power
                 splitting architecture to achieve information and
                 energy co-transmission, the joint resource allocation
                 problem is constructed with the objective function of
                 maximizing the sum of the collected energy of all
                 users, under the constraints of signal-to-noise ratio,
                 active RIS and base station transmit power, and power
                 splitting factors. Second, the considered non-convex
                 problem can be turned into a standard convex problem by
                 using alternating optimization, semi-definite
                 relaxation, successive convex approximation, penalty
                 function, etc., and then an alternating iterative
                 algorithm for harvesting energy is proposed. The
                 proposed algorithm splits the problem into two
                 sub-problems and then performs iterative optimization
                 separately, and then the whole is alternately optimized
                 to obtain the optimal solution. Simulation results show
                 that the proposed algorithm improves the performance by
                 45.2\% and 103.7\% compared to the passive RIS
                 algorithm and the traditional without-RIS algorithm,
                 respectively, at the maximum permissible transmitting
                 power of 45 dBm at the base station.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhang:2024:PPO,
  author =       "Chen Zhang and Celimuge Wu and Min Lin and Yangfei Lin
                 and William Liu",
  title =        "Proximal Policy Optimization for Efficient
                 {D2D-Assisted} Computation Offloading and Resource
                 Allocation in Multi-Access Edge Computing",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "19",
  day =          "02",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010019",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/19",
  abstract =     "In the advanced 5G and beyond networks, multi-access
                 edge computing (MEC) is increasingly recognized as a
                 promising technology, offering the dual advantages of
                 reducing energy utilization in cloud data centers while
                 catering to the demands for reliability and real-time
                 responsiveness in end devices. However, the inherent
                 complexity and variability of MEC networks pose
                 significant challenges in computational offloading
                 decisions. To tackle this problem, we propose a
                 proximal policy optimization (PPO)-based
                 Device-to-Device (D2D)-assisted computation offloading
                 and resource allocation scheme. We construct a
                 realistic MEC network environment and develop a Markov
                 decision process (MDP) model that minimizes time loss
                 and energy consumption. The integration of a D2D
                 communication-based offloading framework allows for
                 collaborative task offloading between end devices and
                 MEC servers, enhancing both resource utilization and
                 computational efficiency. The MDP model is solved using
                 the PPO algorithm in deep reinforcement learning to
                 derive an optimal policy for offloading and resource
                 allocation. Extensive comparative analysis with three
                 benchmarked approaches has confirmed our scheme's
                 superior performance in latency, energy consumption,
                 and algorithmic convergence, demonstrating its
                 potential to improve MEC network operations in the
                 context of emerging 5G and beyond technologies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kochetkova:2024:CQS,
  author =       "Irina Kochetkova and Kseniia Leonteva and Ibram
                 Ghebrial and Anastasiya Vlaskina and Sofia Burtseva and
                 Anna Kushchazli and Konstantin Samouylov",
  title =        "Controllable Queuing System with Elastic Traffic and
                 Signals for Resource Capacity Planning in {5G} Network
                 Slicing",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "18",
  day =          "31",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010018",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/18",
  abstract =     "Fifth-generation (5G) networks provide network slicing
                 capabilities, enabling the deployment of multiple
                 logically isolated network slices on a single
                 infrastructure platform to meet specific requirements
                 of users. This paper focuses on modeling and analyzing
                 resource capacity planning and reallocation for network
                 slicing, specifically between two providers
                 transmitting elastic traffic, such during as web
                 browsing. A controller determines the need for resource
                 reallocation and plans new resource capacity
                 accordingly. A Markov decision process is employed in a
                 controllable queuing system to find the optimal
                 resource capacity for each provider. The reward
                 function incorporates three network slicing principles:
                 maximum matching for equal resource partitioning,
                 maximum share of signals resulting in resource
                 reallocation, and maximum resource utilization. To
                 efficiently compute the optimal resource capacity
                 planning policy, we developed an iterative algorithm
                 that begins with maximum resource utilization as the
                 starting point. Through numerical demonstrations, we
                 show the optimal policy and metrics of resource
                 reallocation for two services: web browsing and bulk
                 data transfer. The results highlight fast convergence
                 within three iterations and the effectiveness of the
                 balanced three-principle approach in resource capacity
                 planning for 5G network slicing.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Asano:2024:ITT,
  author =       "Mizuki Asano and Takumi Miyoshi and Taku Yamazaki",
  title =        "{Internet-of-Things} Traffic Analysis and Device
                 Identification Based on Two-Stage Clustering in Smart
                 Home Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "17",
  day =          "31",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010017",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/17",
  abstract =     "Smart home environments, which consist of various
                 Internet of Things (IoT) devices to support and improve
                 our daily lives, are expected to be widely adopted in
                 the near future. Owing to a lack of awareness regarding
                 the risks associated with IoT devices and challenges in
                 replacing or the updating their firmware, adequate
                 security measures have not been implemented. Instead,
                 IoT device identification methods based on traffic
                 analysis have been proposed. Since conventional methods
                 process and analyze traffic data simultaneously, bias
                 in the occurrence rate of traffic patterns has a
                 negative impact on the analysis results. Therefore,
                 this paper proposes an IoT traffic analysis and device
                 identification method based on two-stage clustering in
                 smart home environments. In the first step, traffic
                 patterns are extracted by clustering IoT traffic at a
                 local gateway located in each smart home and
                 subsequently sent to a cloud server. In the second
                 step, the cloud server extracts common traffic units to
                 represent IoT traffic by clustering the patterns
                 obtained in the first step. Two-stage clustering can
                 reduce the impact of data bias, because each cluster
                 extracted in the first clustering is summarized as one
                 value and used as a single data point in the second
                 clustering, regardless of the occurrence rate of
                 traffic patterns. Through the proposed two-stage
                 clustering method, IoT traffic is transformed into time
                 series vector data that consist of common unit patterns
                 and can be identified based on time series
                 representations. Experiments using public IoT traffic
                 datasets indicated that the proposed method could
                 identify 21 IoTs devices with an accuracy of 86.9\%.
                 Therefore, we can conclude that traffic analysis using
                 two-stage clustering is effective for improving the
                 clustering quality, device identification, and
                 implementation in distributed environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Misirli:2024:AMM,
  author =       "Javid Misirli and Emiliano Casalicchio",
  title =        "An Analysis of Methods and Metrics for Task Scheduling
                 in Fog Computing",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "16",
  day =          "30",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010016",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/16",
  abstract =     "The Internet of Things (IoT) uptake brought a paradigm
                 shift in application deployment. Indeed, IoT
                 applications are not centralized in cloud data centers,
                 but the computation and storage are moved close to the
                 consumers, creating a computing continuum between the
                 edge of the network and the cloud. This paradigm shift
                 is called fog computing, a concept introduced by Cisco
                 in 2012. Scheduling applications in this decentralized,
                 heterogeneous, and resource-constrained environment is
                 challenging. The task scheduling problem in fog
                 computing has been widely explored and addressed using
                 many approaches, from traditional operational research
                 to heuristics and machine learning. This paper aims to
                 analyze the literature on task scheduling in fog
                 computing published in the last five years to classify
                 the criteria used for decision-making and the technique
                 used to solve the task scheduling problem. We propose a
                 taxonomy of task scheduling algorithms, and we identify
                 the research gaps and challenges.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Achkouty:2024:RIQ,
  author =       "Fouad Achkouty and Richard Chbeir and Laurent Gallon
                 and Elio Mansour and Antonio Corral",
  title =        "Resource Indexing and Querying in Large Connected
                 Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "15",
  day =          "30",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010015",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/15",
  abstract =     "The proliferation of sensor and actuator devices in
                 Internet of things (IoT) networks has garnered
                 significant attention in recent years. However, the
                 increasing number of IoT devices, and the corresponding
                 resources, has introduced various challenges,
                 particularly in indexing and querying. In essence,
                 resource management has become more complex due to the
                 non-uniform distribution of related devices and their
                 limited capacity. Additionally, the diverse demands of
                 users have further complicated resource indexing. This
                 paper proposes a distributed resource indexing and
                 querying algorithm for large connected environments,
                 specifically designed to address the challenges posed
                 by IoT networks. The algorithm considers both the
                 limited device capacity and the non-uniform
                 distribution of devices, acknowledging that devices
                 cannot store information about the entire environment.
                 Furthermore, it places special emphasis on uncovered
                 zones, to reduce the response time of queries related
                 to these areas. Moreover, the algorithm introduces
                 different types of queries, to cater to various user
                 needs, including fast queries and urgent queries
                 suitable for different scenarios. The effectiveness of
                 the proposed approach was evaluated through extensive
                 experiments covering index creation, coverage, and
                 query execution, yielding promising and insightful
                 results.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Serghini:2024:DCN,
  author =       "Omar Serghini and Hayat Semlali and Asmaa Maali and
                 Abdelilah Ghammaz and Salvatore Serrano",
  title =        "{1-D} Convolutional Neural Network-Based Models for
                 Cooperative Spectrum Sensing",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "14",
  day =          "29",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010014",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/14",
  abstract =     "Spectrum sensing is an essential function of cognitive
                 radio technology that can enable the reuse of available
                 radio resources by so-called secondary users without
                 creating harmful interference with licensed users. The
                 application of machine learning techniques to spectrum
                 sensing has attracted considerable interest in the
                 literature. In this contribution, we study cooperative
                 spectrum sensing in a cognitive radio network where
                 multiple secondary users cooperate to detect a primary
                 user. We introduce multiple cooperative spectrum
                 sensing schemes based on a deep neural network, which
                 incorporate a one-dimensional convolutional neural
                 network and a long short-term memory network. The
                 primary objective of these schemes is to effectively
                 learn the activity patterns of the primary user. The
                 scenario of an imperfect transmission channel is
                 considered for service messages to demonstrate the
                 robustness of the proposed model. The performance of
                 the proposed methods is evaluated with the receiver
                 operating characteristic curve, the probability of
                 detection for various SNR levels and the computational
                 time. The simulation results confirm the effectiveness
                 of the bidirectional long short-term memory-based
                 method, surpassing the performance of the other
                 proposed schemes and the current state-of-the-art
                 methods in terms of detection probability, while
                 ensuring a reasonable online detection time.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kabamba:2024:VLO,
  author =       "Herve M. Kabamba and Matthew Khouzam and Michel R.
                 Dagenais",
  title =        "{Vnode}: Low-Overhead Transparent Tracing of {{\tt
                 Node.js}}-Based Microservice Architectures",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "13",
  day =          "29",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010013",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/java2020.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/13",
  abstract =     "Tracing serves as a key method for evaluating the
                 performance of microservices-based architectures, which
                 are renowned for their scalability, resource
                 efficiency, and high availability. Despite their
                 advantages, these architectures often pose unique
                 debugging challenges that necessitate trade-offs,
                 including the burden of instrumentation overhead. With
                 Node.js emerging as a leading development environment
                 recognized for its rapidly growing ecosystem, there is
                 a pressing need for innovative performance debugging
                 approaches that reduce the telemetry data collection
                 efforts and the overhead incurred by the environment's
                 instrumentation. In response, we introduce a new
                 approach designed for transparent tracing and
                 performance debugging of microservices in cloud
                 settings. This approach is centered around our newly
                 developed Internal Transparent Tracing and Context
                 Reconstruction (ITTCR) technique. ITTCR is adept at
                 correlating internal metrics from various distributed
                 trace files to reconstruct the intricate execution
                 contexts of microservices operating in a Node.js
                 environment. Our method achieves transparency by
                 directly instrumenting the Node.js virtual machine,
                 enabling the collection and analysis of trace events in
                 a transparent manner. This process facilitates the
                 creation of visualization tools, enhancing the
                 understanding and analysis of microservice performance
                 in cloud environments. Compared to other methods, our
                 approach incurs an overhead of approximately 5\% on the
                 system for the trace collection infrastructure while
                 exhibiting minimal utilization of system resources
                 during analysis execution. Experiments demonstrate that
                 our technique scales well with very large trace files
                 containing huge numbers of events and performs analyses
                 in very acceptable timeframes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2024:EEP,
  author =       "Xiu Li and Aron Henriksson and Martin Duneld and Jalal
                 Nouri and Yongchao Wu",
  title =        "Evaluating Embeddings from Pre-Trained Language Models
                 and Knowledge Graphs for Educational Content
                 Recommendation",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "12",
  day =          "29",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010012",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/12",
  abstract =     "Educational content recommendation is a cornerstone of
                 AI-enhanced learning. In particular, to facilitate
                 navigating the diverse learning resources available on
                 learning platforms, methods are needed for
                 automatically linking learning materials, e.g., in
                 order to recommend textbook content based on exercises.
                 Such methods are typically based on semantic textual
                 similarity (STS) and the use of embeddings for text
                 representation. However, it remains unclear what types
                 of embeddings should be used for this task. In this
                 study, we carry out an extensive empirical evaluation
                 of embeddings derived from three different types of
                 models: (i) static embeddings trained using a
                 concept-based knowledge graph, (ii) contextual
                 embeddings from a pre-trained language model, and (iii)
                 contextual embeddings from a large language model
                 (LLM). In addition to evaluating the models
                 individually, various ensembles are explored based on
                 different strategies for combining two models in an
                 early vs. late fusion fashion. The evaluation is
                 carried out using digital textbooks in Swedish for
                 three different subjects and two types of exercises.
                 The results show that using contextual embeddings from
                 an LLM leads to superior performance compared to the
                 other models, and that there is no significant
                 improvement when combining these with static embeddings
                 trained using a knowledge graph. When using embeddings
                 derived from a smaller language model, however, it
                 helps to combine them with knowledge graph embeddings.
                 The performance of the best-performing model is high
                 for both types of exercises, resulting in a mean
                 Recall@3 of 0.96 and 0.95 and a mean MRR of 0.87 and
                 0.86 for quizzes and study questions, respectively,
                 demonstrating the feasibility of using STS based on
                 text embeddings for educational content recommendation.
                 The ability to link digital learning materials in an
                 unsupervised manner---relying only on readily available
                 pre-trained models---facilitates the development of
                 AI-enhanced learning.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bagheri:2024:SGS,
  author =       "Nasour Bagheri and Ygal Bendavid and Masoumeh Safkhani
                 and Samad Rostampour",
  title =        "Smart Grid Security: a {PUF}-Based Authentication and
                 Key Agreement Protocol",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "9",
  day =          "28",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010009",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/9",
  abstract =     "A smart grid is an electricity network that uses
                 advanced technologies to facilitate the exchange of
                 information and electricity between utility companies
                 and customers. Although most of the technologies
                 involved in such grids have reached maturity, smart
                 meters---as connected devices---introduce new security
                 challenges. To overcome this significant obstacle to
                 grid modernization, safeguarding privacy has emerged as
                 a paramount concern. In this paper, we begin by
                 evaluating the security levels of recently proposed
                 authentication methods for smart meters. Subsequently,
                 we introduce an enhanced protocol named PPSG, designed
                 for smart grids, which incorporates physical unclonable
                 functions (PUF) and an elliptic curve cryptography
                 (ECC) module to address the vulnerabilities identified
                 in previous approaches. Our security analysis,
                 utilizing a real-or-random (RoR) model, demonstrates
                 that PPSG effectively mitigates the weaknesses found in
                 prior methods. To assess the practicality of PPSG, we
                 conduct simulations using an Arduino UNO board,
                 measuring computation, communication, and energy costs.
                 Our results, including a processing time of 153 ms, a
                 communication cost of 1376 bits, and an energy
                 consumption of 13.468 mJ, align with the requirements
                 of resource-constrained devices within smart grids.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Toman:2024:LAS,
  author =       "Patrick Toman and Nalini Ravishanker and Nathan Lally
                 and Sanguthevar Rajasekaran",
  title =        "Latent Autoregressive Student- t Prior Process Models
                 to Assess Impact of Interventions in Time Series",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "8",
  day =          "28",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010008",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/8",
  abstract =     "With the advent of the ``Internet of Things'' (IoT),
                 insurers are increasingly leveraging remote sensor
                 technology in the development of novel insurance
                 products and risk management programs. For example,
                 Hartford Steam Boiler's (HSB) IoT freeze loss program
                 uses IoT temperature sensors to monitor indoor
                 temperatures in locations at high risk of water-pipe
                 burst (freeze loss) with the goal of reducing
                 insurances losses via real-time monitoring of the
                 temperature data streams. In the event these monitoring
                 systems detect a potentially risky temperature
                 environment, an alert is sent to the end-insured
                 (business manager, tenant, maintenance staff, etc.),
                 prompting them to take remedial action by raising
                 temperatures. In the event that an alert is sent and
                 freeze loss occurs, the firm is not liable for any
                 damages incurred by the event. For the program to be
                 effective, there must be a reliable method of verifying
                 if customers took appropriate corrective action after
                 receiving an alert. Due to the program's scale, direct
                 follow up via text or phone calls is not possible for
                 every alert event. In addition, direct feedback from
                 customers is not necessarily reliable. In this paper,
                 we propose the use of a non-linear, auto-regressive
                 time series model, coupled with the time series
                 intervention analysis method known as causal impact, to
                 directly evaluate whether or not a customer took action
                 directly from IoT temperature streams. Our method
                 offers several distinct advantages over other methods
                 as it is (a) readily scalable with continued program
                 growth, (b) entirely automated, and (c) inherently less
                 biased than human labelers or direct customer response.
                 We demonstrate the efficacy of our method using a
                 sample of actual freeze alert events from the freeze
                 loss program.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liu:2024:UUB,
  author =       "Qiang Liu and Rui Han and Yang Li",
  title =        "Utilizing User Bandwidth Resources in
                 Information-Centric Networking through Blockchain-Based
                 Incentive Mechanism",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "11",
  day =          "28",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010011",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/11",
  abstract =     "Idle bandwidth resources are inefficiently distributed
                 among different users. Currently, the utilization of
                 user bandwidth resources mostly relies on traditional
                 IP networks, implementing relevant techniques at the
                 application layer, which creates scalability issues and
                 brings additional system overheads. Information-Centric
                 Networking (ICN), based on the idea of separating
                 identifiers and locators, offers the potential to
                 aggregate idle bandwidth resources from a network layer
                 perspective. This paper proposes a method for utilizing
                 user bandwidth resources in ICN; specifically, we treat
                 the use of user bandwidth resources as a service and
                 assign service IDs (identifiers), and when network
                 congestion (the network nodes are overloaded) occurs,
                 the traffic can be routed to the user side for
                 forwarding through the ID/NA (Network Address)
                 cooperative routing mechanism of ICN, thereby improving
                 the scalability of ICN transmission and the utilization
                 of underlying network resources. To enhance the
                 willingness of users to contribute idle bandwidth
                 resources, we establish a secure and trustworthy
                 bandwidth trading market using blockchain technology.
                 We also design an incentive mechanism based on the
                 Proof-of-Network-Contribution (PoNC) consensus
                 algorithm; users can ``mine'' by forwarding packets.
                 The experimental results show that utilizing idle
                 bandwidth can significantly improve the scalability of
                 ICN transmission under experimental conditions,
                 bringing a maximum throughput improvement of 19.4\% and
                 reducing the packet loss rate. Compared with existing
                 methods, using ICN technology to aggregate idle
                 bandwidth for network transmission will have a more
                 stable and lower latency, and it brings a maximum
                 utilization improvement of 13.7\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Santonicola:2024:ACA,
  author =       "Emanuele Santonicola and Ennio Andrea Adinolfi and
                 Simone Coppola and Francesco Pascale",
  title =        "Automotive Cybersecurity Application Based on
                 {CARDIAN}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "10",
  day =          "28",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010010",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/10",
  abstract =     "Nowadays, a vehicle can contain from 20 to 100 ECUs,
                 which are responsible for ordering, controlling and
                 monitoring all the components of the vehicle itself.
                 Each of these units can also send and receive
                 information to other units on the network or
                 externally. For most vehicles, the controller area
                 network (CAN) is the main communication protocol and
                 system used to build their internal network.
                 Technological development, the growing integration of
                 devices and the numerous advances in the field of
                 connectivity have allowed the vehicle to become
                 connected, and the flow of information exchanged
                 between the various ECUs (electronic control units)
                 becomes increasingly important and varied. Furthermore,
                 the vehicle itself is capable of exchanging information
                 with other vehicles, with the surrounding environment
                 and with the Internet. As shown by the CARDIAN project,
                 this type of innovation allows the user an increasingly
                 safe and varied driving experience, but at the same
                 time, it introduces a series of vulnerabilities and
                 dangers due to the connection itself. The job of making
                 the vehicle safe therefore becomes critical. In recent
                 years, it has been demonstrated in multiple ways how
                 easy it is to compromise the safety of a vehicle and
                 its passengers by injecting malicious messages into the
                 CAN network present inside the vehicle itself. The
                 purpose of this article is the construction of a system
                 that, integrated within the vehicle network, is able to
                 effectively recognize any type of intrusion and
                 tampering.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhao:2024:DID,
  author =       "Yadi Zhao and Lei Yan and Jian Wu and Ximing Song",
  title =        "Design and Implementation of a Digital Twin System for
                 Log Rotary Cutting Optimization",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "7",
  day =          "25",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010007",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/7",
  abstract =     "To address the low level of intelligence and low
                 utilization of logs in current rotary cutting
                 equipment, this paper proposes a digital twin-based
                 system for optimizing the rotary cutting of logs using
                 a five-dimensional model of digital twins. The system
                 features a log perception platform to capture
                 three-dimensional point cloud data, outlining the logs'
                 contours. Utilizing the Delaunay3D algorithm, this
                 model performs a three-dimensional reconstruction of
                 the log point cloud, constructing a precise digital
                 twin. Feature information is extracted from the point
                 cloud using the least squares method. Processing
                 parameters, determined through the kinematic model, are
                 verified in rotary cutting simulations via Bool
                 operations. The system's efficacy has been
                 substantiated through experimental validation,
                 demonstrating its capability to output specific
                 processing schemes for irregular logs and to verify
                 these through simulation. This approach notably
                 improves log recovery rates, decreasing volume error
                 from 12.8\% to 2.7\% and recovery rate error from
                 23.5\% to 5.7\% The results validate the efficacy of
                 the proposed digital twin system in optimizing the
                 rotary cutting process, demonstrating its capability
                 not only to enhance the utilization rate of log
                 resources but also to improve the economic efficiency
                 of the factory, thereby facilitating industrial
                 development.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liu:2024:TTD,
  author =       "Jing Liu and Xuesong Hai and Keqin Li",
  title =        "{TDLearning}: Trusted Distributed Collaborative
                 Learning Based on Blockchain Smart Contracts",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "1",
  pages =        "6",
  day =          "25",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16010006",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/1/6",
  abstract =     "Massive amounts of data drive the performance of deep
                 learning models, but in practice, data resources are
                 often highly dispersed and bound by data privacy and
                 security concerns, making it difficult for multiple
                 data sources to share their local data directly. Data
                 resources are difficult to aggregate effectively,
                 resulting in a lack of support for model training. How
                 to collaborate between data sources in order to
                 aggregate the value of data resources is therefore an
                 important research question. However, existing
                 distributed-collaborative-learning architectures still
                 face serious challenges in collaborating between nodes
                 that lack mutual trust, with security and trust issues
                 seriously affecting the confidence and willingness of
                 data sources to participate in collaboration.
                 Blockchain technology provides trusted distributed
                 storage and computing, and combining it with
                 collaboration between data sources to build trusted
                 distributed-collaborative-learning architectures is an
                 extremely valuable research direction for application.
                 We propose a trusted distributed-collaborative-learning
                 mechanism based on blockchain smart contracts. Firstly,
                 the mechanism uses blockchain smart contracts to define
                 and encapsulate collaborative behaviours, relationships
                 and norms between distributed collaborative nodes.
                 Secondly, we propose a model-fusion method based on
                 feature fusion, which replaces the direct sharing of
                 local data resources with distributed-model
                 collaborative training and organises distributed data
                 resources for distributed collaboration to improve
                 model performance. Finally, in order to verify the
                 trustworthiness and usability of the proposed
                 mechanism, on the one hand, we implement formal
                 modelling and verification of the smart contract by
                 using Coloured Petri Net and prove that the mechanism
                 satisfies the expected trustworthiness properties by
                 verifying the formal model of the smart contract
                 associated with the mechanism. On the other hand, the
                 model-fusion method based on feature fusion is
                 evaluated in different datasets and collaboration
                 scenarios, while a typical collaborative-learning case
                 is implemented for a comprehensive analysis and
                 validation of the mechanism. The experimental results
                 show that the proposed mechanism can provide a trusted
                 and fair collaboration infrastructure for
                 distributed-collaboration nodes that lack mutual trust
                 and organise decentralised data resources for
                 collaborative model training to develop effective
                 global models.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Khan:2024:EED,
  author =       "Muhammad Nafees Ulfat Khan and Weiping Cao and Zhiling
                 Tang and Ata Ullah and Wanghua Pan",
  title =        "Energy-Efficient {De}-Duplication Mechanism for
                 Healthcare Data Aggregation in {IoT}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "66",
  day =          "19",
  month =        feb,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020066",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/66",
  abstract =     "The rapid development of the Internet of Things (IoT)
                 has opened the way for transformative advances in
                 numerous fields, including healthcare. IoT-based
                 healthcare systems provide unprecedented opportunities
                 to gather patients' real-time data and make appropriate
                 decisions at the right time. Yet, the deployed sensors
                 generate normal readings most of the time, which are
                 transmitted to Cluster Heads (CHs). Handling these
                 voluminous duplicated data is quite challenging. The
                 existing techniques have high energy consumption,
                 storage costs, and communication costs. To overcome
                 these problems, in this paper, an innovative
                 Energy-Efficient Fuzzy Data Aggregation System
                 (EE-FDAS) has been presented. In it, at the first
                 level, it is checked that sensors either generate
                 normal or critical readings. In the first case,
                 readings are converted to Boolean digit 0. This reduced
                 data size takes only 1 digit which considerably reduces
                 energy consumption. In the second scenario, sensors
                 generating irregular readings are transmitted in their
                 original 16 or 32-bit form. Then, data are aggregated
                 and transmitted to respective CHs. Afterwards, these
                 data are further transmitted to Fog servers, from where
                 doctors have access. Lastly, for later usage, data are
                 stored in the cloud server. For checking the
                 proficiency of the proposed EE-FDAS scheme, extensive
                 simulations are performed using NS-2.35. The results
                 showed that EE-FDAS has performed well in terms of
                 aggregation factor, energy consumption, packet drop
                 rate, communication, and storage cost.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bellavista:2024:IID,
  author =       "Paolo Bellavista and Giuseppe {Di Modica}",
  title =        "{IoTwins}: Implementing Distributed and Hybrid Digital
                 Twins in Industrial Manufacturing and Facility
                 Management Settings",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "65",
  day =          "17",
  month =        feb,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020065",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/65",
  abstract =     "A Digital Twin (DT) refers to a virtual representation
                 or digital replica of a physical object, system,
                 process, or entity. This concept involves creating a
                 detailed, real-time digital counterpart that mimics the
                 behavior, characteristics, and attributes of its
                 physical counterpart. DTs have the potential to improve
                 efficiency, reduce costs, and enhance decision-making
                 by providing a detailed, real-time understanding of the
                 physical systems they represent. While this technology
                 is finding application in numerous fields, such as
                 energy, healthcare, and transportation, it appears to
                 be a key component of the digital transformation of
                 industries fostered by the fourth Industrial revolution
                 (Industry 4.0). In this paper, we present the research
                 results achieved by IoTwins, a European research
                 project aimed at investigating opportunities and issues
                 of adopting DTs in the fields of industrial
                 manufacturing and facility management. Particularly, we
                 discuss a DT model and a reference architecture for use
                 by the research community to implement a platform for
                 the development and deployment of industrial DTs in the
                 cloud continuum. Guided by the devised architectures'
                 principles, we implemented an open platform and a
                 development methodology to help companies build
                 DT-based industrial applications and deploy them in the
                 so-called Edge/Cloud continuum. To prove the research
                 value and the usability of the implemented platform, we
                 discuss a simple yet practical development use case.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Matsuoka:2024:OOP,
  author =       "Ryo Matsuoka and Koichi Kobayashi and Yuh Yamashita",
  title =        "Online Optimization of Pickup and Delivery Problem
                 Considering Feasibility",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "64",
  day =          "17",
  month =        feb,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020064",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/64",
  abstract =     "A pickup and delivery problem by multiple agents has
                 many applications, such as food delivery service and
                 disaster rescue. In this problem, there are cases where
                 fuels must be considered (e.g., the case of using
                 drones as agents). In addition, there are cases where
                 demand forecasting should be considered (e.g., the case
                 where a large number of orders are carried by a small
                 number of agents). In this paper, we consider an online
                 pickup and delivery problem considering fuel and demand
                 forecasting. First, the pickup and delivery problem
                 with fuel constraints is formulated. The information on
                 demand forecasting is included in the cost function.
                 Based on the orders, the agents' paths (e.g., the paths
                 from stores to customers) are calculated. We suppose
                 that the target area is given by an undirected graph.
                 Using a given graph, several constraints such as the
                 moves and fuels of the agents are introduced. This
                 problem is reduced to a mixed integer linear
                 programming (MILP) problem. Next, in online
                 optimization, the MILP problem is solved depending on
                 the acceptance of orders. Owing to new orders, the
                 calculated future paths may be changed. Finally, by
                 using a numerical example, we present the effectiveness
                 of the proposed method.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Shi:2024:SIB,
  author =       "Haohan Shi and Xiyu Shi and Safak Dogan",
  title =        "Speech Inpainting Based on Multi-Layer Long Short-Term
                 Memory Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "63",
  day =          "17",
  month =        feb,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020063",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/63",
  abstract =     "Audio inpainting plays an important role in addressing
                 incomplete, damaged, or missing audio signals,
                 contributing to improved quality of service and overall
                 user experience in multimedia communications over the
                 Internet and mobile networks. This paper presents an
                 innovative solution for speech inpainting using Long
                 Short-Term Memory (LSTM) networks, i.e., a restoring
                 task where the missing parts of speech signals are
                 recovered from the previous information in the time
                 domain. The lost or corrupted speech signals are also
                 referred to as gaps. We regard the speech inpainting
                 task as a time-series prediction problem in this
                 research work. To address this problem, we designed
                 multi-layer LSTM networks and trained them on different
                 speech datasets. Our study aims to investigate the
                 inpainting performance of the proposed models on
                 different datasets and with varying LSTM layers and
                 explore the effect of multi-layer LSTM networks on the
                 prediction of speech samples in terms of perceived
                 audio quality. The inpainted speech quality is
                 evaluated through the Mean Opinion Score (MOS) and a
                 frequency analysis of the spectrogram. Our proposed
                 multi-layer LSTM models are able to restore up to 1 s
                 of gaps with high perceptual audio quality using the
                 features captured from the time domain only.
                 Specifically, for gap lengths under 500 ms, the MOS can
                 reach up to 3--4, and for gap lengths ranging between
                 500 ms and 1 s, the MOS can reach up to 2--3. In the
                 time domain, the proposed models can proficiently
                 restore the envelope and trend of lost speech signals.
                 In the frequency domain, the proposed models can
                 restore spectrogram blocks with higher similarity to
                 the original signals at frequencies less than 2.0 kHz
                 and comparatively lower similarity at frequencies in
                 the range of 2.0 kHz--8.0 kHz.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Calcagno:2024:MOD,
  author =       "Salvatore Calcagno and Andrea Calvagna and Emiliano
                 Tramontana and Gabriella Verga",
  title =        "Merging Ontologies and Data from Electronic Health
                 Records",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "62",
  day =          "17",
  month =        feb,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020062",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/62",
  abstract =     "The Electronic Health Record (EHR) is a system for
                 collecting and storing patient medical records as data
                 that can be mechanically accessed, hence facilitating
                 and assisting the medical decision-making process. EHRs
                 exist in several formats, and each format lists
                 thousands of keywords to classify patients data. The
                 keywords are specific and are medical jargon; hence,
                 data classification is very accurate. As the keywords
                 constituting the formats of medical records express
                 concepts by means of specific jargon without
                 definitions or references, their proper use is left to
                 clinicians and could be affected by their background,
                 hence the interpretation of data could become slow or
                 less accurate than that desired. This article presents
                 an approach that accurately relates data in EHRs to
                 ontologies in the medical realm. Thanks to ontologies,
                 clinicians can be assisted when writing or analysing
                 health records, e.g., our solution promptly suggests
                 rigorous definitions for scientific terms, and
                 automatically connects data spread over several parts
                 of EHRs. The first step of our approach consists of
                 converting selected data and keywords from several EHR
                 formats into a format easier to parse, then the second
                 step is merging the extracted data with specialised
                 medical ontologies. Finally, enriched versions of the
                 medical data are made available to professionals. The
                 proposed approach was validated by taking samples of
                 medical records and ontologies in the real world. The
                 results have shown both versatility on handling data,
                 precision of query results, and appropriate suggestions
                 for relations among medical records.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Papenfuss:2024:EEE,
  author =       "Dennis Papenfu{\ss} and Bennet Gerlach and Stefan
                 Fischer and Mohamed Ahmed Hail",
  title =        "Enhancing Energy Efficiency in {IoT-NDN} via Parameter
                 Optimization",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "61",
  day =          "16",
  month =        feb,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020061",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/61",
  abstract =     "The IoT encompasses objects, sensors, and everyday
                 items not typically considered computers. IoT devices
                 are subject to severe energy, memory, and computation
                 power constraints. Employing NDN for the IoT is a
                 recent approach to accommodate these issues. To gain a
                 deeper insight into how different network parameters
                 affect energy consumption, analyzing a range of
                 parameters using hyperparameter optimization seems
                 reasonable. The experiments from this work's
                 ndnSIM-based hyperparameter setup indicate that the
                 data packet size has the most significant impact on
                 energy consumption, followed by the caching scheme,
                 caching strategy, and finally, the forwarding strategy.
                 The energy footprint of these parameters is orders of
                 magnitude apart. Surprisingly, the packet request
                 sequence influences the caching parameters' energy
                 footprint more than the graph size and topology.
                 Regarding energy consumption, the results indicate that
                 data compression may be more relevant than expected,
                 and caching may be more significant than the forwarding
                 strategy. The framework for ndnSIM developed in this
                 work can be used to simulate NDN networks more
                 efficiently. Furthermore, the work presents a valuable
                 basis for further research on the effect of specific
                 parameter combinations not examined before.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Qu:2024:MTO,
  author =       "Qian Qu and Mohsen Hatami and Ronghua Xu and Deeraj
                 Nagothu and Yu Chen and Xiaohua Li and Erik Blasch and
                 Erika Ardiles-Cruz and Genshe Chen",
  title =        "The Microverse: a Task-Oriented Edge-Scale Metaverse",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "60",
  day =          "13",
  month =        feb,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020060",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/60",
  abstract =     "Over the past decade, there has been a remarkable
                 acceleration in the evolution of smart cities and
                 intelligent spaces, driven by breakthroughs in
                 technologies such as the Internet of Things (IoT),
                 edge--fog--cloud computing, and machine learning
                 (ML)/artificial intelligence (AI). As society begins to
                 harness the full potential of these smart environments,
                 the horizon brightens with the promise of an immersive,
                 interconnected 3D world. The forthcoming paradigm shift
                 in how we live, work, and interact owes much to
                 groundbreaking innovations in augmented reality (AR),
                 virtual reality (VR), extended reality (XR),
                 blockchain, and digital twins (DTs). However, realizing
                 the expansive digital vista in our daily lives is
                 challenging. Current limitations include an incomplete
                 integration of pivotal techniques, daunting bandwidth
                 requirements, and the critical need for
                 near-instantaneous data transmission, all impeding the
                 digital VR metaverse from fully manifesting as
                 envisioned by its proponents. This paper seeks to delve
                 deeply into the intricacies of the immersive,
                 interconnected 3D realm, particularly in applications
                 demanding high levels of intelligence. Specifically,
                 this paper introduces the microverse, a task-oriented,
                 edge-scale, pragmatic solution for smart cities. Unlike
                 all-encompassing metaverses, each microverse instance
                 serves a specific task as a manageable digital twin of
                 an individual network slice. Each microverse enables
                 on-site/near-site data processing, information fusion,
                 and real-time decision-making within the
                 edge--fog--cloud computing framework. The microverse
                 concept is verified using smart public safety
                 surveillance (SPSS) for smart communities as a case
                 study, demonstrating its feasibility in practical smart
                 city applications. The aim is to stimulate discussions
                 and inspire fresh ideas in our community, guiding us as
                 we navigate the evolving digital landscape of smart
                 cities to embrace the potential of the metaverse.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fu:2024:DTB,
  author =       "Tianjie Fu and Peiyu Li and Chenke Shi and Youzhu
                 Liu",
  title =        "Digital-Twin-Based Monitoring System for Slab
                 Production Process",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "59",
  day =          "13",
  month =        feb,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020059",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/59",
  abstract =     "The growing demand for high-quality steel across
                 various industries has led to an increasing need for
                 superior-grade steel. The quality of slab ingots is a
                 pivotal factor influencing the final quality of steel
                 production. However, the current level of intelligence
                 in the steelmaking industry's processes is relatively
                 insufficient. Consequently, slab ingot quality
                 inspection is characterized by high-temperature risks
                 and imprecision. The positional accuracy of quality
                 detection is inadequate, and the precise quantification
                 of slab ingot production and quality remains
                 challenging. This paper proposes a digital twin
                 (DT)-based monitoring system for the slab ingot
                 production process that integrates DT technology with
                 slab ingot process detection. A neural network is
                 introduced for defect identification to ensure precise
                 defect localization and efficient recognition.
                 Concurrently, environmental production factors are
                 considered, leading to the introduction of a defect
                 prediction module. The effectiveness of this system is
                 validated through experimental verification.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Adesokan:2024:COC,
  author =       "Adedamola Adesokan and Rowan Kinney and Eirini Eleni
                 Tsiropoulou",
  title =        "{CROWDMATCH}: Optimizing Crowdsourcing Matching
                 through the Integration of Matching Theory and
                 Coalition Games",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "58",
  day =          "11",
  month =        feb,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020058",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/58",
  abstract =     "This paper tackles the challenges inherent in
                 crowdsourcing dynamics by introducing the CROWDMATCH
                 mechanism. Aimed at enabling crowdworkers to
                 strategically select suitable crowdsourcers while
                 contributing information to crowdsourcing tasks,
                 CROWDMATCH considers incentives, information
                 availability and cost, and the decisions of fellow
                 crowdworkers to model the utility functions for both
                 the crowdworkers and the crowdsourcers. Specifically,
                 the paper presents an initial Approximate CROWDMATCH
                 mechanism grounded in matching theory principles,
                 eliminating externalities from crowdworkers' decisions
                 and enabling each entity to maximize its utility.
                 Subsequently, the Accurate CROWDMATCH mechanism is
                 introduced, which is initiated by the outcome of the
                 Approximate CROWDMATCH mechanism, and coalition
                 game-theoretic principles are employed to refine the
                 matching process by accounting for externalities. The
                 paper's contributions include the introduction of the
                 CROWDMATCH system model, the development of both
                 Approximate and Accurate CROWDMATCH mechanisms, and a
                 demonstration of their superior performance through
                 comprehensive simulation results. The mechanisms'
                 scalability in large-scale crowdsourcing systems and
                 operational advantages are highlighted, distinguishing
                 them from existing methods and highlighting their
                 efficacy in empowering crowdworkers in crowdsourcer
                 selection.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bellaj:2024:DMM,
  author =       "Mohammed Bellaj and Najib Naja and Abdellah Jamali",
  title =        "Distributed Mobility Management Support for
                 Low-Latency Data Delivery in Named Data Networking for
                 {UAVs}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "57",
  day =          "10",
  month =        feb,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020057",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/57",
  abstract =     "Named Data Networking (NDN) has emerged as a promising
                 architecture to overcome the limitations of the
                 conventional Internet Protocol (IP) architecture,
                 particularly in terms of mobility, security, and data
                 availability. However, despite the advantages it
                 offers, producer mobility management remains a
                 significant challenge for NDN, especially for moving
                 vehicles and emerging technologies such as Unmanned
                 Aerial Vehicles (UAVs), known for their high-speed and
                 unpredictable movements, which makes it difficult for
                 NDN to maintain seamless communication. To solve this
                 mobility problem, we propose a Distributed Mobility
                 Management Scheme (DMMS) to support UAV mobility and
                 ensure low-latency content delivery in NDN
                 architecture. DMMS utilizes decentralized Anchors to
                 forward proactively the consumer's Interest packets
                 toward the producer's predicted location when handoff
                 occurs. Moreover, it introduces a new forwarding
                 approach that combines the standard and location-based
                 forwarding strategy to improve forwarding efficiency
                 under producer mobility without changing the network
                 structure. Using a realistic scenario, DMMS is
                 evaluated and compared against two well-known
                 solutions, namely MAP-ME and Kite, using the ndnSIM
                 simulations. We demonstrate that DMMS achieves better
                 results compared to Kite and MAP-ME solutions in terms
                 of network cost and consumer quality-of-service
                 metrics.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Khalil:2024:SON,
  author =       "Ayman Khalil and Besma Zeddini",
  title =        "A Secure Opportunistic Network with Efficient Routing
                 for Enhanced Efficiency and Sustainability",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "56",
  day =          "08",
  month =        feb,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020056",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/56",
  abstract =     "The intersection of cybersecurity and opportunistic
                 networks has ushered in a new era of innovation in the
                 realm of wireless communications. In an increasingly
                 interconnected world, where seamless data exchange is
                 pivotal for both individual users and organizations,
                 the need for efficient, reliable, and sustainable
                 networking solutions has never been more pressing.
                 Opportunistic networks, characterized by intermittent
                 connectivity and dynamic network conditions, present
                 unique challenges that necessitate innovative
                 approaches for optimal performance and sustainability.
                 This paper introduces a groundbreaking paradigm that
                 integrates the principles of cybersecurity with
                 opportunistic networks. At its core, this study
                 presents a novel routing protocol meticulously designed
                 to significantly outperform existing solutions
                 concerning key metrics such as delivery probability,
                 overhead ratio, and communication delay. Leveraging
                 cybersecurity's inherent strengths, our protocol not
                 only fortifies the network's security posture but also
                 provides a foundation for enhancing efficiency and
                 sustainability in opportunistic networks. The
                 overarching goal of this paper is to address the
                 inherent limitations of conventional opportunistic
                 network protocols. By proposing an innovative routing
                 protocol, we aim to optimize data delivery, minimize
                 overhead, and reduce communication latency. These
                 objectives are crucial for ensuring seamless and timely
                 information exchange, especially in scenarios where
                 traditional networking infrastructures fall short. By
                 large-scale simulations, the new model proves its
                 effectiveness in the different scenarios, especially in
                 terms of message delivery probability, while ensuring
                 reasonable overhead and latency.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2024:AIS,
  author =       "Meng Li and Jiqiang Liu and Yeping Yang",
  title =        "Automated Identification of Sensitive Financial Data
                 Based on the Topic Analysis",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "55",
  day =          "08",
  month =        feb,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020055",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/55",
  abstract =     "Data governance is an extremely important protection
                 and management measure throughout the entire life cycle
                 of data. However, there are still data governance
                 issues, such as data security risks, data privacy
                 breaches, and difficulties in data management and
                 access control. These problems lead to a risk of data
                 breaches and abuse. Therefore, the security
                 classification and grading of data has become an
                 important task to accurately identify sensitive data
                 and adopt appropriate maintenance and management
                 measures with different sensitivity levels. This work
                 started from the problems existing in the current data
                 security classification and grading work, such as
                 inconsistent classification and grading standards,
                 difficult data acquisition and sorting, and weak
                 semantic information of data fields, to find the
                 limitations of the current methods and the direction
                 for improvement. The automatic identification method of
                 sensitive financial data proposed in this paper is
                 based on topic analysis and was constructed by
                 incorporating Jieba word segmentation, word frequency
                 statistics, the skip-gram model, K-means clustering,
                 and other technologies. Expert assistance was sought to
                 select appropriate keywords for enhanced accuracy. This
                 work used the descriptive text library and real
                 business data of a Chinese financial institution for
                 training and testing to further demonstrate its
                 effectiveness and usefulness. The evaluation indicators
                 illustrated the effectiveness of this method in the
                 classification of data security. The proposed method
                 addressed the challenge of sensitivity level division
                 in texts with limited semantic information, which
                 overcame the limitations on model expansion across
                 different domains and provided an optimized application
                 model. All of the above pointed out the direction for
                 the real-time updating of the method.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kenyeres:2024:MTM,
  author =       "Martin Kenyeres and Ivana Budinsk{\'a} and Ladislav
                 Hluch{\'y} and Agostino Poggi",
  title =        "Modern Trends in Multi-Agent Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "54",
  day =          "08",
  month =        feb,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020054",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/54",
  abstract =     "Data governance is an extremely important protection
                 and management measure throughout the entire life cycle
                 of data. However, there are still data governance
                 issues, such as data security risks, data privacy
                 breaches, and difficulties in data management and
                 access control. These problems lead to a risk of data
                 breaches and abuse. Therefore, the security
                 classification and grading of data has become an
                 important task to accurately identify sensitive data
                 and adopt appropriate maintenance and management
                 measures with different sensitivity levels. This work
                 started from the problems existing in the current data
                 security classification and grading work, such as
                 inconsistent classification and grading standards,
                 difficult data acquisition and sorting, and weak
                 semantic information of data fields, to find the
                 limitations of the current methods and the direction
                 for improvement. The automatic identification method of
                 sensitive financial data proposed in this paper is
                 based on topic analysis and was constructed by
                 incorporating Jieba word segmentation, word frequency
                 statistics, the skip-gram model, K-means clustering,
                 and other technologies. Expert assistance was sought to
                 select appropriate keywords for enhanced accuracy. This
                 work used the descriptive text library and real
                 business data of a Chinese financial institution for
                 training and testing to further demonstrate its
                 effectiveness and usefulness. The evaluation indicators
                 illustrated the effectiveness of this method in the
                 classification of data security. The proposed method
                 addressed the challenge of sensitivity level division
                 in texts with limited semantic information, which
                 overcame the limitations on model expansion across
                 different domains and provided an optimized application
                 model. All of the above pointed out the direction for
                 the real-time updating of the method.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Cafaro:2024:SAF,
  author =       "Massimo Cafaro and Italo Epicoco and Marco Pulimeno",
  title =        "State-of-the-Art Future {Internet} Technology in
                 {Italy} 2022--2023",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "53",
  day =          "06",
  month =        feb,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020053",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/53",
  abstract =     "Data governance is an extremely important protection
                 and management measure throughout the entire life cycle
                 of data. However, there are still data governance
                 issues, such as data security risks, data privacy
                 breaches, and difficulties in data management and
                 access control. These problems lead to a risk of data
                 breaches and abuse. Therefore, the security
                 classification and grading of data has become an
                 important task to accurately identify sensitive data
                 and adopt appropriate maintenance and management
                 measures with different sensitivity levels. This work
                 started from the problems existing in the current data
                 security classification and grading work, such as
                 inconsistent classification and grading standards,
                 difficult data acquisition and sorting, and weak
                 semantic information of data fields, to find the
                 limitations of the current methods and the direction
                 for improvement. The automatic identification method of
                 sensitive financial data proposed in this paper is
                 based on topic analysis and was constructed by
                 incorporating Jieba word segmentation, word frequency
                 statistics, the skip-gram model, K-means clustering,
                 and other technologies. Expert assistance was sought to
                 select appropriate keywords for enhanced accuracy. This
                 work used the descriptive text library and real
                 business data of a Chinese financial institution for
                 training and testing to further demonstrate its
                 effectiveness and usefulness. The evaluation indicators
                 illustrated the effectiveness of this method in the
                 classification of data security. The proposed method
                 addressed the challenge of sensitivity level division
                 in texts with limited semantic information, which
                 overcame the limitations on model expansion across
                 different domains and provided an optimized application
                 model. All of the above pointed out the direction for
                 the real-time updating of the method.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mukhopadhyay:2024:QAI,
  author =       "Adwitiya Mukhopadhyay and Aryadevi Remanidevi Devidas
                 and Venkat P. Rangan and Maneesha Vinodini Ramesh",
  title =        "A {QoS}-Aware {IoT} Edge Network for Mobile
                 Telemedicine Enabling In-Transit Monitoring of
                 Emergency Patients",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "52",
  day =          "06",
  month =        feb,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020052",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/52",
  abstract =     "Addressing the inadequacy of medical facilities in
                 rural communities and the high number of patients
                 affected by ailments that need to be treated
                 immediately is of prime importance for all countries.
                 The various recent healthcare emergency situations
                 bring out the importance of telemedicine and demand
                 rapid transportation of patients to nearby hospitals
                 with available resources to provide the required
                 medical care. Many current healthcare facilities and
                 ambulances are not equipped to provide real-time risk
                 assessment for each patient and dynamically provide the
                 required medical interventions. This work proposes an
                 IoT-based mobile medical edge (IM 2 E) node to be
                 integrated with wearable and portable devices for the
                 continuous monitoring of emergency patients transported
                 via ambulances and it delves deeper into the existing
                 challenges, such as (a) a lack of a simplified patient
                 risk scoring system, (b) the need for architecture that
                 enables seamless communication for dynamically varying
                 QoS requirements, and (c)the need for context-aware
                 knowledge regarding the effect of end-to-end delay and
                 the packet loss ratio (PLR) on the real-time monitoring
                 of health risks in emergency patients. The proposed
                 work builds a data path selection model to identify the
                 most effective path through which to route the data
                 packets in an effective manner. The signal-to-noise
                 interference ratio and the fading in the path are
                 chosen to analyze the suitable path for data
                 transmission.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lin:2024:OSA,
  author =       "Ming-Yen Lin and Ping-Chun Wu and Sue-Chen Hsueh",
  title =        "Optimizing Session-Aware Recommenders: a Deep Dive
                 into {GRU}-Based Latent Interaction Integration",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "51",
  day =          "01",
  month =        feb,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020051",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/51",
  abstract =     "This study introduces session-aware recommendation
                 models, leveraging GRU (Gated Recurrent Unit) and
                 attention mechanisms for advanced latent interaction
                 data integration. A primary advancement is enhancing
                 latent context, a critical factor for boosting
                 recommendation accuracy. We address the existing
                 models' rigidity by dynamically blending short-term
                 (most recent) and long-term (historical) preferences,
                 moving beyond static period definitions. Our
                 approaches, pre-combination (LCII-Pre) and
                 post-combination (LCII-Post), with fixed (Fix) and
                 flexible learning (LP) weight configurations, are
                 thoroughly evaluated. We conducted extensive
                 experiments to assess our models' performance on public
                 datasets such as Amazon and MovieLens 1M. Notably, on
                 the MovieLens 1M dataset, LCII-Pre Fix achieved a
                 1.85\% and 2.54\% higher Recall@20 than II-RNN and
                 BERT4Rec +st+TSA, respectively. On the Steam dataset,
                 LCII-Post LP outperformed these models by 18.66\% and
                 5.5\%. Furthermore, on the Amazon dataset, LCII showed
                 a 2.59\% and 1.89\% improvement in Recall@20 over
                 II-RNN and CAII. These results affirm the significant
                 enhancement our models bring to session-aware
                 recommendation systems, showcasing their potential for
                 both academic and practical applications in the
                 field.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kumar:2024:ESC,
  author =       "Pradeep Kumar and Guo-Liang Shih and Bo-Lin Guo and
                 Siva Kumar Nagi and Yibeltal Chanie Manie and Cheng-Kai
                 Yao and Michael Augustine Arockiyadoss and Peng-Chun
                 Peng",
  title =        "Enhancing Smart City Safety and Utilizing {AI} Expert
                 Systems for Violence Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "50",
  day =          "31",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020050",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/50",
  abstract =     "Violent attacks have been one of the hot issues in
                 recent years. In the presence of closed-circuit
                 televisions (CCTVs) in smart cities, there is an
                 emerging challenge in apprehending criminals, leading
                 to a need for innovative solutions. In this paper, the
                 propose a model aimed at enhancing real-time emergency
                 response capabilities and swiftly identifying
                 criminals. This initiative aims to foster a safer
                 environment and better manage criminal activity within
                 smart cities. The proposed architecture combines an
                 image-to-image stable diffusion model with violence
                 detection and pose estimation approaches. The diffusion
                 model generates synthetic data while the object
                 detection approach uses YOLO v7 to identify violent
                 objects like baseball bats, knives, and pistols,
                 complemented by MediaPipe for action detection.
                 Further, a long short-term memory (LSTM) network
                 classifies the action attacks involving violent
                 objects. Subsequently, an ensemble consisting of an
                 edge device and the entire proposed model is deployed
                 onto the edge device for real-time data testing using a
                 dash camera. Thus, this study can handle violent
                 attacks and send alerts in emergencies. As a result,
                 our proposed YOLO model achieves a mean average
                 precision (MAP) of 89.5\% for violent attack detection,
                 and the LSTM classifier model achieves an accuracy of
                 88.33\% for violent action classification. The results
                 highlight the model's enhanced capability to accurately
                 detect violent objects, particularly in effectively
                 identifying violence through the implemented artificial
                 intelligence system.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Saadatfar:2024:NDG,
  author =       "Hamid Saadatfar and Hamid Gholampour Ahangar and Javad
                 Hassannataj Joloudari",
  title =        "A New Dynamic Game-Based Pricing Model for Cloud
                 Environment",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "49",
  day =          "31",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020049",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/49",
  abstract =     "Resource pricing in cloud computing has become one of
                 the main challenges for cloud providers. The challenge
                 is determining a fair and appropriate price to satisfy
                 users and resource providers. To establish a
                 justifiable price, it is imperative to take into
                 account the circumstances and requirements of both the
                 provider and the user. This research tries to provide a
                 pricing mechanism for cloud computing based on game
                 theory. The suggested approach considers three aspects:
                 the likelihood of faults, the interplay among virtual
                 machines, and the amount of energy used, in order to
                 determine a justifiable price. In the game that is
                 being proposed, the provider is responsible for
                 determining the price of the virtual machine that can
                 be made available to the user on each physical machine.
                 The user, on the other hand, has the authority to
                 choose between the virtual machines that are offered in
                 order to run their application. The whole game is
                 implemented as a function of the resource broker
                 component. The proposed mechanism is simulated and
                 evaluated using the CloudSim simulator. Its performance
                 is compared with several previous recent mechanisms.
                 The results indicate that the suggested mechanism has
                 successfully identified a more rational price for both
                 the user and the provider, consequently enhancing the
                 overall profitability of the cloud system.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Assiri:2024:EPA,
  author =       "Azizah Assiri and Hassen Sallay",
  title =        "Efficient Privacy-Aware Forwarding for Enhanced
                 Communication Privacy in Opportunistic Mobile Social
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "48",
  day =          "31",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020048",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/48",
  abstract =     "Opportunistic mobile social networks (OMSNs) have
                 become increasingly popular in recent years due to the
                 rise of social media and smartphones. However, message
                 forwarding and sharing social information through
                 intermediary nodes on OMSNs raises privacy concerns as
                 personal data and activities become more exposed.
                 Therefore, maintaining privacy without limiting
                 efficient social interaction is a challenging task.
                 This paper addresses this specific problem of
                 safeguarding user privacy during message forwarding by
                 integrating a privacy layer on the state-of-the-art
                 OMSN routing decision models that empowers users to
                 control their message dissemination. Mainly, we present
                 three user-centric privacy-aware forwarding modes
                 guiding the selection of the next hop in the forwarding
                 path based on social metrics such as common friends and
                 exchanged messages between OMSN nodes. More
                 specifically, we define different social relationship
                 strengths approximating real-world scenarios (familiar,
                 weak tie, stranger) and trust thresholds to give users
                 choices on trust levels for different social contexts
                 and guide the routing decisions. We evaluate the
                 privacy enhancement and network performance through
                 extensive simulations using ONE simulator for several
                 routing schemes (Epidemic, Prophet, and Spray and Wait)
                 and different movement models (random way, bus, and
                 working day). We demonstrate that our modes can enhance
                 privacy by up to 45\% in various network scenarios, as
                 measured by the reduction in the likelihood of
                 unintended message propagation, while keeping the
                 message-delivery process effective and efficient.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gkontzis:2024:EUR,
  author =       "Andreas F. Gkontzis and Sotiris Kotsiantis and
                 Georgios Feretzakis and Vassilios S. Verykios",
  title =        "Enhancing Urban Resilience: Smart City Data Analyses,
                 Forecasts, and Digital Twin Techniques at the
                 Neighborhood Level",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "47",
  day =          "30",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020047",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/47",
  abstract =     "Smart cities, leveraging advanced data analytics,
                 predictive models, and digital twin techniques, offer a
                 transformative model for sustainable urban development.
                 Predictive analytics is critical to proactive planning,
                 enabling cities to adapt to evolving challenges.
                 Concurrently, digital twin techniques provide a virtual
                 replica of the urban environment, fostering real-time
                 monitoring, simulation, and analysis of urban systems.
                 This study underscores the significance of real-time
                 monitoring, simulation, and analysis of urban systems
                 to support test scenarios that identify bottlenecks and
                 enhance smart city efficiency. This paper delves into
                 the crucial roles of citizen report analytics,
                 prediction, and digital twin technologies at the
                 neighborhood level. The study integrates extract,
                 transform, load (ETL) processes, artificial
                 intelligence (AI) techniques, and a digital twin
                 methodology to process and interpret urban data streams
                 derived from citizen interactions with the city's
                 coordinate-based problem mapping platform. Using an
                 interactive GeoDataFrame within the digital twin
                 methodology, dynamic entities facilitate simulations
                 based on various scenarios, allowing users to
                 visualize, analyze, and predict the response of the
                 urban system at the neighborhood level. This approach
                 reveals antecedent and predictive patterns, trends, and
                 correlations at the physical level of each city area,
                 leading to improvements in urban functionality,
                 resilience, and resident quality of life.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Corda:2024:CAB,
  author =       "Erica Corda and Silvia M. Massa and Daniele Riboni",
  title =        "Context-Aware Behavioral Tips to Improve Sleep Quality
                 via Machine Learning and Large Language Models",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "46",
  day =          "30",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020046",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/46",
  abstract =     "As several studies demonstrate, good sleep quality is
                 essential for individuals' well-being, as a lack of
                 restoring sleep may disrupt different physical, mental,
                 and social dimensions of health. For this reason, there
                 is increasing interest in tools for the monitoring of
                 sleep based on personal sensors. However, there are
                 currently few context-aware methods to help individuals
                 to improve their sleep quality through behavior change
                 tips. In order to tackle this challenge, in this paper,
                 we propose a system that couples machine learning
                 algorithms and large language models to forecast the
                 next night's sleep quality, and to provide
                 context-aware behavior change tips to improve sleep. In
                 order to encourage adherence and to increase trust, our
                 system includes the use of large language models to
                 describe the conditions that the machine learning
                 algorithm finds harmful to sleep health, and to explain
                 why the behavior change tips are generated as a
                 consequence. We develop a prototype of our system,
                 including a smartphone application, and perform
                 experiments with a set of users. Results show that our
                 system's forecast is correlated to the actual sleep
                 quality. Moreover, a preliminary user study suggests
                 that the use of large language models in our system is
                 useful in increasing trust and engagement.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Aftowicz:2024:NPU,
  author =       "Marcin Aftowicz and Ievgen Kabin and Zoya Dyka and
                 Peter Langend{\"o}rfer",
  title =        "Non-Profiled Unsupervised Horizontal Iterative Attack
                 against Hardware Elliptic Curve Scalar Multiplication
                 Using Machine Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "45",
  day =          "29",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020045",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/45",
  abstract =     "While IoT technology makes industries, cities, and
                 homes smarter, it also opens the door to security
                 risks. With the right equipment and physical access to
                 the devices, the attacker can leverage side-channel
                 information, like timing, power consumption, or
                 electromagnetic emanation, to compromise cryptographic
                 operations and extract the secret key. This work
                 presents a side channel analysis of a cryptographic
                 hardware accelerator for the Elliptic Curve Scalar
                 Multiplication operation, implemented in a
                 Field-Programmable Gate Array and as an
                 Application-Specific Integrated Circuit. The presented
                 framework consists of initial key extraction using a
                 state-of-the-art statistical horizontal attack and is
                 followed by regularized Artificial Neural Networks,
                 which take, as input, the partially incorrect key
                 guesses from the horizontal attack and correct them
                 iteratively. The initial correctness of the horizontal
                 attack, measured as the fraction of correctly extracted
                 bits of the secret key, was improved from 75\% to 98\%
                 by applying the iterative learning.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kempelis:2024:CVM,
  author =       "Arturs Kempelis and Inese Polaka and Andrejs Romanovs
                 and Antons Patlins",
  title =        "Computer Vision and Machine Learning-Based Predictive
                 Analysis for Urban Agricultural Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "44",
  day =          "28",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020044",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/44",
  abstract =     "Urban agriculture presents unique challenges,
                 particularly in the context of microclimate monitoring,
                 which is increasingly important in food production.
                 This paper explores the application of convolutional
                 neural networks (CNNs) to forecast key sensor
                 measurements from thermal images within this context.
                 This research focuses on using thermal images to
                 forecast sensor measurements of relative air humidity,
                 soil moisture, and light intensity, which are integral
                 to plant health and productivity in urban farming
                 environments. The results indicate a higher accuracy in
                 forecasting relative air humidity and soil moisture
                 levels, with Mean Absolute Percentage Errors (MAPEs)
                 within the range of 10--12\%. These findings correlate
                 with the strong dependency of these parameters on
                 thermal patterns, which are effectively extracted by
                 the CNNs. In contrast, the forecasting of light
                 intensity proved to be more challenging, yielding lower
                 accuracy. The reduced performance is likely due to the
                 more complex and variable factors that affect light in
                 urban environments. The insights gained from the higher
                 predictive accuracy for relative air humidity and soil
                 moisture may inform targeted interventions for urban
                 farming practices, while the lower accuracy in light
                 intensity forecasting highlights the need for further
                 research into the integration of additional data
                 sources or hybrid modeling approaches. The conclusion
                 suggests that the integration of these technologies can
                 significantly enhance the predictive maintenance of
                 plant health, leading to more sustainable and efficient
                 urban farming practices. However, the study also
                 acknowledges the challenges in implementing these
                 technologies in urban agricultural models.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gonzalez-Ambriz:2024:SGB,
  author =       "Sergio Jes{\'u}s Gonz{\'a}lez-Ambriz and Rolando
                 Menchaca-M{\'e}ndez and Sergio Alejandro
                 Pinacho-Castellanos and Mario Eduardo
                 Rivero-{\'A}ngeles",
  title =        "A Spectral Gap-Based Topology Control Algorithm for
                 Wireless Backhaul Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "43",
  day =          "26",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020043",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/43",
  abstract =     "This paper presents the spectral gap-based topology
                 control algorithm (SGTC) for wireless backhaul
                 networks, a novel approach that employs the Laplacian
                 Spectral Gap (LSG) to find expander-like graphs that
                 optimize the topology of the network in terms of
                 robustness, diameter, energy cost, and network entropy.
                 The latter measures the network's ability to promote
                 seamless traffic offloading from the Macro Base
                 Stations to smaller cells by providing a high diversity
                 of shortest paths connecting all the stations. Given
                 the practical constraints imposed by cellular
                 technologies, the proposed algorithm uses simulated
                 annealing to search for feasible network topologies
                 with a large LSG. Then, it computes the Pareto front of
                 the set of feasible solutions found during the
                 annealing process when considering robustness,
                 diameter, and entropy as objective functions. The
                 algorithm's result is the Pareto efficient solution
                 that minimizes energy cost. A set of experimental
                 results shows that by optimizing the LSG, the proposed
                 algorithm simultaneously optimizes the set of desirable
                 topological properties mentioned above. The results
                 also revealed that generating networks with good
                 spectral expansion is possible even under the
                 restrictions imposed by current wireless technologies.
                 This is a desirable feature because these networks have
                 strong connectivity properties even if they do not have
                 a large number of links.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Karras:2024:TAB,
  author =       "Aristeidis Karras and Anastasios Giannaros and
                 Christos Karras and Leonidas Theodorakopoulos and
                 Constantinos S. Mammassis and George A. Krimpas and
                 Spyros Sioutas",
  title =        "{TinyML} Algorithms for Big Data Management in
                 Large-Scale {IoT} Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "42",
  day =          "25",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020042",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/42",
  abstract =     "In the context of the Internet of Things (IoT), Tiny
                 Machine Learning (TinyML) and Big Data, enhanced by
                 Edge Artificial Intelligence, are essential for
                 effectively managing the extensive data produced by
                 numerous connected devices. Our study introduces a set
                 of TinyML algorithms designed and developed to improve
                 Big Data management in large-scale IoT systems. These
                 algorithms, named TinyCleanEDF, EdgeClusterML,
                 CompressEdgeML, CacheEdgeML, and TinyHybridSenseQ,
                 operate together to enhance data processing, storage,
                 and quality control in IoT networks, utilizing the
                 capabilities of Edge AI. In particular, TinyCleanEDF
                 applies federated learning for Edge-based data cleaning
                 and anomaly detection. EdgeClusterML combines
                 reinforcement learning with self-organizing maps for
                 effective data clustering. CompressEdgeML uses neural
                 networks for adaptive data compression. CacheEdgeML
                 employs predictive analytics for smart data caching,
                 and TinyHybridSenseQ concentrates on data quality
                 evaluation and hybrid storage strategies. Our
                 experimental evaluation of the proposed techniques
                 includes executing all the algorithms in various
                 numbers of Raspberry Pi devices ranging from one to
                 ten. The experimental results are promising as we
                 outperform similar methods across various evaluation
                 metrics. Ultimately, we anticipate that the proposed
                 algorithms offer a comprehensive and efficient approach
                 to managing the complexities of IoT, Big Data, and Edge
                 AI.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Nitu:2024:BLB,
  author =       "Melania Nitu and Mihai Dascalu",
  title =        "Beyond Lexical Boundaries: {LLM}-Generated Text
                 Detection for {Romanian} Digital Libraries",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "41",
  day =          "25",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020041",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/41",
  abstract =     "Machine-generated content reshapes the landscape of
                 digital information; hence, ensuring the authenticity
                 of texts within digital libraries has become a
                 paramount concern. This work introduces a corpus of
                 approximately 60 k Romanian documents, including
                 human-written samples as well as generated texts using
                 six distinct Large Language Models (LLMs) and three
                 different generation methods. Our robust experimental
                 dataset covers five domains, namely books, news, legal,
                 medical, and scientific publications. The exploratory
                 text analysis revealed differences between
                 human-authored and artificially generated texts,
                 exposing the intricacies of lexical diversity and
                 textual complexity. Since Romanian is a less-resourced
                 language requiring dedicated detectors on which
                 out-of-the-box solutions do not work, this paper
                 introduces two techniques for discerning
                 machine-generated texts. The first method leverages a
                 Transformer-based model to categorize texts as human or
                 machine-generated, while the second method extracts and
                 examines linguistic features, such as identifying the
                 top textual complexity indices via Kruskal--Wallis mean
                 rank and computes burstiness, which are further fed
                 into a machine-learning model leveraging an extreme
                 gradient-boosting decision tree. The methods show
                 competitive performance, with the first technique's
                 results outperforming the second one in two out of five
                 domains, reaching an F1 score of 0.96. Our study also
                 includes a text similarity analysis between
                 human-authored and artificially generated texts,
                 coupled with a SHAP analysis to understand which
                 linguistic features contribute more to the classifier's
                 decision.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hossain:2024:HAI,
  author =       "Mahmud Hossain and Golam Kayas and Ragib Hasan and
                 Anthony Skjellum and Shahid Noor and S. M. Riazul
                 Islam",
  title =        "A Holistic Analysis of {Internet of Things} ({IoT})
                 Security: Principles, Practices, and New Perspectives",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "40",
  day =          "24",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020040",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/40",
  abstract =     "Driven by the rapid escalation of its utilization, as
                 well as ramping commercialization, Internet of Things
                 (IoT) devices increasingly face security threats. Apart
                 from denial of service, privacy, and safety concerns,
                 compromised devices can be used as enablers for
                 committing a variety of crime and e-crime. Despite
                 ongoing research and study, there remains a significant
                 gap in the thorough analysis of security challenges,
                 feasible solutions, and open secure problems for IoT.
                 To bridge this gap, we provide a comprehensive overview
                 of the state of the art in IoT security with a critical
                 investigation-based approach. This includes a detailed
                 analysis of vulnerabilities in IoT-based systems and
                 potential attacks. We present a holistic review of the
                 security properties required to be adopted by IoT
                 devices, applications, and services to mitigate IoT
                 vulnerabilities and, thus, successful attacks.
                 Moreover, we identify challenges to the design of
                 security protocols for IoT systems in which constituent
                 devices vary markedly in capability (such as storage,
                 computation speed, hardware architecture, and
                 communication interfaces). Next, we review existing
                 research and feasible solutions for IoT security. We
                 highlight a set of open problems not yet addressed
                 among existing security solutions. We provide a set of
                 new perspectives for future research on such issues
                 including secure service discovery, on-device
                 credential security, and network anomaly detection. We
                 also provide directions for designing a forensic
                 investigation framework for IoT infrastructures to
                 inspect relevant criminal cases, execute a cyber
                 forensic process, and determine the facts about a given
                 incident. This framework offers a means to better
                 capture information on successful attacks as part of a
                 feedback mechanism to thwart future vulnerabilities and
                 threats. This systematic holistic review will both
                 inform on current challenges in IoT security and
                 ideally motivate their future resolution.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lopes:2024:VTP,
  author =       "Ricardo Lopes and Marcello Trovati and Ella Pereira",
  title =        "Volumetric Techniques for Product Routing and Loading
                 Optimisation in {Industry 4.0}: a Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "39",
  day =          "24",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020039",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/39",
  abstract =     "Industry 4.0 has become a crucial part in the majority
                 of processes, components, and related modelling, as
                 well as predictive tools that allow a more efficient,
                 automated and sustainable approach to industry. The
                 availability of large quantities of data, and the
                 advances in IoT, AI, and data-driven frameworks, have
                 led to an enhanced data gathering, assessment, and
                 extraction of actionable information, resulting in a
                 better decision-making process. Product picking and its
                 subsequent packing is an important area, and has drawn
                 increasing attention for the research community.
                 However, depending of the context, some of the related
                 approaches tend to be either highly mathematical, or
                 applied to a specific context. This article aims to
                 provide a survey on the main methods, techniques, and
                 frameworks relevant to product packing and to highlight
                 the main properties and features that should be further
                 investigated to ensure a more efficient and optimised
                 approach.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ma:2024:RSS,
  author =       "Min Ma and Shanrong Liu and Shufei Wang and Shengnan
                 Shi",
  title =        "Refined Semi-Supervised Modulation Classification:
                 Integrating Consistency Regularization and
                 Pseudo-Labeling Techniques",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "38",
  day =          "23",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020038",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/38",
  abstract =     "Automatic modulation classification (AMC) plays a
                 crucial role in wireless communication by identifying
                 the modulation scheme of received signals, bridging
                 signal reception and demodulation. Its main challenge
                 lies in performing accurate signal processing without
                 prior information. While deep learning has been applied
                 to AMC, its effectiveness largely depends on the
                 availability of labeled samples. To address the
                 scarcity of labeled data, we introduce a novel
                 semi-supervised AMC approach combining consistency
                 regularization and pseudo-labeling. This method
                 capitalizes on the inherent data distribution of
                 unlabeled data to supplement the limited labeled data.
                 Our approach involves a dual-component objective
                 function for model training: one part focuses on the
                 loss from labeled data, while the other addresses the
                 regularized loss for unlabeled data, enhanced through
                 two distinct levels of data augmentation. These
                 combined losses concurrently refine the model
                 parameters. Our method demonstrates superior
                 performance over established benchmark algorithms, such
                 as decision trees (DTs), support vector machines
                 (SVMs), pi-models, and virtual adversarial training
                 (VAT). It exhibits a marked improvement in the
                 recognition accuracy, particularly when the proportion
                 of labeled samples is as low as 1--4\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Pokhrel:2024:DME,
  author =       "Shiva Raj Pokhrel and Jonathan Kua and Deol Satish and
                 Sebnem Ozer and Jeff Howe and Anwar Walid",
  title =        "{DDPG-MPCC}: an Experience Driven Multipath
                 Performance Oriented Congestion Control",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "2",
  pages =        "37",
  day =          "23",
  month =        jan,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16020037",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:35 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/2/37",
  abstract =     "We introduce a novel multipath data transport approach
                 at the transport layer referred to as ` Deep
                 Deterministic Policy Gradient for Multipath
                 Performance-oriented Congestion Control ' (DDPG-MPCC),
                 which leverages deep reinforcement learning to enhance
                 congestion management in multipath networks. Our method
                 combines DDPG with online convex optimization to
                 optimize fairness and performance in simultaneously
                 challenging multipath internet congestion control
                 scenarios. Through experiments by developing kernel
                 implementation, we show how DDPG-MPCC performs compared
                 to the state-of-the-art solutions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Norbu:2024:FAT,
  author =       "Tenzin Norbu and Joo Yeon Park and Kok Wai Wong and
                 Hui Cui",
  title =        "Factors Affecting Trust and Acceptance for Blockchain
                 Adoption in Digital Payment Systems: a Systematic
                 Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "106",
  day =          "21",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030106",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/106",
  abstract =     "Blockchain technology has become significant for
                 financial sectors, especially digital payment systems,
                 offering enhanced security, transparency, and
                 efficiency. However, there is limited research on the
                 factors influencing user trust in and acceptance of
                 blockchain adoption in digital payment systems. This
                 systematic review provides insight into the key factors
                 impacting consumers' perceptions and behaviours towards
                 embracing blockchain technology. A total of 1859
                 studies were collected, with 48 meeting the criteria
                 for comprehensive analysis. The results showed that
                 security, privacy, transparency, and regulation are the
                 most significant factors influencing trust for
                 blockchain adoption. The most influential factors
                 identified in the Unified Theory of Acceptance and Use
                 of Technology (UTAUT) model include performance
                 expectancy, effort expectancy, social influence, and
                 facilitating conditions. Incorporating a trust and
                 acceptance model could be a viable approach to tackling
                 obstacles and ensuring the successful integration of
                 blockchain technology into digital payment systems.
                 Understanding these factors is crucial for creating a
                 favourable atmosphere for adopting blockchain
                 technology in digital payments. User-perspective
                 research on blockchain adoption in digital payment
                 systems is still insufficient, and this aspect still
                 requires further investigation. Blockchain adoption in
                 digital payment systems has not been sufficiently
                 conducted from the user's perspective, and there is a
                 scope for it to be carried out. This review aims to
                 shed light on the factors of trust in and acceptance of
                 blockchain adoption in digital payment systems so that
                 the full potential of blockchain technology can be
                 realised. Understanding these factors and their
                 intricate connections is imperative in fostering a
                 conducive environment for the widespread acceptance of
                 blockchain technology in digital payments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Jiang:2024:UCM,
  author =       "Shui Jiang and Yanning Ge and Xu Yang and Wencheng
                 Yang and Hui Cui",
  title =        "{UAV} Control Method Combining Reptile
                 Meta-Reinforcement Learning and Generative Adversarial
                 Imitation Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "105",
  day =          "20",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030105",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/105",
  abstract =     "Reinforcement learning (RL) is pivotal in empowering
                 Unmanned Aerial Vehicles (UAVs) to navigate and make
                 decisions efficiently and intelligently within complex
                 and dynamic surroundings. Despite its significance, RL
                 is hampered by inherent limitations such as low sample
                 efficiency, restricted generalization capabilities, and
                 a heavy reliance on the intricacies of reward function
                 design. These challenges often render single-method RL
                 approaches inadequate, particularly in the context of
                 UAV operations where high costs and safety risks in
                 real-world applications cannot be overlooked. To
                 address these issues, this paper introduces a novel RL
                 framework that synergistically integrates meta-learning
                 and imitation learning. By leveraging the Reptile
                 algorithm from meta-learning and Generative Adversarial
                 Imitation Learning (GAIL), coupled with state
                 normalization techniques for processing state data,
                 this framework significantly enhances the model's
                 adaptability. It achieves this by identifying and
                 leveraging commonalities across various tasks, allowing
                 for swift adaptation to new challenges without the need
                 for complex reward function designs. To ascertain the
                 efficacy of this integrated approach, we conducted
                 simulation experiments within both two-dimensional
                 environments. The empirical results clearly indicate
                 that our GAIL-enhanced Reptile method surpasses
                 conventional single-method RL algorithms in terms of
                 training efficiency. This evidence underscores the
                 potential of combining meta-learning and imitation
                 learning to surmount the traditional barriers faced by
                 reinforcement learning in UAV trajectory planning and
                 decision-making processes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Miguel:2024:UCV,
  author =       "Joaquim Miguel and Pedro Mendon{\c{c}}a and Agnelo
                 Quelhas and Jo{\~a}o M. L. P. Caldeira and Vasco N. G.
                 J. Soares",
  title =        "Using Computer Vision to Collect Information on
                 Cycling and Hiking Trails Users",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "104",
  day =          "20",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030104",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/104",
  abstract =     "Hiking and cycling have become popular activities for
                 promoting well-being and physical activity. Portugal
                 has been investing in hiking and cycling trail
                 infrastructures to boost sustainable tourism. However,
                 the lack of reliable data on the use of these trails
                 means that the times of greatest affluence or the type
                 of user who makes the most use of them are not
                 recorded. These data are of the utmost importance to
                 the managing bodies, with which they can adjust their
                 actions to improve the management, maintenance,
                 promotion, and use of the infrastructures for which
                 they are responsible. The aim of this work is to
                 present a review study on projects, techniques, and
                 methods that can be used to identify and count the
                 different types of users on these trails. The most
                 promising computer vision techniques are identified and
                 described: YOLOv3-Tiny, MobileNet-SSD V2, and
                 FasterRCNN with ResNet-50. Their performance is
                 evaluated and compared. The results observed can be
                 very useful for proposing future prototypes. The
                 challenges, future directions, and research
                 opportunities are also discussed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Moreno-Vozmediano:2024:IRO,
  author =       "Rafael Moreno-Vozmediano and Rub{\'e}n S. Montero and
                 Eduardo Huedo and Ignacio M. Llorente",
  title =        "Intelligent Resource Orchestration for {5G} Edge
                 Infrastructures",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "103",
  day =          "19",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030103",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/103",
  abstract =     "The adoption of edge infrastructure in 5G environments
                 stands out as a transformative technology aimed at
                 meeting the increasing demands of latency-sensitive and
                 data-intensive applications. This research paper
                 presents a comprehensive study on the intelligent
                 orchestration of 5G edge computing infrastructures. The
                 proposed Smart 5G Edge-Cloud Management Architecture,
                 built upon an OpenNebula foundation, incorporates a
                 ONEedge5G experimental component, which offers
                 intelligent workload forecasting and infrastructure
                 orchestration and automation capabilities, for optimal
                 allocation of virtual resources across diverse edge
                 locations. The research evaluated different forecasting
                 models, based both on traditional statistical
                 techniques and machine learning techniques, comparing
                 their accuracy in CPU usage prediction for a dataset of
                 virtual machines (VMs). Additionally, an integer linear
                 programming formulation was proposed to solve the
                 optimization problem of mapping VMs to physical servers
                 in distributed edge infrastructure. Different
                 optimization criteria such as minimizing server usage,
                 load balancing, and reducing latency violations were
                 considered, along with mapping constraints.
                 Comprehensive tests and experiments were conducted to
                 evaluate the efficacy of the proposed architecture.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zu:2024:SMS,
  author =       "Lijun Zu and Wenyu Qi and Hongyi Li and Xiaohua Men
                 and Zhihui Lu and Jiawei Ye and Liang Zhang",
  title =        "{UP-SDCG}: a Method of Sensitive Data Classification
                 for Collaborative Edge Computing in Financial Cloud
                 Environment",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "102",
  day =          "18",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030102",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/102",
  abstract =     "The digital transformation of banks has led to a
                 paradigm shift, promoting the open sharing of data and
                 services with third-party providers through APIs, SDKs,
                 and other technological means. While data sharing
                 brings personalized, convenient, and enriched services
                 to users, it also introduces security risks, including
                 sensitive data leakage and misuse, highlighting the
                 importance of data classification and grading as the
                 foundational pillar of security. This paper presents a
                 cloud-edge collaborative banking data open application
                 scenario, focusing on the critical need for an accurate
                 and automated sensitive data classification and
                 categorization method. The regulatory outpost module
                 addresses this requirement, aiming to enhance the
                 precision and efficiency of data classification.
                 Firstly, regulatory policies impose strict requirements
                 concerning data protection. Secondly, the sheer volume
                 of business and the complexity of the work situation
                 make it impractical to rely on manual experts, as they
                 incur high labor costs and are unable to guarantee
                 significant accuracy. Therefore, we propose a scheme
                 UP-SDCG for automatically classifying and grading
                 financially sensitive structured data. We developed a
                 financial data hierarchical classification library.
                 Additionally, we employed library augmentation
                 technology and implemented a synonym discrimination
                 model. We conducted an experimental analysis using
                 simulation datasets, where UP-SDCG achieved precision
                 surpassing 95\%, outperforming the other three
                 comparison models. Moreover, we performed real-world
                 testing in financial institutions, achieving good
                 detection results in customer data, supervision, and
                 additional in personally sensitive information,
                 aligning with application goals. Our ongoing work will
                 extend the model's capabilities to encompass
                 unstructured data classification and grading,
                 broadening the scope of application.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Pozzebon:2024:EFC,
  author =       "Alessandro Pozzebon",
  title =        "Edge and Fog Computing for the {Internet of Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "101",
  day =          "16",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030101",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/101",
  abstract =     "Over the last years few years, the number of
                 interconnected devices within the context of Internet
                 of Things (IoT) has rapidly grown; some statistics
                 state that the total number of IoT-connected devices in
                 2023 has reached the groundbreaking number of 17
                 billion [\ldots{}]",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kalyani:2024:ASD,
  author =       "Yogeswaranathan Kalyani and Liam Vorster and Rebecca
                 Whetton and Rem Collier",
  title =        "Application Scenarios of Digital Twins for Smart Crop
                 Farming through Cloud--Fog--Edge Infrastructure",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "100",
  day =          "16",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030100",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/100",
  abstract =     "In the last decade, digital twin (DT) technology has
                 received considerable attention across various domains,
                 such as manufacturing, smart healthcare, and smart
                 cities. The digital twin represents a digital
                 representation of a physical entity, object, system, or
                 process. Although it is relatively new in the
                 agricultural domain, it has gained increasing attention
                 recently. Recent reviews of DTs show that this
                 technology has the potential to revolutionise
                 agriculture management and activities. It can also
                 provide numerous benefits to all agricultural
                 stakeholders, including farmers, agronomists,
                 researchers, and others, in terms of making decisions
                 on various agricultural processes. In smart crop
                 farming, DTs help simulate various farming tasks like
                 irrigation, fertilisation, nutrient management, and
                 pest control, as well as access real-time data and
                 guide farmers through `what-if' scenarios. By utilising
                 the latest technologies, such as cloud--fog--edge
                 computing, multi-agent systems, and the semantic web,
                 farmers can access real-time data and analytics. This
                 enables them to make accurate decisions about
                 optimising their processes and improving efficiency.
                 This paper presents a proposed architectural framework
                 for DTs, exploring various potential application
                 scenarios that integrate this architecture. It also
                 analyses the benefits and challenges of implementing
                 this technology in agricultural environments.
                 Additionally, we investigate how cloud--fog--edge
                 computing contributes to developing decentralised,
                 real-time systems essential for effective management
                 and monitoring in agriculture.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Quarati:2024:LOG,
  author =       "Alfonso Quarati and Riccardo Albertoni",
  title =        "Linked Open Government Data: Still a Viable Option for
                 Sharing and Integrating Public Data?",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "99",
  day =          "15",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030099",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/99",
  abstract =     "Linked Data (LD) principles, when applied to Open
                 Government Data (OGD), aim to make government data
                 accessible and interconnected, unlocking its full
                 potential and facilitating widespread reuse. As a
                 modular and scalable solution to fragmented government
                 data, Linked Open Government Data (LOGD) improve
                 citizens' understanding of government functions while
                 promoting greater data interoperability, ultimately
                 leading to more efficient government processes.
                 However, despite promising developments in the early
                 2010s, including the release of LOGD datasets by some
                 government agencies, and studies and methodological
                 proposals by numerous scholars, a cursory examination
                 of government websites and portals suggests that
                 interest in this technology has gradually waned. Given
                 the initial expectations surrounding LOGD, this paper
                 goes beyond a superficial analysis and provides a
                 deeper insight into the evolution of interest in LOGD
                 by raising questions about the extent to which the
                 dream of LD has influenced the reality of OGD and
                 whether it remains sustainable.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{BinSaif:2024:ESD,
  author =       "Muhammad {Bin Saif} and Sara Migliorini and Fausto
                 Spoto",
  title =        "Efficient and Secure Distributed Data Storage and
                 Retrieval Using Interplanetary File System and
                 Blockchain",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "98",
  day =          "15",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030098",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/98",
  abstract =     "Blockchain technology has been successfully applied in
                 recent years to promote the immutability, traceability,
                 and authenticity of previously collected and stored
                 data. However, the amount of data stored in the
                 blockchain is usually limited for economic and
                 technological issues. Namely, the blockchain usually
                 stores only a fingerprint of data, such as the hash of
                 data, while full, raw information is stored off-chain.
                 This is generally enough to guarantee immutability and
                 traceability, but misses to support another important
                 property, that is, data availability. This is
                 particularly true when a traditional, centralized
                 database is chosen for off-chain storage. For this
                 reason, many proposals try to properly combine
                 blockchain with decentralized IPFS storage. However,
                 the storage of data on IPFS could pose some privacy
                 problems. This paper proposes a solution that properly
                 combines blockchain, IPFS, and encryption techniques to
                 guarantee immutability, traceability, availability, and
                 data privacy.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{LeuchAlencar:2024:DFI,
  author =       "Ancilon {Leuch Alencar} and Marcelo {Dornbusch Lopes}
                 and Anita Maria {da Rocha Fernandes} and Julio Cesar
                 {Santos dos Anjos} and Juan Francisco {De Paz Santana}
                 and Valderi Reis {Quietinho Leithardt}",
  title =        "Detection of Forged Images Using a Combination of
                 Passive Methods Based on Neural Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "97",
  day =          "14",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030097",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/97",
  abstract =     "In the current era of social media, the proliferation
                 of images sourced from unreliable origins underscores
                 the pressing need for robust methods to detect forged
                 content, particularly amidst the rapid evolution of
                 image manipulation technologies. Existing literature
                 delineates two primary approaches to image manipulation
                 detection: active and passive. Active techniques
                 intervene preemptively, embedding structures into
                 images to facilitate subsequent authenticity
                 verification, whereas passive methods analyze image
                 content for traces of manipulation. This study presents
                 a novel solution to image manipulation detection by
                 leveraging a multi-stream neural network architecture.
                 Our approach harnesses three convolutional neural
                 networks (CNNs) operating on distinct data streams
                 extracted from the original image. We have developed a
                 solution based on two passive detection methodologies.
                 The system utilizes two separate streams to extract
                 specific data subsets, while a third stream processes
                 the unaltered image. Each net independently processes
                 its respective data stream, capturing diverse facets of
                 the image. The outputs from these nets are then fused
                 through concatenation to ascertain whether the image
                 has undergone manipulation, yielding a comprehensive
                 detection framework surpassing the efficacy of its
                 constituent methods. Our work introduces a unique
                 dataset derived from the fusion of four publicly
                 available datasets, featuring organically manipulated
                 images that closely resemble real-world scenarios. This
                 dataset offers a more authentic representation than
                 other state-of-the-art methods that use algorithmically
                 generated datasets based on image patches. By
                 encompassing genuine manipulation scenarios, our
                 dataset enhances the model's ability to generalize
                 across varied manipulation techniques, thereby
                 improving its performance in real-world settings. After
                 training, the merged approach obtained an accuracy of
                 89.59\% in the set of validation images, significantly
                 higher than the model trained with only unaltered
                 images, which obtained 78.64\%, and the two other
                 models trained using images with a feature selection
                 method applied to enhance inconsistencies that obtained
                 68.02\% for Error-Level Analysis images and 50.70\% for
                 the method using Discrete Wavelet Transform. Moreover,
                 our proposed approach exhibits reduced accuracy
                 variance compared to alternative models, underscoring
                 its stability and robustness across diverse datasets.
                 The approach outlined in this work needs to provide
                 information about the specific location or type of
                 tempering, which limits its practical applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Xing:2024:MIS,
  author =       "Mengchi Xing and Haojiang Deng and Rui Han",
  title =        "A Method for {5G--ICN} Seamless Mobility Support Based
                 on Router Buffered Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "96",
  day =          "13",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030096",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/96",
  abstract =     "The 5G core network adopts a Control and User Plane
                 Separation (CUPS) architecture to meet the challenges
                 of low-latency business requirements. In this
                 architecture, a balance between management costs and
                 User Experience (UE) is achieved by moving User Plane
                 Function (UPF) to the edge of the network. However,
                 cross-UPF handover during communication between the UE
                 and the remote server will cause TCP/IP session
                 interruption and affect continuity of delay-sensitive
                 real-time communication continuity. Information-Centric
                 Networks (ICNs) separate identity and location, and
                 their ability to route based on identity can
                 effectively handle mobility. Therefore, based on the
                 5G-ICN architecture, we propose a seamless mobility
                 support method based on router buffered data (BDMM),
                 making full use of the ICN's identity-based routing
                 capabilities to solve the problem of UE cross-UPF
                 handover affecting business continuity. BDMM also uses
                 the ICN router data buffering capabilities to reduce
                 packet loss during handovers. We design a dynamic
                 buffer resource allocation strategy (DBRAS) that can
                 adjust the buffer resource allocation results in time
                 according to network traffic changes and business types
                 to solve the problem of unreasonable buffer resource
                 allocation. Finally, experimental results show that our
                 method outperforms other methods in terms of average
                 packet delay, weighted average packet loss rate, and
                 network overhead. In addition, our method also has good
                 performance in average handover delay.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lai:2024:PFL,
  author =       "Ying-Hsun Lai and Shin-Yeh Chen and Wen-Chi Chou and
                 Hua-Yang Hsu and Han-Chieh Chao",
  title =        "Personalized Federated Learning with Adaptive Feature
                 Extraction and Category Prediction in Non-{IID}
                 Datasets",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "95",
  day =          "11",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030095",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/95",
  abstract =     "Federated learning trains a neural network model using
                 the client's data to maintain the benefits of
                 centralized model training while maintaining their
                 privacy. However, if the client data are not
                 independently and identically distributed (non-IID)
                 because of different environments, the accuracy of the
                 model may suffer from client drift during training
                 owing to discrepancies in each client's data. This
                 study proposes a personalized federated learning
                 algorithm based on the concept of multitask learning to
                 divide each client model into two layers: a feature
                 extraction layer and a category prediction layer. The
                 feature extraction layer maps the input data to a
                 low-dimensional feature vector space. Furthermore, the
                 parameters of the neural network are aggregated with
                 those of other clients using an adaptive method. The
                 category prediction layer maps low-dimensional feature
                 vectors to the label sample space, with its parameters
                 remaining unaffected by other clients to maintain
                 client uniqueness. The proposed personalized federated
                 learning method produces faster learning model
                 convergence rates and higher accuracy rates for the
                 non-IID datasets in our experiments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yao:2024:DIO,
  author =       "Yu Yao and Quan Qian",
  title =        "Dynamic Industrial Optimization: a Framework
                 Integrates Online Machine Learning for Processing
                 Parameters Design",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "94",
  day =          "10",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030094",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/94",
  abstract =     "We develop the online process parameter design (OPPD)
                 framework for efficiently handling streaming data
                 collected from industrial automation equipment. This
                 framework integrates online machine learning, concept
                 drift detection and Bayesian optimization techniques.
                 Initially, concept drift detection mitigates the impact
                 of anomalous data on model updates. Data without
                 concept drift are used for online model training and
                 updating, enabling accurate predictions for the next
                 processing cycle. Bayesian optimization is then
                 employed for inverse optimization and process parameter
                 design. Within OPPD, we introduce the online
                 accelerated support vector regression (OASVR) algorithm
                 for enhanced computational efficiency and model
                 accuracy. OASVR simplifies support vector regression,
                 boosting both speed and durability. Furthermore, we
                 incorporate a dynamic window mechanism to regulate the
                 training data volume for adapting to real-time demands
                 posed by diverse online scenarios. Concept drift
                 detection uses the EI-kMeans algorithm, and the
                 Bayesian inverse design employs an upper confidence
                 bound approach with an adaptive learning rate. Applied
                 to single-crystal fabrication, the OPPD framework
                 outperforms other models, with an RMSE of 0.12, meeting
                 precision demands in production.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Almudayni:2024:IIM,
  author =       "Ziyad Almudayni and Ben Soh and Alice Li",
  title =        "{IMBA}: {IoT}-Mist Bat-Inspired Algorithm for
                 Optimising Resource Allocation in {IoT} Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "93",
  day =          "08",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030093",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/93",
  abstract =     "The advent of the Internet of Things (IoT) has
                 revolutionised our interaction with the environment,
                 facilitating seamless connections among sensors,
                 actuators, and humans. Efficient task scheduling stands
                 as a cornerstone in maximising resource utilisation and
                 ensuring timely task execution in IoT systems. The
                 implementation of efficient task scheduling
                 methodologies can yield substantial enhancements in
                 productivity and cost-effectiveness for IoT
                 infrastructures. To that end, this paper presents the
                 IoT-mist bat-inspired algorithm (IMBA), designed
                 specifically to optimise resource allocation in IoT
                 environments. IMBA's efficacy lies in its ability to
                 elevate user service quality through enhancements in
                 task completion rates, load distribution, network
                 utilisation, processing time, and power efficiency.
                 Through comparative analysis, IMBA demonstrates
                 superiority over traditional methods, such as fuzzy
                 logic and round-robin algorithms, across all
                 performance metrics.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Giannakoulopoulos:2024:UEF,
  author =       "Andreas Giannakoulopoulos and Minas Pergantis and
                 Aristeidis Lamprogeorgos",
  title =        "User Experience, Functionality and Aesthetics
                 Evaluation in an Academic Multi-Site {Web} Ecosystem",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "92",
  day =          "08",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030092",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/92",
  abstract =     "The present study focuses on using qualitative and
                 quantitative data to evaluate the functionality, user
                 experience (UX), and aesthetic approach offered by an
                 academic multi-site Web ecosystem consisting of
                 multiple interconnected websites. Large entities in
                 various industry fields often have the need for an
                 elaborate Web presence. In an effort to address the
                 challenges posed by this need specifically in the field
                 of academia, the authors developed, over a period of
                 many years, a multi-site ecosystem within the Ionian
                 University, which focuses on interconnectivity and a
                 collaborative approach to academic content management.
                 This system, known as ``Publish@Ionio'', uses a
                 singular content management infrastructure to allow for
                 the creation of content for different websites that
                 share both information and resources while at the same
                 time allowing for individual variations in both
                 functionality and aesthetics. The ecosystem was
                 evaluated through quantitative data from its operation
                 and qualitative feedback from a focus-group interview
                 with experts, including website editors and
                 administrative staff. The collected data were used to
                 assess the strengths and weaknesses of the multi-site
                 approach based on the actions and needs of the
                 individuals in charge of generating content. The study
                 led to conclusions on the advantages that
                 interoperability offers in terms of digital and human
                 resource management, the benefits of a unified
                 aesthetic approach that allows for variability, and the
                 necessity of collaborative content management tools
                 that are tailored to the content's nature.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Femminella:2024:IIT,
  author =       "Mauro Femminella and Gianluca Reali",
  title =        "Implementing {Internet of Things} Service Platforms
                 with Network Function Virtualization Serverless
                 Technologies",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "91",
  day =          "08",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030091",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/91",
  abstract =     "The need for adaptivity and scalability in
                 telecommunication systems has led to the introduction
                 of a software-based approach to networking, in which
                 network functions are virtualized and implemented in
                 software modules, based on network function
                 virtualization (NFV) technologies. The growing demand
                 for low latency, efficiency, flexibility and security
                 has placed some limitations on the adoption of these
                 technologies, due to some problems of traditional
                 virtualization solutions. However, the introduction of
                 lightweight virtualization approaches is paving the way
                 for new and better infrastructures for implementing
                 network functions. This article discusses these new
                 virtualization solutions and shows a proposal, based on
                 serverless computing, that uses them to implement
                 container-based virtualized network functions for the
                 delivery of advanced Internet of Things (IoT) services.
                 It includes open source software components to
                 implement both the virtualization layer, implemented
                 through Firecracker, and the runtime environment, based
                 on Kata containers. A set of experiments shows that the
                 proposed approach is fast, in order to boost new
                 network functions, and more efficient than some
                 baseline solutions, with minimal resource footprint.
                 Therefore, it is an excellent candidate to implement
                 NFV functions in the edge deployment of serverless
                 services for the IoT.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Toivonen:2024:VAH,
  author =       "Heidi Toivonen and Francesco Lelli",
  title =        "The Varieties of Agency in Human--Smart Device
                 Relationships: The Four Agency Profiles",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "90",
  day =          "07",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030090",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/90",
  abstract =     "This paper investigates how users of smart devices
                 attribute agency both to themselves and to their
                 devices. Statistical analyses, tag cloud analysis, and
                 sentiment analysis were applied on survey data
                 collected from 587 participants. As a result of a
                 preliminary factorial analysis, two independent
                 constructs of agency emerged: (i) user agency and (ii)
                 device agency. These two constructs received further
                 support from a sentiment analysis and a tag cloud
                 analysis conducted on the written responses provided in
                 a survey. We also studied how user agency and device
                 agency relate to various background variables, such as
                 the user's professional knowledge of smart devices. We
                 present a new preliminary model, where the two agency
                 constructs are used to conceptualize agency in
                 human--smart device relationships in a matrix composed
                 of a controller, collaborator, detached, and victim.
                 Our model with the constructs of user agency and device
                 agency fosters a richer understanding of the users'
                 experiences in their interactions with devices. The
                 results could facilitate designing interfaces that
                 better take into account the users' views of their own
                 capabilities as well as the capacities of their
                 devices; the findings can assist in tackling challenges
                 such as the feeling of lacking agency experienced by
                 technologically savvy users.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{ElDebeiki:2024:APP,
  author =       "Mostafa {El Debeiki} and Saba Al-Rubaye and Adolfo
                 Perrusqu{\'\i}a and Christopher Conrad and Juan
                 Alejandro Flores-Campos",
  title =        "An Advanced Path Planning and {UAV} Relay System:
                 Enhancing Connectivity in Rural Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "89",
  day =          "06",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030089",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/89",
  abstract =     "The use of unmanned aerial vehicles (UAVs) is
                 increasing in transportation applications due to their
                 high versatility and maneuverability in complex
                 environments. Search and rescue is one of the most
                 challenging applications of UAVs due to the
                 non-homogeneous nature of the environmental and
                 communication landscapes. In particular, mountainous
                 areas pose difficulties due to the loss of connectivity
                 caused by large valleys and the volumes of hazardous
                 weather. In this paper, the connectivity issue in
                 mountainous areas is addressed using a path planning
                 algorithm for UAV relay. The approach is based on two
                 main phases: (1) the detection of areas of interest
                 where the connectivity signal is poor, and (2) an
                 energy-aware and resilient path planning algorithm that
                 maximizes the coverage links. The approach uses a
                 viewshed analysis to identify areas of visibility
                 between the areas of interest and the cell-towers. This
                 allows the construction of a blockage map that prevents
                 the UAV from passing through areas with no coverage,
                 whilst maximizing the coverage area under energy
                 constraints and hazardous weather. The proposed
                 approach is validated under open-access datasets of
                 mountainous zones, and the obtained results confirm the
                 benefits of the proposed approach for communication
                 networks in remote and challenging environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lightbody:2024:DIS,
  author =       "Dominic Lightbody and Duc-Minh Ngo and Andriy Temko
                 and Colin C. Murphy and Emanuel Popovici",
  title =        "{Dragon\_Pi}: {IoT} Side-Channel Power Data Intrusion
                 Detection Dataset and Unsupervised Convolutional
                 Autoencoder for Intrusion Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "88",
  day =          "05",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030088",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/88",
  abstract =     "The growth of the Internet of Things (IoT) has led to
                 a significant rise in cyber attacks and an expanded
                 attack surface for the average consumer. In order to
                 protect consumers and infrastructure, research into
                 detecting malicious IoT activity must be of the highest
                 priority. Security research in this area has two key
                 issues: the lack of datasets for training artificial
                 intelligence (AI)-based intrusion detection models and
                 the fact that most existing datasets concentrate only
                 on one type of network traffic. Thus, this study
                 introduces Dragon\_Pi, an intrusion detection dataset
                 designed for IoT devices based on side-channel power
                 consumption data. Dragon\_Pi comprises a collection of
                 normal and under-attack power consumption traces from
                 separate testbeds featuring a DragonBoard 410c and a
                 Raspberry Pi. Dragon\_Slice is trained on this dataset;
                 it is an unsupervised convolutional autoencoder (CAE)
                 trained exclusively on held-out normal slices from
                 Dragon\_Pi for anomaly detection. The Dragon\_Slice
                 network has two iterations in this study. The original
                 achieves 0.78 AUC without post-processing and 0.876 AUC
                 with post-processing. A second iteration of
                 Dragon\_Slice, utilising dropout to further impede the
                 CAE's ability to reconstruct anomalies, outperforms the
                 original network with a raw AUC of 0.764 and a
                 post-processed AUC of 0.89.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Warch:2024:ATG,
  author =       "Dominik Warch and Patrick Stellbauer and Pascal Neis",
  title =        "Advanced Techniques for Geospatial Referencing in
                 Online Media Repositories",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "87",
  day =          "01",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030087",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/87",
  abstract =     "In the digital transformation era, video media
                 libraries' untapped potential is immense, restricted
                 primarily by their non-machine-readable nature and
                 basic search functionalities limited to standard
                 metadata. This study presents a novel multimodal
                 methodology that utilizes advances in artificial
                 intelligence, including neural networks, computer
                 vision, and natural language processing, to extract and
                 geocode geospatial references from videos. Leveraging
                 the geospatial information from videos enables semantic
                 searches, enhances search relevance, and allows for
                 targeted advertising, particularly on mobile platforms.
                 The methodology involves a comprehensive process,
                 including data acquisition from ARD Mediathek, image
                 and text analysis using advanced machine learning
                 models, and audio and subtitle processing with
                 state-of-the-art linguistic models. Despite challenges
                 like model interpretability and the complexity of
                 geospatial data extraction, this study's findings
                 indicate significant potential for advancing the
                 precision of spatial data analysis within video
                 content, promising to enrich media libraries with more
                 navigable, contextually rich content. This advancement
                 has implications for user engagement, targeted
                 services, and broader urban planning and cultural
                 heritage applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Loh:2024:THS,
  author =       "Peter K. K. Loh and Aloysius Z. Y. Lee and Vivek
                 Balachandran",
  title =        "Towards a Hybrid Security Framework for Phishing
                 Awareness Education and Defense",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "86",
  day =          "01",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030086",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/86",
  abstract =     "The rise in generative Artificial Intelligence (AI)
                 has led to the development of more sophisticated
                 phishing email attacks, as well as an increase in
                 research on using AI to aid the detection of these
                 advanced attacks. Successful phishing email attacks
                 severely impact businesses, as employees are usually
                 the vulnerable targets. Defense against such attacks,
                 therefore, requires realizing defense along both
                 technological and human vectors. Security hardening
                 research work along the technological vector is few and
                 focuses mainly on the use of machine learning and
                 natural language processing to distinguish between
                 machine- and human-generated text. Common existing
                 approaches to harden security along the human vector
                 consist of third-party organized training programmes,
                 the content of which needs to be updated over time.
                 There is, to date, no reported approach that provides
                 both phishing attack detection and progressive end-user
                 training. In this paper, we present our contribution,
                 which includes the design and development of an
                 integrated approach that employs AI-assisted and
                 generative AI platforms for phishing attack detection
                 and continuous end-user education in a hybrid security
                 framework. This framework supports
                 scenario-customizable and evolving user education in
                 dealing with increasingly advanced phishing email
                 attacks. The technological design and functional
                 details for both platforms are presented and discussed.
                 Performance tests showed that the phishing attack
                 detection sub-system using the Convolutional Neural
                 Network (CNN) deep learning model architecture achieved
                 the best overall results: above 94\% accuracy, above
                 95\% precision, and above 94\% recall.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alrubayyi:2024:STP,
  author =       "Hadeel Alrubayyi and Moudy Sharaf Alshareef and
                 Zunaira Nadeem and Ahmed M. Abdelmoniem and Mona
                 Jaber",
  title =        "Security Threats and Promising Solutions Arising from
                 the Intersection of {AI} and {IoT}: a Study of {IoMT}
                 and {IoET} Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "85",
  day =          "29",
  month =        feb,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030085",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/85",
  abstract =     "The hype of the Internet of Things as an enabler for
                 intelligent applications and related promise for
                 ushering accessibility, efficiency, and quality of
                 service is met with hindering security and data privacy
                 concerns. It follows that such IoT systems, which are
                 empowered by artificial intelligence, need to be
                 investigated with cognisance of security threats and
                 mitigation schemes that are tailored to their specific
                 constraints and requirements. In this work, we present
                 a comprehensive review of security threats in IoT and
                 emerging countermeasures with a particular focus on
                 malware and man-in-the-middle attacks. Next, we
                 elaborate on two use cases: the Internet of Energy
                 Things and the Internet of Medical Things. Innovative
                 artificial intelligence methods for automating energy
                 theft detection and stress levels are first detailed,
                 followed by an examination of contextual security
                 threats and privacy breach concerns. An artificial
                 immune system is employed to mitigate the risk of
                 malware attacks, differential privacy is proposed for
                 data protection, and federated learning is harnessed to
                 reduce data exposure.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Harnes:2024:SAT,
  author =       "H{\aa}kon Harnes and Donn Morrison",
  title =        "{SoK}: Analysis Techniques for {WebAssembly}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "84",
  day =          "29",
  month =        feb,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030084",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/84",
  abstract =     "WebAssembly is a low-level bytecode language that
                 enables high-level languages like C, C++, and Rust to
                 be executed in the browser at near-native performance.
                 In recent years, WebAssembly has gained widespread
                 adoption and is now natively supported by all modern
                 browsers. Despite its benefits, WebAssembly has
                 introduced significant security challenges, primarily
                 due to vulnerabilities inherited from memory-unsafe
                 source languages. Moreover, the use of WebAssembly
                 extends beyond traditional web applications to smart
                 contracts on blockchain platforms, where
                 vulnerabilities have led to significant financial
                 losses. WebAssembly has also been used for malicious
                 purposes, like cryptojacking, where website visitors'
                 hardware resources are used for crypto mining without
                 their consent. To address these issues, several
                 analysis techniques for WebAssembly binaries have been
                 proposed. This paper presents a systematic review of
                 these analysis techniques, focusing on vulnerability
                 analysis, cryptojacking detection, and smart contract
                 security. The analysis techniques are categorized into
                 static, dynamic, and hybrid methods, evaluating their
                 strengths and weaknesses based on quantitative data.
                 Our findings reveal that static techniques are
                 efficient but may struggle with complex binaries, while
                 dynamic techniques offer better detection at the cost
                 of increased overhead. Hybrid approaches, which merge
                 the strengths of static and dynamic methods, are not
                 extensively used in the literature and emerge as a
                 promising direction for future research. Lastly, this
                 paper identifies potential future research directions
                 based on the state of the current literature.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Saleem:2024:EET,
  author =       "Gulshan Saleem and Usama Ijaz Bajwa and Rana Hammad
                 Raza and Fan Zhang",
  title =        "Edge-Enhanced {TempoFuseNet}: a Two-Stream Framework
                 for Intelligent Multiclass Video Anomaly Recognition in
                 {5G} and {IoT} Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "83",
  day =          "29",
  month =        feb,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030083",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/83",
  abstract =     "Surveillance video analytics encounters unprecedented
                 challenges in 5G and IoT environments, including
                 complex intra-class variations, short-term and
                 long-term temporal dynamics, and variable video
                 quality. This study introduces Edge-Enhanced
                 TempoFuseNet, a cutting-edge framework that
                 strategically reduces spatial resolution to allow the
                 processing of low-resolution images. A dual upscaling
                 methodology based on bicubic interpolation and an
                 encoder--bank--decoder configuration is used for
                 anomaly classification. The two-stream architecture
                 combines the power of a pre-trained Convolutional
                 Neural Network (CNN) for spatial feature extraction
                 from RGB imagery in the spatial stream, while the
                 temporal stream focuses on learning short-term temporal
                 characteristics, reducing the computational burden of
                 optical flow. To analyze long-term temporal patterns,
                 the extracted features from both streams are combined
                 and routed through a Gated Recurrent Unit (GRU) layer.
                 The proposed framework (TempoFuseNet) outperforms the
                 encoder--bank--decoder model in terms of performance
                 metrics, achieving a multiclass macro average accuracy
                 of 92.28\%, an F1-score of 69.29\%, and a false
                 positive rate of 4.41\%. This study presents a
                 significant advancement in the field of video anomaly
                 recognition and provides a comprehensive solution to
                 the complex challenges posed by real-world surveillance
                 scenarios in the context of 5G and IoT.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Xu:2024:MLS,
  author =       "Hanyue Xu and Kah Phooi Seng and Jeremy Smith and Li
                 Minn Ang",
  title =        "Multi-Level Split Federated Learning for Large-Scale
                 {AIoT} System Based on Smart Cities",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "82",
  day =          "28",
  month =        feb,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030082",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/82",
  abstract =     "In the context of smart cities, the integration of
                 artificial intelligence (AI) and the Internet of Things
                 (IoT) has led to the proliferation of AIoT systems,
                 which handle vast amounts of data to enhance urban
                 infrastructure and services. However, the collaborative
                 training of deep learning models within these systems
                 encounters significant challenges, chiefly due to data
                 privacy concerns and dealing with communication latency
                 from large-scale IoT devices. To address these issues,
                 multi-level split federated learning (multi-level SFL)
                 has been proposed, merging the benefits of split
                 learning (SL) and federated learning (FL). This
                 framework introduces a novel multi-level aggregation
                 architecture that reduces communication delays,
                 enhances scalability, and addresses system and
                 statistical heterogeneity inherent in large AIoT
                 systems with non-IID data distributions. The
                 architecture leverages the Message Queuing Telemetry
                 Transport (MQTT) protocol to cluster IoT devices
                 geographically and employs edge and fog computing
                 layers for initial model parameter aggregation.
                 Simulation experiments validate that the multi-level
                 SFL outperforms traditional SFL by improving model
                 accuracy and convergence speed in large-scale, non-IID
                 environments. This paper delineates the proposed
                 architecture, its workflow, and its advantages in
                 enhancing the robustness and scalability of AIoT
                 systems in smart cities while preserving data
                 privacy.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2024:SEE,
  author =       "Yushan Li and Satoshi Fujita",
  title =        "A Synergistic {Elixir-EDA-MQTT} Framework for Advanced
                 Smart Transportation Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "81",
  day =          "28",
  month =        feb,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030081",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/81",
  abstract =     "This paper proposes a novel event-driven architecture
                 for enhancing edge-based vehicular systems within smart
                 transportation. Leveraging the inherent real-time,
                 scalable, and fault-tolerant nature of the Elixir
                 language, we present an innovative architecture
                 tailored for edge computing. This architecture employs
                 MQTT for efficient event transport and utilizes
                 Elixir's lightweight concurrency model for distributed
                 processing. Robustness and scalability are further
                 ensured through the EMQX broker. We demonstrate the
                 effectiveness of our approach through two smart
                 transportation case studies: a traffic light system for
                 dynamically adjusting signal timing, and a cab dispatch
                 prototype designed for high concurrency and real-time
                 data processing. Evaluations on an Apple M1 chip reveal
                 consistently low latency responses below 5 ms and
                 efficient multicore utilization under load. These
                 findings showcase the system's robust throughput and
                 multicore programming capabilities, confirming its
                 suitability for real-time, distributed edge computing
                 applications in smart transportation. Therefore, our
                 work suggests that integrating Elixir with an
                 event-driven model represents a promising approach for
                 developing scalable, responsive applications in edge
                 computing. This opens avenues for further exploration
                 and adoption of Elixir in addressing the evolving
                 demands of edge-based smart transportation systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kim:2024:TDL,
  author =       "Haedam Kim and Suhyun Park and Hyemin Hong and Jieun
                 Park and Seongmin Kim",
  title =        "A Transferable Deep Learning Framework for Improving
                 the Accuracy of {Internet of Things} Intrusion
                 Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "80",
  day =          "28",
  month =        feb,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030080",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/80",
  abstract =     "As the size of the IoT solutions and services market
                 proliferates, industrial fields utilizing IoT devices
                 are also diversifying. However, the proliferation of
                 IoT devices, often intertwined with users' personal
                 information and privacy, has led to a continuous surge
                 in attacks targeting these devices. However,
                 conventional network-level intrusion detection systems
                 with pre-defined rulesets are gradually losing their
                 efficacy due to the heterogeneous environments of IoT
                 ecosystems. To address such security concerns,
                 researchers have utilized ML-based network-level
                 intrusion detection techniques. Specifically, transfer
                 learning has been dedicated to identifying unforeseen
                 malicious traffic in IoT environments based on
                 knowledge distillation from the rich source domain data
                 sets. Nevertheless, since most IoT devices operate in
                 heterogeneous but small-scale environments, such as
                 home networks, selecting adequate source domains for
                 learning proves challenging. This paper introduces a
                 framework designed to tackle this issue. In instances
                 where assessing an adequate data set through
                 pre-learning using transfer learning is non-trivial,
                 our proposed framework advocates the selection of a
                 data set as the source domain for transfer learning.
                 This selection process aims to determine the
                 appropriateness of implementing transfer learning,
                 offering the best practice in such scenarios. Our
                 evaluation demonstrates that the proposed framework
                 successfully chooses a fitting source domain data set,
                 delivering the highest accuracy.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Pellegrino:2024:MHL,
  author =       "Mattia Pellegrino and Gianfranco Lombardo and George
                 Adosoglou and Stefano Cagnoni and Panos M. Pardalos and
                 Agostino Poggi",
  title =        "A Multi-Head {LSTM} Architecture for Bankruptcy
                 Prediction with Time Series Accounting Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "79",
  day =          "27",
  month =        feb,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030079",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/79",
  abstract =     "With the recent advances in machine learning (ML),
                 several models have been successfully applied to
                 financial and accounting data to predict the likelihood
                 of companies' bankruptcy. However, time series have
                 received little attention in the literature, with a
                 lack of studies on the application of deep learning
                 sequence models such as Recurrent Neural Networks
                 (RNNs) and the recent Attention-based models in
                 general. In this research work, we investigated the
                 application of Long Short-Term Memory (LSTM) networks
                 to exploit time series of accounting data for
                 bankruptcy prediction. The main contributions of our
                 work are the following: (a) We proposed a multi-head
                 LSTM that models each financial variable in a time
                 window independently and compared it with a
                 single-input LSTM and other traditional ML models. The
                 multi-head LSTM outperformed all the other models. (b)
                 We identified the optimal time series length for
                 bankruptcy prediction to be equal to 4 years of
                 accounting data. (c) We made public the dataset we used
                 for the experiments which includes data from 8262
                 different public companies in the American stock market
                 generated in the period between 1999 and 2018.
                 Furthermore, we proved the efficacy of the multi-head
                 LSTM model in terms of fewer false positives and the
                 better division of the two classes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Salariseddigh:2024:DIF,
  author =       "Mohammad Javad Salariseddigh and Ons Dabbabi and
                 Christian Deppe and Holger Boche",
  title =        "Deterministic {$K$}-Identification for Future
                 Communication Networks: The Binary Symmetric Channel
                 Results",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "78",
  day =          "26",
  month =        feb,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030078",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/78",
  abstract =     "Numerous applications of the Internet of Things (IoT)
                 feature an event recognition behavior where the
                 established Shannon capacity is not authorized to be
                 the central performance measure. Instead, the
                 identification capacity for such systems is considered
                 to be an alternative metric, and has been developed in
                 the literature. In this paper, we develop deterministic
                 K-identification (DKI) for the binary symmetric channel
                 (BSC) with and without a Hamming weight constraint
                 imposed on the codewords. This channel may be of use
                 for IoT in the context of smart system technologies,
                 where sophisticated communication models can be reduced
                 to a BSC for the aim of studying basic information
                 theoretical properties. We derive inner and outer
                 bounds on the DKI capacity of the BSC when the size of
                 the goal message set K may grow in the codeword length
                 n. As a major observation, we find that, for
                 deterministic encoding, assuming that K grows
                 exponentially in n, i.e., K=2n{\kappa}, where {\kappa}
                 is the identification goal rate, then the number of
                 messages that can be accurately identified grows
                 exponentially in n, i.e., 2nR, where R is the DKI
                 coding rate. Furthermore, the established inner and
                 outer bound regions reflects impact of the input
                 constraint (Hamming weight) and the channel statistics,
                 i.e., the cross-over probability.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Almani:2024:EVV,
  author =       "Dimah Almani and Tim Muller and Xavier Carpent and
                 Takahito Yoshizawa and Steven Furnell",
  title =        "Enabling Vehicle-to-Vehicle Trust in Rural Areas: an
                 Evaluation of a Pre-Signature Scheme for
                 Infrastructure-Limited Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "3",
  pages =        "77",
  day =          "26",
  month =        feb,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16030077",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Wed Apr 10 09:47:36 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/3/77",
  abstract =     "This research investigates the deployment and
                 effectiveness of the novel Pre-Signature scheme,
                 developed to allow for up-to-date reputation being
                 available in Vehicle-to-Vehicle (V2V) communications in
                 rural landscapes, where the communications
                 infrastructure is limited. We discuss how existing
                 standards and specifications can be adjusted to
                 incorporate the Pre-Signature scheme to disseminate
                 reputation. Addressing the unique challenges posed by
                 sparse or irregular Roadside Units (RSUs) coverage in
                 these areas, the study investigates the implications of
                 such environmental factors on the integrity and
                 reliability of V2V communication networks. Using the
                 widely used SUMO traffic simulation tool, we create and
                 simulate real-world rural scenarios. We have conducted
                 an in-depth performance evaluation of the Pre-Signature
                 scheme under the typical infrastructural limitations
                 encountered in rural scenarios. Our findings
                 demonstrate the scheme's usefulness in scenarios with
                 variable or constrained RSUs access. Furthermore, the
                 relationships between the three variables,
                 communication range, amount of RSUs, and degree of
                 home-to-vehicle connectivity overnight, are studied,
                 offering an exhaustive analysis of the determinants
                 influencing V2V communication efficiency in rural
                 contexts. The important findings are (1) that access to
                 accurate Reputation Values increases with all three
                 variables and (2) the necessity of Pre-Signatures
                 decreases if the amount and range of RSUs increase to
                 high numbers. Together, these findings imply that areas
                 with a low degree of adoption of RSUs (typically rural
                 areas) benefit the most from our approach.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhang:2024:MCM,
  author =       "Bing Zhang and Hui Li and Shuai Zhang and Jing Sun and
                 Ning Wei and Wenhong Xu and Huan Wang",
  title =        "Multi-Constraint and Multi-Policy Path Hopping Active
                 Defense Method Based on {SDN}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "143",
  day =          "22",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040143",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/143",
  abstract =     "Path hopping serves as an active defense mechanism in
                 network security, yet it encounters challenges like a
                 restricted path switching space, the recurrent use of
                 similar paths and vital nodes, a singular triggering
                 mechanism for path switching, and fixed hopping
                 intervals. This paper introduces an active defense
                 method employing multiple constraints and strategies
                 for path hopping. A depth-first search (DFS) traversal
                 is utilized to compute all possible paths between
                 nodes, thereby broadening the path switching space
                 while simplifying path generation complexity.
                 Subsequently, constraints are imposed on residual
                 bandwidth, selection periods, path similitude, and
                 critical nodes to reduce the likelihood of reusing
                 similar paths and crucial nodes. Moreover, two path
                 switching strategies are formulated based on the
                 weights of residual bandwidth and critical nodes, along
                 with the calculation of path switching periods. This
                 facilitates adaptive switching of path hopping paths
                 and intervals, contingent on the network's residual
                 bandwidth threshold, in response to diverse attack
                 scenarios. Simulation outcomes illustrate that this
                 method, while maintaining normal communication
                 performance, expands the path switching space
                 effectively, safeguards against eavesdropping and
                 link-flooding attacks, enhances path switching
                 diversity and unpredictability, and fortifies the
                 network's resilience against malicious attacks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lin:2024:EFO,
  author =       "Hsin-Tung Lin and Chih-Yu Wen",
  title =        "Edge Federated Optimization for Heterogeneous Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "142",
  day =          "22",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040142",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/142",
  abstract =     "This study focuses on optimizing federated learning in
                 heterogeneous data environments. We implement the
                 FedProx and a baseline algorithm (i.e., the FedAvg)
                 with advanced optimization strategies to tackle non-IID
                 data issues in distributed learning. Model freezing and
                 pruning techniques are explored to showcase the
                 effective operations of deep learning models on
                 resource-constrained edge devices. Experimental results
                 show that at a pruning rate of 10\%, the FedProx with
                 structured pruning in the MIT-BIH and ST databases
                 achieved the best F1 scores, reaching 96.01\% and
                 77.81\%, respectively, which achieves a good balance
                 between system efficiency and model accuracy compared
                 to those of the FedProx with the original
                 configuration, reaching F1 scores of 66.12\% and
                 89.90\%, respectively. Similarly, with layer freezing
                 technique, unstructured pruning method, and a pruning
                 rate of 20\%, the FedAvg algorithm effectively balances
                 classification performance and degradation of pruned
                 model accuracy, achieving F1 scores of 88.75\% and
                 72.75\%, respectively, compared to those of the FedAvg
                 with the original configuration, reaching 56.82\% and
                 85.80\%, respectively. By adopting model optimization
                 strategies, a practical solution is developed for
                 deploying complex models in edge federated learning,
                 vital for its efficient implementation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2024:CLA,
  author =       "Zuopeng Li and Hengshuai Ju and Zepeng Ren",
  title =        "Correction: {Li} et al. {A Learning Game-Based
                 Approach to Task-Dependent Edge Resource Allocation.
                 Future Internet 2023, {\bf 15}, 395}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "141",
  day =          "22",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040141",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/141",
  abstract =     "This study focuses on optimizing federated learning in
                 heterogeneous data environments. We implement the
                 FedProx and a baseline algorithm (i.e., the FedAvg)
                 with advanced optimization strategies to tackle non-IID
                 data issues in distributed learning. Model freezing and
                 pruning techniques are explored to showcase the
                 effective operations of deep learning models on
                 resource-constrained edge devices. Experimental results
                 show that at a pruning rate of 10\%, the FedProx with
                 structured pruning in the MIT-BIH and ST databases
                 achieved the best F1 scores, reaching 96.01\% and
                 77.81\%, respectively, which achieves a good balance
                 between system efficiency and model accuracy compared
                 to those of the FedProx with the original
                 configuration, reaching F1 scores of 66.12\% and
                 89.90\%, respectively. Similarly, with layer freezing
                 technique, unstructured pruning method, and a pruning
                 rate of 20\%, the FedAvg algorithm effectively balances
                 classification performance and degradation of pruned
                 model accuracy, achieving F1 scores of 88.75\% and
                 72.75\%, respectively, compared to those of the FedAvg
                 with the original configuration, reaching 56.82\% and
                 85.80\%, respectively. By adopting model optimization
                 strategies, a practical solution is developed for
                 deploying complex models in edge federated learning,
                 vital for its efficient implementation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liu:2024:SSU,
  author =       "Yuze Liu and Weihong Wu and Ying Wang and Jiang Liu
                 and Fan Yang",
  title =        "{SUDC}: Synchronous Update with the Division and
                 Combination of {SRv6} Policy",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "140",
  day =          "22",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040140",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/140",
  abstract =     "With the expansion of network scale, new network
                 services are emerging. Segment Routing over IPv6 (SRv6)
                 can meet the diverse needs of more new services due to
                 its excellent scalability and programmability. In the
                 intelligent 6-Generation (6G) scenario, frequent SRv6
                 Traffic Engineering (TE) policy updates will result in
                 the serious problem of unsynchronized updates across
                 routers. Existing solutions suffer from issues such as
                 long update cycles or large data overhead. To optimize
                 the policy-update process, this paper proposes a scheme
                 called Synchronous Update with the Division and
                 Combination of SRv6 Policy (SUDC). Based on the
                 characteristics of the SRv6 TE policy, SUDC divides the
                 policies and introduces Bit Index Explicit Replication
                 IPv6 Encapsulation (BIERv6) to multicast the policy
                 blocks derived from policy dividing. The contribution
                 of this paper is to propose the policy-dividing and
                 combination mechanism and the policy-dividing
                 algorithm. The simulation results demonstrate that
                 compared with the existing schemes, the update overhead
                 and update cycle of SUDC are reduced by 46.71\% and
                 46.6\%, respectively. The problem of unsynchronized
                 updates across routers has been further improved.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rahman:2024:CRM,
  author =       "Md Motiur Rahman and Deepti Gupta and Smriti Bhatt and
                 Shiva Shokouhmand and Miad Faezipour",
  title =        "A Comprehensive Review of Machine Learning Approaches
                 for Anomaly Detection in Smart Homes: Experimental
                 Analysis and Future Directions",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "139",
  day =          "19",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040139",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/139",
  abstract =     "Detecting anomalies in human activities is
                 increasingly crucial today, particularly in nuclear
                 family settings, where there may not be constant
                 monitoring of individuals' health, especially the
                 elderly, during critical periods. Early anomaly
                 detection can prevent from attack scenarios and
                 life-threatening situations. This task becomes notably
                 more complex when multiple ambient sensors are deployed
                 in homes with multiple residents, as opposed to
                 single-resident environments. Additionally, the
                 availability of datasets containing anomalies
                 representing the full spectrum of abnormalities is
                 limited. In our experimental study, we employed eight
                 widely used machine learning and two deep learning
                 classifiers to identify anomalies in human activities.
                 We meticulously generated anomalies, considering all
                 conceivable scenarios. Our findings reveal that the
                 Gated Recurrent Unit (GRU) excels in accurately
                 classifying normal and anomalous activities, while the
                 na{\"\i}ve Bayes classifier demonstrates relatively
                 poor performance among the ten classifiers considered.
                 We conducted various experiments to assess the impact
                 of different training--test splitting ratios, along
                 with a five-fold cross-validation technique, on the
                 performance. Notably, the GRU model consistently
                 outperformed all other classifiers under both
                 conditions. Furthermore, we offer insights into the
                 computational costs associated with these classifiers,
                 encompassing training and prediction phases. Extensive
                 ablation experiments conducted in this study underscore
                 that all these classifiers can effectively be deployed
                 for anomaly detection in two-resident homes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lemmi:2024:SBE,
  author =       "Laura Lemmi and Carlo Puliafito and Antonio Virdis and
                 Enzo Mingozzi",
  title =        "{SRv6}-Based Edge Service Continuity in {5G} Mobile
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "138",
  day =          "19",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040138",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/138",
  abstract =     "Ensuring compliance with the stringent latency
                 requirements of edge services requires close
                 cooperation between the network and computing
                 components. Within mobile 5G networks, the nomadic
                 behavior of users may impact the performance of edge
                 services, prompting the need for workload migration
                 techniques. These techniques allow services to follow
                 users by moving between edge nodes. This paper
                 introduces an innovative approach for edge service
                 continuity by integrating Segment Routing over IPv6
                 (SRv6) into the 5G core data plane alongside the ETSI
                 multi-access edge computing (MEC) architecture. Our
                 approach maintains compatibility with non-SRv6 5G
                 network components. We use SRv6 for packet steering and
                 Software-Defined Networking (SDN) for dynamic network
                 configuration. Leveraging the SRv6 Network Programming
                 paradigm, we achieve lossless workload migration by
                 implementing a packet buffer as a virtual network
                 function. Our buffer may be dynamically allocated and
                 configured within the network. We test our proposed
                 solution on a small-scale testbed consisting of an Open
                 Network Operating System (ONOS) SDN controller and a
                 core network made of P4 BMv2 switches, emulated using
                 Mininet. A comparison with a non-SRv6 alternative that
                 uses IPv6 routing shows the higher scalability and
                 flexibility of our approach in terms of the number of
                 rules to be installed and time required for
                 configuration.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kampourakis:2024:SDS,
  author =       "Vyron Kampourakis and Georgios Michail Makrakis and
                 Constantinos Kolias",
  title =        "From Seek-and-Destroy to Split-and-Destroy: Connection
                 Partitioning as an Effective Tool against Low-Rate
                 {DoS} Attacks",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "137",
  day =          "19",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040137",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/137",
  abstract =     "Low-rate Denial of Service (LDoS) attacks are today
                 considered one of the biggest threats against modern
                 data centers and industrial infrastructures. Unlike
                 traditional Distributed Denial of Service (DDoS)
                 attacks that are mainly volumetric, LDoS attacks
                 exhibit a very small network footprint, and therefore
                 can easily elude standard detection and defense
                 mechanisms. This work introduces a defense strategy
                 that may prove particularly effective against attacks
                 that are based on long-lived connections, an inherent
                 trait of LDoS attacks. Our approach is based on
                 iteratively partitioning the active connections of a
                 victim server across a number of replica servers, and
                 then re-evaluating the health status of each replica
                 instance. At its core, this approach relies on live
                 migration and containerization technologies. The main
                 advantage of the proposed approach is that it can
                 discover and isolate malicious connections with
                 virtually no information about the type and
                 characteristics of the performed attack. Additionally,
                 while the defense takes place, there is little to no
                 indication of the fact to the attacker. We assess
                 various rudimentary schemes to quantify the scalability
                 of our approach. The results from the simulations
                 indicate that it is possible to save the vast majority
                 of the benign connections (80\%) in less than 5 min.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liu:2024:COB,
  author =       "Yazhi Liu and Pengfei Zhong and Zhigang Yang and Wei
                 Li and Siwei Li",
  title =        "Computation Offloading Based on a Distributed Overlay
                 Network Cache-Sharing Mechanism in Multi-Access Edge
                 Computing",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "136",
  day =          "19",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040136",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/136",
  abstract =     "Multi-access edge computing (MEC) enhances service
                 quality for users and reduces computational overhead by
                 migrating workloads and application data to the network
                 edge. However, current solutions for task offloading
                 and cache replacement in edge scenarios are constrained
                 by factors such as communication bandwidth, wireless
                 network coverage, and limited storage capacity of edge
                 devices, making it challenging to achieve high cache
                 reuse and lower system energy consumption. To address
                 these issues, a framework leveraging cooperative edge
                 servers deployed in wireless access networks across
                 different geographical regions is designed.
                 Specifically, we propose the Distributed Edge Service
                 Caching and Offloading (DESCO) network architecture and
                 design a decentralized resource-sharing algorithm based
                 on consistent hashing, named Cache Chord. Subsequently,
                 based on DESCO and aiming to minimize overall user
                 energy consumption while maintaining user latency
                 constraints, we introduce the real-time computation
                 offloading (RCO) problem and transform RCO into a
                 multi-player static game, prove the existence of Nash
                 equilibrium solutions, and solve it using a
                 multi-dimensional particle swarm optimization
                 algorithm. Finally, simulation results demonstrate that
                 the proposed solution reduces the average energy
                 consumption by over 27\% in the DESCO network compared
                 to existing algorithms.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wilson:2024:BEP,
  author =       "Stanly Wilson and Kwabena Adu-Duodu and Yinhao Li and
                 Ringo Sham and Mohammed Almubarak and Yingli Wang and
                 Ellis Solaiman and Charith Perera and Rajiv Ranjan and
                 Omer Rana",
  title =        "Blockchain-Enabled Provenance Tracking for Sustainable
                 Material Reuse in Construction Supply Chains",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "135",
  day =          "17",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040135",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/135",
  abstract =     "The growing complexity of construction supply chains
                 and the significant impact of the construction industry
                 on the environment demand an understanding of how to
                 reuse and repurpose materials. In response to this
                 critical challenge, research gaps that are significant
                 in promoting material circularity are described.
                 Despite its potential, the use of blockchain technology
                 in construction faces challenges in verifiability,
                 scalability, privacy, and interoperability. We propose
                 a novel multilayer blockchain framework to enhance
                 provenance tracking and data retrieval to enable a
                 reliable audit trail. The framework utilises a
                 privacy-centric solution that combines decentralised
                 and centralised storage, security, and privacy.
                 Furthermore, the framework implements access control to
                 strengthen security and privacy, fostering transparency
                 and information sharing among the stakeholders. These
                 contributions collectively lead to trusted material
                 circularity in a built environment. The implementation
                 framework aims to create a prototype for blockchain
                 applications in construction supply chains.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Jiang:2024:LDT,
  author =       "Yuning Jiang and Wei Wang and Jianguo Ding and Xin Lu
                 and Yanguo Jing",
  title =        "Leveraging Digital Twin Technology for Enhanced
                 Cybersecurity in Cyber--Physical Production Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "134",
  day =          "17",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040134",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/134",
  abstract =     "The convergence of cyber and physical systems through
                 cyber--physical systems (CPSs) has been integrated into
                 cyber--physical production systems (CPPSs), leading to
                 a paradigm shift toward intelligent manufacturing.
                 Despite the transformative benefits that CPPS provides,
                 its increased connectivity exposes manufacturers to
                 cyber-attacks through exploitable vulnerabilities. This
                 paper presents a novel approach to CPPS security
                 protection by leveraging digital twin (DT) technology
                 to develop a comprehensive security model. This model
                 enhances asset visibility and supports prioritization
                 in mitigating vulnerable components through DT-based
                 virtual tuning, providing quantitative assessment
                 results for effective mitigation. Our proposed DT
                 security model also serves as an advanced simulation
                 environment, facilitating the evaluation of CPPS
                 vulnerabilities across diverse attack scenarios without
                 disrupting physical operations. The practicality and
                 effectiveness of our approach are illustrated through
                 its application in a human--robot collaborative
                 assembly system, demonstrating the potential of DT
                 technology.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liu:2024:SDS,
  author =       "Bowen Liu and Qiang Tang",
  title =        "Secure Data Sharing in Federated Learning through
                 Blockchain-Based Aggregation",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "133",
  day =          "15",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040133",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/133",
  abstract =     "In this paper, we explore the realm of federated
                 learning (FL), a distributed machine learning (ML)
                 paradigm, and propose a novel approach that leverages
                 the robustness of blockchain technology. FL, a concept
                 introduced by Google in 2016, allows multiple entities
                 to collaboratively train an ML model without the need
                 to expose their raw data. However, it faces several
                 challenges, such as privacy concerns and malicious
                 attacks (e.g., data poisoning attacks). Our paper
                 examines the existing EIFFeL framework, a protocol for
                 decentralized real-time messaging in continuous
                 integration and delivery pipelines, and introduces an
                 enhanced scheme that leverages the trustworthy nature
                 of blockchain technology. Our scheme eliminates the
                 need for a central server and any other third party,
                 such as a public bulletin board, thereby mitigating the
                 risks associated with the compromise of such third
                 parties.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ahuja:2024:SST,
  author =       "Rohit Ahuja and Sahil Chugh and Raman Singh",
  title =        "{SeedChain}: A Secure and Transparent
                 Blockchain-Driven Framework to Revolutionize the Seed
                 Supply Chain",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "132",
  day =          "15",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040132",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/132",
  abstract =     "Farming is a major sector required for any nation to
                 become self-sustainable. Quality seeds heavily
                 influence the effectiveness of farming. Seeds
                 cultivated by breeders pass through several entities in
                 order to reach farmers. The existing seed supply chain
                 is opaque and intractable, which not only hinders the
                 growth of crops but also makes the life of a farmer
                 miserable. Blockchain has been widely employed to
                 enable fair and secure transactions between farmers and
                 buyers, but concerns related to transparency and
                 traceability in the seed supply chain, counterfeit
                 seeds, middlemen involvement, and inefficient processes
                 in the agricultural ecosystem have not received enough
                 attention. To address these concerns, a
                 blockchain-based solution is proposed that brings
                 breeders, farmers, warehouse owners, transporters, and
                 food corporations to a single platform to enhance
                 transparency, traceability, and trust among trust-less
                 parties. A smart contract updates the status of seeds
                 from a breeder from submitted to approved. Then, a
                 non-fungible token (NFT) corresponding to approved
                 seeds is minted for the breeder, which records the date
                 of cultivation and its owner (breeder). The NFT enables
                 farmers to keep track of seeds right from the date of
                 their cultivation and their owner, which helps them to
                 make better decisions about picking seeds from the
                 correct owner. Farmers directly interact with
                 warehouses to purchase seeds, which removes the need
                 for middlemen and improves the trust among trust-less
                 entities. Furthermore, a tender for the transportation
                 of seeds is auctioned on the basis of the priority
                 location, locp, Score, and bid\_amount of every
                 transporter, which provides a fair chance to every
                 transporter to restrict the monopoly of a single
                 transporter. The proposed system achieves immutability,
                 decentralization, and efficiency inherently from the
                 blockchain. We implemented the proposed scheme and
                 deployed it on the Ethereum network. Smart contracts
                 deployed over the Ethereum network interact with
                 React-based web pages. The analysis and results of the
                 proposed model indicate that it is viable and secure,
                 as well as superior to the current seed supply chain
                 system.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2024:CCM,
  author =       "Wei Li and Mengzhen Ren and Yazhi Liu and Chenyu Li
                 and Hui Qian and Zhenyou Zhang",
  title =        "Congestion Control Mechanism Based on Backpressure
                 Feedback in Data Center Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "131",
  day =          "15",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040131",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/131",
  abstract =     "In order to solve the congestion problem caused by the
                 dramatic growth of traffic in data centers, many
                 end-to-end congestion controls have been proposed to
                 respond to congestion in one round-trip time (RTT). In
                 this paper, we propose a new congestion control
                 mechanism based on backpressure feedback (BFCC), which
                 is designed with the primary goal of switch-to-switch
                 congestion control to resolve congestion in a one-hop
                 RTT. This approach utilizes a programmable data plane
                 to continuously monitor network congestion in real time
                 and identify real-congested flows. In addition, it
                 employs targeted flow control through backpressure
                 feedback. We validate the feasibility of this mechanism
                 on BMV2, a programmable virtual switch based on
                 programming protocol-independent packet processors
                 (P4). Simulation results demonstrate that BFCC greatly
                 enhances flow completion times (FCTs) compared to other
                 end-to-end congestion control mechanisms. It achieves
                 1.2--2 $ \times $ faster average completion times than
                 other mechanisms.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Todoli-Ferrandis:2024:PMI,
  author =       "David Todoli-Ferrandis and Javier Silvestre-Blanes and
                 V{\'\i}ctor Sempere-Pay{\'a} and Salvador
                 Santonja-Climent",
  title =        "Polling Mechanisms for Industrial {IoT} Applications
                 in Long-Range Wide-Area Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "130",
  day =          "12",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040130",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/130",
  abstract =     "LoRaWAN is a low-power wide-area network (LPWAN)
                 technology that is well suited for industrial IoT
                 (IIoT) applications. One of the challenges of using
                 LoRaWAN for IIoT is the need to collect data from a
                 large number of devices. Polling is a common way to
                 collect data from devices, but it can be inefficient
                 for LoRaWANs, which are designed for low data rates and
                 long battery life. LoRaWAN devices operating in two
                 specific modes can receive messages from a gateway even
                 when they are not sending data themselves. This allows
                 the gateway to send commands to devices at any time,
                 without having to wait for them to check for messages.
                 This paper proposes various polling mechanisms for
                 industrial IoT applications in LoRaWANs and presents
                 specific considerations for designing efficient polling
                 mechanisms in the context of industrial IoT
                 applications leveraging LoRaWAN technology.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Koukis:2024:AAD,
  author =       "Georgios Koukis and Konstantina Safouri and Vassilis
                 Tsaoussidis",
  title =        "All about Delay-Tolerant Networking ({DTN})
                 Contributions to Future {Internet}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "129",
  day =          "09",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040129",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/129",
  abstract =     "Although several years have passed since its first
                 introduction, the significance of Delay-Tolerant
                 Networking (DTN) remains evident, particularly in
                 challenging environments where traditional networks
                 face operational limitations such as disrupted
                 communication or high latency. This survey paper aims
                 to explore the diverse array of applications where DTN
                 technologies have proven successful, with a focus on
                 emerging and novel application paradigms. In
                 particular, we focus on the contributions of DTN in the
                 Future Internet, including its contribution to space
                 applications, smart cities and the Internet of Things,
                 but also to underwater communications. We also discuss
                 its potential to be used jointly with
                 information-centric networks to change the internet
                 communication paradigm in the future.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{He:2024:SEA,
  author =       "Peixiong He and Yi Zhou and Xiao Qin",
  title =        "A Survey on Energy-Aware Security Mechanisms for the
                 {Internet of Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "128",
  day =          "08",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040128",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/128",
  abstract =     "The Internet of Things (IoT) employs sensors and the
                 Internet for information exchange, enabling intelligent
                 identification, monitoring, and management, which has
                 deeply impacted various sectors such as power, medical
                 care, and security, transforming social activities and
                 lifestyles. Regrettably, IoT systems suffer from two
                 main challenges, namely sustainability and security.
                 Hence, pondering how to enhance sustainable and
                 energy-efficient practices for IoT systems to mitigate
                 risks becomes a worthwhile endeavor. To address this
                 issue, we conduct a survey of energy-aware security
                 mechanisms in the Internet of Things. Specifically, we
                 examine the challenges that IoT is facing in terms of
                 energy efficiency and security, and we inspect current
                 energy-saving and privacy-preserving technologies for
                 IoT systems. Moreover, we delineate a vision for the
                 future of IoT, emphasizing energy-aware security
                 mechanisms. Finally, we outline the challenges
                 encountered in achieving energy-aware security
                 mechanisms, as well as the direction of future
                 research. Motivated by this study, we envision
                 advancements in the IoT that not only harness the
                 benefits of science and technology but also enhance the
                 security and safety of our data.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wei:2024:MWM,
  author =       "Zhongcheng Wei and Yanhu Dong",
  title =        "Multi-{WiIR}: Multi-User Identity Legitimacy
                 Authentication Based on {WiFi} Device",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "127",
  day =          "08",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040127",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/127",
  abstract =     "With the proliferation of WiFi devices, WiFi-based
                 identification technology has garnered attention in the
                 security domain and has demonstrated initial success.
                 Nonetheless, when untrained illegitimate users appear,
                 the classifier tends to categorize them as if they were
                 trained users. In response to this issue, researchers
                 have proposed identity legitimacy authentication
                 systems to identify illicit users, albeit only
                 applicable to individual users. In this article, we
                 propose a multi-user legitimacy authentication system
                 based on WiFi, termed Multi-WiIR. Leveraging WiFi
                 signals, the system captures users' walking patterns to
                 ascertain their legitimacy. The core concept entails
                 training a multi-branch deep neural network, designated
                 WiIR-Net, for feature extraction of individual users.
                 Binary classifiers are then applied to each user, and
                 legitimacy is established by comparing the model's
                 output to predefined thresholds, thus facilitating
                 multi-user legitimacy authentication. Moreover, the
                 study experimentally investigated the impact of the
                 number of legitimate individuals on accuracy rates. The
                 results demonstrated that The Multi-WiIR system showed
                 commendable performance with low latency, being capable
                 of conducting legitimacy recognition in scenarios
                 involving up to four users, with an accuracy rate
                 reaching 85.11\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Maier:2024:MMS,
  author =       "Florian Maier and Markus Weinberger",
  title =        "Metaverse Meets Smart Cities --- Applications,
                 Benefits, and Challenges",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "126",
  day =          "08",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040126",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/126",
  abstract =     "The metaverse aims to merge the virtual and real
                 worlds. The target is to generate a virtual community
                 where social components play a crucial role and combine
                 different areas such as entertainment, work, shopping,
                 and services. This idea is explicitly appealing in the
                 context of smart cities. The metaverse offers
                 digitalization approaches and can strengthen citizens'
                 social community. While the existing literature covers
                 the exemplary potential of smart city metaverse
                 applications, this study aims to provide a
                 comprehensive overview of the potential and already
                 implemented metaverse applications in the context of
                 cities and municipalities. In addition, challenges
                 related to these applications are identified. The study
                 combines literature reviews and expert interviews to
                 ensure a broad overview. Forty-eight smart city
                 metaverse applications from eleven areas were
                 identified, and actual projects from eleven cities
                 demonstrate the current state of development. Still,
                 further research should evaluate the benefits of the
                 various applications and find strategies to overcome
                 the identified challenges.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Balaskas:2024:PYD,
  author =       "Stefanos Balaskas and Georgia Kotsari and Maria
                 Rigou",
  title =        "Perspectives of Young Digital Natives on Digital
                 Marketing: Exploring Annoyance and Effectiveness with
                 Eye-Tracking Analysis",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "125",
  day =          "08",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040125",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/125",
  abstract =     "Currently, there are a wide range of approaches to
                 deploying digital ads, with advanced technologies now
                 being harnessed to craft advertising that is engaging
                 and even tailored to personal interests and
                 preferences, yet potentially distracting and
                 irritating. This research seeks to evaluate
                 contemporary digital advertising methods by assessing
                 how annoying they are to users, particularly when they
                 distract users from intended tasks or cause delays in
                 regular online activities. To pursue this, an
                 eye-tracking study was conducted, with 51 participants
                 navigating a specially designed website featuring seven
                 distinct types of advertisements without a specific
                 content to avoid the effect of ad content on the
                 collected data. Participants were asked to execute
                 specific information-seeking tasks during the
                 experiment and afterwards to report if they recalled
                 seeing each ad and the degree of annoyance by each ad
                 type. Ad effectiveness is assessed by eye-tracking
                 metrics (time to first fixation, average fixation
                 duration, dwell time, fixation count, and revisit
                 count) depicting how appealing an ad is as a marketing
                 stimulus. Findings indicated that pop-ups, ads with
                 content reorganization, and non-skippable videos ranked
                 as the most annoying forms of advertising. Conversely,
                 in-content ads without content reorganization, banners,
                 and right rail ads were indicated as less intrusive
                 options, seeming to strike a balance between
                 effectiveness and user acceptance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liu:2024:TAH,
  author =       "Haibo Liu and Yang Liao and Changting Shi and Jing
                 Shen",
  title =        "Task Allocation of Heterogeneous Multi-Unmanned
                 Systems Based on Improved Sheep Flock Optimization
                 Algorithm",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "124",
  day =          "07",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040124",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/124",
  abstract =     "The objective of task allocation in unmanned systems
                 is to complete tasks at minimal costs. However, the
                 current algorithms employed for coordinating multiple
                 unmanned systems in task allocation tasks frequently
                 converge to local optima, thus impeding the
                 identification of the best solutions. To address these
                 challenges, this study builds upon the sheep flock
                 optimization algorithm (SFOA) by preserving individuals
                 eliminated during the iterative process within a prior
                 knowledge set, which is continuously updated. During
                 the reproduction phase of the algorithm, this prior
                 knowledge is utilized to guide the generation of new
                 individuals, preventing their rapid reconvergence to
                 local optima. This approach aids in reducing the
                 frequency at which the algorithm converges to local
                 optima, continually steering the algorithm towards the
                 global optimum and thereby enhancing the efficiency of
                 task allocation. Finally, various task scenarios are
                 presented to evaluate the performances of various
                 algorithms. The results show that the algorithm
                 proposed in this paper is more likely than other
                 algorithms to escape from local optima and find the
                 global optimum.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Baskar:2024:MCB,
  author =       "Premalatha Baskar and Prakasam Periasamy",
  title =        "Minimum-Cost-Based Neighbour Node Discovery Scheme for
                 Fault Tolerance under {IoT}-Fog Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "123",
  day =          "03",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040123",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/123",
  abstract =     "The exponential growth in data traffic in the real
                 world has drawn attention to the emerging computing
                 technique called Fog Computing (FC) for offloading
                 tasks in fault-free environments. This is a promising
                 computing standard that offers higher computing
                 benefits with a reduced cost, higher flexibility, and
                 increased availability. With the increased number of
                 tasks, the occurrence of faults increases and affects
                 the offloading of tasks. A suitable mechanism is
                 essential to rectify the faults that occur in the Fog
                 network. In this research, the fault-tolerance (FT)
                 mechanism is proposed based on cost optimization and
                 fault minimization. Initially, the faulty nodes are
                 identified based on the remaining residual energy with
                 the proposed Priority Task-based Fault-Tolerance (PTFT)
                 mechanism. The Minimum-Cost Neighbour Candidate Node
                 Discovery (MCNCND) algorithm is proposed to discover
                 the neighbouring candidate Fog access node that can
                 replace the faulty Fog node. The Replication and
                 Pre-emptive Forwarding (RPF) algorithm is proposed to
                 forward the task information to the new candidate Fog
                 access node for reliable transmission. These proposed
                 mechanisms are simulated, analysed, and compared with
                 existing FT methods. It is observed that the proposed
                 FT mechanism improves the utilization of an active
                 number of Fog access nodes. It also saved a residual
                 energy of 1.55 J without replicas, compared to the 0.85
                 J of energy that is used without the FT method.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Singh:2024:SBS,
  author =       "Radheshyam Singh and Leo Mendiboure and Jos{\'e} Soler
                 and Michael St{\"u}bert Berger and Tidiane Sylla and
                 Marion Berbineau and Lars Dittmann",
  title =        "{SDN}-Based Secure Common Emergency Service for
                 Railway and Road Co-Existence Scenarios",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "122",
  day =          "02",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040122",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/122",
  abstract =     "In the near future, there will be a greater emphasis
                 on sharing network resources between roads and railways
                 to improve transportation efficiency and reduce
                 infrastructure costs. This could enable the development
                 of global Cooperative Intelligent Transport Systems
                 (C-ITSs). In this paper, a software-defined networking
                 (SDN)-based common emergency service is developed and
                 validated for a railway and road telecommunication
                 shared infrastructure. Along with this, the developed
                 application is capable of reducing the chances of
                 distributed denial-of-service (DDoS) situations. A
                 level-crossing scenario is considered to demonstrate
                 the developed solution where railway tracks are
                 perpendicular to the roads. Two cases are considered to
                 validate and analyze the developed SDN application for
                 common emergency scenarios. In case 1, no
                 cross-communication is available between the road and
                 railway domains. In this case, emergency message
                 distribution is carried out by the assigned emergency
                 servers with the help of the SDN controller. In case 2,
                 nodes (cars and trains) are defined with two wireless
                 interfaces, and one interface is reserved for emergency
                 data communication. To add the DDoS resiliency to the
                 developed system the messaging behavior of each node is
                 observed and if an abnormality is detected, packets are
                 dropped to avoid malicious activity.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Su:2024:RSC,
  author =       "Bing Su and Jiwu Liang",
  title =        "Research on Secure Community Opportunity Network Based
                 on Trust Model",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "121",
  day =          "01",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040121",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/121",
  abstract =     "With the innovation of wireless communication
                 technology and the surge of data in mobile networks,
                 traditional routing strategies need to be improved.
                 Given the shortcomings of existing opportunistic
                 routing strategies in transmission performance and
                 security, this paper proposes a community opportunistic
                 routing decision-making method based on the trust
                 model. This algorithm calculates the node's trust value
                 through the node's historical forwarding behavior and
                 then calculates the node's trust value based on the
                 trust model. Thresholds and trust attenuation divide
                 dynamic security communities. For message forwarding,
                 nodes in the security community are prioritized as
                 next-hop relay nodes, thus ensuring that message
                 delivery is always in a safe and reliable environment.
                 On this basis, better relay nodes are further selected
                 for message forwarding based on the node centrality,
                 remaining cache space, and remaining energy,
                 effectively improving the message forwarding
                 efficiency. Through node trust value and community
                 cooperation, safe and efficient data transmission is
                 achieved, thereby improving the transmission
                 performance and security of the network. Through
                 comparison of simulation and opportunistic network
                 routing algorithms, compared with traditional methods,
                 this strategy has the highest transmission success rate
                 of 81\% with slightly increased routing overhead, and
                 this algorithm has the lowest average transmission
                 delay.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Agusti-Torra:2024:MBC,
  author =       "Anna Agust{\'\i}-Torra and Marc Ferr{\'e}-Mancebo and
                 Gabriel David Orozco-Urrutia and David
                 Rinc{\'o}n-Rivera and David Remondo",
  title =        "A Microservices-Based Control Plane for Time-Sensitive
                 Networking",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "120",
  day =          "01",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040120",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/120",
  abstract =     "Time-Sensitive Networking (TSN) aims to provide
                 deterministic communications over Ethernet. The main
                 characteristics of TSN are bounded latency and very
                 high reliability, thus complying with the strict
                 requirements of industrial communications or automotive
                 applications, to name a couple of examples. In order to
                 achieve this goal, TSN defines several scheduling
                 algorithms, among them the Time-Aware Shaper (TAS),
                 which is based on time slots and Gate Control Lists
                 (GCLs). The configuration of network elements to
                 allocate time slots, paths, and GCLs is laborious, and
                 has to be updated promptly and in a dynamic way, as new
                 data flows arrive or disappear. The IEEE 802.1Qcc
                 standard provides the basis to design a TSN control
                 plane to face these challenges, following the
                 Software-Defined Networking (SDN) paradigm. However,
                 most of the current SDN/TSN control plane solutions are
                 monolithic applications designed to run on dedicated
                 servers, and do not provide the required flexibility to
                 escalate when facing increasing service requests. This
                 work presents {\mu} TSN-CP, an SDN/TSN
                 microservices-based control plane, based on the
                 802.1Qcc standard. Our architecture leverages the
                 advantages of microservices, enabling the control plane
                 to scale up or down in response to varying workloads
                 dynamically. We achieve enhanced flexibility and
                 resilience by breaking down the control plane into
                 smaller, independent microservices. The performance of
                 {\mu} TSN-CP is evaluated in a real environment with
                 TSN switches, and various integer linear problem
                 solvers, running over different computing platforms.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2024:MAD,
  author =       "Huiting Wang and Yazhi Liu and Wei Li and Zhigang
                 Yang",
  title =        "Multi-Agent Deep Reinforcement Learning-Based
                 Fine-Grained Traffic Scheduling in Data Center
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "119",
  day =          "31",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040119",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/119",
  abstract =     "In data center networks, when facing challenges such
                 as traffic volatility, low resource utilization, and
                 the difficulty of a single traffic scheduling strategy
                 to meet demands, it is necessary to introduce
                 intelligent traffic scheduling mechanisms to improve
                 network resource utilization, optimize network
                 performance, and adapt to the traffic scheduling
                 requirements in a dynamic environment. This paper
                 proposes a fine-grained traffic scheduling scheme based
                 on multi-agent deep reinforcement learning (MAFS). This
                 approach utilizes In-Band Network Telemetry to collect
                 real-time network states on the programmable data
                 plane, establishes the mapping relationship between
                 real-time network state information and the forwarding
                 efficiency on the control plane, and designs a
                 multi-agent deep reinforcement learning algorithm to
                 calculate the optimal routing strategy under the
                 current network state. The experimental results
                 demonstrate that compared to other traffic scheduling
                 methods, MAFS can effectively enhance network
                 throughput. It achieves a 1.2 $ \times $ better average
                 throughput and achieves a 1.4--1.7 $ \times $ lower
                 packet loss rate.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Aldaoud:2024:DSM,
  author =       "Manar Aldaoud and Dawood Al-Abri and Medhat Awadalla
                 and Firdous Kausar",
  title =        "Data Structure and Management Protocol to Enhance Name
                 Resolving in Named Data Networking",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "118",
  day =          "30",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040118",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/118",
  abstract =     "Named Data Networking (NDN) is a future Internet
                 architecture that requires an Inter-Domain Routing
                 (IDR) to route its traffic globally. Address resolution
                 is a vital component of any IDR system that relies on a
                 Domain Name System (DNS) resolver to translate domain
                 names into their IP addresses in TCP/IP networks. This
                 paper presents a novel two-element solution to enhance
                 name-to-delivery location resolution in NDN networks,
                 consisting of (1) a mapping table data structure and a
                 searching mechanism and (2) a management protocol to
                 automatically populate and modify the mapping table.
                 The proposed solution is implemented and tested on the
                 Peer Name Provider Server (PNPS) mapping table, and its
                 performance is compared with two other algorithms:
                 component and character tries. The findings show a
                 notable enhancement in the operational speed of the
                 mapping table when utilizing the proposed data
                 structure. For instance, the insertion process is 37
                 times faster compared to previous algorithms.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tang:2024:CSW,
  author =       "Maolin Tang and Wei Li",
  title =        "Continuous Space Wireless Communication Tower
                 Placement by Hybrid Simulated Annealing",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "117",
  day =          "29",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040117",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/117",
  abstract =     "Wireless communication tower placement arises in many
                 real-world applications. This paper investigates a new
                 emerging wireless communication tower placement
                 problem, namely, continuous space wireless
                 communication tower placement. Unlike existing wireless
                 communication tower placement problems, which are
                 discrete computational problems, this new wireless
                 communication tower placement problem is a continuous
                 space computational problem. In this paper, we
                 formulate the new wireless communication tower
                 placement problem and propose a hybrid simulated
                 annealing algorithm that can take advantage of the
                 powerful exploration capacity of simulated annealing
                 and the strong exploitation capacity of a local
                 optimization procedure. We also demonstrate through
                 experiments the effectiveness of this hybridization
                 technique and the good performance and scalability of
                 the hybrid simulated annulling in this paper.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Dhamala:2024:PEG,
  author =       "Binita Kusum Dhamala and Babu R. Dawadi and Pietro
                 Manzoni and Baikuntha Kumar Acharya",
  title =        "Performance Evaluation of Graph Neural Network-Based
                 {RouteNet} Model with Attention Mechanism",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "116",
  day =          "29",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040116",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/116",
  abstract =     "Graph representation is recognized as an efficient
                 method for modeling networks, precisely illustrating
                 intricate, dynamic interactions within various entities
                 of networks by representing entities as nodes and their
                 relationships as edges. Leveraging the advantage of the
                 network graph data along with deep learning
                 technologies specialized for analyzing graph data,
                 Graph Neural Networks (GNNs) have revolutionized the
                 field of computer networking by effectively handling
                 structured graph data and enabling precise predictions
                 for various use cases such as performance modeling,
                 routing optimization, and resource allocation. The
                 RouteNet model, utilizing a GNN, has been effectively
                 applied in determining Quality of Service (QoS)
                 parameters for each source-to-destination pair in
                 computer networks. However, a prevalent issue in the
                 current GNN model is their struggle with generalization
                 and capturing the complex relationships and patterns
                 within network data. This research aims to enhance the
                 predictive power of GNN-based models by enhancing the
                 original RouteNet model by incorporating an attention
                 layer into its architecture. A comparative analysis is
                 conducted to evaluate the performance of the Modified
                 RouteNet model against the Original RouteNet model. The
                 effectiveness of the added attention layer has been
                 examined to determine its impact on the overall model
                 performance. The outcomes of this research contribute
                 to advancing GNN-based network performance prediction,
                 addressing the limitations of existing models, and
                 providing reliable frameworks for predicting network
                 delay.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Dolhopolov:2024:IFG,
  author =       "Anton Dolhopolov and Arnaud Castelltort and Anne
                 Laurent",
  title =        "Implementing Federated Governance in Data Mesh
                 Architecture",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "115",
  day =          "29",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040115",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/115",
  abstract =     "Analytical data platforms have been used for decades
                 to improve organizational performance. Starting from
                 the data warehouses used primarily for structured data
                 processing, through the data lakes oriented for raw
                 data storage and post-hoc data analyses, to the data
                 lakehouses---a combination of raw storage and business
                 intelligence pre-processing for improving the
                 platform's efficacy. But in recent years, a new
                 architecture called Data Mesh has emerged. The main
                 promise of this architecture is to remove the barriers
                 between operational and analytical teams in order to
                 boost the overall value extraction from the big data. A
                 number of attempts have been made to formalize and
                 implement it in existing projects. Although being
                 defined as a socio-technical paradigm, data mesh still
                 lacks the technology support to enable its widespread
                 adoption. To overcome this limitation, we propose a new
                 view of the platform requirements alongside the formal
                 governance definition that we believe can help in the
                 successful adoption of the data mesh. It is based on
                 fundamental aspects such as decentralized data domains
                 and federated computational governance. In addition, we
                 also present a blockchain-based implementation of a
                 mesh platform as a practical validation of our
                 theoretical proposal. Overall, this article
                 demonstrates a novel research direction for information
                 system decentralization technologies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kalgaonkar:2024:NAB,
  author =       "Priyank Kalgaonkar and Mohamed El-Sharkawy",
  title =        "{NeXtFusion}: Attention-Based Camera-Radar Fusion
                 Network for Improved Three-Dimensional Object Detection
                 and Tracking",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "4",
  pages =        "114",
  day =          "28",
  month =        mar,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16040114",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Sat Apr 27 07:28:50 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/4/114",
  abstract =     "Accurate perception is crucial for autonomous vehicles
                 (AVs) to navigate safely, especially in adverse weather
                 and lighting conditions where single-sensor networks
                 (e.g., cameras or radar) struggle with reduced
                 maneuverability and unrecognizable targets. Deep
                 Camera-Radar fusion neural networks offer a promising
                 solution for reliable AV perception under any weather
                 and lighting conditions. Cameras provide rich semantic
                 information, while radars act like an X-ray vision,
                 piercing through fog and darkness. This work proposes a
                 novel, efficient Camera-Radar fusion network called
                 NeXtFusion for robust AV perception with an improvement
                 in object detection accuracy and tracking. Our proposed
                 approach of utilizing an attention module enhances
                 crucial feature representation for object detection
                 while minimizing information loss from multi-modal
                 data. Extensive experiments on the challenging nuScenes
                 dataset demonstrate NeXtFusion's superior performance
                 in detecting small and distant objects compared to
                 other methods. Notably, NeXtFusion achieves the highest
                 mAP score (0.473) on the nuScenes validation set,
                 outperforming competitors like OFT (35.1\% improvement)
                 and MonoDIS (9.5\% improvement). Additionally,
                 NeXtFusion demonstrates strong performance in other
                 metrics like mATE (0.449) and mAOE (0.534),
                 highlighting its overall effectiveness in 3D object
                 detection. Furthermore, visualizations of nuScenes data
                 processed by NeXtFusion further demonstrate its
                 capability to handle diverse real-world scenarios.
                 These results suggest that NeXtFusion is a promising
                 deep fusion network for improving AV perception and
                 safety for autonomous driving.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kim:2024:VVD,
  author =       "Young Sook Kim and Seng-Phil Hong and Marko Majer",
  title =        "Validation of Value-Driven Token Economy: Focus on
                 Blockchain Content Platform",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "178",
  day =          "20",
  month =        may,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050178",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/178",
  abstract =     "This study explores the architectural framework of a
                 value-driven token economy on a blockchain content
                 platform and critically evaluates the relationship
                 between blockchain's decentralization and sustainable
                 economic practices. The existing literature often
                 glorifies the rapid market expansion of
                 cryptocurrencies but overlooks how underlying
                 blockchain technology can fundamentally enhance content
                 platforms through a more structured user engagement and
                 equitable reward system. This study proposes a new
                 token economy architecture by adopting the
                 triple-bottom -line (TBL) framework and validates its
                 practicality and effectiveness through an
                 analytic-hierarchy-process (AHP) survey of industry
                 experts. The study shows that the most influential
                 factor in a successful token economy is not profit
                 maximization but fostering a user-centric community
                 where engagement and empowerment are prioritized. This
                 shift can be expected to combine blockchain technology
                 with meaningful economic innovation by challenging
                 traditional profit-driven business models and
                 refocusing on sustainability and user value.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Aggrawal:2024:TCM,
  author =       "Sakhi Aggrawal and Alejandra J. Magana",
  title =        "Teamwork Conflict Management Training and Conflict
                 Resolution Practice via Large Language Models",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "177",
  day =          "19",
  month =        may,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050177",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/177",
  abstract =     "This study implements a conflict management training
                 approach guided by principles of transformative
                 learning and conflict management practice simulated via
                 an LLM. Transformative learning is more effective when
                 learners are engaged mentally and behaviorally in
                 learning experiences. Correspondingly, the conflict
                 management training approach involved a three-step
                 procedure consisting of a learning phase, a practice
                 phase enabled by an LLM, and a reflection phase.
                 Fifty-six students enrolled in a systems development
                 course were exposed to the transformative learning
                 approach to conflict management so they would be better
                 prepared to address any potential conflicts within
                 their teams as they approached a semester-long software
                 development project. The study investigated the
                 following: (1) How did the training and practice affect
                 students' level of confidence in addressing conflict?
                 (2) Which conflict management styles did students use
                 in the simulated practice? (3) Which strategies did
                 students employ when engaging with the simulated
                 conflict? The findings indicate that: (1) 65\% of the
                 students significantly increased in confidence in
                 managing conflict by demonstrating collaborative,
                 compromising, and accommodative approaches; (2) 26\% of
                 the students slightly increased in confidence by
                 implementing collaborative and accommodative
                 approaches; and (3) 9\% of the students did not
                 increase in confidence, as they were already confident
                 in applying collaborative approaches. The three most
                 frequently used strategies for managing conflict were
                 identifying the root cause of the problem, actively
                 listening, and being specific and objective in
                 explaining their concerns.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fiaz:2024:MFP,
  author =       "Faisal Fiaz and Syed Muhammad Sajjad and Zafar Iqbal
                 and Muhammad Yousaf and Zia Muhammad",
  title =        "{MetaSSI}: a Framework for Personal Data Protection,
                 Enhanced Cybersecurity and Privacy in Metaverse Virtual
                 Reality Platforms",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "176",
  day =          "18",
  month =        may,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050176",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/176",
  abstract =     "The Metaverse brings together components of parallel
                 processing computing platforms, the digital development
                 of physical systems, cutting-edge machine learning, and
                 virtual identity to uncover a fully digitalized
                 environment with equal properties to the real world. It
                 possesses more rigorous requirements for connection,
                 including safe access and data privacy, which are
                 necessary with the advent of Metaverse technology.
                 Traditional, centralized, and network-centered
                 solutions fail to provide a resilient identity
                 management solution. There are multifaceted security
                 and privacy issues that hinder the secure adoption of
                 this game-changing technology in contemporary
                 cyberspace. Moreover, there is a need to dedicate
                 efforts towards a secure-by-design Metaverse that
                 protects the confidentiality, integrity, and privacy of
                 the personally identifiable information (PII) of users.
                 In this research paper, we propose a logical substitute
                 for established centralized identity management systems
                 in compliance with the complexity of the Metaverse.
                 This research proposes a sustainable Self-Sovereign
                 Identity (SSI), a fully decentralized identity
                 management system to mitigate PII leaks and
                 corresponding cyber threats on all multiverse
                 platforms. The principle of the proposed framework
                 ensures that the users are the only custodians and
                 proprietors of their own identities. In addition, this
                 article provides a comprehensive approach to the
                 implementation of the SSI principles to increase
                 interoperability and trustworthiness in the Metaverse.
                 Finally, the proposed framework is validated using
                 mathematical modeling and proved to be stringent and
                 resilient against modern-day cyber attacks targeting
                 Metaverse platforms.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Auer:2024:CAC,
  author =       "Isabel Auer and Stephan Schl{\"o}gl and Gundula
                 Glowka",
  title =        "Chatbots in Airport Customer Service --- Exploring Use
                 Cases and Technology Acceptance",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "175",
  day =          "17",
  month =        may,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050175",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/175",
  abstract =     "Throughout the last decade, chatbots have gained
                 widespread adoption across various industries,
                 including healthcare, education, business, e-commerce,
                 and entertainment. These types of artificial, usually
                 cloud-based, agents have also been used in airport
                 customer service, although there has been limited
                 research concerning travelers' perspectives on this
                 rather techno-centric approach to handling inquiries.
                 Consequently, the goal of the presented study was to
                 tackle this research gap and explore potential use
                 cases for chatbots at airports, as well as investigate
                 travelers' acceptance of said technology. We employed
                 an extended version of the Technology Acceptance Model
                 considering Perceived Usefulness, Perceived Ease of
                 Use, Trust, and Perceived Enjoyment as predictors of
                 Behavioral Intention, with Affinity for Technology as a
                 potential moderator. A total of n=191 travelers
                 completed our survey. The results show that Perceived
                 Usefulness, Trust, Perceived Ease of Use, and Perceived
                 Enjoyment positively correlate with the Behavioral
                 Intention to use a chatbot for airport customer service
                 inquiries, with Perceived Usefulness showing the
                 highest impact. Travelers' Affinity for Technology, on
                 the other hand, does not seem to have any significant
                 effect.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Nguyen:2024:TSB,
  author =       "Thi-Hao Nguyen and Van-Hung Le and Huu-Son Do and
                 Trung-Hieu Te and Van-Nam Phan",
  title =        "{TQU-SLAM} Benchmark Dataset for Comparative Study to
                 Build Visual Odometry Based on Extracted Features from
                 Feature Descriptors and Deep Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "174",
  day =          "17",
  month =        may,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050174",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/174",
  abstract =     "The problem of data enrichment to train visual SLAM
                 and VO construction models using deep learning (DL) is
                 an urgent problem today in computer vision. DL requires
                 a large amount of data to train a model, and more data
                 with many different contextual and conditional
                 conditions will create a more accurate visual SLAM and
                 VO construction model. In this paper, we introduce the
                 TQU-SLAM benchmark dataset, which includes 160,631
                 RGB-D frame pairs. It was collected from the corridors
                 of three interconnected buildings comprising a length
                 of about 230 m. The ground-truth data of the TQU-SLAM
                 benchmark dataset were prepared manually, including
                 6-DOF camera poses, 3D point cloud data, intrinsic
                 parameters, and the transformation matrix between the
                 camera coordinate system and the real world. We also
                 tested the TQU-SLAM benchmark dataset using the PySLAM
                 framework with traditional features such as
                 SHI\_TOMASI, SIFT, SURF, ORB, ORB2, AKAZE, KAZE, and
                 BRISK and features extracted from DL such as VGG, DPVO,
                 and TartanVO. The camera pose estimation results are
                 evaluated, and we show that the ORB2 features have the
                 best results ( Errd = 5.74 mm), while the ratio of the
                 number of frames with detected keypoints of the
                 SHI\_TOMASI feature is the best ( rd=98.97\% ). At the
                 same time, we also present and analyze the challenges
                 of the TQU-SLAM benchmark dataset for building visual
                 SLAM and VO systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ibarra-Hernandez:2024:MLS,
  author =       "Roilhi F. Ibarra-Hern{\'a}ndez and Francisco R.
                 Castillo-Soria and Carlos A. Guti{\'e}rrez and Abel
                 Garc{\'\i}a-Barrientos and Luis Alberto
                 V{\'a}squez-Toledo and J. Alberto Del-Puerto-Flores",
  title =        "Machine Learning Strategies for Reconfigurable
                 Intelligent Surface-Assisted Communication Systems ---
                 a Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "173",
  day =          "17",
  month =        may,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050173",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/173",
  abstract =     "Machine learning (ML) algorithms have been widely used
                 to improve the performance of telecommunications
                 systems, including reconfigurable intelligent surface
                 (RIS)-assisted wireless communication systems. The RIS
                 can be considered a key part of the backbone of
                 sixth-generation (6G) communication mainly due to its
                 electromagnetic properties for controlling the
                 propagation of the signals in the wireless channel. The
                 ML-optimized (RIS)-assisted wireless communication
                 systems can be an effective alternative to mitigate the
                 degradation suffered by the signal in the wireless
                 channel, providing significant advantages in the
                 system's performance. However, the variety of
                 approaches, system configurations, and channel
                 conditions make it difficult to determine the best
                 technique or group of techniques for effectively
                 implementing an optimal solution. This paper presents a
                 comprehensive review of the reported frameworks in the
                 literature that apply ML and RISs to improve the
                 overall performance of the wireless communication
                 system. This paper compares the ML strategies that can
                 be used to address the RIS-assisted system design. The
                 systems are classified according to the ML method, the
                 databases used, the implementation complexity, and the
                 reported performance gains. Finally, we shed light on
                 the challenges and opportunities in designing and
                 implementing future RIS-assisted wireless communication
                 systems based on ML strategies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tsoulos:2024:UOT,
  author =       "Ioannis G. Tsoulos and Alexandros Tzallas and
                 Evangelos Karvounis",
  title =        "Using Optimization Techniques in Grammatical
                 Evolution",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "172",
  day =          "16",
  month =        may,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050172",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/172",
  abstract =     "The Grammatical Evolution technique has been
                 successfully applied to a wide range of problems in
                 various scientific fields. However, in many cases,
                 techniques that make use of Grammatical Evolution
                 become trapped in local minima of the objective problem
                 and fail to reach the optimal solution. One simple
                 method to tackle such situations is the usage of hybrid
                 techniques, where local minimization algorithms are
                 used in conjunction with the main algorithm. However,
                 Grammatical Evolution is an integer optimization
                 problem and, as a consequence, techniques should be
                 formulated that are applicable to it as well. In the
                 current work, a modified version of the Simulated
                 Annealing algorithm is used as a local optimization
                 procedure in Grammatical Evolution. This approach was
                 tested on the Constructed Neural Networks and a
                 remarkable improvement of the experimental results was
                 shown, both in classification data and in data fitting
                 cases.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liu:2024:SBS,
  author =       "Na Liu and Wei-Tek Tsai",
  title =        "{SmartDED}: a Blockchain- and Smart Contract-Based
                 Digital Electronic Detonator Safety Supervision
                 System",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "171",
  day =          "16",
  month =        may,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050171",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/171",
  abstract =     "Digital electronic detonators, as a civil explosive,
                 are of prime importance for people's life and property
                 safety in the process of production and operation.
                 Therefore, the Ministry of Industry and Information
                 Technology and the Ministry of Public Security of the
                 People's Republic of China have extremely high
                 requirements for their essential safety. Existing
                 schemes are vulnerable to tampering and single points
                 of failure, which makes tracing unqualified digital
                 electronic detonators difficult and identifying the
                 responsibility for digital electronic detonator
                 accidents hard. This paper presents a digital
                 electronic detonator safety supervision system based on
                 a consortium blockchain. To achieve dynamic supply
                 chain supervision, we propose a novel digital
                 electronic detonator supervision model together with
                 three codes in one. We also propose a blockchain-based
                 system that employs smart contracts to achieve
                 efficient traceability and ensure security. We
                 implemented the proposed model using a consortium
                 blockchain platform and provide the cost. The
                 evaluation results validate that the proposed system is
                 efficient.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fath:2024:IIM,
  author =       "Alireza Fath and Nicholas Hanna and Yi Liu and Scott
                 Tanch and Tian Xia and Dryver Huston",
  title =        "Indoor Infrastructure Maintenance Framework Using
                 Networked Sensors, Robots, and Augmented Reality Human
                 Interface",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "170",
  day =          "15",
  month =        may,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050170",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/170",
  abstract =     "Sensing and cognition by homeowners and technicians
                 for home maintenance are prime examples of
                 human--building interaction. Damage, decay, and pest
                 infestation present signals that humans interpret and
                 then act upon to remedy and mitigate. The maintenance
                 cognition process has direct effects on sustainability
                 and economic vitality, as well as the health and
                 well-being of building occupants. While home
                 maintenance practices date back to antiquity, they
                 readily submit to augmentation and improvement with
                 modern technologies. This paper describes the use of
                 networked smart technologies embedded with machine
                 learning (ML) and presented in electronic formats to
                 better inform homeowners and occupants about safety and
                 maintenance issues, as well as recommend courses of
                 remedial action. The demonstrated technologies include
                 robotic sensing in confined areas, LiDAR scans of
                 structural shape and deformation, moisture and gas
                 sensing, water leak detection, network embedded ML, and
                 augmented reality interfaces with multi-user teaming
                 capabilities. The sensor information passes through a
                 private local dynamic network to processors with neural
                 network pattern recognition capabilities to abstract
                 the information, which then feeds to humans through
                 augmented reality and conventional smart device
                 interfaces. This networked sensor system serves as a
                 testbed and demonstrator for home maintenance
                 technologies, for what can be termed Home Maintenance
                 4.0.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Frattolillo:2024:BSC,
  author =       "Franco Frattolillo",
  title =        "Blockchain and Smart Contracts for Digital Copyright
                 Protection",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "169",
  day =          "14",
  month =        may,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050169",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/169",
  abstract =     "In a global context characterized by a pressing need
                 to find a solution to the problem of digital copyright
                 protection, buyer-seller watermarking protocols based
                 on asymmetric fingerprinting and adopting a
                 ``buyer-friendly'' approach have proven effective in
                 addressing such a problem. They can ensure high levels
                 of usability and security. However, they usually resort
                 to trusted third parties (TTPs) to guarantee the
                 protection process, and this is often perceived as a
                 relevant drawback since TTPs may cause conspiracy or
                 collusion problems, besides the fact that they are
                 generally considered as some sort of ``big brother''.
                 This paper presents a buyer-seller watermarking
                 protocol that can achieve the right compromise between
                 usability and security without employing a TTP. The
                 protocol is built around previous experiences conducted
                 in the field of protocols based on the buyer-friendly
                 approach. Its peculiarity consists of exploiting smart
                 contracts executed within a blockchain to implement
                 preset and immutable rules that run automatically under
                 specific conditions without control from some kind of
                 central authority. The result is a simple, usable, and
                 secure watermarking protocol able to do without TTPs.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Imran:2024:ERA,
  author =       "Muhammad Imran and Annalisa Appice and Donato
                 Malerba",
  title =        "Evaluating Realistic Adversarial Attacks against
                 Machine Learning Models for {Windows PE} Malware
                 Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "168",
  day =          "12",
  month =        may,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050168",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/168",
  abstract =     "During the last decade, the cybersecurity literature
                 has conferred a high-level role to machine learning as
                 a powerful security paradigm to recognise malicious
                 software in modern anti-malware systems. However, a
                 non-negligible limitation of machine learning methods
                 used to train decision models is that adversarial
                 attacks can easily fool them. Adversarial attacks are
                 attack samples produced by carefully manipulating the
                 samples at the test time to violate the model integrity
                 by causing detection mistakes. In this paper, we
                 analyse the performance of five realistic target-based
                 adversarial attacks, namely Extend, Full DOS, Shift,
                 FGSM padding + slack and GAMMA, against two machine
                 learning models, namely MalConv and LGBM, learned to
                 recognise Windows Portable Executable (PE) malware
                 files. Specifically, MalConv is a Convolutional Neural
                 Network (CNN) model learned from the raw bytes of
                 Windows PE files. LGBM is a Gradient-Boosted Decision
                 Tree model that is learned from features extracted
                 through the static analysis of Windows PE files.
                 Notably, the attack methods and machine learning models
                 considered in this study are state-of-the-art methods
                 broadly used in the machine learning literature for
                 Windows PE malware detection tasks. In addition, we
                 explore the effect of accounting for adversarial
                 attacks on securing machine learning models through the
                 adversarial training strategy. Therefore, the main
                 contributions of this article are as follows: (1) We
                 extend existing machine learning studies that commonly
                 consider small datasets to explore the evasion ability
                 of state-of-the-art Windows PE attack methods by
                 increasing the size of the evaluation dataset. (2) To
                 the best of our knowledge, we are the first to carry
                 out an exploratory study to explain how the considered
                 adversarial attack methods change Windows PE malware to
                 fool an effective decision model. (3) We explore the
                 performance of the adversarial training strategy as a
                 means to secure effective decision models against
                 adversarial Windows PE malware files generated with the
                 considered attack methods. Hence, the study explains
                 how GAMMA can actually be considered the most effective
                 evasion method for the performed comparative analysis.
                 On the other hand, the study shows that the adversarial
                 training strategy can actually help in recognising
                 adversarial PE malware generated with GAMMA by also
                 explaining how it changes model decisions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ye:2024:HSA,
  author =       "Anjia Ye and Ananda Maiti and Matthew Schmidt and
                 Scott J. Pedersen",
  title =        "A Hybrid Semi-Automated Workflow for Systematic and
                 Literature Review Processes with Large Language Model
                 Analysis",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "167",
  day =          "12",
  month =        may,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050167",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/167",
  abstract =     "Systematic reviews (SRs) are a rigorous method for
                 synthesizing empirical evidence to answer specific
                 research questions. However, they are labor-intensive
                 because of their collaborative nature, strict
                 protocols, and typically large number of documents.
                 Large language models (LLMs) and their applications
                 such as gpt-4/ChatGPT have the potential to reduce the
                 human workload of the SR process while maintaining
                 accuracy. We propose a new hybrid methodology that
                 combines the strengths of LLMs and humans using the
                 ability of LLMs to summarize large bodies of text
                 autonomously and extract key information. This is then
                 used by a researcher to make inclusion/exclusion
                 decisions quickly. This process replaces the typical
                 manually performed title/abstract screening, full-text
                 screening, and data extraction steps in an SR while
                 keeping a human in the loop for quality control. We
                 developed a semi-automated LLM-assisted (Gemini-Pro)
                 workflow with a novel innovative prompt development
                 strategy. This involves extracting three categories of
                 information including identifier, verifier, and data
                 field (IVD) from the formatted documents. We present a
                 case study where our hybrid approach reduced errors
                 compared with a human-only SR. The hybrid workflow
                 improved the accuracy of the case study by identifying
                 6/390 (1.53\%) articles that were misclassified by the
                 human-only process. It also matched the human-only
                 decisions completely regarding the rest of the 384
                 articles. Given the rapid advances in LLM technology,
                 these results will undoubtedly improve over time.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Patwe:2024:BES,
  author =       "Sonali Patwe and Sunil B. Mane",
  title =        "Blockchain-Enabled Secure and Interoperable
                 Authentication Scheme for Metaverse Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "166",
  day =          "11",
  month =        may,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050166",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/166",
  abstract =     "The metaverse, which amalgamates physical and virtual
                 realms for diverse social activities, has been the
                 focus of extensive application development by
                 organizations, research institutes, and companies.
                 However, these applications are often isolated,
                 employing distinct authentication methods across
                 platforms. Achieving interoperable authentication is
                 crucial for when avatars traverse different metaverses
                 to mitigate security concerns like impersonation,
                 mutual authentication, replay, and server spoofing. To
                 address these issues, we propose a blockchain-enabled
                 secure and interoperable authentication scheme. This
                 mechanism uniquely identifies users in the physical
                 world as well as avatars, facilitating seamless
                 navigation across verses. Our proposal is substantiated
                 through informal security analyses, employing automated
                 verification of internet security protocols and
                 applications (AVISPA), the real-or-random (ROR) model,
                 and Burrows--Abadi--Needham (BAN) logic and showcasing
                 effectiveness against a broad spectrum of security
                 threats. Comparative assessments against similar
                 schemes demonstrate our solution's superiority in terms
                 of communication costs, computation costs, and security
                 features. Consequently, our blockchain-enabled,
                 interoperable, and secure authentication scheme stands
                 as a robust solution for ensuring security in metaverse
                 environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhang:2024:RIS,
  author =       "Yuzhu Zhang and Hao Xu",
  title =        "Reconfigurable-Intelligent-Surface-Enhanced Dynamic
                 Resource Allocation for the Social {Internet of
                 Electric Vehicle Charging Networks} with
                 Causal-Structure-Based Reinforcement Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "165",
  day =          "11",
  month =        may,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050165",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/165",
  abstract =     "Charging stations and electric vehicle (EV) charging
                 networks signify a significant advancement in
                 technology as a frontier application of the Social
                 Internet of Things (SIoT), presenting both challenges
                 and opportunities for current 6G wireless networks. One
                 primary challenge in this integration is limited
                 wireless network resources, particularly when serving a
                 large number of users within distributed EV charging
                 networks in the SIoT. Factors such as congestion during
                 EV travel, varying EV user preferences, and
                 uncertainties in decision-making regarding charging
                 station resources significantly impact system operation
                 and network resource allocation. To address these
                 challenges, this paper develops a novel framework
                 harnessing the potential of emerging technologies,
                 specifically reconfigurable intelligent surfaces (RISs)
                 and causal-structure-enhanced asynchronous advantage
                 actor--critic (A3C) reinforcement learning techniques.
                 This framework aims to optimize resource allocation,
                 thereby enhancing communication support within EV
                 charging networks. Through the integration of RIS
                 technology, which enables control over electromagnetic
                 waves, and the application of causal reinforcement
                 learning algorithms, the framework dynamically adjusts
                 resource allocation strategies to accommodate evolving
                 conditions in EV charging networks. An essential aspect
                 of this framework is its ability to simultaneously meet
                 real-world social requirements, such as ensuring
                 efficient utilization of network resources. Numerical
                 simulation results validate the effectiveness and
                 adaptability of this approach in improving wireless
                 network efficiency and enhancing user experience within
                 the SIoT context. Through these simulations, it becomes
                 evident that the developed framework offers promising
                 solutions to the challenges posed by integrating the
                 SIoT with EV charging networks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhang:2024:PPF,
  author =       "Yu Zhang and Xiaowei Peng and Hequn Xian",
  title =        "{pFedBASC}: Personalized Federated Learning with
                 Blockchain-Assisted Semi-Centralized Framework",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "164",
  day =          "11",
  month =        may,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050164",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/164",
  abstract =     "As network technology advances, there is an increasing
                 need for a trusted new-generation information
                 management system. Blockchain technology provides a
                 decentralized, transparent, and tamper-proof
                 foundation. Meanwhile, data islands have become a
                 significant obstacle for machine learning applications.
                 Although federated learning (FL) ensures data privacy
                 protection, server-side security concerns persist.
                 Traditional methods have employed a blockchain system
                 in FL frameworks to maintain a tamper-proof global
                 model database. In this context, we propose a novel
                 personalized federated learning (pFL) with
                 blockchain-assisted semi-centralized framework,
                 pFedBASC. This approach, tailored for the Internet of
                 Things (IoT) scenarios, constructs a semi-centralized
                 IoT structure and utilizes trusted network connections
                 to support FL. We concentrate on designing the
                 aggregation process and FL algorithm, as well as the
                 block structure. To address data heterogeneity and
                 communication costs, we propose a pFL method called
                 FedHype. In this method, each client is assigned a
                 compact hypernetwork (HN) alongside a normal target
                 network (TN) whose parameters are generated by the HN.
                 Clients pull together other clients' HNs for local
                 aggregation to personalize their TNs, reducing
                 communication costs. Furthermore, FedHype can be
                 integrated with other existing algorithms, enhancing
                 its functionality. Experimental results reveal that
                 pFedBASC effectively tackles data heterogeneity issues
                 while maintaining positive accuracy, communication
                 efficiency, and robustness.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ma:2024:BBZ,
  author =       "Zhe Ma and Xuhesheng Chen and Tiejiang Sun and Xukang
                 Wang and Ying Cheng Wu and Mengjie Zhou",
  title =        "Blockchain-Based Zero-Trust Supply Chain Security
                 Integrated with Deep Reinforcement Learning for
                 Inventory Optimization",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "163",
  day =          "10",
  month =        may,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050163",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/163",
  abstract =     "Modern supply chain systems face significant
                 challenges, including lack of transparency, inefficient
                 inventory management, and vulnerability to disruptions
                 and security threats. Traditional optimization methods
                 often struggle to adapt to the complex and dynamic
                 nature of these systems. This paper presents a novel
                 blockchain-based zero-trust supply chain security
                 framework integrated with deep reinforcement learning
                 (SAC-rainbow) to address these challenges. The
                 SAC-rainbow framework leverages the Soft Actor--Critic
                 (SAC) algorithm with prioritized experience replay for
                 inventory optimization and a blockchain-based
                 zero-trust mechanism for secure supply chain
                 management. The SAC-rainbow algorithm learns adaptive
                 policies under demand uncertainty, while the blockchain
                 architecture ensures secure, transparent, and traceable
                 record-keeping and automated execution of supply chain
                 transactions. An experiment using real-world supply
                 chain data demonstrated the superior performance of the
                 proposed framework in terms of reward maximization,
                 inventory stability, and security metrics. The
                 SAC-rainbow framework offers a promising solution for
                 addressing the challenges of modern supply chains by
                 leveraging blockchain, deep reinforcement learning, and
                 zero-trust security principles. This research paves the
                 way for developing secure, transparent, and efficient
                 supply chain management systems in the face of growing
                 complexity and security risks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fan:2024:BUB,
  author =       "Caixiang Fan and Hamzeh Khazaei and Petr Musilek",
  title =        "{BPET}: a Unified Blockchain-Based Framework for
                 Peer-to-Peer Energy Trading",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "162",
  day =          "7",
  month =        may,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050162",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/162",
  abstract =     "Recent years have witnessed a significant dispersion
                 of renewable energy and the emergence of
                 blockchain-enabled transactive energy systems. These
                 systems facilitate direct energy trading among
                 participants, cutting transmission losses, improving
                 energy efficiency, and fostering renewable energy
                 adoption. However, developing such a system is usually
                 challenging and time-consuming due to the diversity of
                 energy markets. The lack of a market-agnostic design
                 hampers the widespread adoption of blockchain-based
                 peer-to-peer energy trading globally. In this paper, we
                 propose and develop a novel unified blockchain-based
                 peer-to-peer energy trading framework, called BPET.
                 This framework incorporates microservices and
                 blockchain as the infrastructures and adopts a highly
                 modular smart contract design so that developers can
                 easily extend it by plugging in localized energy market
                 rules and rapidly developing a customized
                 blockchain-based peer-to-peer energy trading system.
                 Additionally, we have developed the price formation
                 mechanisms, e.g., the system marginal price calculation
                 algorithm and the pool price calculation algorithm, to
                 demonstrate the extensibility of the BPET framework. To
                 validate the proposed solution, we have conducted a
                 comprehensive case study using real trading data from
                 the Alberta Electric System Operator. The experimental
                 results confirm the system's capability of processing
                 energy trading transactions efficiently and effectively
                 within the Alberta electricity wholesale market.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chen:2024:AEM,
  author =       "Jieli Chen and Kah Phooi Seng and Li Minn Ang and
                 Jeremy Smith and Hanyue Xu",
  title =        "{AI}-Empowered Multimodal Hierarchical Graph-Based
                 Learning for Situation Awareness on Enhancing Disaster
                 Responses",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "161",
  day =          "7",
  month =        may,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050161",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/161",
  abstract =     "Situational awareness (SA) is crucial in disaster
                 response, enhancing the understanding of the
                 environment. Social media, with its extensive user
                 base, offers valuable real-time information for such
                 scenarios. Although SA systems excel in extracting
                 disaster-related details from user-generated content, a
                 common limitation in prior approaches is their emphasis
                 on single-modal extraction rather than embracing
                 multi-modalities. This paper proposed a multimodal
                 hierarchical graph-based situational awareness (MHGSA)
                 system for comprehensive disaster event classification.
                 Specifically, the proposed multimodal hierarchical
                 graph contains nodes representing different disaster
                 events and the features of the event nodes are
                 extracted from the corresponding images and acoustic
                 features. The proposed feature extraction modules with
                 multi-branches for vision and audio features provide
                 hierarchical node features for disaster events of
                 different granularities, aiming to build a
                 coarse-granularity classification task to constrain the
                 model and enhance fine-granularity classification. The
                 relationships between different disaster events in
                 multi-modalities are learned by graph convolutional
                 neural networks to enhance the system's ability to
                 recognize disaster events, thus enabling the system to
                 fuse complex features of vision and audio. Experimental
                 results illustrate the effectiveness of the proposed
                 visual and audio feature extraction modules in
                 single-modal scenarios. Furthermore, the MHGSA
                 successfully fuses visual and audio features, yielding
                 promising results in disaster event classification
                 tasks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kaleem:2024:ORP,
  author =       "Sarah Kaleem and Muhammad Asim and Mohammed El-Affendi
                 and Muhammad Babar",
  title =        "Optimizing Requirements Prioritization for {IoT}
                 Applications Using Extended Analytical Hierarchical
                 Process and an Advanced Grouping Framework",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "160",
  day =          "6",
  month =        may,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050160",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/160",
  abstract =     "Effective requirement collection and prioritization
                 are paramount within the inherently distributed nature
                 of the Internet of Things (IoT) application. Current
                 methods typically categorize IoT application
                 requirements subjectively into inessential, desirable,
                 and mandatory groups. This often leads to
                 prioritization challenges, especially when dealing with
                 requirements of equal importance and when the number of
                 requirements grows. This increases the complexity of
                 the Analytical Hierarchical Process (AHP) to O(n2)
                 dimensions. This research introduces a novel framework
                 that integrates an enhanced AHP with an advanced
                 grouping model to address these issues. This integrated
                 approach mitigates the subjectivity found in
                 traditional grouping methods and efficiently manages
                 larger sets of requirements. The framework consists of
                 two main modules: the Pre-processing Module and the
                 Prioritization Module. The latter includes three units:
                 the Grouping Processing Unit (GPU) for initial
                 classification using a new grouping approach, the
                 Review Processing Unit (RPU) for post-grouping
                 assessment, and the AHP Processing Unit (APU) for final
                 prioritization. This framework is evaluated through a
                 detailed case study, demonstrating its ability to
                 effectively streamline requirement prioritization in
                 IoT applications, thereby enhancing design quality and
                 operational efficiency.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Althamary:2024:EMT,
  author =       "Ibrahim Althamary and Rubbens Boisguene and Chih-Wei
                 Huang",
  title =        "Enhanced Multi-Task Traffic Forecasting in Beyond {5G}
                 Networks: Leveraging Transformer Technology and
                 Multi-Source Data Fusion",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "159",
  day =          "5",
  month =        may,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050159",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/159",
  abstract =     "Managing cellular networks in the Beyond 5G (B5G) era
                 is a complex and challenging task requiring advanced
                 deep learning approaches. Traditional models focusing
                 on internet traffic (INT) analysis often fail to
                 capture the rich temporal and spatial contexts
                 essential for accurate INT predictions. Furthermore,
                 these models do not account for the influence of
                 external factors such as weather, news, and social
                 trends. This study proposes a multi-source CNN-RNN
                 (MSCR) model that leverages a rich dataset, including
                 periodic, weather, news, and social data to address
                 these limitations. This model enables the capture and
                 fusion of diverse data sources for improved INT
                 prediction accuracy. An advanced deep learning model,
                 the transformer-enhanced CNN-RNN (TE-CNN-RNN), has been
                 introduced. This model is specifically designed to
                 predict INT data only. This model demonstrates the
                 effectiveness of transformers in extracting detailed
                 temporal-spatial features, outperforming conventional
                 CNN-RNN models. The experimental results demonstrate
                 that the proposed MSCR and TE-CNN-RNN models outperform
                 existing state-of-the-art models for traffic
                 forecasting. These findings underscore the
                 transformative power of transformers for capturing
                 intricate temporal-spatial features and the importance
                 of multi-source data and deep learning techniques for
                 optimizing cell site management in the B5G era.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zaway:2024:OWC,
  author =       "Lassaad Zaway and Nader {Ben Amor} and Jalel Ktari and
                 Mohamed Jallouli and Larbi Chrifi Alaoui and Laurent
                 Delahoche",
  title =        "Optimization of Wheelchair Control via Multi-Modal
                 Integration: Combining Webcam and {EEG}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "158",
  day =          "3",
  month =        may,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050158",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/158",
  abstract =     "Even though Electric Powered Wheelchairs (EPWs) are a
                 useful tool for meeting the needs of people with
                 disabilities, some disabled people find it difficult to
                 use regular EPWs that are joystick-controlled. Smart
                 wheelchairs that use Brain--Computer Interface (BCI)
                 technology present an efficient solution to this
                 problem. This article presents a cutting-edge
                 intelligent control wheelchair that is intended to
                 improve user involvement and security. The suggested
                 method combines facial expression analysis via a camera
                 with EEG signal processing using the EMOTIV Insight EEG
                 dataset. The system generates control commands by
                 identifying specific EEG patterns linked to facial
                 expressions such as eye blinking, winking left and
                 right, and smiling. Simultaneously, the system uses
                 computer vision algorithms and inertial measurements to
                 analyze gaze direction in order to establish the user's
                 intended steering. The outcomes of the experiments
                 prove that the proposed system is reliable and
                 efficient in meeting the various requirements of
                 people, presenting a positive development in the field
                 of smart wheelchair technology.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Dang:2024:RAO,
  author =       "Tuan-Kiet Dang and Khai-Duy Nguyen and Binh
                 Kieu-Do-Nguyen and Trong-Thuc Hoang and Cong-Kha Pham",
  title =        "Realization of Authenticated One-Pass Key
                 Establishment on {RISC-V} Micro-Controller for {IoT}
                 Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "157",
  day =          "3",
  month =        may,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050157",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/risc-v.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/157",
  abstract =     "Internet-of-things networks consist of multiple sensor
                 devices spread over a wide area. In order to protect
                 the data from unauthorized access and tampering, it is
                 essential to ensure secure communication between the
                 sensor devices and the central server. This security
                 measure aims to guarantee authenticity,
                 confidentiality, and data integrity. Unlike traditional
                 computing systems, sensor node devices are often
                 limited regarding memory and computing power.
                 Lightweight communication protocols, such as LoRaWAN,
                 were introduced to overcome these limitations. However,
                 despite the lightweight feature, the protocol is
                 vulnerable to different types of attacks. This proposal
                 presents a highly secure key establishment protocol
                 that combines two cryptography schemes: Elliptic Curve
                 Qu--Vanstone and signcryption key encapsulation. The
                 protocol provides a method to establish a secure
                 channel that inherits the security properties of the
                 two schemes. Also, it allows for fast rekeying with
                 only one exchange message, significantly reducing the
                 handshake complexity in low-bandwidth communication. In
                 addition, the selected schemes complement each other
                 and share the same mathematical operations in elliptic
                 curve cryptography. Moreover, with the rise of a
                 community-friendly platform like RISC-V, we implemented
                 the protocol on a RISC-V system to evaluate its
                 overheads regarding the cycle count and execution
                 time.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Samuel:2024:FCS,
  author =       "Cyril Naves Samuel and Fran{\c{c}}ois Verdier and
                 Severine Glock and Patricia Guitton-Ouhamou",
  title =        "A Fair Crowd-Sourced Automotive Data Monetization
                 Approach Using Substrate Hybrid Consensus Blockchain",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "156",
  day =          "30",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050156",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/156",
  abstract =     "This work presents a private consortium
                 blockchain-based automotive data monetization
                 architecture implementation using the Substrate
                 blockchain framework. Architecture is decentralized
                 where crowd-sourced data from vehicles are collectively
                 auctioned ensuring data privacy and security. Smart
                 Contracts and OffChain worker interactions built along
                 with the blockchain make it interoperable with external
                 systems to send or receive data. The work is deployed
                 in a Kubernetes cloud platform and evaluated on
                 different parameters like throughput, hybrid consensus
                 algorithms AuRa and BABE, along with GRANDPA
                 performance in terms of forks and scalability for
                 increasing node participants. The hybrid consensus
                 algorithms are studied in depth to understand the
                 difference and performance in the separation of block
                 creation by AuRa and BABE followed by chain
                 finalization through the GRANDPA protocol.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Boeding:2024:NAT,
  author =       "Matthew Boeding and Michael Hempel and Hamid Sharif",
  title =        "Novel Approach towards a Fully Deep Learning-Based
                 {IoT} Receiver Architecture: From Estimation to
                 Decoding",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "155",
  day =          "30",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050155",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/155",
  abstract =     "As the Internet of Things (IoT) continues to expand,
                 wireless communication is increasingly widespread
                 across diverse industries and remote devices. This
                 includes domains such as Operational Technology in the
                 Smart Grid. Notably, there is a surge in
                 resource-constrained devices leveraging wireless
                 communication, especially with the advances of 5G/6G
                 technology. Nevertheless, the transmission of wireless
                 communications demands substantial power and
                 computational resources, presenting a significant
                 challenge to these devices and their operations. In
                 this work, we propose the use of deep learning to
                 improve the Bit Error Rate (BER) performance of
                 Orthogonal Frequency Division Multiplexing (OFDM)
                 wireless receivers. By improving the BER performance of
                 these receivers, devices can transmit with less power,
                 thereby improving IoT devices' battery life. The
                 architecture presented in this paper utilizes a
                 depthwise Convolutional Neural Network (CNN) for
                 channel estimation and demodulation, whereas a Graph
                 Neural Network (GNN) is utilized for Low-Density Parity
                 Check (LDPC) decoding, tested against a proposed (1998,
                 1512) LDPC code. Our results show higher performance
                 than traditional receivers in both isolated tests for
                 the CNN and GNN, and a combined end-to-end test with
                 lower computational complexity than other proposed deep
                 learning models. For BER improvement, our proposed
                 approach showed a 1 dB improvement for eliminating BER
                 in QPSK models. Additionally, it improved 16-QAM Rician
                 BER by five decades, 16-QAM LOS model BER by four
                 decades, 64-QAM Rician BER by 2.5 decades, and 64-QAM
                 LOS model BER by three decades.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sprunger:2024:MRP,
  author =       "John David Sprunger and Alvin Lim and David M. Bevly",
  title =        "A Method for the Rapid Propagation of Emergency Event
                 Notifications in a Long Vehicle Convoy",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "154",
  day =          "29",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050154",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/154",
  abstract =     "Convoys composed of autonomous vehicles could improve
                 the transportation and freight industries in several
                 ways. One of the avenues of improvement is in fuel
                 efficiency, where the vehicles maintain a close
                 following distance to each other in order to reduce air
                 resistance by way of the draft effect. While close
                 following distances improve fuel efficiency, they also
                 reduce both the margin of safety and the system's
                 tolerance to disturbances in relative position. The
                 system's tolerance to disturbances is known as string
                 stability, where the error magnitude either grows or
                 decays as it propagates rearward through the convoy.
                 One of the major factors in a system's string stability
                 is its delay in sending state updates to other
                 vehicles, the most pertinent being a hard braking
                 maneuver. Both external sensors and vehicle-to-vehicle
                 communication standards have relatively long delays
                 between peer vehicle state changes and the information
                 being actionable by the ego vehicle. The system
                 presented here, called the Convoy Vehicular Ad Hoc
                 Network (Convoy VANET), was designed to reliably
                 propagate emergency event messages with low delay while
                 maintaining reasonable channel efficiency. It
                 accomplishes this using a combination of several
                 techniques, notably relative position-based
                 retransmission delays. Our results using Network
                 Simulator 3 (ns3) show the system propagating messages
                 down a 20-vehicle convoy in less than 100 ms even with
                 more than a 35\% message loss between vehicles that are
                 not immediately adjacent. These simulation results show
                 the potential for this kind of system in situations
                 where emergency information must be disseminated
                 quickly in low-reliability wireless environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Nunez-Agurto:2024:NTC,
  author =       "Daniel Nu{\~n}ez-Agurto and Walter Fuertes and Luis
                 Marrone and Eduardo Benavides-Astudillo and Christian
                 Coronel-Guerrero and Franklin Perez",
  title =        "A Novel Traffic Classification Approach by Employing
                 Deep Learning on Software-Defined Networking",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "153",
  day =          "29",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050153",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/153",
  abstract =     "The ever-increasing diversity of Internet applications
                 and the rapid evolution of network infrastructure due
                 to emerging technologies have made network management
                 more challenging. Effective traffic classification is
                 critical for efficiently managing network resources and
                 aligning with service quality and security demands. The
                 centralized controller of software-defined networking
                 provides a comprehensive network view, simplifying
                 traffic analysis and offering direct programmability
                 features. When combined with deep learning techniques,
                 these characteristics enable the incorporation of
                 intelligence into networks, leading to optimization and
                 improved network management and maintenance. Therefore,
                 this research aims to develop a model for traffic
                 classification by application types and network attacks
                 using deep learning techniques to enhance the quality
                 of service and security in software-defined networking.
                 The SEMMA method is employed to deploy the model, and
                 the classifiers are trained with four algorithms,
                 namely LSTM, BiLSTM, GRU, and BiGRU, using selected
                 features from two public datasets. These results
                 underscore the remarkable effectiveness of the GRU
                 model in traffic classification. Hence, the outcomes
                 achieved in this research surpass state-of-the-art
                 methods and showcase the effectiveness of a deep
                 learning model within a traffic classification in an
                 SDN environment.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Jamal:2024:HMA,
  author =       "Mansoor Jamal and Zaib Ullah and Muddasar Naeem and
                 Musarat Abbas and Antonio Coronato",
  title =        "A Hybrid Multi-Agent Reinforcement Learning Approach
                 for Spectrum Sharing in Vehicular Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "152",
  day =          "28",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050152",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/152",
  abstract =     "Efficient spectrum sharing is essential for maximizing
                 data communication performance in Vehicular Networks
                 (VNs). In this article, we propose a novel hybrid
                 framework that leverages Multi-Agent Reinforcement
                 Learning (MARL), thereby combining both centralized and
                 decentralized learning approaches. This framework
                 addresses scenarios where multiple vehicle-to-vehicle
                 (V2V) links reuse the frequency spectrum preoccupied by
                 vehicle-to-infrastructure (V2I) links. We introduce the
                 QMIX technique with the Deep Q Networks (DQNs)
                 algorithm to facilitate collaborative learning and
                 efficient spectrum management. The DQN technique uses a
                 neural network to approximate the Q value function in
                 high-dimensional state spaces, thus mapping input
                 states to (action, Q value) tables that facilitate
                 self-learning across diverse scenarios. Similarly, the
                 QMIX is a value-based technique for multi-agent
                 environments. In the proposed model, each V2V agent
                 having its own DQN observes the environment, receives
                 observation, and obtains a common reward. The QMIX
                 network receives Q values from all agents considering
                 individual benefits and collective objectives. This
                 mechanism leads to collective learning while V2V agents
                 dynamically adapt to real-time conditions, thus
                 improving VNs performance. Our research finding
                 highlights the potential of hybrid MARL models for
                 dynamic spectrum sharing in VNs and paves the way for
                 advanced cooperative learning strategies in vehicular
                 communication environments. Furthermore, we conducted
                 an in-depth exploration of the simulation environment
                 and performance evaluation criteria, thus concluding in
                 a comprehensive comparative analysis with cutting-edge
                 solutions in the field. Simulation results show that
                 the proposed framework efficiently performs against the
                 benchmark architecture in terms of V2V transmission
                 probability and V2I peak data transfer.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Aung:2024:EMS,
  author =       "Aye Nyein Aung and Che-Wei Liao and Jeih-Weih Hung",
  title =        "Effective Monoaural Speech Separation through
                 Convolutional Top-Down Multi-View Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "151",
  day =          "28",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050151",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/151",
  abstract =     "Speech separation, sometimes known as the ``cocktail
                 party problem'', is the process of separating
                 individual speech signals from an audio mixture that
                 includes ambient noises and several speakers. The goal
                 is to extract the target speech in this complicated
                 sound scenario and either make it easier to understand
                 or increase its quality so that it may be used in
                 subsequent processing. Speech separation on overlapping
                 audio data is important for many speech-processing
                 tasks, including natural language processing, automatic
                 speech recognition, and intelligent personal
                 assistants. New speech separation algorithms are often
                 built on a deep neural network (DNN) structure, which
                 seeks to learn the complex relationship between the
                 speech mixture and any specific speech source of
                 interest. DNN-based speech separation algorithms
                 outperform conventional statistics-based methods,
                 although they typically need a lot of processing and/or
                 a larger model size. This study presents a new
                 end-to-end speech separation network called
                 ESC-MASD-Net (effective speaker separation through
                 convolutional multi-view attention and SuDoRM-RF
                 network), which has relatively fewer model parameters
                 compared with the state-of-the-art speech separation
                 architectures. The network is partly inspired by the
                 SuDoRM-RF++ network, which uses multiple
                 time-resolution features with downsampling and
                 resampling for effective speech separation.
                 ESC-MASD-Net incorporates the multi-view attention and
                 residual conformer modules into SuDoRM-RF++.
                 Additionally, the U-Convolutional block in ESC-MASD-Net
                 is refined with a conformer layer. Experiments
                 conducted on the WHAM! dataset show that ESC-MASD-Net
                 outperforms SuDoRM-RF++ significantly in the SI-SDRi
                 metric. Furthermore, the use of the conformer layer has
                 also improved the performance of ESC-MASD-Net.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhang:2024:EDI,
  author =       "Jingzhe Zhang and Tiange Chen and Wenjie Gong and
                 Jiayue Liu and Jiangjie Chen",
  title =        "Exploring Data Input Problems in Mixed Reality
                 Environments: Proposal and Evaluation of Natural
                 Interaction Techniques",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "150",
  day =          "27",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050150",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/150",
  abstract =     "Data input within mixed reality environments poses
                 significant interaction challenges, notably in
                 immersive visual analytics applications. This study
                 assesses five numerical input techniques: three
                 benchmark methods (Touch-Slider, Keyboard,
                 Pinch-Slider) and two innovative multimodal techniques
                 (Bimanual Scaling, Gesture and Voice). An experimental
                 design was employed to compare these techniques' input
                 efficiency, accuracy, and user experience across
                 varying precision and distance conditions. The findings
                 reveal that multimodal techniques surpass slider
                 methods in input efficiency yet are comparable to
                 keyboards; the voice method excels in reducing
                 cognitive load but falls short in accuracy; and the
                 scaling method marginally leads in user satisfaction
                 but imposes a higher physical load. Furthermore, this
                 study outlines these techniques' pros and cons and
                 offers design guidelines and future research
                 directions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Calvagna:2024:BBR,
  author =       "Andrea Calvagna and Giovanni Marotta and Giuseppe
                 Pappalardo and Emiliano Tramontana",
  title =        "A Blockchain-Based Real-Time Power Balancing Service
                 for Trustless Renewable Energy Grids",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "5",
  pages =        "149",
  day =          "26",
  month =        apr,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16050149",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon May 27 07:17:16 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/5/149",
  abstract =     "We face a decentralized renewable energy production
                 scenario, where a large number of small energy
                 producers, i.e., prosumers, contribute to a common
                 distributor entity, who resells energy directly to
                 end-users. A major challenge for the distributor is to
                 ensure power stability, constantly balancing produced
                 vs consumed energy flows. In this context, being able
                 to provide quick restore actions in response to
                 unpredictable unbalancing events is a must, as
                 fluctuations are the norm for renewable energy sources.
                 To this aim, the high scalability and diversity of
                 sources are crucial requirements for the said balancing
                 to be actually manageable. In this study, we explored
                 the challenges and benefits of adopting a
                 blockchain-based software architecture as a scalable,
                 trustless interaction platform between prosumers' smart
                 energy meters and the distributor. Our developed
                 prototype accomplishes the energy load balancing
                 service via smart contracts deployed in a real
                 blockchain network with an increasing number of
                 simulated prosumers. We show that the blockchain-based
                 application managed to react in a timely manner to
                 energy unbalances for up to a few hundred prosumers.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lai:2024:ASR,
  author =       "Joel Weijia Lai",
  title =        "Adapting Self-Regulated Learning in an Age of
                 Generative Artificial Intelligence Chatbots",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "218",
  day =          "20",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060218",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/218",
  abstract =     "The increasing use of generative artificial
                 intelligence (GenAI) has led to a rise in conversations
                 about how teachers and students should adopt these
                 tools to enhance the learning process. Self-regulated
                 learning (SRL) research is important for addressing
                 this question. A popular form of GenAI is the large
                 language model chatbot, which allows users to seek
                 answers to their queries. This article seeks to adapt
                 current SRL models to understand student learning with
                 these chatbots. This is achieved by classifying the
                 prompts supplied by a learner to an educational chatbot
                 into learning actions and processes using the
                 process--action library. Subsequently, through process
                 mining, we can analyze these data to provide valuable
                 insights for learners, educators, instructional
                 designers, and researchers into the possible
                 applications of chatbots for SRL.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chen:2024:ODP,
  author =       "Shaolong Chen and Yunzi Dai and Liwei Liu and Xinting
                 Yu",
  title =        "Optimizing Data Parallelism for {FM}-Based Short-Read
                 Alignment on the Heterogeneous Non-Uniform Memory
                 Access Architectures",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "217",
  day =          "19",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060217",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/217",
  abstract =     "Sequence alignment is a critical factor in the variant
                 analysis of genomic research. Since the FM
                 (Ferrainas--Manzini) index was developed, it has proven
                 to be a model in a compact format with efficient
                 pattern matching and high-speed query searching, which
                 has attracted much research interest in the field of
                 sequence alignment. Such characteristics make it a
                 convenient tool for handling large-scale sequence
                 alignment projects executed with a small memory. In
                 bioinformatics, the massive success of next-generation
                 sequencing technology has led to an exponential growth
                 in genomic data, presenting a computational challenge
                 for sequence alignment. In addition, the use of a
                 heterogeneous computing system, composed of various
                 types of nodes, is prevalent in the field of HPC
                 (high-performance computing), which presents a
                 promising solution for sequence alignment. However,
                 conventional methodologies in short-read alignment are
                 limited in performance on current heterogeneous
                 computing infrastructures. Therefore, we developed a
                 parallel sequence alignment to investigate the
                 applicability of this approach in NUMA-based
                 (Non-Uniform Memory Access) heterogeneous architectures
                 against traditional alignment algorithms. This proposed
                 work combines the LF (longest-first) distribution
                 policy with the EP (enhanced partitioning) strategy for
                 effective load balancing and efficient parallelization
                 among heterogeneous architectures. The newly proposed
                 LF-EP-based FM aligner shows excellent efficiency and a
                 significant improvement over NUMA-based heterogeneous
                 computing platforms. We provide significantly improved
                 performance over several popular FM aligners in many
                 dimensions such as read length, sequence number,
                 sequence distance, alignment speedup, and result
                 quality. These resultant evaluation metrics cover the
                 quality assessment, complexity analysis, and speedup
                 evaluation of our approach. Utilizing the capabilities
                 of NUMA-based heterogeneous computing architectures,
                 our approach effectively provides a convenient solution
                 for large-scale short-read alignment in the
                 heterogeneous system.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Harutyunyan:2024:DCA,
  author =       "Ashot Harutyunyan and Arnak Poghosyan and Tigran
                 Bunarjyan and Andranik Haroyan and Marine Harutyunyan
                 and Lilit Harutyunyan and Nelson Baloian",
  title =        "Discovery of Cloud Applications from Logs",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "216",
  day =          "18",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060216",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/216",
  abstract =     "Continuous discovery and update of applications or
                 their boundaries running in cloud environments in an
                 automatic way is a highly required function of modern
                 data center operation solutions. Prior attempts to
                 address this problem within various products or
                 projects were/are applying rule-driven approaches or
                 machine learning techniques on specific types of
                 data--network traffic as well as property/configuration
                 data of infrastructure objects, which all have their
                 drawbacks in effectively identifying roles of those
                 resources. The current proposal (ADLog) leverages log
                 data of sources, which contain incomparably richer
                 contextual information, and demonstrates a reliable way
                 of discriminating application objects. Specifically,
                 using native constructs of VMware Aria Operations for
                 Logs in terms of event types and their distributions,
                 we group those entities, which then can be potentially
                 enriched with indicative tags automatically and
                 recommended for further management tasks and policies.
                 Our methods differentiate not only diverse kinds of
                 applications, but also their specific deployments, thus
                 providing hierarchical representation of the
                 applications in time and topology. For several
                 applications under Aria Ops management in our
                 experimental test bed, we discover those in terms of
                 similarity behavior of their components with a high
                 accuracy. The validation of the proposal paves the path
                 for an AI-driven solution in cloud management
                 scenarios.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Filho:2024:DTM,
  author =       "Vitor Hugo dos Santos Filho and Luis Maur{\'\i}cio
                 Martins de Resende and Joseane Pontes",
  title =        "Development of a Theoretical Model for Digital Risks
                 Arising from the Implementation of {Industry 4.0}
                 ({TMR-I4.0})",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "215",
  day =          "17",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060215",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/215",
  abstract =     "This study aims to develop a theoretical model for
                 digital risks arising from implementing Industry 4.0
                 (represented by the acronym TMR-I4.0). A systematic
                 literature review was initially conducted using the
                 Methodi Ordinatio methodology to map the principal
                 dimensions and digital risks associated with Industry
                 4.0 in order to achieve this objective. After
                 completing the nine steps of Methodi, a bibliographic
                 portfolio with 118 articles was obtained. These
                 articles were then subjected to content analysis using
                 QSR Nvivo {\reg} version 10 software to categorize
                 digital risks. The analysis resulted in the
                 identification of 9 dimensions and 43 digital risks.
                 The categorization of these risks allowed the
                 construction of maps showing the digital risks and
                 their impacts resulting from the implementation of
                 Industry 4.0. This study advances the literature by
                 proposing a comprehensive categorization of digital
                 risks associated with Industry 4.0, which resulted from
                 an exhaustive literature review. At the conclusion of
                 the study, based on the proposed Theoretical Risk Model
                 for Digital Risks arising from the implementation of
                 Industry 4.0, a research agenda for future studies will
                 be proposed, enabling other researchers to further
                 explore the landscape of digital risks in Industry
                 4.0.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Nunes:2024:AFM,
  author =       "Pedro Nunes and Eug{\'e}nio Rocha and Jos{\'e}
                 Santos",
  title =        "Adaptive Framework for Maintenance Scheduling Based on
                 Dynamic Preventive Intervals and Remaining Useful Life
                 Estimation",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "214",
  day =          "17",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060214",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/214",
  abstract =     "Data-based prognostic methods exploit sensor data to
                 forecast the remaining useful life (RUL) of industrial
                 settings to optimize the scheduling of maintenance
                 actions. However, implementing sensors may not be
                 cost-effective or practical for all components.
                 Traditional preventive approaches are not based on
                 sensor data; however, they schedule maintenance at
                 equally spaced intervals, which is not a cost-effective
                 approach since the distribution of the time between
                 failures changes with the degradation state of other
                 parts or changes in working conditions. This study
                 introduces a novel framework comprising two maintenance
                 scheduling strategies. In the absence of sensor data,
                 we propose a novel dynamic preventive policy that
                 adjusts intervention intervals based on the most recent
                 failure data. When sensor data are available, a method
                 for RUL prediction, designated k-LSTM-GFT, is enhanced
                 to dynamically account for RUL prediction uncertainty.
                 The results demonstrate that dynamic preventive
                 maintenance can yield cost reductions of up to 51.8\%
                 compared to conventional approaches. The predictive
                 approach optimizes the exploitation of RUL, achieving
                 costs that are only 3--5\% higher than the minimum cost
                 achievable while ensuring the safety of critical
                 systems since all of the failures are avoided.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fang:2024:LMC,
  author =       "Cheng Fang and Feifei Liang and Tianchi Li and
                 Fangheng Guan",
  title =        "Learning Modality Consistency and Difference
                 Information with Multitask Learning for Multimodal
                 Sentiment Analysis",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "213",
  day =          "17",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060213",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/213",
  abstract =     "The primary challenge in Multimodal sentiment analysis
                 (MSA) lies in developing robust joint representations
                 that can effectively learn mutual information from
                 diverse modalities. Previous research in this field
                 tends to rely on feature concatenation to obtain joint
                 representations. However, these approaches fail to
                 fully exploit interactive patterns to ensure
                 consistency and differentiation across different
                 modalities. To address this limitation, we propose a
                 novel framework for multimodal sentiment analysis,
                 named CDML (Consistency and Difference using a
                 Multitask Learning network). Specifically, CDML uses an
                 attention mechanism to assign the attention weights of
                 each modality efficiently. Adversarial training is used
                 to obtain consistent information between modalities.
                 Finally, the difference among the modalities is
                 acquired by the multitask learning framework.
                 Experiments on two benchmark MSA datasets, CMU-MOSI and
                 CMU-MOSEI, showcase that our proposed method
                 outperforms the seven existing approaches by at least
                 1.3\% for Acc-2 and 1.7\% for F1.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Garg:2024:IIM,
  author =       "Umang Garg and Santosh Kumar and Aniket Mahanti",
  title =        "{IMTIBOT}: an Intelligent Mitigation Technique for
                 {IoT} Botnets",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "212",
  day =          "17",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060212",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/212",
  abstract =     "The tremendous growth of the Internet of Things (IoT)
                 has gained a lot of attention in the global market. The
                 massive deployment of IoT is also inherent in various
                 security vulnerabilities, which become easy targets for
                 hackers. IoT botnets are one type of critical malware
                 that degrades the performance of the IoT network and is
                 difficult to detect by end-users. Although there are
                 several traditional IoT botnet mitigation techniques
                 such as access control, data encryption, and secured
                 device configuration, these traditional mitigation
                 techniques are difficult to apply due to normal traffic
                 behavior, similar packet transmission, and the
                 repetitive nature of IoT network traffic. Motivated by
                 botnet obfuscation, this article proposes an
                 intelligent mitigation technique for IoT botnets, named
                 IMTIBoT. Using this technique, we harnessed the
                 stacking of ensemble classifiers to build an
                 intelligent system. This stacking classifier technique
                 was tested using an experimental testbed of IoT nodes
                 and sensors. This system achieved an accuracy of 0.984,
                 with low latency.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Qian:2024:IPF,
  author =       "Jingshi Qian and Jiahe Li and Nobuyoshi Komuro and
                 Won-Suk Kim and Younghwan Yoo",
  title =        "Improved Particle Filter in Machine Learning-Based
                 {BLE} Fingerprinting Method to Reduce Indoor Location
                 Estimation Errors",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "211",
  day =          "15",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060211",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/211",
  abstract =     "Indoor position fingerprint-based location estimation
                 methods have been widely used by applications on
                 smartphones. In these localization estimation methods,
                 it is very popular to use the RSSI (Received Signal
                 Strength Indication) of signals to represent the
                 position fingerprint. This paper proposes the design of
                 a particle filter for reducing the estimation error of
                 the machine learning-based indoor BLE location
                 fingerprinting method. Unlike the general particle
                 filter, taking into account the distance, the proposed
                 system designs improved likelihood functions,
                 considering the coordinates based on fingerprint points
                 using mean and variance of RSSI values, combining the
                 particle filter with the k-NN (k-Nearest Neighbor)
                 algorithm to realize the reduction in indoor
                 positioning error. The initial position is estimated by
                 the position fingerprinting method based on the machine
                 learning method. By comparing the fingerprint method
                 based on k-NN with general particle filter processing,
                 and the fingerprint estimation method based on only
                 k-NN or SVM (Support Vector Machine), experiment
                 results showed that the proposed method has a smaller
                 minimum error and a better average error than the
                 conventional method.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2024:RDH,
  author =       "Xu Wang and Jui-Chuan Liu and Ching-Chun Chang and
                 Chin-Chen Chang",
  title =        "Reversible Data Hiding in Encrypted {3D} Mesh Models
                 Based on Multi-Group Partition and Closest Pair
                 Prediction",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "210",
  day =          "15",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060210",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/210",
  abstract =     "The reversible data hiding scheme in the encrypted
                 domain is a potential solution to the concerns
                 regarding user privacy in cloud applications. The 3D
                 mesh model is an emerging file format and is widely
                 used in engineering modeling, special effects, and
                 video games. However, studies on reversible data hiding
                 in encrypted 3D mesh models are still in the
                 preliminary stage. In this paper, two novel techniques,
                 multi-group partition (MGP) and closest pair prediction
                 (CPP), are proposed to improve performance. The MGP
                 technique adaptively classifies vertices into reference
                 and embeddable vertices, while the CPP technique
                 efficiently predicts embeddable vertices and generates
                 shorter recovery information to vacate more redundancy
                 for additional data embedding. Experimental results
                 indicate that the proposed scheme significantly
                 improves the embedding rate compared to
                 state-of-the-art schemes and can be used in real-time
                 applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhang:2024:AKA,
  author =       "Jiayi Zhang and Abdelkader Ouda and Raafat Abu-Rukba",
  title =        "Authentication and Key Agreement Protocol in Hybrid
                 Edge--Fog--Cloud Computing Enhanced by {5G} Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "209",
  day =          "14",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060209",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/209",
  abstract =     "The Internet of Things (IoT) has revolutionized
                 connected devices, with applications in healthcare,
                 data analytics, and smart cities. For time-sensitive
                 applications, 5G wireless networks provide
                 ultra-reliable low-latency communication (URLLC) and
                 fog computing offloads IoT processing. Integrating 5G
                 and fog computing can address cloud computing's
                 deficiencies, but security challenges remain,
                 especially in Authentication and Key Agreement aspects
                 due to the distributed and dynamic nature of fog
                 computing. This study presents an innovative mutual
                 Authentication and Key Agreement protocol that is
                 specifically tailored to meet the security needs of fog
                 computing in the context of the edge--fog--cloud
                 three-tier architecture, enhanced by the incorporation
                 of the 5G network. This study improves security in the
                 edge--fog--cloud context by introducing a stateless
                 authentication mechanism and conducting a comparative
                 analysis of the proposed protocol with well-known
                 alternatives, such as TLS 1.3, 5G-AKA, and various
                 handover protocols. The suggested approach has a total
                 transmission cost of only 1280 bits in the
                 authentication phase, which is approximately 30\% lower
                 than other protocols. In addition, the suggested
                 handover protocol only involves two signaling expenses.
                 The computational cost for handover authentication for
                 the edge user is significantly low, measuring 0.243 ms,
                 which is under 10\% of the computing costs of other
                 authentication protocols.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Cotti:2024:EEU,
  author =       "Luca Cotti and Davide Guizzardi and Barbara Rita
                 Barricelli and Daniela Fogli",
  title =        "Enabling End-User Development in Smart Homes: a
                 Machine Learning-Powered Digital Twin for Energy
                 Efficient Management",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "208",
  day =          "14",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060208",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/208",
  abstract =     "End-User Development has been proposed over the years
                 to allow end users to control and manage their Internet
                 of Things-based environments, such as smart homes. With
                 End-User Development, end users are able to create
                 trigger-action rules or routines to tailor the behavior
                 of their smart homes. However, the scientific research
                 proposed to date does not encompass methods that
                 evaluate the suitability of user-created routines in
                 terms of energy consumption. This paper proposes using
                 Machine Learning to build a Digital Twin of a smart
                 home that can predict the energy consumption of smart
                 appliances. The Digital Twin will allow end users to
                 simulate possible scenarios related to the creation of
                 routines. Simulations will be used to assess the
                 effects of the activation of appliances involved in the
                 routines under creation and possibly modify them to
                 save energy consumption according to the Digital Twin's
                 suggestions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Soares:2024:TNB,
  author =       "Rendrikson Soares and Andr{\'e} Ara{\'u}jo",
  title =        "Towards a New Business Model for Streaming Platforms
                 Using Blockchain Technology",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "207",
  day =          "13",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060207",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/207",
  abstract =     "Streaming platforms have revolutionized the digital
                 entertainment industry, but challenges and research
                 opportunities remain to be addressed. One current
                 concern is the lack of transparency in the business
                 model of video streaming platforms, which makes it
                 difficult for content creators to access viewing
                 metrics and receive payments without the intermediary
                 of third parties. Additionally, there is no way to
                 trace payment transactions. This article presents a
                 computational architecture based on blockchain
                 technology to enable transparency in audience
                 management and payments in video streaming platforms.
                 Smart contracts will define the business rules of the
                 streaming services, while middleware will integrate the
                 metadata of the streaming platforms with the proposed
                 computational solution. The proposed solution has been
                 validated through data transactions on different
                 blockchain networks and interviews with content
                 creators from video streaming platforms. The results
                 confirm the viability of the proposed solution in
                 enhancing transparency and auditability in the realm of
                 audience control services and payments on video
                 streaming platforms.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bagunaid:2024:VDP,
  author =       "Wala Bagunaid and Naveen Chilamkurti and Ahmad Salehi
                 Shahraki and Saeed Bamashmos",
  title =        "Visual Data and Pattern Analysis for Smart Education:
                 a Robust {DRL}-Based Early Warning System for Student
                 Performance Prediction",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "206",
  day =          "11",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060206",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/206",
  abstract =     "Artificial Intelligence (AI) and Deep Reinforcement
                 Learning (DRL) have revolutionised e-learning by
                 creating personalised, adaptive, and secure
                 environments. However, challenges such as privacy,
                 bias, and data limitations persist. E-FedCloud aims to
                 address these issues by providing more agile,
                 personalised, and secure e-learning experiences. This
                 study introduces E-FedCloud, an AI-assisted, adaptive
                 e-learning system that automates personalised
                 recommendations and tracking, thereby enhancing student
                 performance. It employs federated learning-based
                 authentication to ensure secure and private access for
                 both course instructors and students. Intelligent
                 Software Agents (ISAs) evaluate weekly student
                 engagement using the Shannon Entropy method,
                 classifying students into either engaged or not-engaged
                 clusters. E-FedCloud utilises weekly engagement status,
                 demographic information, and an innovative DRL-based
                 early warning system, specifically ID2QN, to predict
                 the performance of not-engaged students. Based on these
                 predictions, the system categorises students into three
                 groups: risk of dropping out, risk of scoring lower in
                 the final exam, and risk of failing the end exam. It
                 employs a multi-disciplinary ontology graph and an
                 attention-based capsule network for automated,
                 personalised recommendations. The system also
                 integrates performance tracking to enhance student
                 engagement. Data are securely stored on a blockchain
                 using the LWEA encryption method.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tan:2024:EES,
  author =       "Wuzheng Tan and Shenglong Du and Jian Weng",
  title =        "Enhancing Efficiency and Security in Unbalanced
                 {PSI-CA} Protocols through Cloud Computing and
                 Homomorphic Encryption in Mobile Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "205",
  day =          "7",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060205",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/205",
  abstract =     "Private Set Intersection Cardinality (PSI-CA) is a
                 cryptographic method in secure multi-party computation
                 that allows entities to identify the cardinality of the
                 intersection without revealing their private data.
                 Traditional approaches assume similar-sized datasets
                 and equal computational power, overlooking practical
                 imbalances. In real-world applications, dataset sizes
                 and computational capacities often vary, particularly
                 in Internet of Things and mobile scenarios where device
                 limitations restrict computational types. Traditional
                 PSI-CA protocols are inefficient here, as computational
                 and communication complexities correlate with the size
                 of larger datasets. Thus, adapting PSI-CA protocols to
                 these imbalances is crucial. This paper explores
                 unbalanced scenarios where one party (the receiver) has
                 a relatively small dataset and limited computational
                 power, while the other party (the sender) has a large
                 amount of data and strong computational
                 capabilities.This paper, based on the concept of
                 commutative encryption, introduces Cuckoo filter, cloud
                 computing technology, and homomorphic encryption, among
                 other technologies, to construct three novel solutions
                 for unbalanced Private Set Intersection Cardinality
                 (PSI-CA): an unbalanced PSI-CA protocol based on Cuckoo
                 filter, an unbalanced PSI-CA protocol based on
                 single-cloud assistance, and an unbalanced PSI-CA
                 protocol based on dual-cloud assistance. Depending on
                 performance and security requirements, different
                 protocols can be employed for various applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alshamari:2024:UEW,
  author =       "Majed A. Alshamari and Maha M. Althobaiti",
  title =        "Usability Evaluation of Wearable Smartwatches Using
                 Customized Heuristics and System Usability Scale
                 Score",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "204",
  day =          "6",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060204",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/204",
  abstract =     "The mobile and wearable nature of smartwatches poses
                 challenges in evaluating their usability. This paper
                 presents a study employing customized heuristic
                 evaluation and use of the system usability scale (SUS)
                 on four smartwatches, along with their mobile
                 applications. A total of 11 heuristics were developed
                 and validated by experts by combining Nielsen's
                 heuristic and Motti and Caines' heuristics. In this
                 study, 20 participants used the watches and
                 participated in the SUS survey. A total of 307
                 usability issues were reported by the evaluators. The
                 results of this study show that the Galaxy Watch 5
                 scored highest in terms of efficiency, ease of use,
                 features, and battery life compared to the other three
                 smartwatches and has fewer usability issues. The
                 results indicate that ease of use, features, and
                 flexibility are important usability attributes for
                 future smartwatches. The Galaxy Watch 5 received the
                 highest SUS score of 87.375. Both evaluation methods
                 showed no significant differences in results, and
                 customized heuristics were found to be useful for
                 smartwatch evaluation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Orrillo:2024:ERA,
  author =       "H{\'e}ctor Orrillo and Andr{\'e} Sabino and M{\'a}rio
                 Marques da Silva",
  title =        "Evaluation of Radio Access Protocols for {V2X} in {6G}
                 Scenario-Based Models",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "203",
  day =          "6",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060203",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/203",
  abstract =     "The expansion of mobile connectivity with the arrival
                 of 6G paves the way for the new Internet of Verticals
                 (6G-IoV), benefiting autonomous driving. This article
                 highlights the importance of vehicle-to-everything
                 (V2X) and vehicle-to-vehicle (V2V) communication in
                 improving road safety. Current technologies such as
                 IEEE 802.11p and LTE-V2X are being improved, while new
                 radio access technologies promise more reliable,
                 lower-latency communications. Moreover, 3GPP is
                 developing NR-V2X to improve the performance of
                 communications between vehicles, while IEEE proposes
                 the 802.11bd protocol, aiming for the greater
                 interoperability and detection of transmissions between
                 vehicles. Both new protocols are being developed and
                 improved to make autonomous driving more efficient.
                 This study analyzes and compares the performance of the
                 protocols mentioned, namely 802.11p, 802.11bd, LTE-V2X,
                 and NR-V2X. The contribution of this study is to
                 identify the most suitable protocol that meets the
                 requirements of V2V communications in autonomous
                 driving. The relevance of V2V communication has driven
                 intense research in the scientific community. Among the
                 various applications of V2V communication are
                 Cooperative Awareness, V2V Unicast Exchange, and V2V
                 Decentralized Environmental Notification, among others.
                 To this end, the performance of the Link Layer of these
                 protocols is evaluated and compared. Based on the
                 analysis of the results, it can be concluded that
                 NR-V2X outperforms IEEE 802.11bd in terms of
                 transmission latency (L) and data rate (DR). In terms
                 of the packet error rate (PER), it is shown that both
                 LTE-V2X and NR-V2X exhibit a lower PER compared to IEEE
                 protocols, especially as the distance between the
                 vehicles increases. This advantage becomes even more
                 significant in scenarios with greater congestion and
                 network interference.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Loor:2024:MSI,
  author =       "Fernando Loor and Veronica Gil-Costa and Mauricio
                 Marin",
  title =        "Metric Space Indices for Dynamic Optimization in a
                 Peer to Peer-Based Image Classification Crowdsourcing
                 Platform",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "202",
  day =          "6",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060202",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/202",
  abstract =     "Large-scale computer platforms that process users'
                 online requests must be capable of handling unexpected
                 spikes in arrival rates. These platforms, which are
                 composed of distributed components, can be configured
                 with parameters to ensure both the quality of the
                 results obtained for each request and low response
                 times. In this work, we propose a dynamic optimization
                 engine based on metric space indexing to address this
                 problem. The engine is integrated into the platform and
                 periodically monitors performance metrics to determine
                 whether new configuration parameter values need to be
                 computed. Our case study focuses on a P2P platform
                 designed for classifying crowdsourced images related to
                 natural disasters. We evaluate our approach under
                 scenarios with high and low workloads, comparing it
                 against alternative methods based on deep reinforcement
                 learning. The results show that our approach reduces
                 processing time by an average of 40\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rodrigues:2024:ICC,
  author =       "Gabriel Arquelau Pimenta Rodrigues and Andr{\'e} Luiz
                 Marques Serrano and Guilherme Fay Vergara and Robson de
                 Oliveira Albuquerque and Georges Daniel Amvame Nze",
  title =        "Impact, Compliance, and Countermeasures in Relation to
                 Data Breaches in Publicly Traded {U.S.} Companies",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "201",
  day =          "5",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060201",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/201",
  abstract =     "A data breach is the unauthorized disclosure of
                 sensitive personal data, and it impacts millions of
                 individuals annually in the United States, as reported
                 by Privacy Rights Clearinghouse. These breaches
                 jeopardize the physical safety of the individuals whose
                 data are exposed and result in substantial economic
                 losses for the affected companies. To diminish the
                 frequency and severity of data breaches in the future,
                 it is imperative to research their causes and explore
                 preventive measures. In pursuit of this goal, this
                 study considers a dataset of data breach incidents
                 affecting companies listed on the New York Stock
                 Exchange and NASDAQ. This dataset has been augmented
                 with additional information regarding the targeted
                 company. This paper employs statistical visualizations
                 of the data to clarify these incidents and assess their
                 consequences on the affected companies and individuals
                 whose data were compromised. We then propose mitigation
                 controls based on established frameworks such as the
                 NIST Cybersecurity Framework. Additionally, this paper
                 reviews the compliance scenario by examining the
                 relevant laws and regulations applicable to each case,
                 including SOX, HIPAA, GLBA, and PCI-DSS, and evaluates
                 the impacts of data breaches on stock market prices. We
                 also review guidelines for appropriately responding to
                 data leaks in the U.S., for compliance achievement and
                 cost reduction. By conducting this analysis, this work
                 aims to contribute to a comprehensive understanding of
                 data breaches and empower organizations to safeguard
                 against them proactively, improving the technical
                 quality of their basic services. To our knowledge, this
                 is the first paper to address compliance with data
                 protection regulations, security controls as
                 countermeasures, financial impacts on stock prices, and
                 incident response strategies. Although the discussion
                 is focused on publicly traded companies in the United
                 States, it may also apply to public and private
                 companies worldwide.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Javed:2024:ILM,
  author =       "Abbas Javed and Amna Ehtsham and Muhammad Jawad and
                 Muhammad Naeem Awais and Ayyaz-ul-Haq Qureshi and Hadi
                 Larijani",
  title =        "Implementation of Lightweight Machine Learning-Based
                 Intrusion Detection System on {IoT} Devices of Smart
                 Homes",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "200",
  day =          "5",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060200",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/200",
  abstract =     "Smart home devices, also known as IoT devices, provide
                 significant convenience; however, they also present
                 opportunities for attackers to jeopardize homeowners'
                 security and privacy. Securing these IoT devices is a
                 formidable challenge because of their limited
                 computational resources. Machine learning-based
                 intrusion detection systems (IDSs) have been
                 implemented on the edge and the cloud; however, IDSs
                 have not been embedded in IoT devices. To address this,
                 we propose a novel machine learning-based two-layered
                 IDS for smart home IoT devices, enhancing accuracy and
                 computational efficiency. The first layer of the
                 proposed IDS is deployed on a microcontroller-based
                 smart thermostat, which uploads the data to a website
                 hosted on a cloud server. The second layer of the IDS
                 is deployed on the cloud side for classification of
                 attacks. The proposed IDS can detect the threats with
                 an accuracy of 99.50\% at cloud level
                 (multiclassification). For real-time testing, we
                 implemented the Raspberry Pi 4-based adversary to
                 generate a dataset for man-in-the-middle (MITM) and
                 denial of service (DoS) attacks on smart thermostats.
                 The results show that the XGBoost-based IDS detects
                 MITM and DoS attacks in 3.51 ms on a smart thermostat
                 with an accuracy of 97.59\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{RuizVinals:2024:MFA,
  author =       "Carmen {Ruiz Vi{\~n}als} and Marta {Gil
                 Ib{\'a}{\~n}ez} and Jos{\'e} Luis {Del Olmo Arriaga}",
  title =        "Metaverse and Fashion: an Analysis of Consumer Online
                 Interest",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "199",
  day =          "4",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060199",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/199",
  abstract =     "Recent studies have demonstrated the value that the
                 Internet and web applications bring to businesses.
                 Among other tools are those that enable the analysis
                 and monitoring of searches, such as Google Trends,
                 which is currently used by the fashion industry to
                 guide experiential practices in a context of augmented
                 reality and/or virtual reality, and even to predict
                 purchasing behaviours through the metaverse. Data from
                 this tool provide insight into fashion consumer search
                 patterns. Understanding and managing this digital tool
                 is an essential factor in rethinking businesses'
                 marketing strategies. The aim of this study is to
                 analyse online user search behaviour by analysing and
                 monitoring the terms ``metaverse'' and ``fashion'' on
                 Google Trends. A quantitative descriptive
                 cross-sectional method was employed. The results show
                 that there is growing consumer interest in both
                 concepts on the Internet, despite the lack of
                 homogeneity in the behaviour of the five Google search
                 tools.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Vasilakopoulos:2024:UAI,
  author =       "Zisis Vasilakopoulos and Theocharis Tavantzis and
                 Rafail Promikyridis and Efthimios Tambouris",
  title =        "The Use of Artificial Intelligence in
                 {eParticipation}: Mapping Current Research",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "198",
  day =          "3",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060198",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/198",
  abstract =     "Electronic Participation (eParticipation) enables
                 citizens to engage in political and decision-making
                 processes using information and communication
                 technologies. As in many other fields, Artificial
                 Intelligence (AI) has recently started to dictate some
                 of the realities of eParticipation. As a result, an
                 increasing number of studies are investigating the use
                 of AI in eParticipation. The aim of this paper is to
                 map current research on the use of AI in
                 eParticipation. Following PRISMA methodology, the
                 authors identified 235 relevant papers in Web of
                 Science and Scopus and selected 46 studies for review.
                 For analysis purposes, an analysis framework was
                 constructed that combined eParticipation elements
                 (namely actors, activities, effects, contextual
                 factors, and evaluation) with AI elements (namely
                 areas, algorithms, and algorithm evaluation). The
                 results suggest that certain eParticipation actors and
                 activities, as well as AI areas and algorithms, have
                 attracted significant attention from researchers.
                 However, many more remain largely unexplored. The
                 findings can be of value to both academics looking for
                 unexplored research fields and practitioners looking
                 for empirical evidence on what works and what does
                 not.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Maher:2024:HEN,
  author =       "Carol Maher and Kylie A. Dankiw and Ben Singh and
                 Svetlana Bogomolova and Rachel G. Curtis",
  title =        "In-Home Evaluation of the Neo Care Artificial
                 Intelligence Sound-Based Fall Detection System",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "197",
  day =          "2",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060197",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/197",
  abstract =     "The Neo Care home monitoring system aims to detect
                 falls and other events using artificial intelligence.
                 This study evaluated Neo Care's accuracy and explored
                 user perceptions through a 12-week in-home trial with
                 18 households of adults aged 65+ years old at risk of
                 falls (mean age: 75.3 years old; 67\% female).
                 Participants logged events that were cross-referenced
                 with Neo Care logs to calculate sensitivity and
                 specificity for fall detection and response.
                 Qualitative interviews gathered in-depth user feedback.
                 During the trial, 28 falls/events were documented, with
                 12 eligible for analysis as others occurred outside the
                 home or when devices were offline. Neo Care was
                 activated 4939 times---4930 by everyday household
                 sounds and 9 by actual falls. Fall detection
                 sensitivity was 75.00\% and specificity 6.80\%. For
                 responding to falls, sensitivity was 62.50\% and
                 specificity 17.28\%. Users felt more secure with Neo
                 Care but identified needs for further calibration to
                 improve accuracy. Advantages included avoiding
                 wearables, while key challenges were misinterpreting
                 noises and occasional technical issues like going
                 offline. Suggested improvements were visual indicators,
                 trigger words, and outdoor capability. The study
                 demonstrated Neo Care's potential with modifications.
                 Users found it beneficial, but highlighted areas for
                 improvement. Real-world evaluations and user-centered
                 design are crucial for healthcare technology
                 development.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Baabdullah:2024:EFL,
  author =       "Tahani Baabdullah and Amani Alzahrani and Danda B.
                 Rawat and Chunmei Liu",
  title =        "Efficiency of Federated Learning and Blockchain in
                 Preserving Privacy and Enhancing the Performance of
                 Credit Card Fraud Detection ({CCFD}) Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "196",
  day =          "2",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060196",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/196",
  abstract =     "Increasing global credit card usage has elevated it to
                 a preferred payment method for daily transactions,
                 underscoring its significance in global financial
                 cybersecurity. This paper introduces a credit card
                 fraud detection (CCFD) system that integrates federated
                 learning (FL) with blockchain technology. The
                 experiment employs FL to establish a global learning
                 model on the cloud server, which transmits initial
                 parameters to individual local learning models on fog
                 nodes. With three banks (fog nodes) involved, each bank
                 trains its learning model locally, ensuring data
                 privacy, and subsequently sends back updated parameters
                 to the global learning model. Through the integration
                 of FL and blockchain, our system ensures privacy
                 preservation and data protection. We utilize three
                 machine learning and deep neural network learning
                 algorithms, RF, CNN, and LSTM, alongside deep
                 optimization techniques such as ADAM, SGD, and MSGD.
                 The SMOTE oversampling technique is also employed to
                 balance the dataset before model training. Our proposed
                 framework has demonstrated efficiency and effectiveness
                 in enhancing classification performance and prediction
                 accuracy.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Volosciuc:2024:GIB,
  author =       "Cristian Volosciuc and Razvan Bogdan and Bianca
                 Blajovan and Cristina St{\^a}ngaciu and Marius Marcu",
  title =        "{GreenLab}, an {IoT}-Based Small-Scale Smart
                 Greenhouse",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "195",
  day =          "31",
  month =        may,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060195",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/195",
  abstract =     "In an era of connectivity, the Internet of Things
                 introduces smart solutions for smart and sustainable
                 agriculture, bringing alternatives to overcome the food
                 crisis. Among these solutions, smart greenhouses
                 support crop and vegetable agriculture regardless of
                 season and cultivated area by carefully controlling and
                 managing parameters like temperature, air and soil
                 humidity, and light. Smart technologies have proven to
                 be successful tools for increasing agricultural
                 production at both the macro and micro levels, which is
                 an important step in streamlining small-scale
                 agriculture. This paper presents an experimental
                 Internet of Things-based small-scale greenhouse
                 prototype as a proof of concept for the benefits of
                 merging smart sensing, connectivity, IoT, and
                 mobile-based applications, for growing cultures. Our
                 proposed solution is cost-friendly and includes a
                 photovoltaic panel and a buffer battery for reducing
                 energy consumption costs, while also assuring
                 functionality during night and cloudy weather and a
                 mobile application for easy data visualization and
                 monitoring of the greenhouse.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhao:2024:RMM,
  author =       "Rui Zhao and Jutao Hao and Huan Huo",
  title =        "Research on Multi-Modal Pedestrian Detection and
                 Tracking Algorithm Based on Deep Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "194",
  day =          "31",
  month =        may,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060194",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/194",
  abstract =     "In the realm of intelligent transportation, pedestrian
                 detection has witnessed significant advancements.
                 However, it continues to grapple with challenging
                 issues, notably the detection of pedestrians in complex
                 lighting scenarios. Conventional visible light mode
                 imaging is profoundly affected by varying lighting
                 conditions. Under optimal daytime lighting, visibility
                 is enhanced, leading to superior pedestrian detection
                 outcomes. Conversely, under low-light conditions,
                 visible light mode imaging falters due to the
                 inadequate provision of pedestrian target information,
                 resulting in a marked decline in detection efficacy. In
                 this context, infrared light mode imaging emerges as a
                 valuable supplement, bolstering pedestrian information
                 provision. This paper delves into pedestrian detection
                 and tracking algorithms within a multi-modal image
                 framework grounded in deep learning methodologies.
                 Leveraging the YOLOv4 algorithm as a foundation,
                 augmented by a channel stack fusion module, a novel
                 multi-modal pedestrian detection algorithm tailored for
                 intelligent transportation is proposed. This algorithm
                 capitalizes on the fusion of visible and infrared light
                 mode image features to enhance pedestrian detection
                 performance amidst complex road environments.
                 Experimental findings demonstrate that compared to the
                 Visible-YOLOv4 algorithm, renowned for its high
                 performance, the proposed Double-YOLOv4-CSE algorithm
                 exhibits a notable improvement, boasting a 5.0\%
                 accuracy rate enhancement and a 6.9\% reduction in
                 logarithmic average missing rate. This research's goal
                 is to ensure that the algorithm can run smoothly even
                 on a low configuration 1080 Ti GPU and to improve the
                 algorithm's coverage at the application layer, making
                 it affordable and practical for both urban and rural
                 areas. This addresses the broader research problem
                 within the scope of smart cities and remote ends with
                 limited computational power.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Al-Amidie:2024:ESD,
  author =       "Muthana Al-Amidie and Laith Alzubaidi and Muhammad
                 Aminul Islam and Derek T. Anderson",
  title =        "Enhancing Sensor Data Imputation: {OWA}-Based Model
                 Aggregation for Missing Values",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "193",
  day =          "31",
  month =        may,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060193",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/193",
  abstract =     "Due to some limitations in the data collection process
                 caused either by human-related errors or by collection
                 electronics, sensors, and network connectivity-related
                 errors, the important values at some points could be
                 lost. However, a complete dataset is required for the
                 desired performance of the subsequent applications in
                 various fields like engineering, data science,
                 statistics, etc. An efficient data imputation technique
                 is desired to fill in the missing data values to
                 achieve completeness within the dataset. The fuzzy
                 integral is considered one of the most powerful
                 techniques for multi-source information fusion. It has
                 a wide range of applications in many real-world
                 decision-making problems that often require decisions
                 to be made with partially observable/available
                 information. To address this problem, algorithms impute
                 missing data with a representative sample or by
                 predicting the most likely value given the observed
                 data. In this article, we take a completely different
                 approach to the information fusion task in the ordered
                 weighted averaging (OWA) context. In particular, we
                 empirically explore for different distributions how the
                 weights/importance of the missing sources are
                 distributed across the observed inputs/sources. The
                 experimental results on the synthetic and real-world
                 datasets demonstrate the applicability of the proposed
                 methods.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yang:2024:PCA,
  author =       "Jindong Yang and Xiran Zhang and Wenhao Chen and Fei
                 Rong",
  title =        "{Prophet--CEEMDAN--ARBiLSTM}-Based Model for
                 Short-Term Load Forecasting",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "192",
  day =          "31",
  month =        may,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060192",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/192",
  abstract =     "Accurate short-term load forecasting (STLF) plays an
                 essential role in sustainable energy development.
                 Specifically, energy companies can efficiently plan and
                 manage their generation capacity, lessening resource
                 wastage and promoting the overall efficiency of power
                 resource utilization. However, existing models cannot
                 accurately capture the nonlinear features of
                 electricity data, leading to a decline in the
                 forecasting performance. To relieve this issue, this
                 paper designs an innovative load forecasting method,
                 named Prophet--CEEMDAN--ARBiLSTM, which consists of
                 Prophet, Complete Ensemble Empirical Mode Decomposition
                 with Adaptive Noise (CEEMDAN), and the residual
                 Bidirectional Long Short-Term Memory (BiLSTM) network.
                 Specifically, this paper firstly employs the Prophet
                 method to learn cyclic and trend features from input
                 data, aiming to discern the influence of these features
                 on the short-term electricity load. Then, the paper
                 adopts CEEMDAN to decompose the residual series and
                 yield components with distinct modalities. In the end,
                 this paper designs the advanced residual BiLSTM
                 (ARBiLSTM) block as the input of the above extracted
                 features to obtain the forecasting results. By
                 conducting multiple experiments on the New England
                 public dataset, it demonstrates that the
                 Prophet--CEEMDAN--ARBiLSTM method can achieve better
                 performance compared with the existing Prophet-based
                 ones.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ali:2024:HCN,
  author =       "Mohammad Imran Ali and Shahi Dost and Khurram Shehzad
                 Khattak and Muhammad Imran Khan and Riaz Muhammad",
  title =        "Harnessing the Cloud: a Novel Approach to Smart Solar
                 Plant Monitoring",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "191",
  day =          "29",
  month =        may,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060191",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/191",
  abstract =     "Renewable Energy Sources (RESs) such as hydro, wind,
                 and solar are merging as preferred alternatives to
                 fossil fuels. Among these RESs, solar energy is the
                 most ideal solution; it is gaining extensive interest
                 around the globe. However, due to solar energy's
                 intermittent nature and sensitivity to environmental
                 parameters (e.g., irradiance, dust, temperature, aging
                 and humidity), real-time solar plant monitoring is
                 imperative. This paper's contribution is to compare and
                 analyze current IoT trends and propose future research
                 directions. As a result, this will be instrumental in
                 the development of low-cost, real-time, scalable,
                 reliable, and power-optimized solar plant monitoring
                 systems. In this work, a comparative analysis has been
                 performed on proposed solutions using the existing
                 literature. This comparative analysis has been
                 conducted considering five aspects: computer boards,
                 sensors, communication, servers, and architectural
                 paradigms. IoT architectural paradigms employed have
                 been summarized and discussed with respect to
                 communication, application layers, and storage
                 capabilities. To facilitate enhanced IoT-based solar
                 monitoring, an edge computing paradigm has been
                 proposed. Suggestions are presented for the fabrication
                 of edge devices and nodes using optimum compute boards,
                 sensors, and communication modules. Different cloud
                 platforms have been explored, and it was concluded that
                 the public cloud platform Amazon Web Services is the
                 ideal solution. Artificial intelligence-based
                 techniques, methods, and outcomes are presented, which
                 can help in the monitoring, analysis, and management of
                 solar PV systems. As an outcome, this paper can be used
                 to help researchers and academics develop low-cost,
                 real-time, effective, scalable, and reliable solar
                 monitoring systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Paxinou:2024:TSA,
  author =       "Evgenia Paxinou and Georgios Feretzakis and Rozita
                 Tsoni and Dimitrios Karapiperis and Dimitrios Kalles
                 and Vassilios S. Verykios",
  title =        "Tracing Student Activity Patterns in E-Learning
                 Environments: Insights into Academic Performance",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "190",
  day =          "29",
  month =        may,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060190",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/190",
  abstract =     "In distance learning educational environments like
                 Moodle, students interact with their tutors, their
                 peers, and the provided educational material through
                 various means. Due to advancements in learning
                 analytics, students' transitions within Moodle generate
                 digital trace data that outline learners' self-directed
                 learning paths and reveal information about their
                 academic behavior within a course. These learning paths
                 can be depicted as sequences of transitions between
                 various states, such as completing quizzes, submitting
                 assignments, downloading files, and participating in
                 forum discussions, among others. Considering that a
                 specific learning path summarizes the students'
                 trajectory in a course during an academic year, we
                 analyzed data on students' actions extracted from
                 Moodle logs to investigate how the distribution of user
                 actions within different Moodle resources can impact
                 academic achievements. Our analysis was conducted using
                 a Markov Chain Model, whereby transition matrices were
                 constructed to identify steady states, and eigenvectors
                 were calculated. Correlations were explored between
                 specific states in users' eigenvectors and their final
                 grades, which were used as a proxy of academic
                 performance. Our findings offer valuable insights into
                 the relationship between student actions, link weight
                 vectors, and academic performance, in an attempt to
                 optimize students' learning paths, tutors' guidance,
                 and course structures in the Moodle environment.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2024:DST,
  author =       "Dong Wang and Hongji Yang and Hua Zhou",
  title =        "Dynamic Spatial--Temporal Self-Attention Network for
                 Traffic Flow Prediction",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "6",
  pages =        "189",
  day =          "25",
  month =        may,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16060189",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Tue Jul 2 10:12:15 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/6/189",
  abstract =     "Traffic flow prediction is considered to be one of the
                 fundamental technologies in intelligent transportation
                 systems (ITSs) with a tremendous application prospect.
                 Unlike traditional time series analysis tasks, the key
                 challenge in traffic flow prediction lies in
                 effectively modelling the highly complex and dynamic
                 spatiotemporal dependencies within the traffic data. In
                 recent years, researchers have proposed various methods
                 to enhance the accuracy of traffic flow prediction, but
                 certain issues still persist. For instance, some
                 methods rely on specific static assumptions, failing to
                 adequately simulate the dynamic changes in the data,
                 thus limiting their modelling capacity. On the other
                 hand, some approaches inadequately capture the
                 spatiotemporal dependencies, resulting in the omission
                 of crucial information and leading to unsatisfactory
                 prediction outcomes. To address these challenges, this
                 paper proposes a model called the Dynamic
                 Spatial--Temporal Self-Attention Network (DSTSAN).
                 Firstly, this research enhances the interaction between
                 different dimension features in the traffic data
                 through a feature augmentation module, thereby
                 improving the model's representational capacity.
                 Subsequently, the current investigation introduces two
                 masking matrices: one captures local spatial
                 dependencies and the other captures global spatial
                 dependencies, based on the spatial self-attention
                 module. Finally, the methodology employs a temporal
                 self-attention module to capture and integrate the
                 dynamic temporal dependencies of traffic data. We
                 designed experiments using historical data from the
                 previous hour to predict traffic flow conditions in the
                 hour ahead, and the experiments were extensively
                 compared to the DSTSAN model, with 11 baseline methods
                 using four real-world datasets. The results demonstrate
                 the effectiveness and superiority of the proposed
                 approach.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ruiu:2024:DIE,
  author =       "Pietro Ruiu and Salvatore Saiu and Enrico Grosso",
  title =        "Digital Identity in the {EU}: Promoting {eIDAS}
                 Solutions Based on Biometrics",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "28",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070228",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/228",
  abstract =     "Today, more than ever before, technological progress
                 is evolving rapidly, and in the absence of adequate
                 regulatory frameworks, the big players in the digital
                 market (the so-called Big Techs) are exploiting
                 personal data (name, address, telephone numbers) and
                 private data (political opinions, religious beliefs,
                 financial information, or health status) in an
                 uncontrolled manner. A crucial role in this scenario is
                 played by the weakness of international regulatory
                 frameworks due to the slow response time of legislators
                 who are incapable, from a regulatory point of view, of
                 keeping pace with technological evolution and
                 responding to the new requirements coming from the
                 social context, which is increasingly characterized by
                 the pervasive presence of new technologies, such as
                 smartphones and wearable devices. At the European
                 level, the General Data Protection Regulation (GDPR)
                 and the Regulation on Electronic Identification,
                 Authentication and Trust Services (eIDAS) have marked a
                 significant turning point in the regulatory landscape.
                 However, the mechanisms proposed present clear security
                 issues, particularly in light of emerging concepts such
                 as digital identity. Moreover, despite the centrality
                 of biometric issues within the European regulatory
                 framework and the practical introduction of biometric
                 data within electronic national identity (eID) cards,
                 there are still no efforts to use biometric features
                 for the identification and authentication of a person
                 in a digital context. This paper clarifies and
                 precisely defines the potential impact of
                 biometric-based digital identity and hypothesizes its
                 practical use for accessing network-based services and
                 applications commonly used in daily life. Using the
                 Italian eID card as a model, an authentication scheme
                 leveraging biometric data is proposed, ensuring full
                 compliance with GDPR and eIDAS regulations. The
                 findings suggest that such a scheme can significantly
                 improve the security and reliability of electronic
                 identification systems, promoting broader adoption of
                 eIDAS solutions.",
  acknowledgement = ack-nhfb,
  articleno =    "228",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Henriques:2024:CAF,
  author =       "Lucas Henriques and Felipe Prata Lima and Cecilia
                 Castro",
  title =        "Combining Advanced Feature-Selection Methods to
                 Uncover Atypical Energy-Consumption Patterns",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "28",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070229",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/229",
  abstract =     "Understanding household energy-consumption patterns is
                 essential for developing effective energy-conservation
                 strategies. This study aims to identify `out-profiled'
                 consumers---households that exhibit atypical
                 energy-usage behaviors---by applying four distinct
                 feature-selection methodologies. Specifically, we
                 utilized the chi-square independence test to assess
                 feature independence, recursive feature elimination
                 with multinomial logistic regression (RFE-MLR) to
                 identify optimal feature subsets, random forest (RF) to
                 determine feature importance, and a combined fuzzy
                 rough feature selection with fuzzy rough nearest
                 neighbors (FRFS-FRNN) for handling uncertainty and
                 imprecision in data. These methods were applied to a
                 dataset based on a survey of 383 households in Brazil,
                 capturing various factors such as household size,
                 income levels, geographical location, and appliance
                 usage. Our analysis revealed that key features such as
                 the number of people in the household, heating and air
                 conditioning usage, and income levels significantly
                 influence energy consumption. The novelty of our work
                 lies in the comprehensive application of these advanced
                 feature-selection techniques to identify atypical
                 consumption patterns in a specific regional context.
                 The results showed that households without heating and
                 air conditioning equipment in medium- or
                 high-consumption profiles, and those with lower- or
                 medium-income levels in medium- or high-consumption
                 profiles, were considered out-profiled. These findings
                 provide actionable insights for energy providers and
                 policymakers, enabling the design of targeted
                 energy-conservation strategies. This study demonstrates
                 the importance of tailored approaches in promoting
                 sustainable energy consumption and highlights notable
                 deviations in energy-use patterns, offering a
                 foundation for future research and policy
                 development.",
  acknowledgement = ack-nhfb,
  articleno =    "229",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ahmad:2024:TCI,
  author =       "Ehsan Ahmad and Brian Larson and Abdulbasid Banga",
  title =        "Trusted Composition of {Internet of Medical Things}
                 over Imperfect Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "28",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070230",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/230",
  abstract =     "The Internet of Medical Things (IoMT) represents a
                 specialized domain within the Internet of Things,
                 focusing on medical devices that require regulatory
                 approval to ensure patient safety. Trusted composition
                 of IoMT systems aims to ensure high assurance of the
                 entire composed system, despite potential variability
                 in the assurance levels of individual components.
                 Achieving this trustworthiness in IoMT systems,
                 especially when using less-assured, commercial,
                 off-the-shelf networks like Ethernet and WiFi, presents
                 a significant challenge. To address this challenge,
                 this paper advocates a systematic approach that
                 leverages the Architecture Analysis \& Design Language
                 (AADL) along with Behavior Language for Embedded
                 Systems with Software (BLESS) specification and
                 implementation. This approach aims to provide high
                 assurance on critical components through formal
                 verification, while using less-assured components in a
                 manner that maintains overall system determinism and
                 reliability. A clinical case study involving an
                 automated opioid infusion monitoring IoMT system is
                 presented to illustrate the application of the proposed
                 approach. Through this case study, the effectiveness of
                 the systemic approach in achieving trusted composition
                 of heterogeneous medical devices over less-assured
                 networks is demonstrated.",
  acknowledgement = ack-nhfb,
  articleno =    "230",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Stamatopoulos:2024:EAC,
  author =       "Dionysios Stamatopoulos and Menelaos Katsantonis and
                 Panagiotis Fouliras and Ioannis Mavridis",
  title =        "Exploring the Architectural Composition of Cyber
                 Ranges: a Systematic Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "28",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070231",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/231",
  abstract =     "In light of the ever-increasing complexity of
                 cyber--physical systems (CPSs) and information
                 technology networking systems (ITNs), cyber ranges
                 (CRs) have emerged as a promising solution by providing
                 theoretical and practical cybersecurity knowledge for
                 participants' skill improvement toward a safe work
                 environment. This research adds to the extant
                 respective literature, exploring the architectural
                 composition of CRs. It aims to improve the
                 understanding of their design and how they are
                 deployed, expanding skill levels in constructing better
                 CRs. Our research follows the PRISMA methodology
                 guidelines for transparency, which includes a search
                 flow of articles based on specific criteria and quality
                 valuation of selected articles. To extract valuable
                 research datasets, we identify keyword co-occurrences
                 that selected articles are concentrated on. In the
                 context of literature evidence, we identify key
                 attributes and trends, providing details of CRs
                 concerning their architectural composition and
                 underlying infrastructure, along with today's
                 challenges and future research directions. A total of
                 102 research articles' qualitative analyses reveal a
                 lack of adequate architecture examination when CR
                 elements and services interoperate with other CR
                 elements and services participating, leading to gaps
                 that increase the administration burden. We posit that
                 the results of this study can be leveraged as a
                 baseline for future enhancements toward the development
                 of CRs.",
  acknowledgement = ack-nhfb,
  articleno =    "231",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Cocco:2024:DTC,
  author =       "Luisanna Cocco and Roberto Tonelli",
  title =        "Digital Transformation in the Construction Sector:
                 Blockchain, {BIM} and {SSI} for a More Sustainable and
                 Transparent System",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "28",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070232",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/232",
  abstract =     "This article presents a model built for deep
                 digitalization in the construction industry and for
                 making building information modeling achieve a greater
                 level of transparency, verifiability and effectiveness
                 for the benefit of all stakeholders. Thanks to
                 blockchain and the self-sovereign identity paradigm,
                 the model guarantees data integrity and transaction
                 reliability, enabling the generation of more efficient
                 and productive businesses. The model includes a
                 decentralized application for notarization of the
                 information flow in building information modeling
                 processes; the application is implemented and tested on
                 a local blockchain. The proposed model represents a
                 so-called digital twin and is, hence, a huge system
                 that manages all the information flow associated with a
                 building throughout its life cycle, returning to
                 individuals the control of their own data. In this
                 model, all stakeholders operate based on so-called
                 decentralized identifiers and DID documents, which
                 store on-chain the fingerprints of the information flow
                 in a common data environment.",
  acknowledgement = ack-nhfb,
  articleno =    "232",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Pieska:2024:PIN,
  author =       "Marcus Pieska and Andreas Kassler and Anna Brunstrom
                 and Veselin Rakocevic and Markus Amend",
  title =        "Performance Impact of Nested Congestion Control on
                 Transport-Layer Multipath Tunneling",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "28",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070233",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/233",
  abstract =     "Multipath wireless access aims to seamlessly aggregate
                 multiple access networks to increase data rates and
                 decrease latency. It is currently being standardized
                 through the ATSSS architectural framework as part of
                 the fifth-generation (5G) cellular networks. However,
                 facilitating efficient multi-access communication in
                 next-generation wireless networks poses several
                 challenges due to the complex interplay between
                 congestion control (CC) and packet scheduling. Given
                 that enhanced ATSSS steering functions for traffic
                 splitting advocate the utilization of multi-access
                 tunnels using congestion-controlled multipath network
                 protocols between user equipment and a proxy,
                 addressing the issue of nested CC becomes imperative.
                 In this paper, we evaluate the impact of such nested
                 congestion control loops on throughput over
                 multi-access tunnels using the recently introduced
                 Multipath DCCP (MP-DCCP) tunneling framework. We
                 evaluate different combinations of endpoint and tunnel
                 CC algorithms, including BBR, BBRv2, CUBIC, and
                 NewReno. Using the Cheapest Path First scheduler, we
                 quantify and analyze the impact of the following on the
                 performance of tunnel-based multipath: (1) the location
                 of the multi-access proxy relative to the user; (2) the
                 bottleneck buffer size, and (3) the choice of the
                 congestion control algorithms. Furthermore, our
                 findings demonstrate the superior performance of BBRv2
                 as a tunnel CC algorithm.",
  acknowledgement = ack-nhfb,
  articleno =    "233",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Qian:2024:SIS,
  author =       "Mian Qian and Cheng Qian and Guobin Xu and Pu Tian and
                 Wei Yu",
  title =        "Smart Irrigation Systems from Cyber--Physical
                 Perspective: State of Art and Future Directions",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "29",
  month =        jun,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070234",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/234",
  abstract =     "Irrigation refers to supplying water to soil through
                 pipes, pumps, and spraying systems to ensure even
                 distribution across the field. In traditional farming
                 or gardening, the setup and usage of an agricultural
                 irrigation system solely rely on the personal
                 experience of farmers. The Food and Agriculture
                 Organization of the United Nations (UN) has projected
                 that by 2030, developing countries will expand their
                 irrigated areas by 34\%, while water consumption will
                 only be up 14\%. This discrepancy highlights the
                 importance of accurately monitoring water flow and
                 volume rather than people's rough estimations. The
                 smart irrigation systems, a key subsystem of smart
                 agriculture known as the cyber--physical system (CPS)
                 in the agriculture domain, automate the administration
                 of water flow, volume, and timing via using
                 cutting-edge technologies, especially the Internet of
                 Things (IoT) technology, to solve the challenges. This
                 study explores a comprehensive three-dimensional
                 problem space to thoroughly analyze the IoT's
                 applications in irrigation systems. Our framework
                 encompasses several critical domains in smart
                 irrigation systems. These domains include soil science,
                 sensor technology, communication protocols, data
                 analysis techniques, and the practical implementations
                 of automated irrigation systems, such as remote
                 monitoring, autonomous operation, and intelligent
                 decision-making processes. Finally, we discuss a few
                 challenges and outline future research directions in
                 this promising field.",
  acknowledgement = ack-nhfb,
  articleno =    "234",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sun:2024:PCO,
  author =       "Enbo Sun and Jiaxuan Han and Yiquan Li and Cheng
                 Huang",
  title =        "A Packet Content-Oriented Remote Code Execution Attack
                 Payload Detection Model",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "2",
  month =        jul,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070235",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/235",
  abstract =     "In recent years, various Remote Code Execution
                 vulnerabilities on the Internet have been exposed
                 frequently; thus, more and more security researchers
                 have begun to pay attention to the detection of Remote
                 Code Execution attacks. In this paper, we focus on
                 three kinds of common Remote Code Execution attacks:
                 XML External Entity, Expression Language Injection, and
                 Insecure Deserialization. We propose a packet
                 content-oriented Remote Code Execution attack payload
                 detection model. For the XML External Entity attack, we
                 propose an algorithm to construct the use-definition
                 chain of XML entities, and implement detection based on
                 the integrity of the chain and the behavior of the
                 chain's tail node. For the Expression Language
                 Injection and Insecure Deserialization attack, we
                 extract 34 features to represent the string operation
                 and the use of sensitive classes/methods in the code,
                 and then train a machine learning model to implement
                 detection. At the same time, we build a dataset to
                 evaluate the effect of the proposed model. The
                 evaluation results show that the model performs well in
                 detecting XML External Entity attacks, achieving a
                 precision of 0.85 and a recall of 0.94. Similarly, the
                 model performs well in detecting Expression Language
                 Injection and Insecure Deserialization attacks,
                 achieving a precision of 0.99 and a recall of 0.88.",
  acknowledgement = ack-nhfb,
  articleno =    "235",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mottura:2024:DAC,
  author =       "Stefano Mottura",
  title =        "Does Anyone Care about the Opinion of People on
                 Participating in a {``Social''} Metaverse? {A} Review
                 and a Draft Proposal for a Surveying Tool",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "2",
  month =        jul,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070236",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/236",
  abstract =     "In recent years, the attention paid to the metaverse
                 in the scientific world has increased; the hottest
                 topics include system architecture and enabling
                 technologies, as well as business, privacy, ethical,
                 and security issues. On the other side, at the
                 mainstream level, it is well known that the company
                 Meta (formerly Facebook) is striving to realize its
                 interpretation of a ``social'' metaverse. As Meta is a
                 big leader of social media, it is reasonable to guess
                 that, in the future, users will participate in a new
                 social platform, such as that which the company is
                 building by depicting unlimited and engaging
                 opportunities. Regardless of Meta, we ask what the
                 opinion of people is about this possible future
                 scenario. A literature search of previous works about
                 this topic has been done; the few results we found were
                 not properly on topic and showed heterogeneous content.
                 A survey on interpretations of the metaverse of major
                 information and communication technologies (ICT)
                 companies that impact the consumer world was
                 undertaken; the results show that Meta is the most
                 prominent company with the mission of building a
                 ''social'' metaverse worldwide. Finally, a draft of a
                 tool for assessing the predilection of people for a
                 ``social'' metaverse, based on various facets of the
                 future social platform, is proposed.",
  acknowledgement = ack-nhfb,
  articleno =    "236",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Anton:2024:SBT,
  author =       "Simon D. Duque Anton",
  title =        "Software-Bus-Toolchain ({SBT}): Introducing a
                 Versatile Method for Quickly Implementing
                 {(I)IoT}-Scenarios",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "3",
  month =        jul,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070237",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/237",
  abstract =     "The Internet of Things (IoT) has become ubiquitous.
                 IoT devices are applied in a multitude of applications,
                 e.g., in smart home scenarios, building automation,
                 smart energy and smart cities, healthcare, and
                 industrial environments. Fast and efficient
                 implementation and roll-out of IoT devices is a
                 critical factor for successs and acceptance of IoT
                 devices. At the same time, the variety of hardware
                 platforms that can be used for IoT applications, as
                 well as the number of IoT orchestration platforms is
                 increasing. Finding the right combination of tooling
                 and hardware is not trivial, but essential for building
                 applications that provide value. In this work, a
                 Software-Bus-Toolchain (SBT) is introduced that
                 encapsulates firmware design, data point definition,
                 and communication protocol usage. Furthermore, an IoT
                 control platform is provided to control and evaluate
                 the IoT modules. Thus, using the SBT, solely the
                 business logic has to be designed, while the
                 hardware-design is automated to a high degree. Usage of
                 the Zephyr framework allows the interchange of hardware
                 modules, while interfaces provide easy adaption of data
                 points and communication capabilities. The
                 implementation of interfaces to the IoT-platform as
                 well as to the communication layer provides a universal
                 usage of logic and data elements. The SBT is evaluated
                 in two application scenarios, where its flexible nature
                 is shown.",
  acknowledgement = ack-nhfb,
  articleno =    "237",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Elallid:2024:EAD,
  author =       "Badr {Ben Elallid} and Nabil Benamar and Miloud Bagaa
                 and Yassine Hadjadj-Aoul",
  title =        "Enhancing Autonomous Driving Navigation Using Soft
                 Actor-Critic",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "4",
  month =        jul,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070238",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/238",
  abstract =     "Autonomous vehicles have gained extensive attention in
                 recent years, both in academia and industry. For these
                 self-driving vehicles, decision-making in urban
                 environments poses significant challenges due to the
                 unpredictable behavior of traffic participants and
                 intricate road layouts. While existing decision-making
                 approaches based on Deep Reinforcement Learning (DRL)
                 show potential for tackling urban driving situations,
                 they suffer from slow convergence, especially in
                 complex scenarios with high mobility. In this paper, we
                 present a new approach based on the Soft Actor-Critic
                 (SAC) algorithm to control the autonomous vehicle to
                 enter roundabouts smoothly and safely and ensure it
                 reaches its destination without delay. For this, we
                 introduce a destination vector concatenated with
                 extracted features using Convolutional Neural Networks
                 (CNN). To evaluate the performance of our model, we
                 conducted extensive experiments in the CARLA simulator
                 and compared it with the Deep Q-Network (DQN) and
                 Proximal Policy Optimization (PPO) models. Qualitative
                 results reveal that our model converges rapidly and
                 achieves a high success rate in scenarios with high
                 traffic compared to the DQN and PPO models.",
  acknowledgement = ack-nhfb,
  articleno =    "238",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gupta:2024:TAC,
  author =       "Ragini Gupta and Beitong Tian and Yaohui Wang and
                 Klara Nahrstedt",
  title =        "{TWIN-ADAPT}: Continuous Learning for Digital
                 Twin-Enabled Online Anomaly Classification in
                 {IoT}-Driven Smart Labs",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "4",
  month =        jul,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070239",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/239",
  abstract =     "In the rapidly evolving landscape of scientific
                 semiconductor laboratories (commonly known as,
                 cleanrooms), integrated with Internet of Things (IoT)
                 technology and Cyber-Physical Systems (CPSs), several
                 factors including operational changes, sensor aging,
                 software updates and the introduction of new processes
                 or equipment can lead to dynamic and non-stationary
                 data distributions in evolving data streams. This
                 phenomenon, known as concept drift, poses a substantial
                 challenge for traditional data-driven digital twin
                 static machine learning (ML) models for anomaly
                 detection and classification. Subsequently, the drift
                 in normal and anomalous data distributions over time
                 causes the model performance to decay, resulting in
                 high false alarm rates and missed anomalies. To address
                 this issue, we present TWIN-ADAPT, a continuous
                 learning model within a digital twin framework designed
                 to dynamically update and optimize its anomaly
                 classification algorithm in response to changing data
                 conditions. This model is evaluated against
                 state-of-the-art concept drift adaptation models and
                 tested under simulated drift scenarios using diverse
                 noise distributions to mimic real-world distribution
                 shift in anomalies. TWIN-ADAPT is applied to three
                 critical CPS datasets of Smart Manufacturing Labs (also
                 known as ``Cleanrooms''): Fumehood, Lithography Unit
                 and Vacuum Pump. The evaluation results demonstrate
                 that TWIN-ADAPT's continual learning model for
                 optimized and adaptive anomaly classification achieves
                 a high accuracy and F1 score of 96.97\% and 0.97,
                 respectively, on the Fumehood CPS dataset, showing an
                 average performance improvement of 0.57\% over the
                 offline model. For the Lithography and Vacuum Pump
                 datasets, TWIN-ADAPT achieves an average accuracy of
                 69.26\% and 71.92\%, respectively, with performance
                 improvements of 75.60\% and 10.42\% over the offline
                 model. These significant improvements highlight the
                 efficacy of TWIN-ADAPT's adaptive capabilities.
                 Additionally, TWIN-ADAPT shows a very competitive
                 performance when compared with other benchmark drift
                 adaptation algorithms. This performance demonstrates
                 TWIN-ADAPT's robustness across different modalities and
                 datasets, confirming its suitability for any IoT-driven
                 CPS framework managing diverse data distributions in
                 real time streams. Its adaptability and effectiveness
                 make it a versatile tool for dynamic industrial
                 settings.",
  acknowledgement = ack-nhfb,
  articleno =    "239",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ostrikova:2024:DSS,
  author =       "Darya Ostrikova and Elizaveta Golos and Vitalii
                 Beschastnyi and Egor Machnev and Yuliya Gaidamaka and
                 Konstantin Samouylov",
  title =        "Dynamic {SNR}, Spectral Efficiency, and Rate
                 Characterization in {5G\slash 6G} {mmWave\slash
                 sub-THz} Systems with Macro- and Micro-Mobilities",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "6",
  month =        jul,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070240",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/240",
  abstract =     "The performance of 5G/6G cellular systems operating in
                 millimeter wave (mmWave, 30--100 GHz) and sub-terahertz
                 (sub-THz, 100--300 GHz) bands is conventionally
                 assessed by utilizing the static distributions of user
                 locations. The rationale is that the use of the beam
                 tracking procedure allows for keeping the beams of a
                 base station (BS) and user equipment (UE) aligned at
                 all times. However, by introducing 3GPP Reduced
                 Capability (RedCap) UEs utilizing the Radio Resource
                 Management (RRM) Relaxation procedure, this may no
                 longer be the case, as UEs are allowed to skip
                 synchronization signal blocks (SSB) to improve energy
                 efficiency. Thus, to characterize the performance of
                 such UEs, methods explicitly accounting for UE mobility
                 are needed. In this paper, we will utilize the tools of
                 the stochastic geometry and random walk theory to
                 derive signal-to-noise ratio (SNR), spectral
                 efficiency, and rate as an explicit function of time by
                 accounting for mmWave/sub-THZ specifics, including
                 realistic directional antenna radiation patterns and
                 micro- and macro-mobilities causing dynamic antenna
                 misalignment. Different from other studies in the field
                 that consider time-averaged performance measures, these
                 metrics are obtained as an explicit function of time.
                 Our numerical results illustrate that the
                 macro-mobility specifies the overall trend of the
                 time-dependent spectral efficiency, while local
                 dynamics at 1--3 s scales are mainly governed by
                 micro-mobility. The difference between spectral
                 efficiency corresponding to perfectly synchronized UE
                 and BS antennas and time-dependent spectral efficiency
                 in a completely desynchronized system is rather
                 negligible for realistic cell coverages and stays
                 within approximately 5--10\% for a wide range of system
                 parameters. These conclusions are not affected by the
                 utilized antenna array at the BS side. However,
                 accounting for realistic radiation patterns is critical
                 for a time-dependent performance analysis of 5G/6G
                 mmWave/sub-THz systems.",
  acknowledgement = ack-nhfb,
  articleno =    "240",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Siachos:2024:EAI,
  author =       "Ilias Siachos and Nikos Karacapilidis",
  title =        "Explainable Artificial Intelligence Methods to Enhance
                 Transparency and Trust in Digital Deliberation
                 Settings",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "6",
  month =        jul,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070241",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/241",
  abstract =     "Digital deliberation has been steadily growing in
                 recent years, enabling citizens from different
                 geographical locations and diverse opinions and
                 expertise to participate in policy-making processes.
                 Software platforms aiming to support digital
                 deliberation usually suffer from information overload,
                 due to the large amount of feedback that is often
                 provided. While Machine Learning and Natural Language
                 Processing techniques can alleviate this drawback,
                 their complex structure discourages users from trusting
                 their results. This paper proposes two Explainable
                 Artificial Intelligence models to enhance transparency
                 and trust in the modus operandi of the above
                 techniques, which concern the processes of clustering
                 and summarization of citizens' feedback that has been
                 uploaded on a digital deliberation platform.",
  acknowledgement = ack-nhfb,
  articleno =    "241",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Younis:2024:ECN,
  author =       "Samir A. Younis and Dalia Sobhy and Noha S. Tawfik",
  title =        "Evaluating Convolutional Neural Networks and Vision
                 Transformers for Baby Cry Sound Analysis",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "7",
  month =        jul,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070242",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/242",
  abstract =     "Crying is a newborn's main way of communicating.
                 Despite their apparent similarity, newborn cries are
                 physically generated and have distinct characteristics.
                 Experienced medical professionals, nurses, and parents
                 are able to recognize these variations based on their
                 prior interactions. Nonetheless, interpreting a baby's
                 cries can be challenging for carers, first-time
                 parents, and inexperienced paediatricians. This paper
                 uses advanced deep learning techniques to propose a
                 novel approach for baby cry classification. This study
                 aims to accurately classify different cry types
                 associated with everyday infant needs, including
                 hunger, discomfort, pain, tiredness, and the need for
                 burping. The proposed model achieves an accuracy of
                 98.33\%, surpassing the performance of existing studies
                 in the field. IoT-enabled sensors are utilized to
                 capture cry signals in real time, ensuring continuous
                 and reliable monitoring of the infant's acoustic
                 environment. This integration of IoT technology with
                 deep learning enhances the system's responsiveness and
                 accuracy. Our study highlights the significance of
                 accurate cry classification in understanding and
                 meeting the needs of infants and its potential impact
                 on improving infant care practices. The methodology,
                 including the dataset, preprocessing techniques, and
                 architecture of the deep learning model, is described.
                 The results demonstrate the performance of the proposed
                 model, and the discussion analyzes the factors
                 contributing to its high accuracy.",
  acknowledgement = ack-nhfb,
  articleno =    "242",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ahmed:2024:TOB,
  author =       "Imen Ahmed and Mariem Turki and Mouna Baklouti and
                 Bouthaina Dammak and Amnah Alshahrani",
  title =        "Towards an Optimized Blockchain-Based Secure Medical
                 Prescription-Management System",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "9",
  month =        jul,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070243",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/243",
  abstract =     "This work introduces a blockchain-based secure medical
                 prescription-management system seamlessly integrated
                 with a dynamic Internet of Things (IoT) framework.
                 Notably, this integration constitutes a pivotal
                 challenge in the arena of resource-constrained IoT
                 devices: energy consumption. The choice of a suitable
                 blockchain consensus mechanism emerges as the linchpin
                 in surmounting this hurdle. Thus, this paper conducts a
                 comprehensive comparison of energy consumption between
                 two distinct consensus mechanisms: Proof of Work (PoW)
                 and Quorum-based Byzantine fault tolerance (QBFT).
                 Furthermore, an assessment of the most energy-efficient
                 algorithm is performed across multiple networks and
                 various parameters. This approach ensures the
                 acquisition of reliable and statistically significant
                 data, enabling meaningful conclusions to be drawn about
                 the system's performance in real-world scenarios. The
                 experimental results show that, compared to the PoW,
                 the QBFT consensus mechanism reduced the energy
                 consumption by an average of 5\%. This finding
                 underscores the significant advantage of QBFT in
                 addressing the energy consumption challenges posed by
                 resource-constrained IoT devices. In addition to its
                 inherent benefits of privacy and block time efficiency,
                 the Quorum blockchain emerges as a more sustainable
                 choice for IoT applications due to its lower power
                 consumption.",
  acknowledgement = ack-nhfb,
  articleno =    "243",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Dashkevich:2024:BFS,
  author =       "Natalia Dashkevich and Steve Counsell and Giuseppe
                 Destefanis",
  title =        "Blockchain Financial Statements: Innovating Financial
                 Reporting, Accounting, and Liquidity Management",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "9",
  month =        jul,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070244",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/244",
  abstract =     "The complexity and interconnection within the
                 financial ecosystem demand innovative solutions to
                 improve transparency, security, and efficiency in
                 financial reporting and liquidity management, while
                 also reducing accounting fraud. This paper presents
                 Blockchain Financial Statements (BFS), an innovative
                 accounting system designed to address accounting fraud,
                 reduce data manipulation, and misrepresentation of
                 company financial claims, by enhancing availability of
                 the real-time and tamper-proof accounting data,
                 underpinned by a verifiable approach to financial
                 transactions and reporting. The primary goal of this
                 research is to design, develop, and validate a
                 blockchain-based accounting prototype---the BFS
                 system---that can automate transformation of
                 transactional data, generated by traditional business
                 activity into comprehensive financial statements.
                 Incorporating a Design Science Research Methodology
                 with Domain-Driven Design, this study constructs a BFS
                 artefact that harmonises accounting standards with
                 blockchain technology and business orchestration. The
                 resulting Java implementation of the BFS system
                 demonstrates successful integration of blockchain
                 technology into accounting practices, showing potential
                 in real-time validation of transactions, immutable
                 record-keeping, and enhancement of transparency and
                 efficiency of financial reporting. The BFS framework
                 and implementation signify an advancement in the
                 application of blockchain technology in accounting. It
                 offers a functional solution that enhances
                 transparency, accuracy, and efficiency of financial
                 transactions between banks and businesses. This
                 research underlines the necessity for further
                 exploration into blockchain's potential within
                 accounting systems, suggesting a promising direction
                 for future innovations in tamper-evident financial
                 reporting and liquidity management.",
  acknowledgement = ack-nhfb,
  articleno =    "244",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Qiu:2024:ODE,
  author =       "Wen Qiu and Xun Shao and Hiroshi Masui and William
                 Liu",
  title =        "Optimizing Drone Energy Use for Emergency
                 Communications in Disasters via Deep Reinforcement
                 Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "11",
  month =        jul,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070245",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/245",
  abstract =     "For a communication control system in a disaster area
                 where drones (also called unmanned aerial vehicles
                 (UAVs)) are used as aerial base stations (ABSs), the
                 reliability of communication is a key challenge for
                 drones to provide emergency communication services.
                 However, the effective configuration of UAVs remains a
                 major challenge due to limitations in their
                 communication range and energy capacity. In addition,
                 the relatively high cost of drones and the issue of
                 mutual communication interference make it impractical
                 to deploy an unlimited number of drones in a given
                 area. To maximize the communication services provided
                 by a limited number of drones to the ground user
                 equipment (UE) within a certain time frame while
                 minimizing the drone energy consumption, we propose a
                 multi-agent proximal policy optimization (MAPPO)
                 algorithm. Considering the dynamic nature of the
                 environment, we analyze diverse observation data
                 structures and design novel objective functions to
                 enhance the drone performance. We find that, when drone
                 energy consumption is used as a penalty term in the
                 objective function, the drones---acting as agents---can
                 identify the optimal trajectory that maximizes the UE
                 coverage while minimizing the energy consumption. At
                 the same time, the experimental results reveal that,
                 without considering the machine computing power
                 required for training and convergence time, the
                 proposed key algorithm demonstrates better performance
                 in communication coverage and energy saving as compared
                 with other methods. The average coverage performance is
                 10 -- 45\% higher than that of the other three methods,
                 and it can save up to 3\% more energy.",
  acknowledgement = ack-nhfb,
  articleno =    "245",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lazzaro:2024:AAD,
  author =       "Sara Lazzaro and Francesco Buccafurri",
  title =        "Achieving Accountability and Data Integrity in Message
                 Queuing Telemetry Transport Using Blockchain and
                 Interplanetary File System",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "13",
  month =        jul,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070246",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/246",
  abstract =     "Ensuring accountability and integrity in MQTT
                 communications is important for enabling several IoT
                 applications. This paper presents a novel approach that
                 combines blockchain technology and the interplanetary
                 file system (IPFS) to achieve non-repudiation and data
                 integrity in the MQTT protocol. Our solution operates
                 in discrete temporal rounds, during which the broker
                 constructs a Merkle hash tree (MHT) from the messages
                 received. Then the broker publishes the root on the
                 blockchain and the MHT itself on IPFS. This mechanism
                 guarantees that both publishers and subscribers can
                 verify the integrity of the message exchanged.
                 Furthermore, the interactions with the blockchain made
                 by the publishers and the broker ensure they cannot
                 deny having sent the exchanged messages. We provide a
                 detailed security analysis, showing that under standard
                 assumptions, the proposed solution achieves both data
                 integrity and accountability. Additionally, we provided
                 an experimental campaign to study the scalability and
                 the throughput of the system. Our results show that our
                 solution scales well with the number of clients.
                 Furthermore, from our results, it emerges that the
                 throughput reduction depends on the integrity check
                 operations. However, since the frequency of these
                 checks can be freely chosen, we can set it so that the
                 throughput reduction is negligible. Finally, we
                 provided a detailed analysis of the costs of our
                 solution showing that, overall, the execution costs are
                 relatively low, especially given the critical security
                 and accountability benefits it guarantees. Furthermore,
                 our analysis shows that the higher the number of
                 subscribers in the system, the lower the costs per
                 client in our solution. Again, this confirms that our
                 solution does not present any scalability issues.",
  acknowledgement = ack-nhfb,
  articleno =    "246",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Vaiani:2024:ERV,
  author =       "Lorenzo Vaiani and Luca Cagliero and Paolo Garza",
  title =        "Emotion Recognition from Videos Using Multimodal Large
                 Language Models",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "13",
  month =        jul,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070247",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/247",
  abstract =     "The diffusion of Multimodal Large Language Models
                 (MLLMs) has opened new research directions in the
                 context of video content understanding and
                 classification. Emotion recognition from videos aims to
                 automatically detect human emotions such as anxiety and
                 fear. It requires deeply elaborating multiple data
                 modalities, including acoustic and visual streams.
                 State-of-the-art approaches leverage transformer-based
                 architectures to combine multimodal sources. However,
                 the impressive performance of MLLMs in content
                 retrieval and generation offers new opportunities to
                 extend the capabilities of existing emotion
                 recognizers. This paper explores the performance of
                 MLLMs in the emotion recognition task in a zero-shot
                 learning setting. Furthermore, it presents a
                 state-of-the-art architecture extension based on MLLM
                 content reformulation. The performance achieved on the
                 Hume-Reaction benchmark shows that MLLMs are still
                 unable to outperform the state-of-the-art average
                 performance but, notably, are more effective than
                 traditional transformers in recognizing emotions with
                 an intensity that deviates from the average of the
                 samples.",
  acknowledgement = ack-nhfb,
  articleno =    "247",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Satkauskas:2024:MAD,
  author =       "Nerijus Satkauskas and Algimantas Venckauskas",
  title =        "Multi-Agent Dynamic Fog Service Placement Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "13",
  month =        jul,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070248",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/248",
  abstract =     "Fog computing as a paradigm was offered more than a
                 decade ago to solve Cloud Computing issues. Long
                 transmission distances, higher data flow, data loss,
                 latency, and energy consumption lead to providing
                 services at the edge of the network. But, fog devices
                 are known for being mobile and heterogenous. Their
                 resources can be limited, and their availability can be
                 constantly changing. A service placement optimization
                 is needed to meet the QoS requirements. We propose a
                 service placement orchestration, which functions as a
                 multi-agent system. Fog computing services are
                 represented by agents that can both work independently
                 and cooperate. Service placement is being completed by
                 a two-stage optimization method. Our service placement
                 orchestrator is distributed, services are discovered
                 dynamically, resources can be monitored, and
                 communication messages among fog nodes can be signed
                 and encrypted as a solution to the weakness of
                 multi-agent systems due to the lack of monitoring tools
                 and security.",
  acknowledgement = ack-nhfb,
  articleno =    "248",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Anton-Sancho:2024:UVR,
  author =       "{\'A}lvaro Ant{\'o}n-Sancho and Pablo
                 Fern{\'a}ndez-Arias and Edwan Anderson Ariza and Diego
                 Vergara",
  title =        "The Use of Virtual Reality in the Countries of the
                 {Central American Bank for Economic Integration
                 (CABEI)}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "13",
  month =        jul,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070249",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/249",
  abstract =     "In recent years, virtual reality (VR) technologies
                 have become one of the teaching tools with the greatest
                 training potential in higher education. Thus, the study
                 of factors that influence the adoption and valuation of
                 VR by the educational agents involved is a fruitful
                 line of research, because it can provide keys to
                 promote its incorporation. This article compares the
                 assessments of VR as a teaching technology in higher
                 education given by professors from countries that are
                 members of the Central American Bank for Economic
                 Integration (CABEI) with those of professors from
                 countries in the Latin American region that are not
                 members of CABEI. For this purpose, a validated
                 questionnaire on the perception of VR use was
                 administered to a sample of 1246 professors from the
                 entire Latin American region, and their responses were
                 statistically analyzed. As a result, it was found that
                 professors from CABEI countries give better ratings to
                 the usability dimensions of VR and report a lower
                 number of disadvantages in its use than professors from
                 countries outside CABEI. However, the increase in the
                 digital competence of professors in CABEI countries is
                 more than twice as high as the increase in the
                 valuation of VR. It follows that there is still much
                 room for the integration of VR in higher education in
                 CABEI countries. Furthermore, in CABEI countries there
                 is a more pronounced gap between professors from
                 private and public universities with respect to the
                 above-mentioned ratings than in non-CABEI countries. As
                 a consequence, some implications and suggestions
                 derived from the results are reported.",
  acknowledgement = ack-nhfb,
  articleno =    "249",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Adel:2024:WSS,
  author =       "Amr Adel and Tony Jan",
  title =        "Watch the Skies: a Study on Drone Attack Vectors,
                 Forensic Approaches, and Persisting Security
                 Challenges",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "13",
  month =        jul,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070250",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/250",
  abstract =     "In the rapidly evolving landscape of drone technology,
                 securing unmanned aerial vehicles (UAVs) presents
                 critical challenges and demands unique solutions. This
                 paper offers a thorough examination of the security
                 requirements, threat models, and solutions pertinent to
                 UAVs, emphasizing the importance of cybersecurity and
                 drone forensics. This research addresses the unique
                 requirements of UAV security, outlines various threat
                 models, and explores diverse solutions to ensure data
                 integrity. Drone forensics, a field dedicated to the
                 investigation of security incidents involving UAVs, has
                 been extensively examined and demonstrates its
                 relevance in identifying attack origins or establishing
                 accident causes. This paper further surveys artifacts,
                 tools, and benchmark datasets that are critical in the
                 domain of drone forensics, providing a comprehensive
                 view of current capabilities. Acknowledging the ongoing
                 challenges in UAV security, particularly given the pace
                 of technological advancement and complex operational
                 environments, this study underscores the need for
                 increased collaboration, updated security protocols,
                 and comprehensive regulatory frameworks. Ultimately,
                 this research contributes to a deeper understanding of
                 UAV cybersecurity and aids in fostering future research
                 into the secure and reliable operation of drones.",
  acknowledgement = ack-nhfb,
  articleno =    "250",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gao:2024:SGS,
  author =       "Shaopei Gao and Qiang Liu and Junjie Zeng and Li Li",
  title =        "{SD-GPSR}: a Software-Defined Greedy Perimeter
                 Stateless Routing Method Based on Geographic Location
                 Information",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "17",
  month =        jul,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070251",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/251",
  abstract =     "To mitigate the control overhead of Software-Defined
                 Mobile Ad Hoc Networks (SD-MANETs), this paper proposes
                 a novel approach, termed Software-Defined Greedy
                 Perimeter Stateless Routing (SD-GPSR), which integrates
                 geographical location information. SD-GPSR optimizes
                 routing functions by decentralizing them within the
                 data plane of SD-MANET, utilizing the geographic
                 location information of nodes to enhance routing
                 efficiency. The controller is primarily responsible for
                 providing location services and facilitating partial
                 centralized decision-making. Within the data plane,
                 nodes employ an enhanced distance and angle-based
                 greedy forwarding algorithm, denoted as GPSR\_DA, to
                 efficiently forward data. Additionally, to address the
                 issue of routing voids in the data plane, we employ the
                 A* algorithm to compute an optimal routing path that
                 circumvents such voids. Finally, we conducted a
                 comparative analysis with several state-of-the-art
                 approaches. The evaluation experiments demonstrate that
                 SD-GPSR significantly reduces the control overhead of
                 the network. Simultaneously, there is a notable
                 improvement in both end-to-end latency and packet loss
                 rate across the network.",
  acknowledgement = ack-nhfb,
  articleno =    "251",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kuznetsov:2024:NTE,
  author =       "Oleksandr Kuznetsov and Emanuele Frontoni and Kateryna
                 Kuznetsova and Ruslan Shevchuk and Mikolaj Karpinski",
  title =        "{NFT} Technology for Enhanced Global Digital
                 Registers: a Novel Approach to Tokenization",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "17",
  month =        jul,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070252",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/252",
  abstract =     "In the rapidly evolving field of digital asset
                 management, centralized and decentralized global
                 registries have become essential tools for organizing,
                 tracking, and distributing digital assets. However,
                 existing systems often face challenges regarding
                 security, censorship resistance, interoperability,
                 customizability, and scalability. This research paper
                 aims to address these gaps by proposing a novel
                 decentralized global registry system based on
                 blockchain technology and non-fungible tokens (NFTs).
                 The research paper makes several key contributions to
                 the field of digital asset management. First, it
                 provides a detailed system design for the proposed
                 decentralized global registry, outlining its
                 architectural components, functional modules, and
                 integration with blockchain and NFT technologies.
                 Second, it offers a thorough comparative analysis of
                 the advantages and limitations of the proposed system
                 in relation to existing centralized and decentralized
                 registries. Finally, the paper presents potential use
                 cases and practical applications of the proposed system
                 in various industries, demonstrating its versatility
                 and adaptability to different contexts and
                 requirements. In conclusion, this research paper
                 contributes significantly to the ongoing efforts to
                 improve digital asset management by presenting a novel,
                 decentralized global registry system based on
                 blockchain technology and NFTs. The proposed system
                 addresses the key limitations of existing solutions and
                 offers a promising direction for future research and
                 development in this critical field.",
  acknowledgement = ack-nhfb,
  articleno =    "252",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kaliyaperumal:2024:NHU,
  author =       "Prabu Kaliyaperumal and Sudhakar Periyasamy and
                 Manikandan Thirumalaisamy and Balamurugan Balusamy and
                 Francesco Benedetto",
  title =        "A Novel Hybrid Unsupervised Learning Approach for
                 Enhanced Cybersecurity in the {IoT}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "18",
  month =        jul,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070253",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/253",
  abstract =     "The proliferation of IoT services has spurred a surge
                 in network attacks, heightening cybersecurity concerns.
                 Essential to network defense, intrusion detection and
                 prevention systems (IDPSs) identify malicious
                 activities, including denial of service (DoS),
                 distributed denial of service (DDoS), botnet, brute
                 force, infiltration, and Heartbleed. This study focuses
                 on leveraging unsupervised learning for training
                 detection models to counter these threats effectively.
                 The proposed method utilizes basic autoencoders (bAEs)
                 for dimensionality reduction and encompasses a
                 three-stage detection model: one-class support vector
                 machine (OCSVM) and deep autoencoder (dAE) attack
                 detection, complemented by density-based spatial
                 clustering of applications with noise (DBSCAN) for
                 attack clustering. Accurately delineated clusters aid
                 in mapping attack tactics. The MITRE ATT\&CK framework
                 establishes a ``Cyber Threat Repository'', cataloging
                 attacks and tactics, enabling immediate response based
                 on priority. Leveraging preprocessed and unlabeled
                 normal network traffic data, this approach enables the
                 identification of novel attacks while mitigating the
                 impact of imbalanced training data on model
                 performance. The autoencoder method utilizes
                 reconstruction error, OCSVM employs a kernel function
                 to establish a hyperplane for anomaly detection, while
                 DBSCAN employs a density-based approach to identify
                 clusters, manage noise, accommodate diverse shapes,
                 automatically determining cluster count, ensuring
                 scalability, and minimizing false positives and false
                 negatives. Evaluated on standard datasets such as
                 CIC-IDS2017 and CSECIC-IDS2018, the proposed model
                 outperforms existing state of art methods. Our approach
                 achieves accuracies exceeding 98\% for the two
                 datasets, thus confirming its efficacy and
                 effectiveness for application in efficient intrusion
                 detection systems.",
  acknowledgement = ack-nhfb,
  articleno =    "253",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yu:2024:HAC,
  author =       "Rui Yu and Sooyeon Lee and Jingyi Xie and Syed Masum
                 Billah and John M. Carroll",
  title =        "Human--{AI} Collaboration for Remote Sighted
                 Assistance: Perspectives from the {LLM} Era",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "18",
  month =        jul,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070254",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/254",
  abstract =     "Remote sighted assistance (RSA) has emerged as a
                 conversational technology aiding people with visual
                 impairments (VI) through real-time video chat
                 communication with sighted agents. We conducted a
                 literature review and interviewed 12 RSA users to
                 understand the technical and navigational challenges
                 faced by both agents and users. The technical
                 challenges were categorized into four groups: agents'
                 difficulties in orienting and localizing users,
                 acquiring and interpreting users' surroundings and
                 obstacles, delivering information specific to user
                 situations, and coping with poor network connections.
                 We also presented 15 real-world navigational
                 challenges, including 8 outdoor and 7 indoor scenarios.
                 Given the spatial and visual nature of these
                 challenges, we identified relevant computer vision
                 problems that could potentially provide solutions. We
                 then formulated 10 emerging problems that neither human
                 agents nor computer vision can fully address alone. For
                 each emerging problem, we discussed solutions grounded
                 in human--AI collaboration. Additionally, with the
                 advent of large language models (LLMs), we outlined how
                 RSA can integrate with LLMs within a human--AI
                 collaborative framework, envisioning the future of
                 visual prosthetics.",
  acknowledgement = ack-nhfb,
  articleno =    "254",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Cui:2024:IDI,
  author =       "Bo Cui and Yachao Chai and Zhen Yang and Keqin Li",
  title =        "Intrusion Detection in {IoT} Using Deep Residual
                 Networks with Attention Mechanisms",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "18",
  month =        jul,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070255",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/255",
  abstract =     "Connected devices in IoT systems usually have low
                 computing and storage capacity and lack uniform
                 standards and protocols, making them easy targets for
                 cyberattacks. Implementing security measures like
                 cryptographic authentication, access control, and
                 firewalls for IoT devices is insufficient to fully
                 address the inherent vulnerabilities and potential
                 cyberattacks within the IoT environment. To improve the
                 defensive capabilities of IoT systems, some research
                 has focused on using deep learning techniques to
                 provide new solutions for intrusion detection systems.
                 However, some existing deep learning-based intrusion
                 detection methods suffer from inadequate feature
                 extraction and insufficient model generalization
                 capability. To address the shortcomings of existing
                 detection methods, we propose an intrusion detection
                 model based on temporal convolutional residual modules.
                 An attention mechanism is introduced to assess feature
                 scores and enhance the model's ability to concentrate
                 on critical features, thereby boosting its detection
                 performance. We conducted extensive experiments on the
                 ToN\_IoT dataset and the UNSW-NB15 dataset, and the
                 proposed model achieves accuracies of 99.55\% and
                 89.23\% on the ToN\_IoT and UNSW-NB15 datasets,
                 respectively, with improvements of 0.14\% and 15.3\%
                 compared with the current state-of-the-art models.
                 These results demonstrate the superior detection
                 performance of the proposed model.",
  acknowledgement = ack-nhfb,
  articleno =    "255",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mohideen:2024:BCI,
  author =       "Mohamed Azarudheen Mohamed Mohideen and Muhammad
                 Shahroz Nadeem and James Hardy and Haider Ali and Umair
                 Ullah Tariq and Fariza Sabrina and Muhammad Waqar and
                 Salman Ahmed",
  title =        "Behind the Code: Identifying Zero-Day Exploits in
                 {WordPress}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "19",
  month =        jul,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070256",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/256",
  abstract =     "The rising awareness of cybersecurity among
                 governments and the public underscores the importance
                 of effectively managing security incidents, especially
                 zero-day attacks that exploit previously unknown
                 software vulnerabilities. These zero-day attacks are
                 particularly challenging because they exploit flaws
                 that neither the public nor developers are aware of. In
                 our study, we focused on dynamic application security
                 testing (DAST) to investigate cross-site scripting
                 (XSS) attacks. We closely examined 23 popular WordPress
                 plugins, especially those requiring user or admin
                 interactions, as these are frequent targets for XSS
                 attacks. Our testing uncovered previously unknown
                 zero-day vulnerabilities in three of these plugins.
                 Through controlled environment testing, we accurately
                 identified and thoroughly analyzed these XSS
                 vulnerabilities, revealing their mechanisms, potential
                 impacts, and the conditions under which they could be
                 exploited. One of the most concerning findings was the
                 potential for admin-side attacks, which could lead to
                 multi-site insider threats. Specifically, we found
                 vulnerabilities that allow for the insertion of
                 malicious scripts, creating backdoors that unauthorized
                 users can exploit. We demonstrated the severity of
                 these vulnerabilities by employing a keylogger-based
                 attack vector capable of silently capturing and
                 extracting user data from the compromised plugins.
                 Additionally, we tested a zero-click download strategy,
                 allowing malware to be delivered without any user
                 interaction, further highlighting the risks posed by
                 these vulnerabilities. The National Institute of
                 Standards and Technology (NIST) recognized these
                 vulnerabilities and assigned them CVE numbers:
                 CVE-2023-5119 for the Forminator plugin, CVE-2023-5228
                 for user registration and contact form issues, and
                 CVE-2023-5955 for another critical plugin flaw. Our
                 study emphasizes the critical importance of proactive
                 security measures, such as rigorous input validation,
                 regular security testing, and timely updates, to
                 mitigate the risks posed by zero-day vulnerabilities.
                 It also highlights the need for developers and
                 administrators to stay vigilant and adopt strong
                 security practices to defend against evolving
                 threats.",
  acknowledgement = ack-nhfb,
  articleno =    "256",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zarie:2024:MBV,
  author =       "Mira M. Zarie and Abdelhamied A. Ateya and Mohammed S.
                 Sayed and Mohammed ElAffendi and Mohammad Mahmoud
                 Abdellatif",
  title =        "Microservice-Based Vehicular Network for Seamless and
                 Ultra-Reliable Communications of Connected Vehicles",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "7",
  pages =        "??--??",
  day =          "19",
  month =        jul,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16070257",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:00 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/7/257",
  abstract =     "The fifth-generation (5G) cellular infrastructure is
                 expected to bring about the widespread use of connected
                 vehicles. This technological progress marks the
                 beginning of a new era in vehicular networks, which
                 includes a range of different types and services of
                 self-driving cars and the smooth sharing of information
                 between vehicles. Connected vehicles have also been
                 announced as a main use case of the sixth-generation
                 (6G) cellular, with ultimate requirements beyond the 5G
                 (B5G) and 6G eras. These networks require full
                 coverage, extremely high reliability and availability,
                 very low latency, and significant system adaptability.
                 The significant specifications set for vehicular
                 networks pose considerable design and development
                 challenges. The goals of establishing a latency of 1
                 millisecond, effectively handling large amounts of data
                 traffic, and facilitating high-speed mobility are of
                 utmost importance. To address these difficulties and
                 meet the demands of upcoming networks, e.g., 6G, it is
                 necessary to improve the performance of vehicle
                 networks by incorporating innovative technology into
                 existing network structures. This work presents
                 significant enhancements to vehicular networks to
                 fulfill the demanding specifications by utilizing
                 state-of-the-art technologies, including distributed
                 edge computing, e.g., mobile edge computing (MEC) and
                 fog computing, software-defined networking (SDN), and
                 microservice. The work provides a novel vehicular
                 network structure based on micro-services architecture
                 that meets the requirements of 6G networks. The
                 required offloading scheme is introduced, and a
                 handover algorithm is presented to provide seamless
                 communication over the network. Moreover, a migration
                 scheme for migrating data between edge servers was
                 developed. The work was evaluated in terms of latency,
                 availability, and reliability. The results outperformed
                 existing traditional approaches, demonstrating the
                 potential of our approach to meet the demanding
                 requirements of next-generation vehicular networks.",
  acknowledgement = ack-nhfb,
  articleno =    "257",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Aiche:2024:MTI,
  author =       "Aicha Aiche and Pierre-Martin Tardif and Mohammed
                 Erritali",
  title =        "Modeling Trust in {IoT} Systems for Drinking-Water
                 Management",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "30",
  month =        jul,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080273",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/273",
  abstract =     "This study focuses on trust within water-treatment IoT
                 plants, examining the collaboration between IoT
                 devices, control systems, and skilled personnel. The
                 main aim is to assess the levels of trust between these
                 different critical elements based on specific criteria
                 and to emphasize that trust is neither bidirectional
                 nor transitive. To this end, we have developed a
                 synthetic database representing the critical elements
                 in the system, taking into account characteristics such
                 as accuracy, reliability, and experience. Using a
                 mathematical model based on the (AHP), we calculated
                 levels of trust between these critical elements, taking
                 into account temporal dynamics and the
                 non-bidirectional nature of trust. Our experiments
                 included anomalous scenarios, such as sudden
                 fluctuations in IoT device reliability and significant
                 variations in staff experience. These variations were
                 incorporated to assess the robustness of our approach.
                 The trust levels obtained provide a detailed insight
                 into the relationships between critical elements,
                 enhancing our understanding of trust in the context of
                 water-treatment plants.",
  acknowledgement = ack-nhfb,
  articleno =    "273",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tara:2024:DSO,
  author =       "Andrei Tara and Hjalmar K. Turesson and Nicolae
                 Natea",
  title =        "Dynamic Storage Optimization for Communication between
                 {AI} Agents",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "1",
  month =        aug,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080274",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/274",
  abstract =     "Today, AI is primarily narrow, meaning that each model
                 or agent can only perform one task or a narrow range of
                 tasks. However, systems with broad capabilities can be
                 built by connecting multiple narrow AIs. Connecting
                 various AI agents in an open, multi-organizational
                 environment requires a new communication model. Here,
                 we develop a multi-layered ontology-based communication
                 framework. Ontology concepts provide semantic
                 definitions for the agents' inputs and outputs,
                 enabling them to dynamically identify communication
                 requirements and build processing pipelines. Critical
                 is that the ontology concepts are stored on a
                 decentralized storage medium, allowing fast reading and
                 writing. The multi-layered design offers flexibility by
                 dividing a monolithic ontology model into semantic
                 layers, allowing for the optimization of read and write
                 latencies. We investigate the impact of this
                 optimization by benchmarking experiments on three
                 decentralized storage mediums---IPFS, Tendermint
                 Cosmos, and Hyperledger Fabric---across a wide range of
                 configurations. The increased read-write speeds allow
                 AI agents to communicate efficiently in a decentralized
                 environment utilizing ontology principles, making it
                 easier for AI to be used widely in various
                 applications.",
  acknowledgement = ack-nhfb,
  articleno =    "274",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fiorini:2024:EID,
  author =       "Francesco Fiorini and Michele Pagano and Rosario
                 Giuseppe Garroppo and Antonio Osele",
  title =        "Estimating Interception Density in the {BB84}
                 Protocol: a Study with a Noisy Quantum Simulator",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "2",
  month =        aug,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080275",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/275",
  abstract =     "Quantum computers have the potential to break the
                 public-key cryptosystems widely used in key exchange
                 and digital signature applications. To address this
                 issue, quantum key distribution (QKD) offers a robust
                 countermeasure against quantum computer attacks. Among
                 various QKD schemes, BB84 is the most widely used and
                 studied. However, BB84 implementations are inherently
                 imperfect, resulting in quantum bit error rates (QBERs)
                 even in the absence of eavesdroppers. Distinguishing
                 between QBERs caused by eavesdropping and QBERs due to
                 channel imperfections is fundamentally infeasible. In
                 this context, this paper proposes and examines a
                 practical method for detecting eavesdropping via
                 partial intercept-and-resend attacks in the BB84
                 protocol. A key feature of the proposed method is its
                 consideration of quantum system noise. The efficacy of
                 this method is assessed by employing the Quantum Solver
                 library in conjunction with backend simulators inspired
                 by real quantum machines that model quantum system
                 noise. The simulation outcomes demonstrate the method's
                 capacity to accurately estimate the eavesdropper's
                 interception density in the presence of system noise.
                 Moreover, the results indicate that the estimation
                 accuracy of the eavesdropper's interception density in
                 the presence of system noise is dependent on both the
                 actual interception density value and the key length.",
  acknowledgement = ack-nhfb,
  articleno =    "275",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kabashkin:2024:AIT,
  author =       "Igor Kabashkin and Leonid Shoshin",
  title =        "Artificial Intelligence of Things as New Paradigm in
                 Aviation Health Monitoring Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "2",
  month =        aug,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080276",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/276",
  abstract =     "The integration of artificial intelligence of things
                 (AIoT) is transforming aviation health monitoring
                 systems by combining extensive data collection with
                 advanced analytical capabilities. This study proposes a
                 framework that enhances predictive accuracy,
                 operational efficiency, and safety while optimizing
                 maintenance strategies and reducing costs. Utilizing a
                 three-tiered cloud architecture, the AIoT system
                 enables real-time data acquisition from sensors
                 embedded in aircraft systems, followed by machine
                 learning algorithms to analyze and interpret the data
                 for proactive decision-making. This research examines
                 the evolution from traditional to AIoT-enhanced
                 monitoring, presenting a comprehensive architecture
                 integrated with satellite communication and 6G
                 technology. The mathematical models quantifying the
                 benefits of increased diagnostic depth through AIoT,
                 covering aspects such as predictive accuracy, cost
                 savings, and safety improvements are introduced in this
                 paper. The findings emphasize the strategic importance
                 of investing in AIoT technologies to balance cost,
                 safety, and efficiency in aviation maintenance and
                 operations, marking a paradigm shift from traditional
                 health monitoring to proactive health management in
                 aviation.",
  acknowledgement = ack-nhfb,
  articleno =    "276",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Abella:2024:MLA,
  author =       "Vincent Abella and Johnfil Initan and Jake Mark Perez
                 and Philip Virgil Astillo and Luis Gerardo {Ca{\~n}ete,
                 Jr.} and Gaurav Choudhary",
  title =        "Machine Learning-Assisted Dynamic Proximity-Driven
                 Sorting Algorithm for Supermarket Navigation
                 Optimization: a Simulation-Based Validation",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "2",
  month =        aug,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080277",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/277",
  abstract =     "In-store grocery shopping is still widely preferred by
                 consumers despite the rising popularity of online
                 grocery shopping. Moreover, hardware-based in-store
                 navigation systems and shopping list applications such
                 as Walmart's Store Map, Kroger's Kroger Edge, and
                 Amazon Go have been developed by supermarkets to
                 address the inefficiencies in shopping. But even so,
                 the current systems' cost-effectiveness, optimization
                 capability, and scalability are still an issue. In
                 order to address the existing problems, this study
                 investigates the optimization of grocery shopping by
                 proposing a proximity-driven dynamic sorting algorithm
                 with the assistance of machine learning. This research
                 method provides us with an analysis of the impact and
                 effectiveness of the two machine learning models or
                 ML-DProSA variants---agglomerative hierarchical and
                 affinity propagation clustering algorithms---in
                 different setups and configurations on the performance
                 of the grocery shoppers in a simulation environment
                 patterned from the actual supermarket. The unique
                 shopping patterns of a grocery shopper and the
                 proximity of items based on timestamps are utilized in
                 sorting grocery items, consequently reducing the
                 distance traveled. Our findings reveal that both
                 algorithms reduce dwell times for grocery shoppers
                 compared to having an unsorted grocery shopping list.
                 Ultimately, this research with the ML-DProSA's
                 optimization capabilities aims to be the foundation in
                 providing a mobile application for grocery shopping in
                 any grocery stores.",
  acknowledgement = ack-nhfb,
  articleno =    "277",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tsikteris:2024:TMT,
  author =       "Sean Tsikteris and Aisha B. Rahman and Md. Sadman
                 Siraj and Eirini Eleni Tsiropoulou",
  title =        "{TRUST-ME}: Trust-Based Resource Allocation and Server
                 Selection in Multi-Access Edge Computing",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "4",
  month =        aug,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080278",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/278",
  abstract =     "Multi-access edge computing (MEC) has attracted the
                 interest of the research and industrial community to
                 support Internet of things (IoT) applications by
                 enabling efficient data processing and minimizing
                 latency. This paper presents significant contributions
                 toward optimizing the resource allocation and enhancing
                 the decision-making process in edge computing
                 environments. Specifically, the TRUST-ME model is
                 introduced, which consists of multiple edge servers and
                 IoT devices, i.e., users, with varied computing tasks
                 offloaded to the MEC servers. A utility function was
                 designed to quantify the benefits in terms of latency
                 and cost for the IoT device while utilizing the MEC
                 servers' computing capacities. The core innovation of
                 our work is a novel trust model that was designed to
                 evaluate the IoT devices' confidence in MEC servers.
                 This model integrates both direct and indirect trust
                 and reflects the trustworthiness of the servers based
                 on the direct interactions and social feedback from
                 other devices using the same servers. This dual trust
                 approach helps with accurately gauging the reliability
                 of MEC services and ensuring more informed decision
                 making. A reinforcement learning framework based on the
                 optimistic Q-learning with an upper confidence bounds
                 action selection algorithm enables the IoT devices to
                 autonomously select a MEC server to process their
                 computing tasks. Also, a multilateral bargaining model
                 is proposed for fair resource allocation of the MEC
                 servers' computing resources to the users while
                 accounting for their computing demands. Numerical
                 simulations demonstrated the operational effectiveness,
                 convergence, and scalability of the TRUST-ME model,
                 which was validated through real-world scenarios and
                 comprehensive comparative evaluations against existing
                 approaches.",
  acknowledgement = ack-nhfb,
  articleno =    "278",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Albarracin-Acero:2024:VRC,
  author =       "Diego Alejandro Albarracin-Acero and Fidel Alfonso
                 Romero-Toledo and Claudia Esperanza Saavedra-Bautista
                 and Edwan Anderson Ariza-Echeverri",
  title =        "Virtual Reality in the Classroom: Transforming the
                 Teaching of Electrical Circuits in the Digital Age",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "5",
  month =        aug,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080279",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/279",
  abstract =     "In response to the digital transformation in
                 education, this study explores the efficacy of virtual
                 reality (VR) video games in teaching direct current
                 electrical circuits at a public university in Colombia.
                 Using a mixed-method action research approach, this
                 study aimed to design, implement, and evaluate a
                 VR-based educational strategy to enhance undergraduate
                 learning experiences. The methodology integrated VR
                 into the curriculum, facilitating a comparison of this
                 innovative approach with traditional teaching methods.
                 The results indicate that the VR strategy significantly
                 improved students' comprehension of electrical circuits
                 and increased engagement, demonstrating the utility of
                 immersive technologies in educational settings.
                 Challenges such as the need for technological
                 integration and curriculum adaptation were also
                 identified. This study concludes that VR video games
                 can effectively augment electrical engineering
                 education, offering a model for incorporating advanced
                 digital tools into higher education curricula. This
                 approach aligns with ongoing trends in digital
                 transformation, suggesting significant potential for
                 broad applications across various educational
                 contexts.",
  acknowledgement = ack-nhfb,
  articleno =    "279",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tefera:2024:ADM,
  author =       "Minyechil Alehegn Tefera and Amare Mulatie Dehnaw and
                 Yibeltal Chanie Manie and Cheng-Kai Yao and Shegaw
                 Demessie Bogale and Peng-Chun Peng",
  title =        "Advanced Denoising and Meta-Learning Techniques for
                 Enhancing Smart Health Monitoring Using Wearable
                 Sensors",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "5",
  month =        aug,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080280",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/280",
  abstract =     "This study introduces a novel meta-learning method to
                 enhance diabetes detection using wearable sensor
                 systems in smart health applications. Wearable sensor
                 technology often needs to operate accurately across a
                 wide range of users, each characterized by unique
                 physiological and behavioral patterns. However, the
                 specific data for a particular application or user
                 group might be scarce. Moreover, collecting extensive
                 training data from wearable sensor experiments is
                 challenging, time-consuming, and expensive. In these
                 cases, meta-learning can be particularly useful. This
                 model can quickly adapt to the nuances of new users or
                 specific applications with minimal data. Therefore, to
                 solve the need for a huge amount of training data and
                 to enable the application of artificial intelligence
                 (AI) in data-scarce scenarios, a meta-learning method
                 is proposed. This meta-learning model has been
                 implemented to forecast diabetes, resolve cross-talk
                 issues, and accurately detect R peaks from overlapping
                 electrocardiogram (ECG) signals affected by movement
                 artifacts, poor electrode contact, electrical
                 interference, or muscle activity. Motion artifacts from
                 body movements, external conditions such as
                 temperature, humidity, and electromagnetic
                 interference, and the inherent quality and calibration
                 of the sensor can all contribute to noise. Contact
                 quality between the sensor and the skin, signal
                 processing errors, power supply variations,
                 user-generated interference from activities like
                 talking or exercising, and the materials used in the
                 wearable device also play significant roles in the
                 overall noise in wearable sensor data and can
                 significantly distort the true signal, leading to
                 erroneous interpretations and potential diagnostic
                 errors. Furthermore, discrete wavelet transform (DWT)
                 was also implemented to improve the quality of the data
                 and enhance the performance of the proposed model. The
                 demonstrated results confirmed that with only a limited
                 amount of target data, the proposed meta-learning and
                 DWT denoising method can adapt more quickly and improve
                 the detection of diabetes compared to the traditional
                 method. Therefore, the proposed system is
                 cost-effective, flexible, faster, and adaptable,
                 reduces the need for training data, and can enhance the
                 accuracy of chronic disease detection such as diabetes
                 for smart health systems.",
  acknowledgement = ack-nhfb,
  articleno =    "280",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Baumgartner:2024:MEB,
  author =       "Martin Baumgartner and Karl Kreiner and Fabian
                 Wiesm{\"u}ller and Dieter Hayn and Christian Puelacher
                 and G{\"u}nter Schreier",
  title =        "{Masketeer}: an Ensemble-Based Pseudonymization Tool
                 with Entity Recognition for {German} Unstructured
                 Medical Free Text",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "6",
  month =        aug,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080281",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/281",
  abstract =     "Background: The recent rise of large language models
                 has triggered renewed interest in medical free text
                 data, which holds critical information about patients
                 and diseases. However, medical free text is also highly
                 sensitive. Therefore, de-identification is typically
                 required but is complicated since medical free text is
                 mostly unstructured. With the Masketeer algorithm, we
                 present an effective tool to de-identify German medical
                 text. Methods: We used an ensemble of different masking
                 classes to remove references to identifiable data from
                 over 35,000 clinical notes in accordance with the HIPAA
                 Safe Harbor Guidelines. To retain additional context
                 for readers, we implemented an entity recognition
                 scheme and corpus-wide pseudonymization. Results: The
                 algorithm performed with a sensitivity of 0.943 and
                 specificity of 0.933. Further performance analyses
                 showed linear runtime complexity (O(n)) with both
                 increasing text length and corpus size. Conclusions: In
                 the future, large language models will likely be able
                 to de-identify medical free text more effectively and
                 thoroughly than handcrafted rules. However, such
                 gold-standard de-identification tools based on large
                 language models are yet to emerge. In the current
                 absence of such, we hope to provide best practices for
                 a robust rule-based algorithm designed with expert
                 domain knowledge.",
  acknowledgement = ack-nhfb,
  articleno =    "281",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bouzidi:2024:EAI,
  author =       "Abdelaziz Bouzidi and Lala Rajaoarisoa and Luka
                 Claeys",
  title =        "Explainable Artificial Intelligence Approach for
                 Improving Head-Mounted Fault Display Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "6",
  month =        aug,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080282",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/282",
  abstract =     "To fully harness the potential of wind turbine systems
                 and meet high power demands while maintaining top-notch
                 power quality, wind farm managers run their systems 24
                 h a day/7 days a week. However, due to the system's
                 large size and the complex interactions of its many
                 components operating at high power, frequent critical
                 failures occur. As a result, it has become increasingly
                 important to implement predictive maintenance to ensure
                 the continued performance of these systems. This paper
                 introduces an innovative approach to developing a
                 head-mounted fault display system that integrates
                 predictive capabilities, including deep learning long
                 short-term memory neural networks model integration,
                 with anomaly explanations for efficient predictive
                 maintenance tasks. Then, a 3D virtual model, created
                 from sampled and recorded data coupled with the deep
                 neural diagnoser model, is designed. To generate a
                 transparent and understandable explanation of the
                 anomaly, we propose a novel methodology to identify a
                 possible subset of characteristic variables for
                 accurately describing the behavior of a group of
                 components. Depending on the presence and risk level of
                 an anomaly, the parameter concerned is displayed in a
                 piece of specific information. The system then provides
                 human operators with quick, accurate insights into
                 anomalies and their potential causes, enabling them to
                 take appropriate action. By applying this methodology
                 to a wind farm dataset provided by Energias De
                 Portugal, we aim to support maintenance managers in
                 making informed decisions about inspection,
                 replacement, and repair tasks.",
  acknowledgement = ack-nhfb,
  articleno =    "282",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gentile:2024:OVP,
  author =       "Antonio Francesco Gentile and Davide Macr{\`\i} and
                 Emilio Greco and Peppino Fazio",
  title =        "Overlay and Virtual Private Networks Security
                 Performances Analysis with Open Source Infrastructure
                 Deployment",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "7",
  month =        aug,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080283",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/283",
  abstract =     "Nowadays, some of the most well-deployed
                 infrastructures are Virtual Private Networks (VPNs) and
                 Overlay Networks (ONs). They consist of hardware and
                 software components designed to build private/secure
                 channels, typically over the Internet. They are
                 currently among the most reliable technologies for
                 achieving this objective. VPNs are well-established and
                 can be patched to address security vulnerabilities,
                 while overlay networks represent the next-generation
                 solution for secure communication. In this paper, for
                 both VPNs and ONs, we analyze some important network
                 performance components (RTT and bandwidth) while
                 varying the type of overlay networks utilized for
                 interconnecting traffic between two or more hosts (in
                 the same data center, in different data centers in the
                 same building, or over the Internet). These networks
                 establish connections between KVM (Kernel-based Virtual
                 Machine) instances rather than the typical
                 Docker/LXC/Podman containers. The first analysis aims
                 to assess network performance as it is, without any
                 overlay channels. Meanwhile, the second establishes
                 various channels without encryption and the final
                 analysis encapsulates overlay traffic via IPsec
                 (Transport mode), where encrypted channels like VTI are
                 not already available for use. A deep set of traffic
                 simulation campaigns shows the obtained performance.",
  acknowledgement = ack-nhfb,
  articleno =    "283",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tseng:2024:MCI,
  author =       "Shu-Ming Tseng and Yan-Qi Wang and Yung-Chung Wang",
  title =        "Multi-Class Intrusion Detection Based on Transformer
                 for {IoT} Networks Using {CIC-IoT-2023 Dataset}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "8",
  month =        aug,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080284",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/284",
  abstract =     "This study uses deep learning methods to explore the
                 Internet of Things (IoT) network intrusion detection
                 method based on the CIC-IoT-2023 dataset. This dataset
                 contains extensive data on real-life IoT environments.
                 Based on this, this study proposes an effective
                 intrusion detection method. Apply seven deep learning
                 models, including Transformer, to analyze network
                 traffic characteristics and identify abnormal behavior
                 and potential intrusions through binary and
                 multivariate classifications. Compared with other
                 papers, we not only use a Transformer model, but we
                 also consider the model's performance in the
                 multi-class classification. Although the accuracy of
                 the Transformer model used in the binary classification
                 is lower than that of DNN and CNN + LSTM hybrid models,
                 it achieves better results in the multi-class
                 classification. The accuracy of binary classification
                 of our model is 0.74\% higher than that of papers that
                 also use Transformer on TON-IOT. In the multi-class
                 classification, our best-performing model combination
                 is Transformer, which reaches 99.40\% accuracy. Its
                 accuracy is 3.8\%, 0.65\%, and 0.29\% higher than the
                 95.60\%, 98.75\%, and 99.11\% figures recorded in
                 papers using the same dataset, respectively.",
  acknowledgement = ack-nhfb,
  articleno =    "284",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kareem:2024:SEB,
  author =       "Yunus Kareem and Djamel Djenouri and Essam Ghadafi",
  title =        "A Survey on Emerging Blockchain Technology Platforms
                 for Securing the {Internet of Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "8",
  month =        aug,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080285",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/285",
  abstract =     "The adoption of blockchain platforms to bolster the
                 security of Internet of Things (IoT) systems has
                 attracted significant attention in recent years.
                 Currently, there is a lack of comprehensive and
                 systematic survey papers in the literature addressing
                 these platforms. This paper discusses six of the most
                 popular emerging blockchain platforms adopted by IoT
                 systems and analyses their usage in state-of-the-art
                 works to solve security problems. The platform was
                 compared in terms of security features and other
                 requirements. Findings from the study reveal that most
                 blockchain components contribute directly or indirectly
                 to IoT security. Blockchain platform components such as
                 cryptography, consensus mechanism, and hashing are
                 common ways that security is achieved in all blockchain
                 platform for IoT. Technologies like Interplanetary File
                 System (IPFS) and Transport Layer Security (TLS) can
                 further enhance data and communication security when
                 used alongside blockchain. To enhance the applicability
                 of blockchain in resource-constrained IoT environments,
                 future research should focus on refining cryptographic
                 algorithms and consensus mechanisms to optimise
                 performance and security.",
  acknowledgement = ack-nhfb,
  articleno =    "285",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alghamdi:2024:CDF,
  author =       "Jawaher Alghamdi and Yuqing Lin and Suhuai Luo",
  title =        "Cross-Domain Fake News Detection Using a Prompt-Based
                 Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "8",
  month =        aug,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080286",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/286",
  abstract =     "The proliferation of fake news poses a significant
                 challenge in today's information landscape, spanning
                 diverse domains and topics and undermining traditional
                 detection methods confined to specific domains. In
                 response, there is a growing interest in strategies for
                 detecting cross-domain misinformation. However,
                 traditional machine learning (ML) approaches often
                 struggle with the nuanced contextual understanding
                 required for accurate news classification. To address
                 these challenges, we propose a novel contextualized
                 cross-domain prompt-based zero-shot approach utilizing
                 a pre-trained Generative Pre-trained Transformer (GPT)
                 model for fake news detection (FND). In contrast to
                 conventional fine-tuning methods reliant on extensive
                 labeled datasets, our approach places particular
                 emphasis on refining prompt integration and
                 classification logic within the model's framework. This
                 refinement enhances the model's ability to accurately
                 classify fake news across diverse domains.
                 Additionally, the adaptability of our approach allows
                 for customization across diverse tasks by modifying
                 prompt placeholders. Our research significantly
                 advances zero-shot learning by demonstrating the
                 efficacy of prompt-based methodologies in text
                 classification, particularly in scenarios with limited
                 training data. Through extensive experimentation, we
                 illustrate that our method effectively captures
                 domain-specific features and generalizes well to other
                 domains, surpassing existing models in terms of
                 performance. These findings contribute significantly to
                 the ongoing efforts to combat fake news dissemination,
                 particularly in environments with severely limited
                 training data, such as online platforms.",
  acknowledgement = ack-nhfb,
  articleno =    "286",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Islam:2024:DFV,
  author =       "Tasin Islam and Alina Miron and Xiaohui Liu and
                 Yongmin Li",
  title =        "Dynamic Fashion Video Synthesis from Static Imagery",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "8",
  month =        aug,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080287",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/287",
  abstract =     "Online shopping for clothing has become increasingly
                 popular among many people. However, this trend comes
                 with its own set of challenges. For example, it can be
                 difficult for customers to make informed purchase
                 decisions without trying on the clothes to see how they
                 move and flow. We address this issue by introducing a
                 new image-to-video generator called FashionFlow to
                 generate fashion videos to show how clothing products
                 move and flow on a person. By utilising a latent
                 diffusion model and various other components, we are
                 able to synthesise a high-fidelity video conditioned by
                 a fashion image. The components include the use of
                 pseudo-3D convolution, VAE, CLIP, frame interpolator
                 and attention to generate a smooth video efficiently
                 while preserving vital characteristics from the
                 conditioning image. The contribution of our work is the
                 creation of a model that can synthesise videos from
                 images. We show how we use a pre-trained VAE decoder to
                 process the latent space and generate a video. We
                 demonstrate the effectiveness of our local and global
                 conditioners, which help preserve the maximum amount of
                 detail from the conditioning image. Our model is unique
                 because it produces spontaneous and believable motion
                 using only one image, while other diffusion models are
                 either text-to-video or image-to-video using
                 pre-recorded pose sequences. Overall, our research
                 demonstrates a successful synthesis of fashion videos
                 featuring models posing from various angles, showcasing
                 the movement of the garment. Our findings hold great
                 promise for improving and enhancing the online fashion
                 industry's shopping experience.",
  acknowledgement = ack-nhfb,
  articleno =    "287",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mahbub:2024:FFV,
  author =       "Khaled Mahbub and Antonio Nehme and Mohammad Patwary
                 and Marc Lacoste and Sylvain Allio",
  title =        "{FIVADMI}: a Framework for In-Vehicle Anomaly
                 Detection by Monitoring and Isolation",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "8",
  month =        aug,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080288",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/288",
  abstract =     "Self-driving vehicles have attracted significant
                 attention in the automotive industry that is heavily
                 investing to reach the level of reliability needed from
                 these safety critical systems. Security of in-vehicle
                 communications is mandatory to achieve this goal. Most
                 of the existing research to detect anomalies for
                 in-vehicle communication does not take into account the
                 low processing power of the in-vehicle Network and ECUs
                 (Electronic Control Units). Also, these approaches do
                 not consider system level isolation challenges such as
                 side-channel vulnerabilities, that may arise due to
                 adoption of new technologies in the automotive domain.
                 This paper introduces and discusses the design of a
                 framework to detect anomalies in in-vehicle
                 communications, including side channel attacks. The
                 proposed framework supports real time monitoring of
                 data exchanges among the components of in-vehicle
                 communication network and ensures the isolation of the
                 components in in-vehicle network by deploying them in
                 Trusted Execution Environments (TEEs). The framework is
                 designed based on the AUTOSAR open standard for
                 automotive software architecture and framework. The
                 paper also discusses the implementation and evaluation
                 of the proposed framework.",
  acknowledgement = ack-nhfb,
  articleno =    "288",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Carrillo:2024:TSE,
  author =       "Alexis Carrillo and Mois{\'e}s Betancort",
  title =        "Testing Stimulus Equivalence in Transformer-Based
                 Agents",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "9",
  month =        aug,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080289",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/289",
  abstract =     "This study investigates the ability of
                 transformer-based models (TBMs) to form stimulus
                 equivalence (SE) classes. We employ BERT and GPT as TBM
                 agents in SE tasks, evaluating their performance across
                 training structures (linear series, one-to-many and
                 many-to-one) and relation types (select--reject,
                 select-only). Our findings demonstrate that both models
                 performed above mastery criterion in the baseline phase
                 across all simulations ( n = 12). However, they exhibit
                 limited success in reflexivity, transitivity, and
                 symmetry tests. Notably, both models achieved success
                 only in the linear series structure with select--reject
                 relations, failing in one-to-many and many-to-one
                 structures, and all select-only conditions. These
                 results suggest that TBM may be forming decision rules
                 based on learned discriminations and reject relations,
                 rather than responding according to equivalence class
                 formation. The absence of reject relations appears to
                 influence their responses and the occurrence of
                 hallucinations. This research highlights the potential
                 of SE simulations for: (a) comparative analysis of
                 learning mechanisms, (b) explainability techniques for
                 TBM decision-making, and (c) TBM bench-marking
                 independent of pre-training or fine-tuning. Future
                 investigations can explore upscaling simulations and
                 utilize SE tasks within a reinforcement learning
                 framework.",
  acknowledgement = ack-nhfb,
  articleno =    "289",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Piccardo:2024:BTP,
  author =       "Giorgio Piccardo and Lorenzo Conti and Alessio
                 Martino",
  title =        "Blockchain Technology and Its Potential to Benefit
                 Public Services Provision: a Short Survey",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "9",
  month =        aug,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080290",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/290",
  abstract =     "In the last few years, blockchain has emerged as a
                 cutting-edge technology whose main advantages are
                 transparency, traceability, immutability, enhanced
                 efficiency, and trust, thanks to its decentralized
                 nature. Although many people still identify blockchain
                 with cryptocurrencies and the financial sector, it has
                 many prospective applications beyond digital currency
                 that can serve as use cases for which traditional
                 infrastructures have become obsolete. Governments have
                 started exploring its potential application to public
                 services provision, as confirmed by the increasing
                 number of adoption initiatives, projects, and tests. As
                 the current public administration is often perceived as
                 slow, bureaucratic, lacking transparency, and failing
                 to involve citizens in decision-making processes,
                 blockchain can establish itself as a tool that enables
                 a process of disintermediation, which can revolutionize
                 the way in which public services are managed and
                 provided. In this paper, we will provide a survey of
                 the main application areas which are likely to benefit
                 from blockchain implementation, together with examples
                 of practical implementations carried out by both state
                 and local governments. Later, we will discuss the main
                 challenges that may prevent its widespread adoption,
                 such as government expenditure, technological maturity,
                 and lack of public awareness. Finally, we will wrap up
                 by providing indications on future areas of research
                 for blockchain-based technologies.",
  acknowledgement = ack-nhfb,
  articleno =    "290",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Davidian:2024:ERD,
  author =       "Matan Davidian and Michael Kiperberg and Natalia
                 Vanetik",
  title =        "Early Ransomware Detection with Deep Learning Models",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "11",
  month =        aug,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080291",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/291",
  abstract =     "Ransomware is a growing-in-popularity type of malware
                 that restricts access to the victim's system or data
                 until a ransom is paid. Traditional detection methods
                 rely on analyzing the malware's content, but these
                 methods are ineffective against unknown or zero-day
                 malware. Therefore, zero-day malware detection
                 typically involves observing the malware's behavior,
                 specifically the sequence of application programming
                 interface (API) calls it makes, such as reading and
                 writing files or enumerating directories. While
                 previous studies have used machine learning (ML)
                 techniques to classify API call sequences, they have
                 only considered the API call name. This paper
                 systematically compares various subsets of API call
                 features, different ML techniques, and context-window
                 sizes to identify the optimal ransomware classifier.
                 Our findings indicate that a context-window size of 7
                 is ideal, and the most effective ML techniques are CNN
                 and LSTM. Additionally, augmenting the API call name
                 with the operation result significantly enhances the
                 classifier's precision. Performance analysis suggests
                 that this classifier can be effectively applied in
                 real-time scenarios.",
  acknowledgement = ack-nhfb,
  articleno =    "291",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Dassanayake:2024:MAD,
  author =       "Janith K. Dassanayake and Minxiao Wang and Muhammad Z.
                 Hameed and Ning Yang",
  title =        "Multi-Agent Deep-{$Q$} Network-Based Cache Replacement
                 Policy for Content Delivery Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "14",
  month =        aug,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080292",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/292",
  abstract =     "In today's digital landscape, content delivery
                 networks (CDNs) play a pivotal role in ensuring rapid
                 and seamless access to online content across the globe.
                 By strategically deploying a network of edge servers in
                 close proximity to users, CDNs optimize the delivery of
                 digital content. One key mechanism involves caching
                 frequently requested content at these edge servers,
                 which not only alleviates the load on the source CDN
                 server but also enhances the overall user experience.
                 However, the exponential growth in user demands has led
                 to increased network congestion, subsequently reducing
                 the cache hit ratio within CDNs. To address this
                 reduction, this paper presents an innovative approach
                 for efficient cache replacement in a dynamic caching
                 environment while maximizing the cache hit ratio via a
                 cooperative cache replacement policy based on
                 reinforcement learning. This paper presents an
                 innovative approach to enhance the performance of CDNs
                 through an advanced cache replacement policy based on
                 reinforcement learning. The proposed system model
                 depicts a mesh network of CDNs, with edge servers
                 catering to user requests, and a main source CDN
                 server. The cache replacement problem is initially
                 modeled as a Markov decision process, and it is
                 extended to a multi-agent reinforcement learning
                 problem. We propose a cooperative cache replacement
                 algorithm based on a multi-agent deep-Q network
                 (MADQN), where the edge servers cooperatively learn to
                 efficiently replace the cached content to maximize the
                 cache hit ratio. Experimental results are presented to
                 validate the performance of our proposed approach.
                 Notably, our MADQN policy exhibits superior cache hit
                 ratios and lower average delays compared to traditional
                 caching policies.",
  acknowledgement = ack-nhfb,
  articleno =    "292",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liu:2024:DNO,
  author =       "Lisi Liu and Zijie Xu and Xiaobin Qu",
  title =        "Development of a Novel Open Control System
                 Implementation Method under Industrial {IoT}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "14",
  month =        aug,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080293",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/293",
  abstract =     "The closed architecture of modern control systems
                 impedes them from further development in the
                 environment of the industrial IoT. The open control
                 system is proposed to tackle this issue. Numerous open
                 control prototypes have been proposed, but they do not
                 reach high openness. According to the definition and
                 criteria of open control systems, this paper suggests
                 that the independence between control tasks and the
                 independence between control tasks and infrastructures
                 are the keys to the open control system under the
                 industrial IoT. Through the control domain's formal
                 description and control task virtualization to deal
                 with the keys, this paper proposes a new method to
                 implement open control systems under the industrial
                 IoT. Specifically, given the hybrid characteristic of
                 the control domain, a hierarchical semantic formal
                 based on an extended finite state machine and a
                 dependency network model with the time property is
                 designed to describe the control domain. Considering
                 the infrastructure's heterogeneity in the industrial
                 IoT, a hybrid virtualization approach based on
                 containers and WebAssembly is designed to virtualize
                 control tasks. The proposed open control system
                 implementation method is illustrated by constructing an
                 open computer numerical control demonstration and
                 compared to current open control prototypes.",
  acknowledgement = ack-nhfb,
  articleno =    "293",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fallatah:2024:EMU,
  author =       "Wesam Fallatah and Joakim K{\"a}vrestad and Steven
                 Furnell",
  title =        "Establishing a Model for the User Acceptance of
                 Cybersecurity Training",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "15",
  month =        aug,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080294",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/294",
  abstract =     "Cybersecurity is established as fundamental for
                 organisations and individuals engaging with digital
                 technology. A central topic in cybersecurity is user
                 behaviour, which has been shown to be the root cause or
                 enabler in a majority of all cyber incidents with a
                 resultant need to empower users to adopt secure
                 behaviour. Researchers and practitioners agree that a
                 crucial step in empowering users to adopt secure
                 behaviour is training. Subsequently, there are many
                 different methods for cybersecurity training discussed
                 in the scientific literature and that are adopted in
                 practise. However, research suggests that those
                 training efforts are not effective enough, and one
                 commonly mentioned reason is user adoption problems. In
                 essence, users are not engaging with the provided
                 training to the extent needed to benefit from the
                 training as expected. While the perception and adoption
                 of individual training methods are discussed in the
                 scientific literature, cohesive studies on the factors
                 that impact user adoption are few and far between. To
                 that end, this paper focuses on the user acceptance of
                 cybersecurity training using the technology acceptance
                 model as a theory base. Based on 22 included
                 publications, the research provides an overview of the
                 cybersecurity training acceptance factors that have
                 been discussed in the existing scientific literature.
                 The main contributions are a cohesive compilation of
                 existing knowledge about factors that impact the user
                 acceptance of cybersecurity training and the
                 introduction of the CTAM, a cybersecurity training
                 acceptance model which pinpoints four
                 factors---regulatory control, worry, apathy, and
                 trust---that influence users' intention to adopt
                 cybersecurity training. The results can be used to
                 guide future research as well as to guide practitioners
                 implementing cybersecurity training.",
  acknowledgement = ack-nhfb,
  articleno =    "294",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Xie:2024:DGR,
  author =       "Mingxuan Xie and Tao Zou and Junchen Ye and Bowen Du
                 and Runhe Huang",
  title =        "Dynamic Graph Representation Learning for Passenger
                 Behavior Prediction",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "15",
  month =        aug,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080295",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/295",
  abstract =     "Passenger behavior prediction aims to track passenger
                 travel patterns through historical boarding and
                 alighting data, enabling the analysis of urban station
                 passenger flow and timely risk management. This is
                 crucial for smart city development and public
                 transportation planning. Existing research primarily
                 relies on statistical methods and sequential models to
                 learn from individual historical interactions, which
                 ignores the correlations between passengers and
                 stations. To address these issues, this paper proposes
                 DyGPP, which leverages dynamic graphs to capture the
                 intricate evolution of passenger behavior. First, we
                 formalize passengers and stations as heterogeneous
                 vertices in a dynamic graph, with connections between
                 vertices representing interactions between passengers
                 and stations. Then, we sample the historical
                 interaction sequences for passengers and stations
                 separately. We capture the temporal patterns from
                 individual sequences and correlate the temporal
                 behavior between the two sequences. Finally, we use an
                 MLP-based encoder to learn the temporal patterns in the
                 interactions and generate real-time representations of
                 passengers and stations. Experiments on real-world
                 datasets confirmed that DyGPP outperformed current
                 models in the behavior prediction task, demonstrating
                 the superiority of our model.",
  acknowledgement = ack-nhfb,
  articleno =    "295",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Miao:2024:MBS,
  author =       "Jinpeng Miao and Dasari Rajasekhar and Shivakant
                 Mishra and Sanjeet Kumar Nayak and Ramanarayan Yadav",
  title =        "A Microservice-Based Smart Agriculture System to
                 Detect Animal Intrusion at the Edge",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "16",
  month =        aug,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080296",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/296",
  abstract =     "Smart agriculture stands as a promising domain for
                 IoT-enabled technologies, with the potential to elevate
                 crop quality, quantity, and operational efficiency.
                 However, implementing a smart agriculture system
                 encounters challenges such as the high latency and
                 bandwidth consumption linked to cloud computing,
                 Internet disconnections in rural locales, and the
                 imperative of cost efficiency for farmers. Addressing
                 these hurdles, this paper advocates a fog-based smart
                 agriculture infrastructure integrating edge computing
                 and LoRa communication. We tackle farmers' prime
                 concern of animal intrusion by presenting a solution
                 leveraging low-cost PIR sensors, cameras, and computer
                 vision to detect intrusions and predict animal
                 locations using an innovative algorithm. Our system
                 detects intrusions pre-emptively, identifies intruders,
                 forecasts their movements, and promptly alerts farmers.
                 Additionally, we compare our proposed strategy with
                 other approaches and measure their power consumptions,
                 demonstrating significant energy savings afforded by
                 our strategy. Experimental results highlight the
                 effectiveness, energy efficiency, and
                 cost-effectiveness of our system compared to
                 state-of-the-art systems.",
  acknowledgement = ack-nhfb,
  articleno =    "296",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lin:2024:IRS,
  author =       "Yijie Lin and Jui-Chuan Liu and Ching-Chun Chang and
                 Chin-Chen Chang",
  title =        "An Innovative Recompression Scheme for {VQ} Index
                 Tables",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "19",
  month =        aug,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080297",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/297",
  abstract =     "As we move into the digital era, the pace of
                 technological advancement is accelerating rapidly.
                 Network traffic often becomes congested during the
                 transmission of large data volumes. To mitigate this,
                 data compression plays a crucial role in minimizing
                 transmitted data. Vector quantization (VQ) stands out
                 as a potent compression technique where each image
                 block is encoded independently as an index linked to a
                 codebook, effectively reducing the bit rate. In this
                 paper, we introduce a novel scheme for recompressing VQ
                 indices, enabling lossless restoration of the original
                 indices during decoding without compromising visual
                 quality. Our method not only considers pixel
                 correlations within each image block but also leverages
                 correlations between neighboring blocks, further
                 optimizing the bit rate. The experimental results
                 demonstrated the superior performance of our approach
                 over existing methods.",
  acknowledgement = ack-nhfb,
  articleno =    "297",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Papageorgiou:2024:SUL,
  author =       "Eleftheria Papageorgiou and Christos Chronis and
                 Iraklis Varlamis and Yassine Himeur",
  title =        "A Survey on the Use of Large Language Models ({LLMs})
                 in Fake News",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "19",
  month =        aug,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080298",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/298",
  abstract =     "The proliferation of fake news and fake profiles on
                 social media platforms poses significant threats to
                 information integrity and societal trust. Traditional
                 detection methods, including rule-based approaches,
                 metadata analysis, and human fact-checking, have been
                 employed to combat disinformation, but these methods
                 often fall short in the face of increasingly
                 sophisticated fake content. This review article
                 explores the emerging role of Large Language Models
                 (LLMs) in enhancing the detection of fake news and fake
                 profiles. We provide a comprehensive overview of the
                 nature and spread of disinformation, followed by an
                 examination of existing detection methodologies. The
                 article delves into the capabilities of LLMs in
                 generating both fake news and fake profiles,
                 highlighting their dual role as both a tool for
                 disinformation and a powerful means of detection. We
                 discuss the various applications of LLMs in text
                 classification, fact-checking, verification, and
                 contextual analysis, demonstrating how these models
                 surpass traditional methods in accuracy and efficiency.
                 Additionally, the article covers LLM-based detection of
                 fake profiles through profile attribute analysis,
                 network analysis, and behavior pattern recognition.
                 Through comparative analysis, we showcase the
                 advantages of LLMs over conventional techniques and
                 present case studies that illustrate practical
                 applications. Despite their potential, LLMs face
                 challenges such as computational demands and ethical
                 concerns, which we discuss in more detail. The review
                 concludes with future directions for research and
                 development in LLM-based fake news and fake profile
                 detection, underscoring the importance of continued
                 innovation to safeguard the authenticity of online
                 information.",
  acknowledgement = ack-nhfb,
  articleno =    "298",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Nguyen:2024:LIN,
  author =       "Kieu Anh Nguyen and Yi-Jia Jiang and Chiao-Shin Huang
                 and Meng-Hsun Kuo and Walter Chen",
  title =        "Leveraging {Internet} News-Based Data for Rockfall
                 Hazard Susceptibility Assessment on Highways",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "21",
  month =        aug,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080299",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/299",
  abstract =     "Over three-quarters of Taiwan's landmass consists of
                 mountainous slopes with steep gradients, leading to
                 frequent rockfall hazards that obstruct traffic and
                 cause injuries and fatalities. This study used Google
                 Alerts to compile internet news on rockfall incidents
                 along Taiwan's highway system from April 2019 to
                 February 2024. The locations of these rockfalls were
                 geolocated using Google Earth and integrated with
                 geographical, topographical, environmental, geological,
                 and socioeconomic variables. Employing machine learning
                 algorithms, particularly the Random Forest algorithm,
                 we analyzed the potential for rockfall hazards along
                 roadside slopes. The model achieved an overall accuracy
                 of 0.8514 on the test dataset, with a sensitivity of
                 0.8378, correctly identifying 83.8\% of rockfall
                 locations. Shapley Additive Explanations (SHAP)
                 analysis highlighted that factors such as slope angle
                 and distance to geologically sensitive areas are
                 pivotal in determining rockfall locations. The study
                 underscores the utility of internet-based data
                 collection in providing comprehensive coverage of
                 Taiwan's highway system, and enabled the first broad
                 analysis of rockfall hazard susceptibility for the
                 entire highway network. The consistent importance of
                 topographical and geographical features suggests that
                 integrating detailed spatial data could further enhance
                 predictive performance. The combined use of Random
                 Forest and SHAP analyses offers a robust framework for
                 understanding and improving predictive models, aiding
                 in the development of effective strategies for risk
                 management and mitigation in rockfall-prone areas,
                 ultimately contributing to safer and more reliable
                 transportation networks in mountainous regions.",
  acknowledgement = ack-nhfb,
  articleno =    "299",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lawo:2024:WFB,
  author =       "Daniel Christian Lawo and Rana Abu Bakar and Abraham
                 Cano Aguilera and Filippo Cugini and Jos{\'e} Luis
                 Ima{\~n}a and Idelfonso Tafur Monroy and Juan Jose
                 Vegas Olmos",
  title =        "Wireless and Fiber-Based
                 Post-Quantum-Cryptography-Secured {IPsec} Tunnel",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "21",
  month =        aug,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080300",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/300",
  abstract =     "In the near future, commercially accessible quantum
                 computers are anticipated to revolutionize the world as
                 we know it. These advanced machines are predicted to
                 render traditional cryptographic security measures,
                 deeply ingrained in contemporary communication,
                 obsolete. While symmetric cryptography methods like AES
                 can withstand quantum assaults if key sizes are doubled
                 compared to current standards, asymmetric cryptographic
                 techniques, such as RSA, are vulnerable to compromise.
                 Consequently, there is a pressing need to transition
                 towards post-quantum cryptography (PQC) principles in
                 order to safeguard our privacy effectively. A challenge
                 is to include PQC into existing protocols and thus into
                 the existing communication structure. In this work, we
                 report on the first experimental IPsec tunnel secured
                 by the PQC algorithms Falcon, Dilithium, and Kyber. We
                 deploy our IPsec tunnel in two scenarios. The first
                 scenario represents a high-performance data center
                 environment where many machines are interconnected via
                 high-speed networks. We achieve an IPsec tunnel with an
                 AES-256 GCM encrypted east--west throughput of 100
                 Gbit/s line rate. The second scenario shows an IPsec
                 tunnel between a wireless NVIDIA Jetson and the cloud
                 that achieves a 0.486 Gbit/s AES-256 GCM encrypted
                 north--south throughput. This case represents a mobile
                 device that communicates securely with applications
                 running in the cloud.",
  acknowledgement = ack-nhfb,
  articleno =    "300",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Vasilas:2024:BHS,
  author =       "Teodora Vasilas and Claudiu Bacila and Remus Brad",
  title =        "Beat the Heat: Syscall Attack Detection via Thermal
                 Side Channel",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "21",
  month =        aug,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080301",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/301",
  abstract =     "As the complexity and integration of electronic
                 devices increase, understanding and mitigating
                 side-channel vulnerabilities will remain a critical
                 area of cybersecurity research. The new and intriguing
                 software-based thermal side-channel attacks and
                 countermeasures use thermal emissions from a device to
                 extract or defend sensitive information, by reading
                 information from the built-in thermal sensors via
                 software. This work extends the Hot-n-Cold anomaly
                 detection technique, applying it in circumstances much
                 closer to the real-world computational environments by
                 detecting irregularities in the Linux command behavior
                 through CPU temperature monitoring. The novelty of this
                 approach lies in the introduction of five types of
                 noise across the CPU, including moving files,
                 performing extended math computations, playing songs,
                 and browsing the web while the attack detector is
                 running. We employed Hot-n-Cold to monitor core
                 temperatures on three types of CPUs utilizing two
                 commonly used Linux terminal commands, ls and chmod.
                 The results show a high correlation, approaching 0.96,
                 between the original Linux command and a crafted
                 command, augmented with vulnerable system calls.
                 Additionally, a Machine Learning algorithm was used to
                 classify whether a thermal trace is augmented or not,
                 with an accuracy of up to 88\%. This research
                 demonstrates the potential for detecting attacks
                 through thermal sensors even when there are different
                 types of noise in the CPU, simulating a real-world
                 scenario.",
  acknowledgement = ack-nhfb,
  articleno =    "301",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2024:MOD,
  author =       "Peng Wang and Yonghua Xiong",
  title =        "A Method to Optimize Deployment of Directional Sensors
                 for Coverage Enhancement in the Sensing Layer of
                 {IoT}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "8",
  pages =        "??--??",
  day =          "22",
  month =        aug,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16080302",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Fri Aug 30 06:19:01 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/8/302",
  abstract =     "Directional sensor networks are a widely used
                 architecture in the sensing layer of the Internet of
                 Things (IoT), which has excellent data collection and
                 transmission capabilities. The coverage hole caused by
                 random deployment of sensors is the main factor
                 restricting the quality of data collection in the IoT
                 sensing layer. Determining how to enhance coverage
                 performance by repairing coverage holes is a very
                 challenging task. To this end, we propose a node
                 deployment optimization method to enhance the coverage
                 performance of the IoT sensing layer. Firstly, with the
                 goal of maximizing the effective coverage area, an
                 improved particle swarm optimization (IPSO) algorithm
                 is used to solve and obtain the optimal set of sensing
                 directions. Secondly, we propose a repair path search
                 method based on the improved sparrow search algorithm
                 (ISSA), using the minimum exposure path (MEP) found as
                 the repair path. Finally, a node scheduling algorithm
                 is designed based on MEP to determine the optimal
                 deployment location of mobile nodes and achieve
                 coverage enhancement. The simulation results show that
                 compared with existing algorithms, the proposed node
                 deployment optimization method can significantly
                 improve the coverage rate of the IoT sensing layer and
                 reduce energy consumption during the redeployment
                 process.",
  acknowledgement = ack-nhfb,
  articleno =    "302",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Vrahatis:2024:GAN,
  author =       "Aristidis G. Vrahatis and Konstantinos Lazaros and
                 Sotiris Kotsiantis",
  title =        "Graph Attention Networks: a Comprehensive Review of
                 Methods and Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "3",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090318",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/318",
  abstract =     "Real-world problems often exhibit complex
                 relationships and dependencies, which can be
                 effectively captured by graph learning systems. Graph
                 attention networks (GATs) have emerged as a powerful
                 and versatile framework in this direction, inspiring
                 numerous extensions and applications in several areas.
                 In this review, we present a thorough examination of
                 GATs, covering both diverse approaches and a wide range
                 of applications. We examine the principal GAT-based
                 categories, including Global Attention Networks,
                 Multi-Layer Architectures, graph-embedding techniques,
                 Spatial Approaches, and Variational Models.
                 Furthermore, we delve into the diverse applications of
                 GATs in various systems such as recommendation systems,
                 image analysis, medical domain, sentiment analysis, and
                 anomaly detection. This review seeks to act as a
                 navigational reference for researchers and
                 practitioners aiming to emphasize the capabilities and
                 prospects of GATs.",
  acknowledgement = ack-nhfb,
  articleno =    "318",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Su:2024:WTP,
  author =       "Guoxin Su and Li Liu",
  title =        "Workflow Trace Profiling and Execution Time Analysis
                 in Quantitative Verification",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "3",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090319",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/319",
  abstract =     "Workflows orchestrate a collection of computing tasks
                 to form a complex workflow logic. Different from the
                 traditional monolithic workflow management systems,
                 modern workflow systems often manifest high throughput,
                 concurrency and scalability. As service-based systems,
                 execution time monitoring is an important part of
                 maintaining the performance for those systems. We
                 developed a trace profiling approach that leverages
                 quantitative verification (also known as probabilistic
                 model checking ) to analyse complex time metrics for
                 workflow traces. The strength of probabilistic model
                 checking lies in the ability of expressing various
                 temporal properties for a stochastic system model and
                 performing automated quantitative verification. We
                 employ semi-Makrov chains (SMCs) as the formal model
                 and consider the first passage times (FPT) measures in
                 the SMCs. Our approach maintains simple mergeable data
                 summaries of the workflow executions and computes the
                 moment parameters for FPT efficiently. We describe an
                 application of our approach to AWS Step Functions, a
                 notable workflow web service. An empirical evaluation
                 shows that our approach is efficient for computer
                 high-order FPT moments for sizeable workflows in
                 practice. It can compute up to the fourth moment for a
                 large workflow model with 10,000 states within 70 s.",
  acknowledgement = ack-nhfb,
  articleno =    "319",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2024:MSM,
  author =       "Di Li and Zhibang Yang and Siyang Yu and Mingxing Duan
                 and Shenghong Yang",
  title =        "A Micro-Segmentation Method Based on {VLAN-VxLAN}
                 Mapping Technology",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "4",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090320",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/320",
  abstract =     "As information technology continues to evolve, cloud
                 data centres have become increasingly prominent as the
                 preferred infrastructure for data storage and
                 processing. However, this shift has introduced a new
                 array of security challenges, necessitating innovative
                 approaches distinct from traditional network security
                 architectures. In response, the Zero Trust Architecture
                 (ZTA) has emerged as a promising solution, with
                 micro-segmentation identified as a crucial component
                 for enabling continuous auditing and stringent security
                 controls. VxLAN technology is widely utilized in data
                 centres for tenant isolation and virtual machine
                 interconnection within tenant environments. Despite its
                 prevalent use, limited research has focused on its
                 application in micro-segmentation scenarios. To address
                 this gap, we propose a method that leverages VLAN and
                 VxLAN many-to-one mapping, requiring that all internal
                 data centre traffic routes through the VxLAN gateway.
                 This method can be implemented cost-effectively,
                 without necessitating business modifications or causing
                 service disruptions, thereby overcoming the challenges
                 associated with micro-segmentation deployment.
                 Importantly, this approach is based on standard public
                 protocols, making it independent of specific product
                 brands and enabling a network-centric framework that
                 avoids software compatibility issues. To assess the
                 effectiveness of our micro-segmentation approach, we
                 provide a comprehensive evaluation that includes
                 network aggregation and traffic visualization. Building
                 on the implementation of micro-segmentation, we also
                 introduce an enhanced asset behaviour algorithm. This
                 algorithm constructs behavioural profiles based on the
                 historical traffic of internal network assets, enabling
                 the rapid identification of abnormal behaviours and
                 facilitating timely defensive actions. Empirical
                 results demonstrate that our algorithm is highly
                 effective in detecting anomalous behaviour in intranet
                 assets, making it a powerful tool for enhancing
                 security in cloud data centres. In summary, the
                 proposed approach offers a robust and efficient
                 solution to the challenges of micro-segmentation in
                 cloud data centres, contributing to the advancement of
                 secure and reliable cloud infrastructure.",
  acknowledgement = ack-nhfb,
  articleno =    "320",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bani-Hani:2024:VDC,
  author =       "Raed M. Bani-Hani and Ahmed S. Shatnawi and Lana
                 Al-Yahya",
  title =        "Vulnerability Detection and Classification of
                 {Ethereum} Smart Contracts Using Deep Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "4",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090321",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/321",
  abstract =     "Smart contracts are programs that reside and execute
                 on a blockchain, like any transaction. They are
                 automatically executed when preprogrammed terms and
                 conditions are met. Although the smart contract (SC)
                 must be presented in the blockchain for the integrity
                 of data and transactions stored within it, it is highly
                 exposed to several vulnerabilities attackers exploit to
                 access the data. In this paper, classification and
                 detection of vulnerabilities targeting smart contracts
                 are performed using deep learning algorithms over two
                 datasets containing 12,253 smart contracts. These
                 contracts are converted into RGB and Grayscale images
                 and then inserted into Residual Network (ResNet50),
                 Visual Geometry Group-19 (VGG19), Dense Convolutional
                 Network (DenseNet201), k-nearest Neighbors (KNN), and
                 Random Forest (RF) algorithms for binary and
                 multi-label classification. A comprehensive analysis is
                 conducted to detect and classify vulnerabilities using
                 different performance metrics. The performance of these
                 algorithms was outstanding, accurately classifying
                 vulnerabilities with high F1 scores and accuracy rates.
                 For binary classification, RF emerged in RGB images as
                 the best algorithm based on the highest F1 score of
                 86.66\% and accuracy of 86.66\%. Moving on to
                 multi-label classification, VGG19 stood out in RGB
                 images as the standout algorithm, achieving an
                 impressive accuracy of 89.14\% and an F1 score of
                 85.87\%. To the best of our knowledge, and according to
                 the available literature, this study is the first to
                 investigate binary classification of vulnerabilities
                 targeting Ethereum smart contracts, and the
                 experimental results of the proposed methodology for
                 multi-label vulnerability classification outperform
                 existing literature.",
  acknowledgement = ack-nhfb,
  articleno =    "321",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Aslan:2024:SBE,
  author =       "Lara Aslan and Michal Ptaszynski and Jukka
                 Jauhiainen",
  title =        "Are Strong Baselines Enough? {False} News Detection
                 with Machine Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "5",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090322",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/322",
  abstract =     "False news refers to false, fake, or misleading
                 information presented as real news. In recent years,
                 there has been a noticeable increase in false news on
                 the Internet. The goal of this paper was to study the
                 automatic detection of such false news using machine
                 learning and natural language processing techniques and
                 to determine which techniques work the most
                 effectively. This article first studies what
                 constitutes false news and how it differs from other
                 types of misleading information. We also study the
                 results achieved by other researchers on the same
                 topic. After building a foundation to understand false
                 news and the various ways of automatically detecting
                 it, this article provides its own experiments. These
                 experiments were carried out on four different
                 datasets, one that was made just for this article,
                 using 10 different machine learning methods. The
                 results of this article were satisfactory and provided
                 answers to the original research questions set up at
                 the beginning of this article. This article could
                 determine from the experiments that passive aggressive
                 algorithms, support vector machines, and random forests
                 are the most efficient methods for automatic false news
                 detection. This article also concluded that more
                 complex experiments, such as using multiple levels of
                 identifying false news or detecting computer-generated
                 false news, require more complex machine learning
                 models.",
  acknowledgement = ack-nhfb,
  articleno =    "322",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Del-Valle-Soto:2024:EEC,
  author =       "Carolina Del-Valle-Soto and Ramon A. Brise{\~n}o and
                 Ramiro Vel{\'a}zquez and Gabriel Guerra-Rosales and
                 Santiago Perez-Ochoa and Isaac H. Preciado-Bazavilvazo
                 and Paolo Visconti and Jos{\'e} Varela-Ald{\'a}s",
  title =        "Enhancing Elderly Care through Low-Cost Wireless
                 Sensor Networks and Artificial Intelligence: a Study on
                 Vital Sign Monitoring and Sleep Improvement",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "6",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090323",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/323",
  abstract =     "This research explores the application of wireless
                 sensor networks for the non-invasive monitoring of
                 sleep quality and vital signs in elderly individuals,
                 addressing significant challenges faced by the aging
                 population. The study implemented and evaluated WSNs in
                 home environments, focusing on variables such as
                 breathing frequency, deep sleep, snoring, heart rate,
                 heart rate variability (HRV), oxygen saturation, Rapid
                 Eye Movement (REM sleep), and temperature. The results
                 demonstrated substantial improvements in key metrics:
                 68\% in breathing frequency, 68\% in deep sleep, 70\%
                 in snoring reduction, 91\% in HRV, and 85\% in REM
                 sleep. Additionally, temperature control was identified
                 as a critical factor, with higher temperatures
                 negatively impacting sleep quality. By integrating AI
                 with WSN data, this study provided personalized health
                 recommendations, enhancing sleep quality and overall
                 health. This approach also offered significant support
                 to caregivers, reducing their burden. This research
                 highlights the cost-effectiveness and scalability of
                 WSN technology, suggesting its feasibility for
                 widespread adoption. The findings represent a
                 significant advancement in geriatric health monitoring,
                 paving the way for more comprehensive and integrated
                 care solutions.",
  acknowledgement = ack-nhfb,
  articleno =    "323",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Dritsas:2024:MLB,
  author =       "Elias Dritsas and Maria Trigka",
  title =        "Machine Learning for Blockchain and {IoT} Systems in
                 Smart Cities: a Survey",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "6",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090324",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/324",
  abstract =     "The integration of machine learning (ML), blockchain,
                 and the Internet of Things (IoT) in smart cities
                 represents a pivotal advancement in urban innovation.
                 This convergence addresses the complexities of modern
                 urban environments by leveraging ML's data analytics
                 and predictive capabilities to enhance the intelligence
                 of IoT systems, while blockchain provides a secure,
                 decentralized framework that ensures data integrity and
                 trust. The synergy of these technologies not only
                 optimizes urban management but also fortifies security
                 and privacy in increasingly connected cities. This
                 survey explores the transformative potential of
                 ML-driven blockchain-IoT ecosystems in enabling
                 autonomous, resilient, and sustainable smart city
                 infrastructure. It also discusses the challenges such
                 as scalability, privacy, and ethical considerations,
                 and outlines possible applications and future research
                 directions that are critical for advancing smart city
                 initiatives. Understanding these dynamics is essential
                 for realizing the full potential of smart cities, where
                 technology enhances not only efficiency but also urban
                 sustainability and resilience.",
  acknowledgement = ack-nhfb,
  articleno =    "324",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Dumitru-Guzu:2024:NFC,
  author =       "Oana-Mihaela Dumitru-Guzu and Vladeanu Calin and
                 Robert Kooij",
  title =        "A Novel Framework for Cross-Cluster Scaling in
                 Cloud-Native {5G} {NextGen} Core",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "6",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090325",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/325",
  abstract =     "Cloud-native technologies are widely considered the
                 ideal candidates for the future of vertical application
                 development due to their boost in flexibility,
                 scalability, and especially cost efficiency. Since
                 multi-site support is paramount for 5G, we employ a
                 multi-cluster model that scales on demand, shifting the
                 boundaries of both horizontal and vertical scaling for
                 shared resources. Our approach is based on the liquid
                 computing paradigm, which has the benefit of adapting
                 to the changing environment. Despite being a
                 decentralized deployment shared across data centers,
                 the 5G mobile core can be managed as a single cluster
                 entity running in a public cloud. We achieve this by
                 following the cloud-native patterns for declarative
                 configuration based on Kubernetes APIs and on-demand
                 resource allocation. Moreover, in our setup, we analyze
                 the offloading of both the Open5GS user and control
                 plane functions under two different peering scenarios.
                 A significant improvement in terms of latency and
                 throughput is achieved for the in-band peering,
                 considering the traffic between clusters is ensured by
                 the Liqo control plane through a VPN tunnel. We also
                 validate three end-to-end network slicing use cases,
                 showcasing the full 5G core automation and leveraging
                 the capabilities of Kubernetes multi-cluster
                 deployments and inter-service monitoring through the
                 applied service mesh solution.",
  acknowledgement = ack-nhfb,
  articleno =    "325",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2024:PPA,
  author =       "Lihui Li and Hanwen Deng and Zhongyi Zhai and
                 Sheng-Lung Peng",
  title =        "Privacy-Preserving Authentication Based on {PUF} for
                 {VANETs}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "8",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090326",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/326",
  abstract =     "The secret key is stored in an ideal tamper-proof
                 device so that a vehicle can implement a secure
                 authentication with the road-side units (RSUs) and
                 other drivers. However, some adversaries can capture
                 the secret key by physical attacks. To resist physical
                 attacks, we propose a physical-preserving
                 authentication based on a physical unclonable function
                 for vehicular ad hoc networks. In the proposed scheme,
                 a physical unclonable function is deployed on the
                 vehicle and the RSU to provide a challenge--response
                 mechanism. A secret key is only generated by the
                 challenge--response mechanism when it is needed, which
                 eliminates the need to store a long-term secret key. As
                 a result, this prevents secret keys from being captured
                 by adversaries, improving system security. In addition,
                 route planning is introduced into the proposed scheme
                 so that a vehicle can obtain the authentication key of
                 RSUs on its route before vehicle-to-infrastructure
                 authentication, which greatly speeds up the
                 authentication when the vehicle enters the RSUs'
                 coverage. Furthermore, a detailed analysis demonstrates
                 that the proposed scheme achieves security objectives
                 in vehicular ad hoc networks. Ultimately, when
                 contrasted with similar schemes, the performance
                 assessment demonstrates that our proposed scheme
                 surpasses others in terms of computational overhead,
                 communication overhead and packet loss rate.",
  acknowledgement = ack-nhfb,
  articleno =    "326",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ruta:2024:ICT,
  author =       "Michele Ruta and Floriano Scioscia and Giuseppe Loseto
                 and Agnese Pinto and Corrado Fasciano and Giovanna
                 Capurso and Eugenio {Di Sciascio}",
  title =        "{Internet of Conscious Things}: Ontology-Based Social
                 Capabilities for Smart Objects",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "8",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090327",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/327",
  abstract =     "Emerging distributed intelligence paradigms for the
                 Internet of Things (IoT) call for flexible and dynamic
                 reconfiguration of elementary services, resources and
                 devices. In order to achieve such capability, this
                 paper faces complex interoperability and autonomous
                 decision problems by proposing a thorough framework
                 based on the integration of the Semantic Web of Things
                 (SWoT) and Social Internet of Things (SIoT) paradigms.
                 SWoT enables low-power knowledge representation and
                 autonomous reasoning at the edge of the network through
                 carefully optimized inference services and engines.
                 This layer provides service/resource management and
                 discovery primitives for a decentralized collaborative
                 social protocol in the IoT, based on the Linked Data
                 Notifications (LDN) over Linked Data Platform on
                 Constrained Application Protocol (LDP-CoAP). The
                 creation and evolution of friend and follower
                 relationships between pairs of devices is regulated by
                 means of novel dynamic models assessing trust as a
                 usefulness reputation score. The close SWoT-SIoT
                 integration overcomes the functional limitations of
                 existing proposals, which focus on either social device
                 or semantic resource management only. A smart mobility
                 case study on Plug-in Electric Vehicles (PEVs)
                 illustrates the benefits of the proposal in pervasive
                 collaborative scenarios, while experiments show the
                 computational sustainability of the dynamic
                 relationship management approach.",
  acknowledgement = ack-nhfb,
  articleno =    "327",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Adarbah:2024:NFE,
  author =       "Haitham Y. Adarbah and Mehmet Sabir Kiraz and Suleyman
                 Kardas and Ali H. Al-Bayatti and Hilal M. Y.
                 Al-Bayatti",
  title =        "A New Framework for Enhancing {VANETs} through {Layer
                 2 DLT} Architectures with Multiparty Threshold Key
                 Management and {PETs}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "9",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090328",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/328",
  abstract =     "This work proposes a new architectural approach to
                 enhance the security, privacy, and scalability of
                 VANETs through threshold key management and Privacy
                 Enhancing Technologies (PETs), such as homomorphic
                 encryption and secure multiparty computation,
                 integrated with Decentralized Ledger Technologies
                 (DLTs). These advanced mechanisms are employed to
                 eliminate centralization and protect the privacy of
                 transferred and processed information in VANETs,
                 thereby addressing privacy concerns. We begin by
                 discussing the weaknesses of existing VANET
                 architectures concerning trust, privacy, and
                 scalability and then introduce a new architectural
                 framework that shifts from centralized to decentralized
                 approaches. This transition applies a decentralized
                 ledger mechanism to ensure correctness, reliability,
                 accuracy, and security against various known attacks.
                 The use of Layer 2 DLTs in our framework enhances key
                 management, trust distribution, and data privacy,
                 offering cost and speed advantages over Layer 1 DLTs,
                 thereby enabling secure vehicle-to-everything (V2X)
                 communication. The proposed framework is superior to
                 other frameworks as it improves decentralized trust
                 management, adopts more efficient PETs, and leverages
                 Layer 2 DLT for scalability. The integration of
                 multiparty threshold key management and homomorphic
                 encryption also enhances data confidentiality and
                 integrity, thus securing against various existing
                 cryptographic attacks. Finally, we discuss potential
                 future developments to improve the security and
                 reliability of VANETs in the next generation of
                 networks, including 5G networks.",
  acknowledgement = ack-nhfb,
  articleno =    "328",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rancea:2024:ECH,
  author =       "Alexandru Rancea and Ionut Anghel and Tudor Cioara",
  title =        "Edge Computing in Healthcare: Innovations,
                 Opportunities, and Challenges",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "10",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090329",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/329",
  abstract =     "Edge computing promising a vision of processing data
                 close to its generation point, reducing latency and
                 bandwidth usage compared with traditional cloud
                 computing architectures, has attracted significant
                 attention lately. The integration of edge computing in
                 modern systems takes advantage of Internet of Things
                 (IoT) devices and can potentially improve the systems'
                 performance, scalability, privacy, and security with
                 applications in different domains. In the healthcare
                 domain, modern IoT devices can nowadays be used to
                 gather vital parameters and information that can be fed
                 to edge Artificial Intelligence (AI) techniques able to
                 offer precious insights and support to healthcare
                 professionals. However, issues regarding data privacy
                 and security, AI optimization, and computational
                 offloading at the edge pose challenges to the adoption
                 of edge AI. This paper aims to explore the current
                 state of the art of edge AI in healthcare by using the
                 Preferred Reporting Items for Systematic Reviews and
                 Meta-Analyses (PRISMA) methodology and analyzing more
                 than 70 Web of Science articles. We have defined the
                 relevant research questions, clear inclusion and
                 exclusion criteria, and classified the research works
                 in three main directions: privacy and security,
                 AI-based optimization methods, and edge offloading
                 techniques. The findings highlight the many advantages
                 of integrating edge computing in a wide range of
                 healthcare use cases requiring data privacy and
                 security, near real-time decision-making, and efficient
                 communication links, with the potential to transform
                 future healthcare services and eHealth applications.
                 However, further research is needed to enforce new
                 security-preserving methods and for better
                 orchestrating and coordinating the load in distributed
                 and decentralized scenarios.",
  acknowledgement = ack-nhfb,
  articleno =    "329",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Shrestha:2024:FIC,
  author =       "Shyam Kumar Shrestha and Shiva Raj Pokhrel and
                 Jonathan Kua",
  title =        "On the Fairness of {Internet} Congestion Control over
                 {WiFi} with Deep Reinforcement Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "10",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090330",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/330",
  abstract =     "For over forty years, TCP has been the main protocol
                 for transporting data on the Internet. To improve
                 congestion control algorithms (CCAs), delay bounding
                 algorithms such as Vegas, FAST, BBR, PCC, and Copa have
                 been developed. However, despite being designed to
                 ensure fairness between data flows, these CCAs can
                 still lead to unfairness and, in some cases, even cause
                 data flow starvation in WiFi networks under certain
                 conditions. We propose a new CCA switching solution
                 that works with existing TCP and WiFi standards. This
                 solution is offline and uses Deep Reinforcement
                 Learning (DRL) trained on features such as
                 noncongestive delay variations to predict and prevent
                 extreme unfairness and starvation. Our DRL-driven
                 approach allows for dynamic and efficient CCA
                 switching. We have tested our design preliminarily in
                 realistic datasets, ensuring that they support both
                 fairness and efficiency over WiFi networks, which
                 requires further investigation and extensive evaluation
                 before online deployment.",
  acknowledgement = ack-nhfb,
  articleno =    "330",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Moubayed:2024:CED,
  author =       "Abdallah Moubayed",
  title =        "A Complete {EDA} and {DL} Pipeline for Softwarized
                 {5G} Network Intrusion Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "10",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090331",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/331",
  abstract =     "The rise of 5G networks is driven by increasing
                 deployments of IoT devices and expanding mobile and
                 fixed broadband subscriptions. Concurrently, the
                 deployment of 5G networks has led to a surge in
                 network-related attacks, due to expanded attack
                 surfaces. Machine learning (ML), particularly deep
                 learning (DL), has emerged as a promising tool for
                 addressing these security challenges in 5G networks. To
                 that end, this work proposed an exploratory data
                 analysis (EDA) and DL-based framework designed for 5G
                 network intrusion detection. The approach aimed to
                 better understand dataset characteristics, implement a
                 DL-based detection pipeline, and evaluate its
                 performance against existing methodologies.
                 Experimental results using the 5G-NIDD dataset showed
                 that the proposed DL-based models had extremely high
                 intrusion detection and attack identification
                 capabilities (above 99.5\% and outperforming other
                 models from the literature), while having a reasonable
                 prediction time. This highlights their effectiveness
                 and efficiency for such tasks in softwarized 5G
                 environments.",
  acknowledgement = ack-nhfb,
  articleno =    "331",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Takabatake:2024:TEN,
  author =       "Wataru Takabatake and Yohei Shibata and Kenji Hoshino
                 and Tomoaki Ohtsuki",
  title =        "Time-Efficient Neural-Network-Based Dynamic Area
                 Optimization Algorithm for High-Altitude Platform
                 Station Mobile Communications",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "11",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090332",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/332",
  abstract =     "There is a growing interest in high-altitude platform
                 stations (HAPSs) as potential telecommunication
                 infrastructures in the stratosphere, providing direct
                 communication services to ground-based smartphones.
                 Enhanced coverage and capacity can be realized in HAPSs
                 by adopting multicell configurations. To improve the
                 communication quality, previous studies have
                 investigated methods based on search algorithms, such
                 as genetic algorithms (GAs), which dynamically optimize
                 antenna parameters. However, these methods face hurdles
                 in swiftly adapting to sudden distribution shifts from
                 natural disasters or major events due to their high
                 computational requirements. Moreover, they do not
                 utilize the previous optimization results, which
                 require calculations each time. This study introduces a
                 novel optimization approach based on a neural network
                 (NN) model that is trained on GA solutions. The simple
                 model is easy to implement and allows for instantaneous
                 adaptation to unexpected distribution changes. However,
                 the NN faces the difficulty of capturing the
                 dependencies among neighboring cells. To address the
                 problem, a classifier chain (CC), which chains multiple
                 classifiers to learn output relationships, is
                 integrated into the NN. However, the performance of the
                 CC depends on the output sequence. Therefore, we employ
                 an ensemble approach to integrate the CCs with
                 different sequences and select the best solution. The
                 results of simulations based on distributions in Japan
                 indicate that the proposed method achieves a total
                 throughput whose cumulative distribution function (CDF)
                 is close to that obtained by the GA solutions. In
                 addition, the results show that the proposed method is
                 more time-efficient than GA in terms of the total time
                 required to optimize each user distribution.",
  acknowledgement = ack-nhfb,
  articleno =    "332",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Jiang:2024:TOR,
  author =       "Guiwen Jiang and Rongxi Huang and Zhiming Bao and
                 Gaocai Wang",
  title =        "A Task Offloading and Resource Allocation Strategy
                 Based on Multi-Agent Reinforcement Learning in Mobile
                 Edge Computing",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "11",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090333",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/333",
  abstract =     "Task offloading and resource allocation is a research
                 hotspot in cloud-edge collaborative computing. Many
                 existing pieces of research adopted single-agent
                 reinforcement learning to solve this problem, which has
                 some defects such as low robustness, large decision
                 space, and ignoring delayed rewards. In view of the
                 above deficiencies, this paper constructs a cloud-edge
                 collaborative computing model, and related task queue,
                 delay, and energy consumption model, and gives joint
                 optimization problem modeling for task offloading and
                 resource allocation with multiple constraints. Then, in
                 order to solve the joint optimization problem, this
                 paper designs a decentralized offloading and scheduling
                 scheme based on ``task-oriented'' multi-agent
                 reinforcement learning. In this scheme, we present
                 information synchronization protocols and offloading
                 scheduling rules and use edge servers as agents to
                 construct a multi-agent system based on the
                 Actor--Critic framework. In order to solve delayed
                 rewards, this paper models the offloading and
                 scheduling problem as a ``task-oriented'' Markov
                 decision process. This process abandons the commonly
                 used equidistant time slot model but uses dynamic and
                 parallel slots in the step of task processing time.
                 Finally, an offloading decision algorithm TOMAC-PPO is
                 proposed. The algorithm applies the proximal policy
                 optimization to the multi-agent system and combines the
                 Transformer neural network model to realize the memory
                 and prediction of network state information.
                 Experimental results show that this algorithm has
                 better convergence speed and can effectively reduce the
                 service cost, energy consumption, and task drop rate
                 under high load and high failure rates. For example,
                 the proposed TOMAC-PPO can reduce the average cost by
                 from 19.4\% to 66.6\% compared to other offloading
                 schemes under the same network load. In addition, the
                 drop rate of some baseline algorithms with 50 users can
                 achieve 62.5\% for critical tasks, while the proposed
                 TOMAC-PPO only has 5.5\%.",
  acknowledgement = ack-nhfb,
  articleno =    "333",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Vergallo:2024:MEC,
  author =       "Roberto Vergallo and Luca Mainetti",
  title =        "Measuring the Effectiveness of Carbon-Aware {AI}
                 Training Strategies in Cloud Instances: a Confirmation
                 Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "13",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090334",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/334",
  abstract =     "While the massive adoption of Artificial Intelligence
                 (AI) is threatening the environment, new research
                 efforts begin to be employed to measure and mitigate
                 the carbon footprint of both training and inference
                 phases. In this domain, two carbon-aware training
                 strategies have been proposed in the literature:
                 Flexible Start and Pause \& Resume. Such
                 strategies---natively Cloud-based---use the time
                 resource to postpone or pause the training algorithm
                 when the carbon intensity reaches a threshold. While
                 such strategies have proved to achieve interesting
                 results on a benchmark of modern models covering
                 Natural Language Processing (NLP) and computer vision
                 applications and a wide range of model sizes (up to
                 6.1B parameters), it is still unclear whether such
                 results may hold also with different algorithms and in
                 different geographical regions. In this confirmation
                 study, we use the same methodology as the
                 state-of-the-art strategies to recompute the saving in
                 carbon emissions of Flexible Start and Pause \& Resume
                 in the Anomaly Detection (AD) domain. Results confirm
                 their effectiveness in two specific conditions, but the
                 percentage reduction behaves differently compared with
                 what is stated in the existing literature.",
  acknowledgement = ack-nhfb,
  articleno =    "334",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Epicoco:2024:PDF,
  author =       "Italo Epicoco and Marco Pulimeno and Massimo Cafaro",
  title =        "Parallel and Distributed Frugal Tracking of a
                 Quantile",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "13",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090335",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/335",
  abstract =     "In this paper, we deal with the problem of monitoring
                 network latency. Indeed, latency is a key network
                 metric related to both network performance and quality
                 of service, since it directly impacts on the overall
                 user's experience. High latency leads to unacceptably
                 slow response times of network services, and may
                 increase network congestion and reduce the throughput,
                 in turn disrupting communications and the user's
                 experience. A common approach to monitoring network
                 latency takes into account the frequently skewed
                 distribution of latency values, and therefore specific
                 quantiles are monitored, such as the 95th, 98th, and
                 99th percentiles. We present a comparative analysis of
                 the speed of convergence of the sequential FRUGAL-1U,
                 FRUGAL-2U, and EASYQUANTILE algorithms and the design
                 and analysis of parallel, message-passing-based
                 versions of these algorithms that can be used for
                 monitoring network latency quickly and accurately.
                 Distributed versions are also discussed. Extensive
                 experimental results are provided and discussed as
                 well.",
  acknowledgement = ack-nhfb,
  articleno =    "335",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yamamoto:2024:IWW,
  author =       "Yudai Yamamoto and Aoi Fukushima and Shingo
                 Yamaguchi",
  title =        "Implementation of White-Hat Worms Using {Mirai} Source
                 Code and Its Optimization through Parameter Tuning",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "13",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090336",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/336",
  abstract =     "Mirai, an IoT malware that emerged in 2016, has been
                 used for large-scale DDoS attacks. The Mirai source
                 code is publicly available and continues to be a threat
                 with a variety of variants still in existence. In this
                 paper, we propose an implementation system for
                 malicious and white-hat worms created using the Mirai
                 source code, as well as a general and detailed
                 implementation method for white-hat worms that is not
                 limited to the Mirai source code. The white-hat worms
                 have the function of a secondary infection, in which
                 the white-hat worm disinfects the malicious worm by
                 infecting devices already infected by the malicious
                 worm, and two parameters, the values of which can be
                 changed to modify the rate at which the white-hat worms
                 can spread their infection. The values of the
                 parameters of the best white-hat worm for disinfection
                 of the malicious botnet and the impact of the value of
                 each parameter on the disinfection of the malicious
                 botnet were analyzed in detail. The analysis revealed
                 that for a white-hat worm to disinfect a malicious
                 botnet, it must be able to infect at least 80\% of all
                 devices and maintain that situation for at least 300 s.
                 Then, by tuning and optimizing the values of the
                 white-hat worm's parameters, we were able to
                 successfully eliminate the malicious botnet,
                 demonstrating the effectiveness of the white-hat
                 botnet's function of eliminating the malicious
                 botnet.",
  acknowledgement = ack-nhfb,
  articleno =    "336",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Shahjehan:2024:RMW,
  author =       "Waleed Shahjehan and Rajkumar Singh Rathore and Syed
                 Waqar Shah and Mohammad Aljaidi and Ali Safaa Sadiq and
                 Omprakash Kaiwartya",
  title =        "A Review on Millimeter-Wave Hybrid Beamforming for
                 Wireless Intelligent Transport Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "14",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090337",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/337",
  abstract =     "As the world braces for an era of ubiquitous and
                 seamless connectivity, hybrid beamforming stands out as
                 a beacon guiding the evolutionary path of wireless
                 communication technologies. Several hybrid beamforming
                 technologies are explored for millimeter-wave
                 multiple-input multi-output (MIMO) communication. The
                 aim is to provide a roadmap for hybrid beamforming that
                 enhances wireless fidelity. In this systematic review,
                 a detailed literature review of algorithms/techniques
                 used in hybrid beamforming along with performance
                 metrics, characteristics, limitations, as well as
                 performance evaluations are provided to enable
                 communication compatible with modern Wireless
                 Intelligent Transport Systems (WITSs). Further, an
                 in-depth analysis of the mmWave hybrid beamforming
                 landscape is provided based on user, link, band,
                 scattering, structure, duplex, carrier, network,
                 applications, codebook, and reflecting intelligent
                 surfaces to optimize system design and performance
                 across diversified user scenarios. Furthermore, the
                 current research trends for hybrid beamforming are
                 provided to enable the development of advanced wireless
                 communication systems with optimized performance and
                 efficiency. Finally, challenges, solutions, and future
                 research directions are provided so that this
                 systematic review can serve as a touchstone for
                 academics and industry professionals alike. The
                 systematic review aims to equip researchers with a deep
                 understanding of the current state of the art and
                 thereby enable the development of next-generation
                 communication in WITSs that are not only adept at
                 coping with contemporary demands but are also
                 future-proofed to assimilate upcoming trends and
                 innovations.",
  acknowledgement = ack-nhfb,
  articleno =    "337",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Margariti:2024:TCS,
  author =       "Spiridoula V. Margariti and Ioannis G. Tsoulos and
                 Evangelia Kiousi and Eleftherios Stergiou",
  title =        "Traffic Classification in Software-Defined Networking
                 Using Genetic Programming Tools",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "19",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090338",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/338",
  abstract =     "The classification of Software-Defined Networking
                 (SDN) traffic is an essential tool for network
                 management, network monitoring, traffic engineering,
                 dynamic resource allocation planning, and applying
                 Quality of Service (QoS) policies. The programmability
                 nature of SDN, the holistic view of the network through
                 SDN controllers, and the capability for dynamic
                 adjustable and reconfigurable controllersare fertile
                 ground for the development of new techniques for
                 traffic classification. Although there are enough
                 research works that have studied traffic classification
                 methods in SDN environments, they have several
                 shortcomings and gaps that need to be further
                 investigated. In this study, we investigated traffic
                 classification methods in SDN using publicly available
                 SDN traffic trace datasets. We apply a series of
                 classifiers, such as MLP (BFGS), FC2 (RBF), FC2 (MLP),
                 Decision Tree, SVM, and GENCLASS, and evaluate their
                 performance in terms of accuracy, detection rate, and
                 precision. Of the methods used, GenClass appears to be
                 more accurate in separating the categories of the
                 problem than the rest, and this is reflected in both
                 precision and recall. The key element of the GenClass
                 method is that it can generate classification rules
                 programmatically and detect the hidden associations
                 that exist between the problem features and the desired
                 classes. However, Genetic Programming-based techniques
                 require significantly higher execution time compared to
                 other machine learning techniques. This is most evident
                 in the feature construction method where at each
                 generation of the genetic algorithm, a set of learning
                 models is required to be trained to evaluate the
                 generated artificial features.",
  acknowledgement = ack-nhfb,
  articleno =    "338",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Shahid:2024:ONP,
  author =       "Kamal Shahid and Saleem Naseer Ahmad and Syed Tahir
                 Hussain Rizvi",
  title =        "Optimizing Network Performance: a Comparative Analysis
                 of {EIGRP}, {OSPF}, and {BGP} in {IPv6}-Based
                 Load-Sharing and Link-Failover Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "20",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090339",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/339",
  abstract =     "The purpose of this study is to evaluate and compare
                 how well different routing protocols perform in terms
                 of load sharing, link failover, and overall network
                 performance. Wireshark was used for packet-level
                 analysis, VMWare was used for virtualization, GNS3 was
                 used for network simulation, and Iperf3 was used to
                 measure network performance parameters. Convergence
                 time, packet losses, network jitter, and network delay
                 are the parameters that were selected for assessment.
                 To examine the behaviors of Open Shortest Path First
                 (OSPF) and Enhanced Interior Gateway Routing Protocol
                 (EIGRP) routing protocols in a variety of network
                 settings, a simulated network environment incorporating
                 both protocols along with Border Gateway Protocol (BGP)
                 is created for the research. The setup for the
                 experiment entails simulating different network
                 conditions, such as fluctuating traffic loads and
                 connection failures, to track how the protocols
                 function in dynamic situations. The efficiency metrics
                 for OSPF and EIGRP with BGP are measured and evaluated
                 using the data generated by Wireshark and Iperf3. The
                 results of this research show that EIGRP has a better
                 failover convergence time and packet loss percentage as
                 compared to the OSPF.",
  acknowledgement = ack-nhfb,
  articleno =    "339",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Khanfor:2024:DAI,
  author =       "Abdullah Khanfor",
  title =        "Determinants to Adopt {Industrial Internet of Things}
                 in Small and Medium-Sized Enterprises",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "20",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090340",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/340",
  abstract =     "The Industrial Internet of Things (IIoT) enhances and
                 optimizes operations and product quality by reducing
                 expenses and preserving critical factory components.
                 The IIoT can also be integrated into the processes of
                 small and medium-sized enterprises (SMEs). However,
                 several factors and risks have discouraged SMEs from
                 adopting the IIoT. This study aims to identify the
                 factors influencing IIoT adoption and address the
                 challenges by conducting semi-structured interviews
                 with experienced stakeholders in SME factories. Group
                 quotations and thematic analysis indicate essential
                 themes from these interviews, suggesting two primary
                 categories, human- and machine-related factors, that
                 affect implementation. The main human-related factor is
                 the decision making of high-level management and owners
                 to implement the IIoT in their plants, which requires
                 skilled individuals to achieve IIoT solutions.
                 Machine-related factors present several challenges,
                 including device compatibility-, device management-,
                 and data storage-associated issues. Comprehending and
                 addressing these factors when deploying the IIoT can
                 ensure successful implementation in SMEs, maximizing
                 the potential benefits of this technology.",
  acknowledgement = ack-nhfb,
  articleno =    "340",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Silva:2024:EDE,
  author =       "Lucas Silva and Jos{\'e} Metr{\^o}lho and Fernando
                 Ribeiro",
  title =        "Efficient Data Exchange between {WebAssembly}
                 Modules",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "20",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090341",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/341",
  abstract =     "In the past two decades, there has been a noticeable
                 decoupling of machines and operating systems. In this
                 context, WebAssembly has emerged as a promising
                 alternative to traditional virtual machines. Originally
                 designed for execution in web browsers, it has expanded
                 to executing code in restricted and secure
                 environments, and it stands out for its rapid startup,
                 small footprint, and portability. However, WebAssembly
                 presents significant challenges in data transfer and
                 the management of interactions with the module. Its
                 specification requires each module to have its own
                 memory, resulting in a ``share-nothing'' architecture.
                 This restriction, combined with the limitations of
                 importing and exporting functions that only handle
                 numerical values, and the absence of an application
                 binary interface (ABI) for sharing more complex data
                 structures, leads to efficiency problems; these are
                 exacerbated by the variety of programming languages
                 that can be compiled and executed in the same
                 environment. To address this inefficiency, the Karmem
                 was designed and developed. It includes a new interface
                 description language (IDL) aimed at facilitating the
                 definition of data, functions, and relationships
                 between modules. Additionally, a proprietary
                 protocol---an optimized ABI for efficient data reading
                 and minimal decoding cost---was created. A code
                 generator capable of producing code for various
                 programming languages was also conceived, ensuring
                 harmonious interaction with the ABI and the foreign
                 function interface. Finally, the compact runtime of
                 Karmem, built atop a WebAssembly runtime, enables
                 communication between modules and shared memory.
                 Results of the experiments conducted show that Karmem
                 represents an innovation in data communication for WASM
                 in multiple environments and demonstrates the ability
                 to overcome challenges of efficiency and
                 interoperability.",
  acknowledgement = ack-nhfb,
  articleno =    "341",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Calle-Cancho:2024:DME,
  author =       "Jesus Calle-Cancho and Carlos Ca{\~n}ada and Rafael
                 Pastor-Vargas and Mercedes E. Paoletti and Juan M.
                 Haut",
  title =        "Decentralized Mechanism for Edge Node Allocation in
                 Access Network: an Experimental Evaluation",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "20",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090342",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/342",
  abstract =     "With the rapid advancement of the Internet of Things
                 and the emergence of 6G networks in smart city
                 environments, a growth in the generation of data,
                 commonly known as big data, is expected to consequently
                 lead to higher latency. To mitigate this latency,
                 mobile edge computing has been proposed to alleviate a
                 portion of the workload from mobile devices by
                 offloading it to nearby edge servers equipped with
                 appropriate computational resources. However, existing
                 solutions often exhibit poor performance when
                 confronted with complex network topologies. Thus, this
                 paper introduces a decentralized mechanism aimed at
                 determining the locations of network edge nodes in such
                 complex network topologies, characterized by lengthy
                 execution times. Our proposal provides performance
                 improvements and offers scalability and flexibility as
                 networks become more complex. Experimental evaluations
                 are conducted using the Shanghai Telecom dataset to
                 validate our proposed approach.",
  acknowledgement = ack-nhfb,
  articleno =    "342",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Reali:2024:AIR,
  author =       "Gianluca Reali and Mauro Femminella",
  title =        "Artificial Intelligence to Reshape the Healthcare
                 Ecosystem",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "20",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090343",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/343",
  abstract =     "This paper intends to provide the reader with an
                 overview of the main processes that are introducing
                 artificial intelligence (AI) into healthcare services.
                 The first part is organized according to an
                 evolutionary perspective. We first describe the role
                 that digital technologies have had in shaping the
                 current healthcare methodologies and the relevant
                 foundations for new evolutionary scenarios.
                 Subsequently, the various evolutionary paths are
                 illustrated with reference to AI techniques and their
                 research activities, specifying their degree of
                 readiness for actual clinical use. The organization of
                 this paper is based on the interplay three pillars,
                 namely, algorithms, enabling technologies and
                 regulations, and healthcare methodologies. Through this
                 organization we introduce the reader to the main
                 evolutionary aspects of the healthcare ecosystem, to
                 associate clinical needs with appropriate
                 methodologies. We also explore the different aspects
                 related to the Internet of the future that are not
                 typically presented in papers that focus on AI, but
                 that are equally crucial to determine the success of
                 current research and development activities in
                 healthcare.",
  acknowledgement = ack-nhfb,
  articleno =    "343",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kobza:2024:ADT,
  author =       "Ondrej Kobza and David Herel and Jan Cuhel and Tommaso
                 Gargiani and Petr Marek and Jan Sedivy",
  title =        "{Alquist 5.0}: Dialogue Trees Meet Generative Models,
                 a Novel Approach for Enhancing {SocialBot}
                 Conversations",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "21",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090344",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/344",
  abstract =     "This article introduces Alquist 5.0, our SocialBot
                 that was designed for the Alexa Prize SocialBot Grand
                 Challenge 5. Building upon previous iterations, we
                 present the integration of our novel neural response
                 generator (NRG) Barista within a hybrid architecture
                 that combines traditional predefined dialogues with
                 advanced neural response generation. We provide a
                 comprehensive analysis of the current state-of-the-art
                 NRGs and large language models (LLMs), leveraging these
                 insights to enhance Barista's capabilities. A key focus
                 of our development was in ensuring the safety of our
                 chatbot and implementing robust measures to prevent
                 profanity and inappropriate content. Additionally, we
                 incorporated a new search engine to improve information
                 retrieval and response accuracy. Expanding the
                 capabilities of our system, we designed Alquist 5.0 to
                 accommodate multimodal devices, utilizing APL templates
                 enriched with custom features to deliver an outstanding
                 conversational experience complemented by an excellent
                 user interface. This paper offers detailed insights
                 into the development of Alquist 5.0, which effectively
                 addresses evolving user demands while preserving its
                 empathetic and knowledgeable conversational prowess
                 across a wide range of topics.",
  acknowledgement = ack-nhfb,
  articleno =    "344",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{John:2024:IBR,
  author =       "Jobish John and Md. Noor-A-Rahim and Aswathi Vijayan
                 and H. Vincent Poor and Dirk Pesch",
  title =        "{Industry 4.0} and Beyond: The Role of {5G}, {WiFi 7},
                 and Time-Sensitive Networking ({TSN}) in Enabling Smart
                 Manufacturing",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "21",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090345",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/345",
  abstract =     "This paper explores the role that 5G, WiFi 7, and
                 Time-Sensitive Networking (TSN) play in driving smart
                 manufacturing as a fundamental part of the Industry 4.0
                 vision. It provides an in-depth analysis of each
                 technology's application in industrial communications,
                 with a focus on TSN and its key elements that enable
                 reliable and secure communication in industrial
                 networks. In addition, this paper includes a
                 comparative study of these technologies, analyzing them
                 based on several industrial use cases, supported
                 secondary applications, industry adoption, and current
                 market trends. This paper concludes by highlighting the
                 challenges and future directions for adopting these
                 technologies in industrial networks and emphasizes
                 their importance in realizing the Industry 4.0 vision
                 within the context of smart manufacturing.",
  acknowledgement = ack-nhfb,
  articleno =    "345",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Almutairi:2024:RBT,
  author =       "Abeer Almutairi and Xavier Carpent and Steven
                 Furnell",
  title =        "Recommendation-Based Trust Evaluation Model for the
                 {Internet of Underwater Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "23",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090346",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/346",
  abstract =     "The Internet of Underwater Things (IoUT) represents an
                 emerging and innovative field with the potential to
                 revolutionize underwater exploration and monitoring.
                 Despite its promise, IoUT faces significant challenges
                 related to reliability and security, which hinder its
                 development and deployment. A particularly critical
                 issue is the establishment of trustworthy communication
                 networks, necessitating the adaptation and enhancement
                 of existing models from terrestrial and marine systems
                 to address the specific requirements of IoUT. This work
                 explores the problem of dishonest recommendations
                 within trust modelling systems, a critical issue that
                 undermines the integrity of trust modelling in IoUT
                 networks. The unique environmental and operational
                 constraints of IoUT exacerbate the severity of this
                 issue, making current detection methods insufficient.
                 To address this issue, a recommendation evaluation
                 method that leverages both filtering and weighting
                 strategies is proposed to enhance the detection of
                 dishonest recommendations. The model introduces a
                 filtering technique that combines outlier detection
                 with deviation analysis to make initial decisions based
                 on both majority outcomes and personal experiences.
                 Additionally, a belief function is developed to weight
                 received recommendations based on multiple criteria,
                 including freshness, similarity, trustworthiness, and
                 the decay of trust over time. This multifaceted
                 weighting strategy ensures that recommendations are
                 evaluated from different perspectives to capture
                 deceptive acts that exploit the complex nature of IoUT
                 to the advantage of dishonest recommenders. To validate
                 the proposed model, extensive comparative analyses with
                 existing trust evaluation methods are conducted.
                 Through a series of simulations, the efficacy of the
                 model in capturing dishonest recommendation attacks and
                 improving the accuracy rate of detecting more
                 sophisticated attack scenarios is demonstrated. These
                 results highlight the potential of the model to
                 significantly enhance the trustworthiness of IoUT
                 establishments.",
  acknowledgement = ack-nhfb,
  articleno =    "346",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bunu:2024:IRP,
  author =       "Sanusi Mohammad Bunu and Omar Younis Alani and
                 Mohammad Saraee",
  title =        "An Improved Routing Protocol for Optimum Quality of
                 Service in Device-to-Device and Energy Efficiency in
                 {5G\slash B5G}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "9",
  day =          "23",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16090347",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Sep 30 08:13:31 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/9/347",
  abstract =     "Some challenges when implementing the optimized link
                 state routing (OLSR) protocol on real-life devices and
                 simulators are unmanageable: link quality, rapid energy
                 depletion, and high processor loads. The causes of
                 these challenges are link state processing, unsuitable
                 multipoint relay (MPR) nodes, and information base
                 maintenance. This paper proposes a structured,
                 energy-efficient link sensing and database maintenance
                 technique. The improved OLSR in the paper replaces the
                 OLSRv2's HELLO, HELLO, and Topology Control (TC)
                 message sequence with a new sequence. MPR nodes are not
                 mandated to broadcast TC messages if the number of
                 nodes and their OLSRv2 addresses remain unchanged after
                 subsequent broadcasts or if no node reported 2-hop
                 symmetric connections. The paper further proposes an
                 MPR selection technique that considers four parameters:
                 node battery level, mobility speed, node degree, and
                 connection to the base station for optimum relay
                 selection. It combines the four parameters into one
                 metric to reduce energy dissipation and control routing
                 overhead. The modifications were implemented in NS-3,
                 and the simulation results show that our improved OLSR
                 outperforms the existing OLSR, OLSRv2 and other
                 improved routing protocols in energy consumption,
                 routing overhead, the packet delivery ratio and
                 end-to-end delay, as compared to the related
                 literature.",
  acknowledgement = ack-nhfb,
  articleno =    "347",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Al-Nidawi:2024:MUO,
  author =       "Yaarob Al-Nidawi and Haider Tarish Haider and Dhiaa
                 Halboot Muhsen and Ghadeer Ghazi Shayea",
  title =        "Multi-User Optimal Load Scheduling of Different
                 Objectives Combined with Multi-Criteria Decision Making
                 for Smart Grid",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "29",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100355",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/355",
  abstract =     "Load balancing between required power demand and the
                 available generation capacity is the main task of
                 demand response for a smart grid. Matching between the
                 objectives of users and utilities is the main gap that
                 should be addressed in the demand response context. In
                 this paper, a multi-user optimal load scheduling is
                 proposed to benefit both utility companies and users.
                 Different objectives are considered to form a
                 multi-objective artificial hummingbird algorithm
                 (MAHA). The cost of energy consumption, peak of load,
                 and user inconvenience are the main objectives
                 considered in this work. A hybrid multi-criteria
                 decision making method is considered to select the
                 dominance solutions. This approach is based on the
                 removal effects of criteria (MERECs) and is utilized
                 for deriving appropriate weights of various criteria.
                 Next, the Vlse Kriterijumska Optimizacija Kompromisno
                 Resenje (VIKOR) method is used to find the best
                 solution of load scheduling from a set of Pareto front
                 solutions produced by MAHA. Multiple pricing schemes
                 are applied in this work, namely the time of use (ToU)
                 and adaptive consumption level pricing scheme (ACLPS),
                 to test the proposed system with regards to different
                 pricing rates. Furthermore, non-cooperative and
                 cooperative users' working schemes are considered to
                 overcome the issue of making a new peak load time
                 through shifting the user load from the peak to
                 off-peak period to realize minimum energy cost. The
                 results demonstrate 81\% cost savings for the proposed
                 method with the cooperative mode while using ACLPS and
                 40\% savings regarding ToU. Furthermore, the peak
                 saving for the same mode of operation provides about
                 68\% and 64\% for ACLPs and ToU, respectively. The
                 finding of this work has been validated against other
                 related contributions to examine the significance of
                 the proposed technique. The analyses in this research
                 have concluded that the presented approach has realized
                 a remarkable saving for the peak power intervals and
                 energy cost while maintaining an acceptable range of
                 the customer inconvenience level.",
  acknowledgement = ack-nhfb,
  articleno =    "355",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

%%% [30-Aug-2024]: TO DO: pages values of single integer are really
%%% article numbers: I fixed them in v16n7--v16n9, but older issues
%%% still need repair.

@Article{Romero:2024:BDG,
  author =       "Abraham Romero and Roberto Hernandez",
  title =        "Blockchain-Driven Generalization of Policy Management
                 for Multiproduct Insurance Companies",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "30",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100356",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/356",
  abstract =     "This article presents a Blockchain-based solution for
                 the management of multipolicies in insurance companies,
                 introducing a standardized policy model to facilitate
                 streamlined operations and enhance collaboration
                 between entities. The model ensures uniform policy
                 management, providing scalability and flexibility to
                 adapt to new market demands. The solution leverages
                 Merkle trees for secure data management, with each
                 policy represented by an independent Merkle tree,
                 enabling updates and additions without altering
                 existing policies. The architecture, implemented on a
                 private Ethereum network using Hyperledger Besu and
                 Tessera, ensures secure and transparent transactions,
                 robust dispute resolution, and fraud prevention
                 mechanisms. The validation phase demonstrated the
                 model's efficiency in reducing data redundancy and
                 ensuring the consistency and integrity of policy
                 information. Additionally, the system's technical
                 management has been simplified, operational
                 redundancies have been eliminated, and privacy is
                 enhanced.",
  acknowledgement = ack-nhfb,
  articleno =    "356",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Peivandizadeh:2024:SKE,
  author =       "Ali Peivandizadeh and Haitham Y. Adarbah and Behzad
                 Molavi and Amirhossein Mohajerzadeh and Ali H.
                 Al-Badi",
  title =        "A Secure Key Exchange and Authentication Scheme for
                 Securing Communications in the {Internet of Things}
                 Environment",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "30",
  month =        sep,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100357",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/357",
  abstract =     "In today's advanced network and digital age, the
                 Internet of Things network is experiencing a
                 significant growing trend and, due to its wide range of
                 services and network coverage, has been able to take a
                 special place in today's technology era. Among the
                 applications that can be mentioned for this network are
                 the field of electronic health, smart residential
                 complexes, and a wide level of connections that have
                 connected the inner-city infrastructure in a complex
                 way to make it smart. The notable and critical issue
                 that exists in this network is the extent of the
                 elements that make up the network and, due to this, the
                 strong and massive data exchanges at the network level.
                 With the increasing deployment of the Internet of
                 Things, a wide range of challenges arise, especially in
                 the discussion of establishing network security.
                 Regarding security concerns, ensuring the
                 confidentiality of the data being exchanged in the
                 network, maintaining the privacy of the network nodes,
                 protecting the identity of the network nodes, and
                 finally implementing the security policies required to
                 deal with a wide range of network cyber threats are of
                 great importance. A fundamental element in the security
                 of IoT networks is the authentication process, wherein
                 nodes are required to validate each other's identities
                 to ensure the establishment of secure communication
                 channels. Through the enforcement of security
                 prerequisites, in this study, we suggested a security
                 protocol focused on reinforcing security
                 characteristics and safeguarding IoT nodes. By
                 utilizing the security features provided by Elliptic
                 Curve Cryptography (ECC) and employing the Elliptic
                 Curve Diffie--Hellman (ECDH) key-exchange mechanism, we
                 designed a protocol for authenticating nodes and
                 establishing encryption keys for every communication
                 session within the Internet of Things. To substantiate
                 the effectiveness and resilience of our proposed
                 protocol in withstanding attacks and network
                 vulnerabilities, we conducted evaluations utilizing
                 both formal and informal means. Furthermore, our
                 results demonstrate that the protocol is characterized
                 by low computational and communication demands, which
                 makes it especially well-suited for IoT nodes operating
                 under resource constraints.",
  acknowledgement = ack-nhfb,
  articleno =    "357",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yanagida:2024:MMD,
  author =       "Ryo Yanagida and Saleem Noel Bhatti",
  title =        "Mobility--Multihoming Duality",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "1",
  month =        oct,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100358",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/358",
  abstract =     "In modern Internet-based communication, especially
                 mobile systems, a mobile node (MN) will commonly have
                 more than one possibility for Internet Protocol (IP)
                 connectivity. For example, an MN such as a smartphone
                 may be associated with an IEEE 802.11 network at a site
                 while also connected to a cellular base station for 5G.
                 In such a scenario, the smartphone might only be able
                 to utilise the IEEE 802.11 network, not making use of
                 the cellular connectivity simultaneously. Currently, IP
                 does not allow applications and devices to easily
                 utilise multiple IP connectivity opportunities ---
                 multihoming for the MN --- without implementing special
                 mechanisms to manage them. We demonstrate how the use
                 of the Identifier Locator Network Protocol (ILNP),
                 realised as an extension to IPv6, can enable mobility
                 with multihoming using a duality mechanism that treats
                 mobility and multihoming as the same logical concept.
                 We present a network layer solution that does not
                 require any modification to transport protocols, can be
                 implemented using existing application programming
                 interfaces (APIs), and can work for any application. We
                 have evaluated our approach using an implementation in
                 Linux and a testbed. The testbed consisted of
                 commercial equipment to demonstrate that our approach
                 can be used over existing network infrastructure
                 requiring only normal unicast routing for IPv6.",
  acknowledgement = ack-nhfb,
  articleno =    "358",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Nayak:2024:IDS,
  author =       "Nanavath Kiran Singh Nayak and Budhaditya
                 Bhattacharyya",
  title =        "An Intrusion Detection System for {5G} {SDN} Network
                 Utilizing Binarized Deep Spiking Capsule Fire Hawk
                 Neural Networks and Blockchain Technology",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "3",
  month =        oct,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100359",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/359",
  abstract =     "The advent of 5G heralds unprecedented connectivity
                 with high throughput and low latency for network users.
                 Software-defined networking (SDN) plays a significant
                 role in fulfilling these requirements. However, it
                 poses substantial security challenges due to its
                 inherent centralized management strategy. Moreover, SDN
                 confronts limitations in handling malicious traffic
                 under 5G's extensive data flow. To deal with these
                 issues, this paper presents a novel intrusion detection
                 system (IDS) designed for 5G SDN networks, leveraging
                 the advanced capabilities of binarized deep spiking
                 capsule fire hawk neural networks (BSHNN) and
                 blockchain technology, which operates across multiple
                 layers. Initially, the lightweight encryption algorithm
                 (LEA) is used at the data acquisition layer to
                 authenticate mobile users via trusted third parties.
                 Followed by optimal switch selection using the mud-ring
                 algorithm in the switch layer, and the data flow rules
                 are secured by employing blockchain technology
                 incorporating searchable encryption algorithms within
                 the blockchain plane. The domain controller layer
                 utilizes binarized deep spiking capsule fire hawk
                 neural network (BSHNN) for real-time data packet
                 classification, while the smart controller layer uses
                 enhanced adapting hidden attribute-weighted naive bayes
                 (EAWNB) to identify suspicious packets during data
                 transmission. The experimental results show that the
                 proposed technique outperforms the state-of-the-art
                 approaches in terms of accuracy (98.02\%), precision
                 (96.40\%), detection rate (96.41\%), authentication
                 time (16.2 s), throughput, delay, and packet loss
                 ratio.",
  acknowledgement = ack-nhfb,
  articleno =    "359",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hung:2024:EHT,
  author =       "Jeih-Weih Hung and Pin-Chen Huang and Li-Yin Li",
  title =        "Employing {Huber} and {TAP} Losses to Improve
                 Inter-{SubNet} in Speech Enhancement",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "4",
  month =        oct,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100360",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/360",
  abstract =     "In this study, improvements are made to Inter-SubNet,
                 a state-of-the-art speech enhancement method.
                 Inter-SubNet is a single-channel speech enhancement
                 framework that enhances the sub-band spectral model by
                 integrating global spectral information, such as
                 cross-band relationships and patterns. Despite the
                 success of Inter-SubNet, one crucial aspect probably
                 overlooked by Inter-SubNet is the unequal perceptual
                 weighting of different spectral regions by the human
                 ear, as it employs MSE as its loss function. In
                 addition, MSE loss has a potential convergence concern
                 for model learning due to gradient explosion. Hence, we
                 propose further enhancing Inter-SubNet by either
                 integrating perceptual loss with MSE loss or modifying
                 MSE loss directly in the learning process. Among
                 various types of perceptual loss, we adopt the temporal
                 acoustic parameter (TAP) loss, which provides detailed
                 estimation for low-level acoustic descriptors, thereby
                 offering a comprehensive evaluation of speech signal
                 distortion. In addition, we leverage Huber loss, a
                 combination of L1 and L2 (MSE) loss, to avoid the
                 potential convergence issue for the training of
                 Inter-SubNet. By the evaluation conducted on the
                 VoiceBank-DEMAND database and task, we see that
                 Inter-SubNet with the modified loss function reveals
                 improvements in speech enhancement performance.
                 Specifically, replacing MSE loss with Huber loss
                 results in increases of 0.057 and 0.38 in WB-PESQ and
                 SI-SDR metrics, respectively. Additionally, integrating
                 TAP loss with MSE loss yields improvements of 0.115 and
                 0.196 in WB-PESQ and CSIG metrics.",
  acknowledgement = ack-nhfb,
  articleno =    "360",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Calzada:2024:DWR,
  author =       "Igor Calzada",
  title =        "Decentralized {Web3} Reshaping {Internet} Governance:
                 Towards the Emergence of New Forms of
                 Nation-Statehood?",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "4",
  month =        oct,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100361",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/361",
  abstract =     "This article explores how decentralized Web3 is
                 reshaping Internet governance by enabling the emergence
                 of new forms of nation-statehood and redefining
                 traditional concepts of state sovereignty. Based on
                 fieldwork conducted in Silicon Valley since August
                 2022, this article systematically addresses the
                 following research question: How is decentralized Web3
                 reshaping Internet governance and influencing the rise
                 in new nation-statehood paradigms? It compares three
                 emerging paradigms around Web3: (i) Network States
                 (Srinivasan), envisioning digital entities rooted in
                 crypto-libertarian principles; (ii) Network
                 Sovereignties (De Filippi), emphasizing communal
                 governance aligned with digital commons; and (iii)
                 Algorithmic Nations (Calzada), drawing on Arendtian
                 thought and demonstrating how communities --- such as
                 indigenous and stateless groups, as well as e-diasporas
                 --- can attain self-determination through data
                 sovereignty. This article contributes a unique
                 conceptual analysis of these paradigms based on
                 fieldwork action research in Silicon Valley, responding
                 to evolving technologies and their potential to reshape
                 Internet governance. This article argues that
                 decentralized Web3 provides a transformative vision for
                 Internet governance but requires careful evaluation to
                 ensure that it promotes inclusivity and equity. It
                 advocates for a hybrid approach that balances global
                 and local dynamics, emphasizing the need for
                 solidarity, digital justice, and an internationalist
                 perspective in shaping future Internet governance
                 protocols.",
  acknowledgement = ack-nhfb,
  articleno =    "361",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Barbierato:2024:DUI,
  author =       "Enrico Barbierato and Alice Gatti",
  title =        "Decoding Urban Intelligence: Clustering and Feature
                 Importance in Smart Cities",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "5",
  month =        oct,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100362",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/362",
  abstract =     "The rapid urbanization trend underscores the need for
                 effective management of city resources and services,
                 making the concept of smart cities increasingly
                 important. This study leverages the IMD Smart City
                 Index (SCI) dataset to analyze and rank smart cities
                 worldwide. Our research has a dual objective: first, we
                 aim to apply a set of unsupervised learning models to
                 cluster cities based on their smartness indices.
                 Second, we aim to employ supervised learning models
                 such as random forest, support vector machines (SVMs),
                 and others to determine the importance of various
                 features that contribute to a city's smartness. Our
                 findings reveal that while smart living was the most
                 critical factor, with an importance of 0.259014. Smart
                 mobility and smart environment also played significant
                 roles, with the importance of 0.170147 and 0.163159,
                 respectively, in determining a city's smartness. While
                 the clustering provides insights into the similarities
                 and groupings among cities, the feature importance
                 analysis elucidates the critical factors that drive
                 these classifications. The integration of these two
                 approaches aims to demonstrate that understanding the
                 similarities between smart cities is of limited utility
                 without a clear comprehension of the importance of the
                 underlying features. This holistic approach provides a
                 comprehensive understanding of what makes a city
                 'smart' and offers a robust framework for policymakers
                 to enhance urban living standards.",
  acknowledgement = ack-nhfb,
  articleno =    "362",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sim:2024:CWT,
  author =       "Kyungmin Sim and Honyeong Heo and Haehyun Cho",
  title =        "Combating {Web} Tracking: Analyzing {Web} Tracking
                 Technologies for User Privacy",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "5",
  month =        oct,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100363",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/363",
  abstract =     "Behind everyday websites, a hidden shadow world tracks
                 the behavior of Internet users. Web tracking analyzes
                 online activity based on collected data and delivers
                 content tailored to users' interests. It gathers vast
                 amounts of information for various purposes, ranging
                 from sensitive personal data to seemingly minor details
                 such as IP addresses, devices, browsing histories,
                 settings, and preferences. While Web tracking is
                 largely a legitimate technology, the increase in
                 illegal user tracking, data breaches, and the unlawful
                 sale of data has become a growing concern. As a result,
                 the demand for technologies that can detect and prevent
                 Web trackers is more important than ever. This paper
                 provides an overview of Web tracking technologies,
                 relevant research, and website measurement tools
                 designed to identify web-based tracking. It also
                 explores technologies for preventing Web tracking and
                 discusses potential directions for future research.",
  acknowledgement = ack-nhfb,
  articleno =    "363",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alsmadi:2024:SDC,
  author =       "Izzat Alsmadi and Iyad Alazzam and Mohammad Al-Ramahi
                 and Mohammad Zarour",
  title =        "Stance Detection in the Context of Fake News --- a New
                 Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "6",
  month =        oct,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100364",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/364",
  abstract =     "Online social networks (OSNs) are inundated with an
                 enormous daily influx of news shared by users
                 worldwide. Information can originate from any OSN user
                 and quickly spread, making the task of fact-checking
                 news both time-consuming and resource-intensive. To
                 address this challenge, researchers are exploring
                 machine learning techniques to automate fake news
                 detection. This paper specifically focuses on detecting
                 the stance of content producers --- whether they
                 support or oppose the subject of the content. Our study
                 aims to develop and evaluate advanced text-mining
                 models that leverage pre-trained language models
                 enhanced with meta features derived from headlines and
                 article bodies. We sought to determine whether
                 incorporating the cosine distance feature could improve
                 model prediction accuracy. After analyzing and
                 assessing several previous competition entries, we
                 identified three key tasks for achieving high accuracy:
                 (1) a multi-stage approach that integrates classical
                 and neural network classifiers, (2) the extraction of
                 additional text-based meta features from headline and
                 article body columns, and (3) the utilization of recent
                 pre-trained embeddings and transformer models.",
  acknowledgement = ack-nhfb,
  articleno =    "364",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hang:2024:LLM,
  author =       "Ching-Nam Hang and Pei-Duo Yu and Roberto Morabito and
                 Chee-Wei Tan",
  title =        "Large Language Models Meet Next-Generation Networking
                 Technologies: a Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "7",
  month =        oct,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100365",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/365",
  abstract =     "The evolution of network technologies has
                 significantly transformed global communication,
                 information sharing, and connectivity. Traditional
                 networks, relying on static configurations and manual
                 interventions, face substantial challenges such as
                 complex management, inefficiency, and susceptibility to
                 human error. The rise of artificial intelligence (AI)
                 has begun to address these issues by automating tasks
                 like network configuration, traffic optimization, and
                 security enhancements. Despite their potential,
                 integrating AI models in network engineering encounters
                 practical obstacles including complex configurations,
                 heterogeneous infrastructure, unstructured data, and
                 dynamic environments. Generative AI, particularly large
                 language models (LLMs), represents a promising
                 advancement in AI, with capabilities extending to
                 natural language processing tasks like translation,
                 summarization, and sentiment analysis. This paper aims
                 to provide a comprehensive review exploring the
                 transformative role of LLMs in modern network
                 engineering. In particular, it addresses gaps in the
                 existing literature by focusing on LLM applications in
                 network design and planning, implementation, analytics,
                 and management. It also discusses current research
                 efforts, challenges, and future opportunities, aiming
                 to provide a comprehensive guide for networking
                 professionals and researchers. The main goal is to
                 facilitate the adoption and advancement of AI and LLMs
                 in networking, promoting more efficient, resilient, and
                 intelligent network systems.",
  acknowledgement = ack-nhfb,
  articleno =    "365",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bolanowski:2024:NMD,
  author =       "Marek Bolanowski and Micha{\l} {\'C}mil and Adrian
                 Starzec",
  title =        "New Model for Defining and Implementing Performance
                 Tests",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "10",
  month =        oct,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100366",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/366",
  abstract =     "The article proposes a new model for defining and
                 implementing performance tests used in the process of
                 designing and operating IT systems. By defining the
                 objectives, types, topological patterns, and methods of
                 implementation, a coherent description of the test
                 preparation and execution is achieved, facilitating the
                 interpretation of results and enabling straightforward
                 replication of test scenarios. The model was used to
                 develop and implement performance tests in a laboratory
                 environment and in a production system. The proposed
                 division of the testing process into layers correlated
                 with the test preparation steps allows to separate
                 quasi-independent areas, which can be handled by
                 isolated teams of engineers. Such an approach allows to
                 accelerate the process of implementation of performance
                 tests and may affect the optimization of the cost of
                 their implementation.",
  acknowledgement = ack-nhfb,
  articleno =    "366",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alharbi:2024:CSM,
  author =       "Najla Alharbi and Bashayer Alkalifah and Ghaida
                 Alqarawi and Murad A. Rassam",
  title =        "Countering Social Media Cybercrime Using Deep
                 Learning: {Instagram} Fake Accounts Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "11",
  month =        oct,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100367",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/367",
  abstract =     "An online social media platform such as Instagram has
                 become a popular communication channel that millions of
                 people are using today. However, this media also
                 becomes an avenue where fake accounts are used to
                 inflate the number of followers on a targeted account.
                 Fake accounts tend to alter the concepts of popularity
                 and influence on the Instagram media platform and
                 significantly impact the economy, politics, and
                 society, which is considered cybercrime. This paper
                 proposes a framework to classify fake and real accounts
                 on Instagram based on a deep learning approach called
                 the Long Short-Term Memory (LSTM) network. Experiments
                 and comparisons with existing machine and deep learning
                 frameworks demonstrate considerable improvement in the
                 proposed framework. It achieved a detection accuracy of
                 97.42\% and 94.21\% on two publicly available Instagram
                 datasets, with F-measure scores of 92.17\% and 89.55\%,
                 respectively. Further experiments on the Twitter
                 dataset reveal the effectiveness of the proposed
                 framework by achieving an impressive accuracy rate of
                 99.42\%.",
  acknowledgement = ack-nhfb,
  articleno =    "367",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fatima:2024:TEF,
  author =       "Mahawish Fatima and Osama Rehman and Ibrahim M. H.
                 Rahman and Aisha Ajmal and Simon Jigwan Park",
  title =        "Towards Ensemble Feature Selection for Lightweight
                 Intrusion Detection in Resource-Constrained {IoT}
                 Devices",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "12",
  month =        oct,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100368",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/368",
  abstract =     "The emergence of smart technologies and the wide
                 adoption of the Internet of Things (IoT) have
                 revolutionized various sectors, yet they have also
                 introduced significant security challenges due to the
                 extensive attack surface they present. In recent years,
                 many efforts have been made to minimize the attack
                 surface. However, most IoT devices are
                 resource-constrained with limited processing power,
                 memory storage, and energy sources. Such devices lack
                 the sufficient means for running existing
                 resource-hungry security solutions, which in turn makes
                 it challenging to secure IoT networks from
                 sophisticated attacks. Feature Selection (FS)
                 approaches in Machine Learning enabled Intrusion
                 Detection Systems (IDS) have gained considerable
                 attention in recent years for having the potential to
                 detect sophisticated cyber-attacks while adhering to
                 the resource limitations issues in IoT networks.
                 Apropos of that, several researchers proposed
                 FS-enabled IDS for IoT networks with a focus on
                 lightweight security solutions. This work presents a
                 comprehensive study discussing FS-enabled lightweight
                 IDS tailored for resource-constrained IoT devices, with
                 a special focus on the emerging Ensemble Feature
                 Selection (EFS) techniques, portraying a new direction
                 for the research community to inspect. The research
                 aims to pave the way for the effective design of
                 futuristic FS/EFS-enabled lightweight IDS for IoT
                 networks, addressing the critical need for robust
                 security measures in the face of resource
                 limitations.",
  acknowledgement = ack-nhfb,
  articleno =    "368",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Owoh:2024:MDB,
  author =       "Nsikak Owoh and John Adejoh and Salaheddin
                 Hosseinzadeh and Moses Ashawa and Jude Osamor and Ayyaz
                 Qureshi",
  title =        "Malware Detection Based on {API} Call Sequence
                 Analysis: a Gated Recurrent Unit--Generative
                 Adversarial Network Model Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "13",
  month =        oct,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100369",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/369",
  abstract =     "Malware remains a major threat to computer systems,
                 with a vast number of new samples being identified and
                 documented regularly. Windows systems are particularly
                 vulnerable to malicious programs like viruses, worms,
                 and trojans. Dynamic analysis, which involves observing
                 malware behavior during execution in a controlled
                 environment, has emerged as a powerful technique for
                 detection. This approach often focuses on analyzing
                 Application Programming Interface (API) calls, which
                 represent the interactions between the malware and the
                 operating system. Recent advances in deep learning have
                 shown promise in improving malware detection accuracy
                 using API call sequence data. However, the potential of
                 Generative Adversarial Networks (GANs) for this purpose
                 remains largely unexplored. This paper proposes a novel
                 hybrid deep learning model combining Gated Recurrent
                 Units (GRUs) and GANs to enhance malware detection
                 based on API call sequences from Windows portable
                 executable files. We evaluate our GRU--GAN model
                 against other approaches like Bidirectional Long
                 Short-Term Memory (BiLSTM) and Bidirectional Gated
                 Recurrent Unit (BiGRU) on multiple datasets. Results
                 demonstrated the superior performance of our hybrid
                 model, achieving 98.9\% accuracy on the most
                 challenging dataset. It outperformed existing models in
                 resource utilization, with faster training and testing
                 times and low memory usage.",
  acknowledgement = ack-nhfb,
  articleno =    "369",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Efthymiadis:2024:AOT,
  author =       "Filippos Efthymiadis and Aristeidis Karras and
                 Christos Karras and Spyros Sioutas",
  title =        "Advanced Optimization Techniques for Federated
                 Learning on Non-{IID} Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "13",
  month =        oct,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100370",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/370",
  abstract =     "Federated learning enables model training on multiple
                 clients locally, without the need to transfer their
                 data to a central server, thus ensuring data privacy.
                 In this paper, we investigate the impact of
                 Non-Independent and Identically Distributed (non-IID)
                 data on the performance of federated training, where we
                 find a reduction in accuracy of up to 29\% for neural
                 networks trained in environments with skewed non-IID
                 data. Two optimization strategies are presented to
                 address this issue. The first strategy focuses on
                 applying a cyclical learning rate to determine the
                 learning rate during federated training, while the
                 second strategy develops a sharing and pre-training
                 method on augmented data in order to improve the
                 efficiency of the algorithm in the case of non-IID
                 data. By combining these two methods, experiments show
                 that the accuracy on the CIFAR-10 dataset increased by
                 about 36\% while achieving faster convergence by
                 reducing the number of required communication rounds by
                 5.33 times. The proposed techniques lead to improved
                 accuracy and faster model convergence, thus
                 representing a significant advance in the field of
                 federated learning and facilitating its application to
                 real-world scenarios.",
  acknowledgement = ack-nhfb,
  articleno =    "370",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chen:2024:MSD,
  author =       "Fanghua Chen and Deguang Shang and Gang Zhou and Ke Ye
                 and Guofang Wu",
  title =        "Multi-Source Data Fusion for Vehicle Maintenance
                 Project Prediction",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "14",
  month =        oct,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100371",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/371",
  abstract =     "Ensuring road safety is heavily reliant on the
                 effective maintenance of vehicles. Accurate predictions
                 of maintenance requirements can substantially reduce
                 ownership costs for vehicle owners. Consequently, this
                 field has attracted increasing attention from
                 researchers in recent years. However, existing studies
                 primarily focus on predicting a limited number of
                 maintenance needs, predominantly based solely on
                 vehicle mileage and driving time. This approach often
                 falls short, as it does not comprehensively monitor the
                 overall health condition of vehicles, thus posing
                 potential safety risks. To address this issue, we
                 propose a deep fusion network model that utilizes
                 multi-source data, including vehicle maintenance record
                 data and vehicle base information data, to provide
                 comprehensive predictions for vehicle maintenance
                 projects. To capture the relationships among various
                 maintenance projects, we create a correlation
                 representation using the maintenance project
                 co-occurrence matrix. Furthermore, building on the
                 correlation representation, we propose a deep fusion
                 network that employs the attention mechanism to
                 efficiently merge vehicle mileage and vehicle base
                 information. Experiments conducted on real data
                 demonstrate the superior performance of our proposed
                 model relative to competitive baseline models in
                 predicting vehicle maintenance projects.",
  acknowledgement = ack-nhfb,
  articleno =    "371",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Otoum:2024:EHD,
  author =       "Yazan Otoum and Chaosheng Hu and Eyad Haj Said and
                 Amiya Nayak",
  title =        "Enhancing Heart Disease Prediction with Federated
                 Learning and Blockchain Integration",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "14",
  month =        oct,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100372",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/372",
  abstract =     "Federated learning offers a framework for developing
                 local models across institutions while safeguarding
                 sensitive data. This paper introduces a novel approach
                 for heart disease prediction using the TabNet model,
                 which combines the strengths of tree-based models and
                 deep neural networks. Our study utilizes the
                 Comprehensive Heart Disease and UCI Heart Disease
                 datasets, leveraging TabNet's architecture to enhance
                 data handling in federated environments. Horizontal
                 federated learning was implemented using the federated
                 averaging algorithm to securely aggregate model updates
                 across participants. Blockchain technology was
                 integrated to enhance transparency and accountability,
                 with smart contracts automating governance. The
                 experimental results demonstrate that TabNet achieved
                 the highest balanced metrics score of 1.594 after 50
                 epochs, with an accuracy of 0.822 and an epsilon value
                 of 6.855, effectively balancing privacy and
                 performance. The model also demonstrated strong
                 accuracy with only 10 iterations on aggregated data,
                 highlighting the benefits of multi-source data
                 integration. This work presents a scalable,
                 privacy-preserving solution for heart disease
                 prediction, combining TabNet and blockchain to address
                 key healthcare challenges while ensuring data
                 integrity.",
  acknowledgement = ack-nhfb,
  articleno =    "372",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Islam:2024:HSS,
  author =       "Rafiq {Ul Islam} and Pasquale Mazzei and Claudio
                 Savaglio",
  title =        "Healthiness and Safety of Smart Environments through
                 Edge Intelligence and {Internet of Things}
                 Technologies",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "14",
  month =        oct,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100373",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/373",
  abstract =     "Smart environments exploit rising technologies like
                 Internet of Things (IoT) and edge intelligence (EI) to
                 achieve unseen effectiveness and efficiency in every
                 tasks, including air sanitization. The latter
                 represents a key preventative measure--made even more
                 evident by the COVID-19 pandemic--to significantly
                 reduce disease transmission and create healthier and
                 safer indoor spaces, for the sake of its occupants.
                 Therefore, in this paper, we present an IoT-based
                 system aimed at the continuous monitoring of the air
                 quality and, through EI techniques, at the proactively
                 activation of ozone lamps, while ensuring safety in
                 sanitization. Indeed, these devices ensure extreme
                 effectiveness in killing viruses and bacteria but, due
                 to ozone toxicity, they must be properly controlled
                 with advanced technologies for preventing occupants
                 from dangerous exposition as well as for ensuring
                 system reliability, operational efficiency, and
                 regulatory compliance.",
  acknowledgement = ack-nhfb,
  articleno =    "373",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Manzoor:2024:SSS,
  author =       "Habib Ullah Manzoor and Attia Shabbir and Ao Chen and
                 David Flynn and Ahmed Zoha",
  title =        "A Survey of Security Strategies in Federated Learning:
                 Defending Models, Data, and Privacy",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "15",
  month =        oct,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100374",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/374",
  abstract =     "Federated Learning (FL) has emerged as a
                 transformative paradigm in machine learning, enabling
                 decentralized model training across multiple devices
                 while preserving data privacy. However, the
                 decentralized nature of FL introduces significant
                 security challenges, making it vulnerable to various
                 attacks targeting models, data, and privacy. This
                 survey provides a comprehensive overview of the defense
                 strategies against these attacks, categorizing them
                 into data and model defenses and privacy attacks. We
                 explore pre-aggregation, in-aggregation, and
                 post-aggregation defenses, highlighting their
                 methodologies and effectiveness. Additionally, the
                 survey delves into advanced techniques such as
                 homomorphic encryption and differential privacy to
                 safeguard sensitive information. The integration of
                 blockchain technology for enhancing security in FL
                 environments is also discussed, along with incentive
                 mechanisms to promote active participation among
                 clients. Through this detailed examination, the survey
                 aims to inform and guide future research in developing
                 robust defense frameworks for FL systems.",
  acknowledgement = ack-nhfb,
  articleno =    "374",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Guo:2024:SES,
  author =       "Xiaotong Guo and Huijie Zhao and Shuwei Shao and
                 Xudong Li and Baochang Zhang and Na Li",
  title =        "{SPDepth}: Enhancing Self-Supervised Indoor Monocular
                 Depth Estimation via Self-Propagation",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "16",
  month =        oct,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100375",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/375",
  abstract =     "Due to the existence of low-textured areas in indoor
                 scenes, some self-supervised depth estimation methods
                 have specifically designed sparse photometric
                 consistency losses and geometry-based losses. However,
                 some of the loss terms cannot supervise all the pixels,
                 which limits the performance of these methods. Some
                 approaches introduce an additional optical flow network
                 to provide dense correspondences supervision, but
                 overload the loss function. In this paper, we propose
                 to perform depth self-propagation based on feature
                 self-similarities, where high-accuracy depths are
                 propagated from supervised pixels to unsupervised ones.
                 The enhanced self-supervised indoor monocular depth
                 estimation network is called SPDepth. Since depth
                 self-similarities are significant in a local range, a
                 local window self-attention module is embedded at the
                 end of the network to propagate depths in a window. The
                 depth of a pixel is weighted using the feature
                 correlation scores with other pixels in the same
                 window. The effectiveness of self-propagation mechanism
                 is demonstrated in the experiments on the NYU Depth V2
                 dataset. The root-mean-squared error of SPDepth is
                 0.585 and the {\delta} 1 accuracy is 77.6\%. Zero-shot
                 generalization studies are also conducted on the
                 7-Scenes dataset and provide a more comprehensive
                 analysis about the application characteristics of
                 SPDepth.",
  acknowledgement = ack-nhfb,
  articleno =    "375",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kuaban:2024:ITA,
  author =       "Godlove Suila Kuaban and Valery Nkemeni and Onyeka J.
                 Nwobodo and Piotr Czekalski and Fabien Mieyeville",
  title =        "{Internet of Things} Adoption in Technology Ecosystems
                 Within the Central {African} Region: The Case of
                 Silicon Mountain",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "16",
  month =        oct,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100376",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/376",
  abstract =     "The Internet of Things (IoT) has emerged as a
                 transformative technology with the potential to
                 revolutionize various sectors and industries worldwide.
                 Despite its global significance, the adoption and
                 implementation of IoT technologies in emerging
                 technology ecosystems within the Central African region
                 still need to be studied and explored. This paper
                 presents a case study of the Silicon Mountain
                 technology ecosystem, located in Fako division of the
                 southwest region of Cameroon, focusing on the barriers
                 and challenges to adopting and integrating IoT
                 technologies within this emerging tech ecosystem.
                 Through a survey-based approach, we investigate the
                 factors influencing IoT adoption in the Silicon
                 Mountain tech ecosystem, including technological,
                 economic, social, and regulatory factors. Our study
                 reveals key insights into the current state of IoT
                 adoption, opportunities for growth and innovation, and
                 IoT adoption challenges. Key among the challenges
                 identified for impeding IoT uptake were issues related
                 to standardization and financial resources, labor
                 shortage in the industry, educational and knowledge
                 gaps, market challenges, government policies, security
                 and data privacy concerns, and inadequate power supply.
                 Based on our findings, we provide recommendations for
                 policymakers, industry stakeholders, and academic
                 institutions to promote and facilitate the widespread
                 adoption of IoT technologies in Silicon Mountain and
                 the Central African region at large.",
  acknowledgement = ack-nhfb,
  articleno =    "376",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Qasim:2024:IET,
  author =       "Kian Raheem Qasim and Noor M. Naser and Ahmed J.
                 Jabur",
  title =        "An {IoT}-Enhanced Traffic Light Control System with
                 {Arduino} and {IR} Sensors for Optimized Traffic
                 Patterns",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "18",
  month =        oct,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100377",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/377",
  abstract =     "Traffic lights play an important role in efficient
                 traffic management, especially in crowded cities.
                 Optimizing traffic helps to reduce crowding, save time,
                 and ensure the smooth flow of traffic. Metaheuristic
                 algorithms have a proven ability to optimize smart
                 traffic management systems. This paper investigates the
                 effectiveness of two metaheuristic algorithms: particle
                 swarm optimization (PSO) and grey wolf optimization
                 (GWO). In addition, we posit a hybrid PSO-GWO method of
                 optimizing traffic light control using IoT-enabled data
                 from sensors. In this study, we aimed to enhance the
                 movement of traffic, minimize delays, and improve
                 overall traffic precision. Our results demonstrate that
                 the hybrid PSO-GWO method outperforms individual PSO
                 and GWO algorithms, achieving superior traffic movement
                 precision (0.925173), greater delay reduction
                 (0.994543), and higher throughput improvement (0.89912)
                 than standalone methods. PSO excels in reducing wait
                 times (0.7934), while GWO shows reasonable performance
                 across a range of metrics. The hybrid approach
                 leverages the power of both PSO and GWO algorithms,
                 proving to be the most effective solution for smart
                 traffic management. This research highlights using
                 hybrid optimization techniques and IoT (Internet of
                 Things) in developing traffic control systems.",
  acknowledgement = ack-nhfb,
  articleno =    "377",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Elkhodr:2024:SRM,
  author =       "Mahmoud Elkhodr and Ketmanto Wangsa and Ergun Gide and
                 Shakir Karim",
  title =        "A Systematic Review and Multifaceted Analysis of the
                 Integration of Artificial Intelligence and Blockchain:
                 Shaping the Future of {Australian} Higher Education",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "18",
  month =        oct,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100378",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/378",
  abstract =     "This study explores the applications and implications
                 of blockchain technology in the Australian higher
                 education system, focusing on its integration with
                 artificial intelligence (AI). By addressing critical
                 challenges in credential verification, administrative
                 efficiency, and academic integrity, this integration
                 aims to enhance the global competitiveness of
                 Australian higher education institutions. A
                 comprehensive review of 25 recent research papers
                 quantifies the benefits, challenges, and prospects of
                 blockchain adoption in educational settings. Our
                 findings reveal that 52\% of the reviewed papers focus
                 on systematic reviews, 28\% focus on application-based
                 studies, and 20\% combine both approaches. The keyword
                 analysis identified 287 total words, with
                 ``blockchain'' and ``education'' as the most prominent
                 themes. This study highlights blockchain's potential to
                 improve credential management, academic integrity,
                 administrative efficiency, and funding mechanisms in
                 education. However, challenges such as technical
                 implementation (24\%), regulatory compliance (32\%),
                 environmental concerns (28\%), and data security risks
                 (40\%) must be addressed to achieve widespread
                 adoption. This study also discusses critical
                 prerequisites for successful blockchain integration,
                 including infrastructure development, staff training,
                 regulatory harmonisation, and the incorporation of AI
                 for personalised learning. Our research concludes that
                 blockchain, when strategically implemented and combined
                 with AI, has the potential to transform the Australian
                 higher education system, significantly enhancing its
                 integrity, efficiency, and global competitiveness.",
  acknowledgement = ack-nhfb,
  articleno =    "378",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hatami:2024:SRT,
  author =       "Mohsen Hatami and Qian Qu and Yu Chen and Hisham
                 Kholidy and Erik Blasch and Erika Ardiles-Cruz",
  title =        "A Survey of the Real-Time Metaverse: Challenges and
                 Opportunities",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "18",
  month =        oct,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100379",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/379",
  abstract =     "The metaverse concept has been evolving from static,
                 pre-rendered virtual environments to a new frontier:
                 the real-time metaverse. This survey paper explores the
                 emerging field of real-time metaverse technologies,
                 which enable the continuous integration of dynamic,
                 real-world data into immersive virtual environments. We
                 examine the key technologies driving this evolution,
                 including advanced sensor systems (LiDAR, radar,
                 cameras), artificial intelligence (AI) models for data
                 interpretation, fast data fusion algorithms, and edge
                 computing with 5G networks for low-latency data
                 transmission. This paper reveals how these technologies
                 are orchestrated to achieve near-instantaneous
                 synchronization between physical and virtual worlds, a
                 defining characteristic that distinguishes the
                 real-time metaverse from its traditional counterparts.
                 The survey provides a comprehensive insight into the
                 technical challenges and discusses solutions to realize
                 responsive dynamic virtual environments. The potential
                 applications and impact of real-time metaverse
                 technologies across various fields are considered,
                 including live entertainment, remote collaboration,
                 dynamic simulations, and urban planning with digital
                 twins. By synthesizing current research and identifying
                 future directions, this survey provides a foundation
                 for understanding and advancing the rapidly evolving
                 landscape of real-time metaverse technologies,
                 contributing to the growing body of knowledge on
                 immersive digital experiences and setting the stage for
                 further innovations in the Metaverse transformative
                 field.",
  acknowledgement = ack-nhfb,
  articleno =    "379",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kufakunesu:2024:CAA,
  author =       "Rachel Kufakunesu and Gerhard P. Hancke and Adnan M.
                 Abu-Mahfouz",
  title =        "Collision Avoidance Adaptive Data Rate Algorithm for
                 {LoRaWAN}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "19",
  month =        oct,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100380",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/380",
  abstract =     "Long-Range Wide-Area Network (LoRaWAN) technology
                 offers efficient connectivity for numerous end devices
                 over a wide coverage area in the Internet of Things
                 (IoT) network, enabling the exchange of data over the
                 Internet between even the most minor Internet-connected
                 devices and systems. One of LoRaWAN's hallmark features
                 is the Adaptive Data Rate (ADR) algorithm. ADR is a
                 resource allocation function which dynamically adjusts
                 the network's data rate, airtime, and energy
                 dissipation to optimise its performance. The allocation
                 of spreading factors plays a critical function in
                 defining the throughput of the end device and its
                 robustness to interference. However, in practical
                 deployments, LoRaWAN networks experience considerable
                 interference, severely affecting the packet delivery
                 ratio, energy utilisation, and general network
                 performance. To address this, we present a novel ADR
                 framework, SSFIR-ADR, which utilises randomised
                 spreading factor allocation to minimise energy
                 consumption and packet collisions while maintaining
                 optimal network performance. We implement a LoRa
                 network composed of a single gateway that connects
                 loads of end nodes to a network server. In terms of
                 energy use, packet delivery rate, and interference rate
                 (IR), our simulation implementation does better than
                 LoRaWAN's legacy ADR scheme for a range of application
                 data intervals.",
  acknowledgement = ack-nhfb,
  articleno =    "380",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Abinayaa:2024:SEC,
  author =       "Sennanur Srinivasan Abinayaa and Prakash Arumugam and
                 Divya Bhavani Mohan and Anand Rajendran and Abderezak
                 Lashab and Baoze Wei and Josep M. Guerrero",
  title =        "Securing the Edge: {CatBoost} Classifier Optimized by
                 the Lyrebird Algorithm to Detect Denial of Service
                 Attacks in {Internet of Things}-Based Wireless Sensor
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "19",
  month =        oct,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100381",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/381",
  abstract =     "The security of Wireless Sensor Networks (WSNs) is of
                 the utmost importance because of their widespread use
                 in various applications. Protecting WSNs from harmful
                 activity is a vital function of intrusion detection
                 systems (IDSs). An innovative approach to WSN intrusion
                 detection (ID) utilizing the CatBoost classifier (Cb-C)
                 and the Lyrebird Optimization Algorithm is presented in
                 this work (LOA). As is typical in ID settings, Cb-C
                 excels at handling datasets that are imbalanced. The
                 lyrebird's remarkable capacity to imitate the sounds of
                 its surroundings served as inspiration for the LOA, a
                 metaheuristic optimization algorithm. The WSN-DS
                 dataset, acquired from Prince Sultan University in
                 Saudi Arabia, is used to assess the suggested method.
                 Among the models presented, LOA-Cb-C produces the
                 highest accuracy of 99.66\%; nevertheless, when
                 compared with the other methods discussed in this
                 article, its error value of 0.34\% is the lowest.
                 Experimental results reveal that the suggested strategy
                 improves WSN-IoT security over the existing methods in
                 terms of detection accuracy and the false alarm rate.",
  acknowledgement = ack-nhfb,
  articleno =    "381",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Salunke:2024:PBP,
  author =       "Sanket Vilas Salunke and Abdelkader Ouda",
  title =        "A Performance Benchmark for the {PostgreSQL} and
                 {MySQL} Databases",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "19",
  month =        oct,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100382",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/sqlbooks.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/382",
  abstract =     "This study highlights the necessity for efficient
                 database management in continuous authentication
                 systems, which rely on large-scale behavioral biometric
                 data such as keystroke patterns. A benchmarking
                 framework was developed to evaluate the PostgreSQL and
                 MySQL databases, minimizing repetitive coding through
                 configurable functions and variables. The methodology
                 involved experiments assessing select and insert
                 queries under primary and complex conditions,
                 simulating real-world scenarios. Our quantified results
                 show PostgreSQL's superior performance in select
                 operations. In primary tests, PostgreSQL's execution
                 time for 1 million records ranged from 0.6 ms to 0.8
                 ms, while MySQL's ranged from 9 ms to 12 ms, indicating
                 that PostgreSQL is about 13 times faster. For select
                 queries with a where clause, PostgreSQL required 0.09
                 ms to 0.13 ms compared to MySQL's 0.9 ms to 1 ms,
                 making it roughly 9 times more efficient. Insert
                 operations were similar, with PostgreSQL at 0.0007 ms
                 to 0.0014 ms and MySQL at 0.0010 ms to 0.0030 ms. In
                 complex experiments with simultaneous operations,
                 PostgreSQL maintained stable performance (0.7 ms to 0.9
                 ms for select queries during inserts), while MySQL's
                 performance degraded significantly (7 ms to 13 ms).
                 These findings underscore PostgreSQL's suitability for
                 environments requiring low data latency and robust
                 concurrent processing capabilities, making it ideal for
                 continuous authentication systems.",
  acknowledgement = ack-nhfb,
  articleno =    "382",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Vasilas:2024:CVA,
  author =       "Teodora Vasilas and Claudiu Bacila and Remus Brad",
  title =        "Correction: {Vasilas et al. Beat the Heat: Syscall
                 Attack Detection via Thermal Side Channel. Future
                 Internet 2024, 16, 301}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "21",
  month =        oct,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100383",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/383",
  abstract =     "The integration of the Internet of Things (IoT) and
                 Distributed Computing Systems (DCS) is transforming
                 business models across industries. IoT devices allow
                 immediate monitoring of equipment and processes,
                 mitigating lost time and enhancing efficiency. In this
                 case, manufacturing companies use IoT sensors to
                 monitor machinery, predict failures, and schedule
                 maintenance. Also, automation via IoT reduces manual
                 intervention, resulting in boosted productivity in
                 smart factories and automated supply chains. IoT
                 devices generate this vast amount of data, which
                 businesses analyze to gain insights into customer
                 behavior, operational inefficiencies, and market
                 trends. In turn, Distributed Computing Systems process
                 this data, providing actionable insights and enabling
                 advanced analytics and machine learning for future
                 trend predictions. While, IoT facilitates personalized
                 products and services by collecting data on customer
                 preferences and usage patterns, enhancing satisfaction
                 and loyalty, IoT devices support new customer
                 interactions, like wearable health devices, and enable
                 subscription-based and pay-per-use models in
                 transportation and utilities. Conversely, real-time
                 monitoring enhances security, as distributed systems
                 quickly respond to threats, ensuring operational
                 safety. It also aids regulatory compliance by providing
                 accurate operational data. In this way, this study,
                 through a Bibliometric Literature Review (LRSB) of 91
                 screened pieces of literature, aims at ascertaining to
                 what extent the aforementioned capacities, overall,
                 enhance business models, in terms of efficiency and
                 effectiveness. The study concludes that those systems
                 altogether leverage businesses, promoting competitive
                 edge, continuous innovation, and adaptability to market
                 dynamics. In particular, overall, the integration of
                 both IoT and Distributed Systems in business models
                 augments its numerous advantages: it develops smart
                 infrastructures e.g., smart grids; edge computing that
                 allows data processing closer to the data source e.g.,
                 autonomous vehicles; predictive analytics, by helping
                 businesses anticipate issues e.g., to foresee equipment
                 failures; personalized services e.g., through
                 e-commerce platforms of personalized recommendations to
                 users; enhanced security, while reducing the risk of
                 centralized attacks e.g., blockchain technology, in how
                 IoT and Distributed Computing Systems altogether impact
                 business models. Future research avenues are
                 suggested.",
  acknowledgement = ack-nhfb,
  articleno =    "383",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rosario:2024:ITD,
  author =       "Alb{\'e}rico Travassos Ros{\'a}rio and Ricardo
                 Raimundo",
  title =        "{Internet of Things} and Distributed Computing Systems
                 in Business Models",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "10",
  day =          "21",
  month =        oct,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16100384",
  ISSN =         "1999-5903",
  ISSN-L =       "1999-5903",
  bibdate =      "Mon Oct 28 06:41:40 MDT 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/10/384",
  abstract =     "The integration of the Internet of Things (IoT) and
                 Distributed Computing Systems (DCS) is transforming
                 business models across industries. IoT devices allow
                 immediate monitoring of equipment and processes,
                 mitigating lost time and enhancing efficiency. In this
                 case, manufacturing companies use IoT sensors to
                 monitor machinery, predict failures, and schedule
                 maintenance. Also, automation via IoT reduces manual
                 intervention, resulting in boosted productivity in
                 smart factories and automated supply chains. IoT
                 devices generate this vast amount of data, which
                 businesses analyze to gain insights into customer
                 behavior, operational inefficiencies, and market
                 trends. In turn, Distributed Computing Systems process
                 this data, providing actionable insights and enabling
                 advanced analytics and machine learning for future
                 trend predictions. While, IoT facilitates personalized
                 products and services by collecting data on customer
                 preferences and usage patterns, enhancing satisfaction
                 and loyalty, IoT devices support new customer
                 interactions, like wearable health devices, and enable
                 subscription-based and pay-per-use models in
                 transportation and utilities. Conversely, real-time
                 monitoring enhances security, as distributed systems
                 quickly respond to threats, ensuring operational
                 safety. It also aids regulatory compliance by providing
                 accurate operational data. In this way, this study,
                 through a Bibliometric Literature Review (LRSB) of 91
                 screened pieces of literature, aims at ascertaining to
                 what extent the aforementioned capacities, overall,
                 enhance business models, in terms of efficiency and
                 effectiveness. The study concludes that those systems
                 altogether leverage businesses, promoting competitive
                 edge, continuous innovation, and adaptability to market
                 dynamics. In particular, overall, the integration of
                 both IoT and Distributed Systems in business models
                 augments its numerous advantages: it develops smart
                 infrastructures e.g., smart grids; edge computing that
                 allows data processing closer to the data source e.g.,
                 autonomous vehicles; predictive analytics, by helping
                 businesses anticipate issues e.g., to foresee equipment
                 failures; personalized services e.g., through
                 e-commerce platforms of personalized recommendations to
                 users; enhanced security, while reducing the risk of
                 centralized attacks e.g., blockchain technology, in how
                 IoT and Distributed Computing Systems altogether impact
                 business models. Future research avenues are
                 suggested.",
  acknowledgement = ack-nhfb,
  articleno =    "384",
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Crespo-Aguado:2024:FHD,
  author =       "Maria Crespo-Aguado and Raul Lozano and Fernando
                 Hernandez-Gobertti and Nuria Molner and David
                 Gomez-Barquero",
  title =        "Flexible Hyper-Distributed {IoT}--Edge--Cloud Platform
                 for Real-Time Digital Twin Applications on 6G-Intended
                 Testbeds for Logistics and Industry",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "431",
  day =          "20",
  month =        nov,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110431",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/431",
  abstract =     "This paper presents the design and development of a
                 flexible hyper-distributed IoT--Edge--Cloud computing
                 platform for real-time Digital Twins in real logistics
                 and industrial environments, intended as a novel living
                 lab and testbed for future 6G applications. It expands
                 the limited capabilities of IoT devices with extended
                 Cloud and Edge computing functionalities, creating an
                 IoT--Edge--Cloud continuum platform composed of
                 multiple stakeholder solutions, in which vertical
                 application developers can take full advantage of the
                 computing resources of the infrastructure. The platform
                 is built together with a private 5G network to connect
                 machines and sensors on a large scale. Artificial
                 intelligence and machine learning are used to allocate
                 computing resources for real-time services by an
                 end-to-end intelligent orchestrator, and real-time
                 distributed analytic tools leverage Edge computing
                 platforms to support different types of Digital Twin
                 applications for logistics and industry, such as
                 immersive remote driving, with specific characteristics
                 and features. Performance evaluations demonstrated the
                 platform's capability to support the high-throughput
                 communications required for Digital Twins, achieving
                 user-experienced rates close to the maximum theoretical
                 values, up to 552 Mb/s for the downlink and 87.3 Mb/s
                 for the uplink in the n78 frequency band. Moreover, the
                 platform's support for Digital Twins was validated via
                 QoE assessments conducted on an immersive remote
                 driving prototype, which demonstrated high levels of
                 user satisfaction in key dimensions such as presence,
                 engagement, control, sensory integration, and cognitive
                 load.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tomer:2024:RIM,
  author =       "Vikas Tomer and Sachin Sharma and Mark Davis",
  title =        "Resilience in the {Internet of Medical Things}: a
                 Review and Case Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "430",
  day =          "20",
  month =        nov,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110430",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/430",
  abstract =     "The Internet of Medical Things (IoMT), an extension of
                 the Internet of Things (IoT), is still in its early
                 stages of development. Challenges that are inherent to
                 IoT, persist in IoMT as well. The major focus is on
                 data transmission within the healthcare domain due to
                 its profound impact on health and public well-being.
                 Issues such as latency, bandwidth constraints, and
                 concerns regarding security and privacy are critical in
                 IoMT owing to the sensitive nature of patient data,
                 including patient identity and health status. Numerous
                 forms of cyber-attacks pose threats to IoMT networks,
                 making the reliable and secure transmission of critical
                 medical data a challenging task. Several other
                 situations, such as natural disasters, war,
                 construction works, etc., can cause IoMT networks to
                 become unavailable and fail to transmit the data. The
                 first step in these situations is to recover from
                 failure as quickly as possible, resume the data
                 transfer, and detect the cause of faults, failures, and
                 errors. Several solutions exist in the literature to
                 make the IoMT resilient to failure. However, no single
                 approach proposed in the literature can simultaneously
                 protect the IoMT networks from various attacks,
                 failures, and faults. This paper begins with a detailed
                 description of IoMT and its applications. It considers
                 the underlying requirements of resilience for IoMT
                 networks, such as monitoring, control, diagnosis, and
                 recovery. This paper comprehensively analyzes existing
                 research efforts to provide IoMT network resilience
                 against diverse causes. After investigating several
                 research proposals, we identify that the combination of
                 software-defined networks (SDNs), machine learning
                 (ML), and microservices architecture (MSA) has the
                 capabilities to fulfill the requirements for achieving
                 resilience in the IoMT networks. It mainly focuses on
                 the analysis of technologies, such as SDN, ML, and MSA,
                 separately, for meeting the resilience requirements in
                 the IoMT networks. SDN can be used for monitoring and
                 control, and ML can be used for anomaly detection and
                 diagnosis, whereas MSA can be used for bringing
                 distributed functionality and recovery into the IoMT
                 networks. This paper provides a case study that
                 describes the remote patient monitoring (RPM) of a
                 heart patient in IoMT networks. It covers the different
                 failure scenarios in IoMT infrastructure. Finally, we
                 provide a proposed methodology that elaborates how
                 distributed functionality can be achieved during these
                 failures using machine learning, software-defined
                 networks, and microservices technologies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Haz:2024:FOS,
  author =       "Amma Liesvarastranta Haz and Yohanes Yohanie Fridelin
                 Panduman and Nobuo Funabiki and Evianita Dewi Fajrianti
                 and Sritrusta Sukaridhoto",
  title =        "Fully Open-Source Meeting Minutes Generation Tool",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "429",
  day =          "20",
  month =        nov,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110429",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/429",
  abstract =     "With the increasing use of online meetings, there is a
                 growing need for efficient tools that can automatically
                 generate meeting minutes from recorded sessions.
                 Current solutions often rely on proprietary systems,
                 limiting adaptability and flexibility. This paper
                 investigates whether various open-source models and
                 methods such as audio-to-text conversion,
                 summarization, keyword extraction, and optical
                 character recognition (OCR) can be integrated to create
                 a meeting minutes generation tool for recorded video
                 presentations. For this purpose, a series of
                 evaluations are conducted to identify suitable models.
                 Then, the models are integrated into a system that is
                 modular yet accurate. The utilization of an open-source
                 approach ensures that the tool remains accessible and
                 adaptable to the latest innovations, thereby ensuring
                 continuous improvement over time. Furthermore, this
                 approach also benefits organizations and individuals by
                 providing a cost-effective and flexible alternative.
                 This work contributes to creating a modular and easily
                 extensible open-source framework that integrates
                 several advanced technologies and future new models
                 into a cohesive system. The system was evaluated on ten
                 videos created under controlled conditions, which may
                 not fully represent typical online presentation
                 recordings. It showed strong performance in
                 audio-to-text conversion with a low word-error rate.
                 Summarization and keyword extraction were functional
                 but showed room for improvement in terms of precision
                 and relevance, as gathered from the users' feedback.
                 These results confirm the system's effectiveness and
                 efficiency in generating usable meeting minutes from
                 recorded presentation videos, with room for improvement
                 in future works.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Carrascal:2024:FPR,
  author =       "David Carrascal and Paula Bartolom{\'e} and Elisa
                 Rojas and Diego Lopez-Pajares and Nicolas Manso and
                 Javier Diaz-Fuentes",
  title =        "Fault Prediction and Reconfiguration Optimization in
                 Smart Grids: {AI}-Driven Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "428",
  day =          "20",
  month =        nov,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110428",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/428",
  abstract =     "Smart grids (SGs) are essential for the efficient and
                 distributed management of electrical distribution
                 networks. A key task in SG management is fault
                 detection and subsequently, network reconfiguration to
                 minimize power losses and balance loads. This process
                 should minimize power losses while optimizing
                 distribution by balancing loads across the grid.
                 However, the current literature yields a lack of
                 methods for efficient fault prediction and fast
                 reconfiguration. To achieve this goal, this paper
                 builds on DEN2DE, an adaptable routing and
                 reconfiguration solution potentially applicable to SGs,
                 and investigates its potential extension with AI-based
                 fault prediction using real-world datasets and randomly
                 generated topologies based on the IEEE 123 Node Test
                 Feeder. The study applies models based on Machine
                 Learning (ML) and Deep Learning (DL) techniques,
                 specifically evaluating Random Forest (RF) and Support
                 Vector Machine (SVM) as ML methods, and Artificial
                 Neural Network (ANN) as a DL method, evaluating each
                 for accuracy, precision, and recall. Results indicate
                 that the RF model with Recursive Feature Elimination
                 (RFECV) achieves 94.28\% precision and 81.05\% recall,
                 surpassing SVM (precision 89.32\%, recall 6.95\%) and
                 ANN (precision 72.17\%, recall 13.49\%) in fault
                 detection accuracy and reliability.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sturley:2024:VVC,
  author =       "Hamish Sturley and Augustin Fournier and Andoni
                 Salcedo-Navarro and Miguel Garcia-Pineda and Jaume
                 Segura-Garcia",
  title =        "Virtualization vs. Containerization, a Comparative
                 Approach for Application Deployment in the Computing
                 Continuum Focused on the Edge",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "427",
  day =          "19",
  month =        nov,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110427",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/427",
  abstract =     "With the emergence of containerization 10 years ago,
                 we saw a compact, convenient and portable way of
                 running apps directly concurrently with virtualization.
                 The major difference is in the architecture. Containers
                 share the same kernel as the guest and then do not
                 virtualize low-layer components like the Central
                 Processing Unit (CPU). On the one hand, they are
                 lighter and more flexible than virtual machines (VMs).
                 On the other hand, VMs can more precisely meet the
                 low-layer needs and are completely autonomous systems.
                 Nowadays, what is the best architecture to use to
                 develop an application? In this paper, we will study
                 the two main virtual methods of deploying this. We will
                 compare both methods on several criteria: compatibility
                 based on user experience and the ease of
                 installation/deployment, scalability based on the
                 automatic elasticity facing the workload and energy
                 efficiency in terms of energy and computer resources.
                 After the tests, we conclude that the containerization
                 option is the most ecologically advantageous option in
                 terms of energy consumption.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Adkins:2024:IPI,
  author =       "Jonathan Adkins and Ali {Al Bataineh} and Majd
                 Khalaf",
  title =        "Identifying Persons of Interest in Digital Forensics
                 Using {NLP}-Based {AI}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "426",
  day =          "18",
  month =        nov,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110426",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/426",
  abstract =     "The field of digital forensics relies on expertise
                 from multiple domains, including computer science,
                 criminology, and law. It also relies on different
                 toolsets and an analyst's expertise to parse enormous
                 amounts of user-generated data to find clues that help
                 crack a case. This process of investigative analysis is
                 often done manually. Artificial Intelligence (AI) can
                 provide practical solutions to efficiently mine
                 enormous amounts of data to find useful patterns that
                 can be leveraged to investigate crimes. Natural
                 Language Processing (NLP) is a subdomain of research
                 under AI that deals with problems involving
                 unstructured data, specifically language. The domain of
                 NLP includes several tools to parse text, including
                 topic modeling, pairwise correlation, word vector
                 cosine distance measurement, and sentiment analysis. In
                 this research, we propose a digital forensic
                 investigative technique that uses an ensemble of NLP
                 tools to identify a person of interest list based on a
                 corpus of text. Our proposed method serves as a type of
                 human feature reduction, where a total pool of suspects
                 is filtered down to a short list of candidates who
                 possess a higher correlation with the crime being
                 investigated.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kubba:2024:ELR,
  author =       "Abbas Kubba and Hafedh Trabelsi and Faouzi Derbel",
  title =        "Enhanced Long-Range Network Performance of an Oil
                 Pipeline Monitoring System Using a Hybrid Deep Extreme
                 Learning Machine Model",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "425",
  day =          "17",
  month =        nov,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110425",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/425",
  abstract =     "Leak detection in oil and gas pipeline networks is a
                 climacteric and frequent issue in the oil and gas
                 field. Many establishments have long depended on
                 stationary hardware or traditional assessments to
                 monitor and detect abnormalities. Rapid technological
                 progress; innovation in engineering; and advanced
                 technologies providing cost-effective, rapidly
                 executed, and easy to implement solutions lead to
                 building an efficient oil pipeline leak detection and
                 real-time monitoring system. In this area, wireless
                 sensor networks (WSNs) are increasingly required to
                 enhance the reliability of checkups and improve the
                 accuracy of real-time oil pipeline monitoring systems
                 with limited hardware resources. The real-time
                 transient model (RTTM) is a leak detection method
                 integrated with LoRaWAN technology, which is proposed
                 in this study to implement a wireless oil pipeline
                 network for long distances. This study will focus on
                 enhancing the LoRa network parameters, e.g., node power
                 consumption, average packet loss, and delay, by
                 applying several machine learning techniques in order
                 to optimize the durability of individual nodes'
                 lifetimes and enhance total system performance. The
                 proposed system is implemented in an OMNeT++ network
                 simulator with several frameworks, such as Flora and
                 Inet, to cover the LoRa network, which is used as the
                 system's network infrastructure. In order to implement
                 artificial intelligence over the FLoRa network, the
                 LoRa network was integrated with several programming
                 tools and libraries, such as Python script and the
                 TensorFlow libraries. Several machine learning
                 algorithms have been applied, such as the random forest
                 (RF) algorithm and the deep extreme learning machine
                 (DELM) technique, to develop the proposed model and
                 improve the LoRa network's performance. They improved
                 the LoRa network's output performance, e.g., its power
                 consumption, packet loss, and packet delay, with
                 different enhancement ratios. Finally, a hybrid deep
                 extreme learning machine model was built and selected
                 as the proposed model due to its ability to improve the
                 LoRa network's performance, with perfect prediction
                 accuracy, a mean square error of 0.75, and an
                 exceptional enhancement ratio of 39\% for LoRa node
                 power consumption.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Paraschiv:2024:ADN,
  author =       "Elena-Anca Paraschiv and Lidia Bajenaru and Cristian
                 Petrache and Ovidiu Bica and Dragos-Nicolae Nicolau",
  title =        "{AI}-Driven Neuro-Monitoring: Advancing Schizophrenia
                 Detection and Management Through Deep Learning and
                 {EEG} Analysis",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "424",
  day =          "16",
  month =        nov,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110424",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/424",
  abstract =     "Schizophrenia is a complex neuropsychiatric disorder
                 characterized by disruptions in brain connectivity and
                 cognitive functioning. Continuous monitoring of neural
                 activity is essential, as it allows for the detection
                 of subtle changes in brain connectivity patterns, which
                 could provide early warnings of cognitive decline or
                 symptom exacerbation, ultimately facilitating timely
                 therapeutic interventions. This paper proposes a novel
                 approach for detecting schizophrenia-related
                 abnormalities using deep learning (DL) techniques
                 applied to electroencephalogram (EEG) data. Using an
                 openly available EEG dataset on schizophrenia, the
                 focus is on preprocessed event-related potentials
                 (ERPs) from key electrode sites and applied transfer
                 entropy (TE) analysis to quantify the directional flow
                 of information between brain regions. TE matrices were
                 generated to capture neural connectivity patterns,
                 which were then used as input for a hybrid DL model,
                 combining convolutional neural networks (CNNs) and
                 Bidirectional Long Short-Term Memory (BiLSTM) networks.
                 The model achieved a performant accuracy of 99.94\% in
                 classifying schizophrenia-related abnormalities,
                 demonstrating its potential for real-time mental health
                 monitoring. The generated TE matrices revealed
                 significant differences in connectivity between the two
                 groups, particularly in frontal and central brain
                 regions, which are critical for cognitive processing.
                 These findings were further validated by correlating
                 the results with EEG data obtained from the Muse 2
                 headband, emphasizing the potential for portable,
                 non-invasive monitoring of schizophrenia in real-world
                 settings. The final model, integrated into the
                 NeuroPredict platform, offers a scalable solution for
                 continuous mental health monitoring. By incorporating
                 EEG data, heart rate, sleep patterns, and environmental
                 metrics, NeuroPredict facilitates early detection and
                 personalized interventions for schizophrenia
                 patients.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Khatiwoda:2024:CCD,
  author =       "Naba Raj Khatiwoda and Babu Ram Dawadi and Sashidhar
                 Ram Joshi",
  title =        "Capacity and Coverage Dimensioning for {5G} Standalone
                 Mixed-Cell Architecture: an Impact of Using Existing
                 {4G} Infrastructure",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "423",
  day =          "14",
  month =        nov,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110423",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/423",
  abstract =     "With the increasing demand for expected data volume
                 daily, current telecommunications infrastructure can
                 not meet requirements without using enhanced
                 technologies adopted by 5G and beyond networks. Due to
                 their diverse features, 5G technologies and services
                 will be phenomenal in the coming days. Proper planning
                 procedures are to be adopted to provide cost-effective
                 and quality telecommunication services. In this paper,
                 we planned 5G network deployment in two frequency
                 ranges, 3.5 GHz and 28 GHz, using a mixed cell
                 structure. We used metaheuristic approaches such as
                 Grey Wolf Optimization (GWO), Sparrow Search Algorithm
                 (SSA), Whale Optimization Algorithm (WOA), Marine
                 Predator Algorithm (MPA), Particle Swarm Optimization
                 (PSO), and Ant Lion Optimization (ALO) for optimizing
                 the locations of remote radio units. The comparative
                 analysis of metaheuristic algorithms shows that the
                 proposed network is efficient in providing an average
                 data rate of 50 Mbps, can meet the coverage
                 requirements of at least 98\%, and meets
                 quality-of-service requirements. We carried out the
                 case study for an urban area and another suburban area
                 of Kathmandu Valley, Nepal. We analyzed the outcomes of
                 5G greenfield deployment and 5G deployment using
                 existing 4G infrastructure. Deploying 5G networks using
                 existing 4G infrastructure, resources can be saved up
                 to 33.7\% and 54.2\% in urban and suburban areas,
                 respectively.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Seyghaly:2024:SSS,
  author =       "Rasool Seyghaly and Jordi Garcia and Xavi Masip-Bruin
                 and Jovana Kuljanin",
  title =        "{SBNNR}: Small-Size Bat-Optimized {KNN} Regression",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "422",
  day =          "14",
  month =        nov,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110422",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/422",
  abstract =     "Small datasets are frequent in some scientific fields.
                 Such datasets are usually created due to the difficulty
                 or cost of producing laboratory and experimental data.
                 On the other hand, researchers are interested in using
                 machine learning methods to analyze this scale of data.
                 For this reason, in some cases, low-performance,
                 overfitting models are developed for small-scale data.
                 As a result, it appears necessary to develop methods
                 for dealing with this type of data. In this research,
                 we provide a new and innovative framework for
                 regression problems with a small sample size. The base
                 of our proposed method is the K-nearest neighbors (KNN)
                 algorithm. For feature selection, instance selection,
                 and hyperparameter tuning, we use the bat optimization
                 algorithm (BA). Generative Adversarial Networks (GANs)
                 are employed to generate synthetic data, effectively
                 addressing the challenges associated with data
                 sparsity. Concurrently, Deep Neural Networks (DNNs), as
                 a deep learning approach, are utilized for feature
                 extraction from both synthetic and real datasets. This
                 hybrid framework integrates KNN, DNN, and GAN as
                 foundational components and is optimized in multiple
                 aspects (features, instances, and hyperparameters)
                 using BA. The outcomes exhibit an enhancement of up to
                 5\% in the coefficient of determination ( R2 score)
                 using the proposed method compared to the standard KNN
                 method optimized through grid search.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Abdelmoniem:2024:TDC,
  author =       "Ahmed M. Abdelmoniem and Mona Jaber and Ali Anwar and
                 Yuchao Zhang and Mingliang Gao",
  title =        "Towards a Decentralized Collaborative Framework for
                 Scalable Edge {AI}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "421",
  day =          "14",
  month =        nov,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110421",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/421",
  abstract =     "Nowadays, Edge Intelligence has seen unprecedented
                 growth in most of our daily life applications.
                 Traditionally, most applications required significant
                 efforts into data collection for data-driven analytics,
                 raising privacy concerns. The proliferation of
                 specialized hardware on sensors, wearable, mobile, and
                 IoT devices has led to the growth of Edge Intelligence,
                 which has become an integral part of the development
                 cycle of most modern applications. However, scalability
                 issues hinder their wide-scale adoption. We aim to
                 focus on these challenges and propose a scalable
                 decentralized edge intelligence framework. Therefore,
                 we analyze and empirically evaluate the challenges of
                 existing methods, and design an architecture that
                 overcomes these challenges. The proposed approach is
                 client-driven and model-centric, allowing models to be
                 shared between entities in a scalable fashion. We
                 conduct experiments over various benchmarks to show
                 that the proposed approach presents an efficient
                 alternative to the existing baseline method, and it can
                 be a viable solution to scale edge intelligence.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Nawaz:2024:ETH,
  author =       "Omer Nawaz and Siamak Khatibi and Muhammad Nauman
                 Sheikh and Markus Fiedler",
  title =        "Eye Tracking and Human Influence Factors' Impact on
                 Quality of Experience of Mobile Gaming",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "420",
  day =          "13",
  month =        nov,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110420",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/420",
  abstract =     "Mobile gaming accounts for more than 50\% of global
                 online gaming revenue, surpassing console and
                 browser-based gaming. The success of mobile gaming
                 titles depends on optimizing applications for the
                 specific hardware constraints of mobile devices, such
                 as smaller displays and lower computational power, to
                 maximize battery life. Additionally, these applications
                 must dynamically adapt to the variations in network
                 speed inherent in mobile environments. Ultimately, user
                 engagement and satisfaction are critical, necessitating
                 a favorable comparison to browser and console-based
                 gaming experiences. While Quality of Experience (QoE)
                 subjective evaluations through user surveys are the
                 most reliable method for assessing user perception,
                 various factors, termed influence factors (IFs), can
                 affect user ratings of stimulus quality. This study
                 examines human influence factors in mobile gaming,
                 specifically analyzing the impact of user delight
                 towards displayed content and the effect of gaze
                 tracking. Using Pupil Core eye-tracking hardware, we
                 captured user interactions with mobile devices and
                 measured visual attention. Video stimuli from eight
                 popular games were selected, with resolutions of 720p
                 and 1080p and frame rates of 30 and 60 fps. Our results
                 indicate a statistically significant impact of user
                 delight on the MOS for most video stimuli across all
                 games. Additionally, a trend favoring higher frame
                 rates over screen resolution emerged in user ratings.
                 These findings underscore the significance of
                 optimizing mobile gaming experiences by incorporating
                 models that estimate human influence factors to enhance
                 user satisfaction and engagement.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Xiao:2024:AAM,
  author =       "Shaoping Xiao and Junchao Li and Zhaoan Wang and
                 Yingbin Chen and Soheyla Tofighi",
  title =        "Advancing Additive Manufacturing Through Machine
                 Learning Techniques: a State-of-the-Art Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "419",
  day =          "13",
  month =        nov,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110419",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/419",
  abstract =     "In the fourth industrial revolution, artificial
                 intelligence and machine learning (ML) have
                 increasingly been applied to manufacturing,
                 particularly additive manufacturing (AM), to enhance
                 processes and production. This study provides a
                 comprehensive review of the state-of-the-art
                 achievements in this domain, highlighting not only the
                 widely discussed supervised learning but also the
                 emerging applications of semi-supervised learning and
                 reinforcement learning. These advanced ML techniques
                 have recently gained significant attention for their
                 potential to further optimize and automate AM
                 processes. The review aims to offer insights into
                 various ML technologies employed in current research
                 projects and to promote the diverse applications of ML
                 in AM. By exploring the latest advancements and trends,
                 this study seeks to foster a deeper understanding of
                 ML's transformative role in AM, paving the way for
                 future innovations and improvements in manufacturing
                 practices.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Calabro:2024:MAS,
  author =       "Antonello Calabr{\`o} and Enrico Cambiaso and Manuel
                 Cheminod and Ivan Cibrario Bertolotti and Luca Durante
                 and Agostino Forestiero and Flavio Lombardi and
                 Giuseppe Manco and Eda Marchetti and Albina Orlando and
                 Giuseppe Papuzzo",
  title =        "A Methodological Approach to Securing Cyber-Physical
                 Systems for Critical Infrastructures",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "418",
  day =          "12",
  month =        nov,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110418",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/418",
  abstract =     "Modern ICT infrastructures, i.e., cyber-physical
                 systems and critical infrastructures relying on
                 interconnected IT (Information Technology)- and OT
                 (Operational Technology)-based components and
                 (sub-)systems, raise complex challenges in tackling
                 security and safety issues. Nowadays, many security
                 controls and mechanisms have been made available and
                 exploitable to solve specific security needs, but, when
                 dealing with very complex and multifaceted
                 heterogeneous systems, a methodology is needed on top
                 of the selection of each security control that will
                 allow the designer/maintainer to drive her/his choices
                 to build and keep the system secure as a whole, leaving
                 the choice of the security controls to the last step of
                 the system design/development. This paper aims at
                 providing a comprehensive methodological approach to
                 design and preliminarily implement an Open Platform
                 Architecture (OPA) to secure the cyber-physical systems
                 of critical infrastructures. Here, the Open Platform
                 Architecture (OPA) depicts how an already existing or
                 under-design target system (TS) can be equipped with
                 technologies that are modern or currently under
                 development, to monitor and timely detect possibly
                 dangerous situations and to react in an automatic way
                 by putting in place suitable countermeasures. A
                 multifaceted use case (UC) that is able to show the
                 OPA, starting from the security and safety requirements
                 to the fully designed system, will be developed step by
                 step to show the feasibility and the effectiveness of
                 the proposed methodology.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fominska:2024:AIE,
  author =       "Iana Fominska and Stefano {Di Tore} and Michele Nappi
                 and Gerardo Iovane and Maurizio Sibilio and Angela
                 Gelo",
  title =        "Approaches to Identifying Emotions and Affections
                 During the Museum Learning Experience in the Context of
                 the Future {Internet}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "417",
  day =          "10",
  month =        nov,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110417",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/417",
  abstract =     "The Future Internet aims to revolutionize digital
                 interaction by integrating advanced technologies like
                 AI and IoT, enabling a dynamic and resilient network.
                 It envisions emotionally intelligent systems that can
                 interpret and respond to human feelings, creating
                 immersive, empathy-driven learning experiences. This
                 evolution aspires to form a responsive digital
                 ecosystem that seamlessly connects technology and human
                 emotion. This paper presents a computational model
                 aimed at enhancing the emotional aspect of learning
                 experiences within museum environments. The model is
                 designed to represent and manage affective and
                 emotional feedback, with a focus on how emotions can
                 significantly impact the learning process in a museum
                 context. The proposed model seeks to identify and
                 quantify emotions during a visitor's engagement with
                 museum exhibits. To achieve this goal, we primarily
                 explored the following: (i) methods and techniques for
                 assessing and recognizing emotional responses in museum
                 visitors, (ii) feedback management strategies based on
                 the detection of visitors' emotional states. Then, the
                 methodology was tested on 1000 cases via specific
                 questionnaire forms, along with the presentation of
                 images and short videos, and the results of data
                 analysis are reported. The findings contribute toward
                 establishing a comprehensive methodology for the
                 identification and quantification of the emotional
                 state of museum visitors.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Marletta:2024:AIR,
  author =       "Daniele Marletta and Alessandro Midolo and Emiliano
                 Tramontana",
  title =        "Automatically Injecting Robustness Statements into
                 Distributed Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "416",
  day =          "10",
  month =        nov,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110416",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/416",
  abstract =     "When developing a distributed application, several
                 issues need to be handled, and software components
                 should include some mechanisms to make their execution
                 resilient when network faults, delays, or tampering
                 occur. For example, synchronous calls represent a
                 too-tight connection between a client requesting a
                 service and the service itself, whereby potential
                 network delays or temporary server overloads would keep
                 the client side hanging, exposing it to a domino
                 effect. The proposed approach assists developers in
                 dealing with such issues by providing an automatic tool
                 that enhances a distributed application using simple
                 blocking calls and makes it robust in the face of
                 adverse events. The proposed devised solution consists
                 in automatically identifying the parts of the
                 application that connect to remote services using
                 simple synchronous calls and substituting them with a
                 generated customized snippet of code that handles
                 potential network delays or faults. To accurately
                 perform the proposed transformation, the devised tool
                 finds application code statements that are
                 data-dependent on the results of the original
                 synchronous calls. Then, for the dependent statements,
                 a solution involving guarding code, proper
                 synchronization, and timeouts is injected. We
                 experimented with the analysis and transformation of
                 several applications and report a meaningful example,
                 together with the analysis of the results achieved.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Papadopoulos:2024:RAF,
  author =       "Christos Papadopoulos and Konstantinos-Filippos
                 Kollias and George F. Fragulis",
  title =        "Recent Advancements in Federated Learning: State of
                 the Art, Fundamentals, Principles, {IoT} Applications
                 and Future Trends",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "415",
  day =          "9",
  month =        nov,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110415",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/415",
  abstract =     "Federated learning (FL) is creating a paradigm shift
                 in machine learning by directing the focus of model
                 training to where the data actually exist. Instead of
                 drawing all data into a central location, which raises
                 concerns about privacy, costs, and delays, FL allows
                 learning to take place directly on the device, keeping
                 the data safe and minimizing the need for transfer.
                 This approach is especially important in areas like
                 healthcare, where protecting patient privacy is
                 critical, and in industrial IoT settings, where moving
                 large numbers of data is not practical. What makes FL
                 even more compelling is its ability to reduce the bias
                 that can occur when all data are centralized, leading
                 to fairer and more inclusive machine learning outcomes.
                 However, it is not without its
                 challenges---particularly with regard to keeping the
                 models secure from attacks. Nonetheless, the potential
                 benefits are clear: FL can lower the costs associated
                 with data storage and processing, while also helping
                 organizations to meet strict privacy regulations like
                 GDPR. As edge computing continues to grow, FL's
                 decentralized approach could play a key role in shaping
                 how we handle data in the future, moving toward a more
                 privacy-conscious world. This study identifies ongoing
                 challenges in ensuring model security against
                 adversarial attacks, pointing to the need for further
                 research in this area.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Salah:2024:EEA,
  author =       "Zaher Salah and Hamza Abu Owida and Esraa Abu Elsoud
                 and Esraa Alhenawi and Suhaila Abuowaida and Nawaf
                 Alshdaifat",
  title =        "An Effective Ensemble Approach for Preventing and
                 Detecting Phishing Attacks in Textual Form",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "414",
  day =          "8",
  month =        nov,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110414",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/414",
  abstract =     "Phishing email assaults have been a prevalent
                 cybercriminal tactic for many decades. Various
                 detectors have been suggested over time that rely on
                 textual information. However, to address the growing
                 prevalence of phishing emails, more sophisticated
                 techniques are required to use all aspects of emails to
                 improve the detection capabilities of machine learning
                 classifiers. This paper presents a novel approach to
                 detecting phishing emails. The proposed methodology
                 combines ensemble learning techniques with various
                 variables, such as word frequency, the presence of
                 specific keywords or phrases, and email length, to
                 improve detection accuracy. We provide two approaches
                 for the planned task; The first technique employs
                 ensemble learning soft voting, while the second employs
                 weighted ensemble learning. Both strategies use
                 distinct machine learning algorithms to concurrently
                 process the characteristics, reducing their complexity
                 and enhancing the model's performance. An extensive
                 assessment and analysis are conducted, considering
                 unique criteria designed to minimize biased and
                 inaccurate findings. Our empirical experiments
                 demonstrates that using ensemble learning to merge
                 attributes in the evolution of phishing emails
                 showcases the competitive performance of ensemble
                 learning over other machine learning algorithms. This
                 superiority is underscored by achieving an F1-score of
                 0.90 in the weighted ensemble method and 0.85 in the
                 soft voting method, showcasing the effectiveness of
                 this approach.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fragkou:2024:JSD,
  author =       "Evangelia Fragkou and Dimitrios Katsaros",
  title =        "A Joint Survey in Decentralized Federated Learning and
                 {TinyML}: a Brief Introduction to Swarm Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "413",
  day =          "8",
  month =        nov,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110413",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/413",
  abstract =     "TinyML/DL is a new subfield of ML that allows for the
                 deployment of ML algorithms on low-power devices to
                 process their own data. The lack of resources restricts
                 the aforementioned devices to running only inference
                 tasks (static TinyML), while training is handled by a
                 more computationally efficient system, such as the
                 cloud. In recent literature, the focus has been on
                 conducting real-time on-device training tasks
                 (Reformable TinyML) while being wirelessly connected.
                 With data processing being shift to edge devices, the
                 development of decentralized federated learning (DFL)
                 schemes becomes justified. Within these setups, nodes
                 work together to train a neural network model,
                 eliminating the necessity of a central coordinator.
                 Ensuring secure communication among nodes is of utmost
                 importance for protecting data privacy during edge
                 device training. Swarm Learning (SL) emerges as a DFL
                 paradigm that promotes collaborative learning through
                 peer-to-peer interaction, utilizing edge computing and
                 blockchain technology. While SL provides a robust
                 defense against adversarial attacks, it comes at a high
                 computational expense. In this survey, we emphasize the
                 current literature regarding both DFL and TinyML/DL
                 fields. We explore the obstacles encountered by
                 resource-starved devices in this collaboration and
                 provide a brief overview of the potential of
                 transitioning to Swarm Learning.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{deCurto:2024:ECS,
  author =       "J. de Curt{\`o} and I. de Zarz{\`a} and Juan-Carlos
                 Cano and Carlos T. Calafate",
  title =        "Enhancing Communication Security in Drones Using
                 {QRNG} in Frequency Hopping Spread Spectrum",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "412",
  day =          "8",
  month =        nov,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110412",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/412",
  abstract =     "This paper presents a novel approach to enhancing the
                 security and reliability of drone communications
                 through the integration of Quantum Random Number
                 Generators (QRNG) in Frequency Hopping Spread Spectrum
                 (FHSS) systems. We propose a multi-drone framework that
                 leverages QRNG technology to generate truly random
                 frequency hopping sequences, significantly improving
                 resistance against jamming and interception attempts.
                 Our method introduces a concurrent access protocol for
                 multiple drones to share a QRNG device efficiently,
                 incorporating robust error handling and a shared memory
                 system for random number distribution. The
                 implementation includes secure communication protocols,
                 ensuring data integrity and confidentiality through
                 encryption and Hash-based Message Authentication Code
                 (HMAC) verification. We demonstrate the system's
                 effectiveness through comprehensive simulations and
                 statistical analyses, including spectral density,
                 frequency distribution, and autocorrelation studies of
                 the generated frequency sequences. The results show a
                 significant enhancement in the unpredictability and
                 uniformity of frequency distributions compared to
                 traditional pseudo-random number generator-based
                 approaches. Specifically, the frequency distributions
                 of the drones exhibited a relatively uniform spread
                 across the available spectrum, with minimal discernible
                 patterns in the frequency sequences, indicating high
                 unpredictability. Autocorrelation analyses revealed a
                 sharp peak at zero lag and linear decrease to zero
                 values for other lags, confirming a general absence of
                 periodicity or predictability in the sequences, which
                 enhances resistance to predictive attacks. Spectral
                 analysis confirmed a relatively flat power spectral
                 density across frequencies, characteristic of truly
                 random sequences, thereby minimizing vulnerabilities to
                 spectral-based jamming. Statistical tests, including
                 Chi-squared and Kolmogorov--Smirnov, further confirm
                 the unpredictability of the frequency sequences
                 generated by QRNG, supporting enhanced security
                 measures against predictive attacks. While some
                 short-term correlations were observed, suggesting areas
                 for improvement in QRNG technology, the overall
                 findings confirm the potential of QRNG-based FHSS
                 systems in significantly improving the security and
                 reliability of drone communications. This work
                 contributes to the growing field of quantum-enhanced
                 wireless communications, offering substantial
                 advancements in security and reliability for drone
                 operations. The proposed system has potential
                 applications in military, emergency response, and
                 secure commercial drone operations, where enhanced
                 communication security is paramount.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Saleh:2024:EDL,
  author =       "Sherine Nagy Saleh and Mazen Nabil Elagamy and Yasmine
                 N. M. Saleh and Radwa Ahmed Osman",
  title =        "An Explainable Deep Learning-Enhanced {IoMT} Model for
                 Effective Monitoring and Reduction of Maternal
                 Mortality Risks",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "411",
  day =          "8",
  month =        nov,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110411",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/411",
  abstract =     "Maternal mortality (MM) is considered one of the major
                 worldwide concerns. Despite the advances of artificial
                 intelligence (AI) in healthcare, the lack of
                 transparency in AI models leads to reluctance to adopt
                 them. Employing explainable artificial intelligence
                 (XAI) thus helps improve the transparency and
                 effectiveness of AI-driven healthcare solutions.
                 Accordingly, this article proposes a complete framework
                 integrating an Internet of Medical Things (IoMT)
                 architecture with an XAI-based deep learning model. The
                 IoMT system continuously monitors pregnant women's
                 vital signs, while the XAI model analyzes the collected
                 data to identify risk factors and generate actionable
                 insights. Additionally, an efficient IoMT transmission
                 model is developed to ensure reliable data transfer
                 with the best-required system quality of service (QoS).
                 Further analytics are performed on the data collected
                 from different regions in a country to address
                 high-risk cities. The experiments demonstrate the
                 effectiveness of the proposed framework by achieving an
                 accuracy of 80\% for patients and 92.6\% for regional
                 risk prediction and providing interpretable
                 explanations. The XAI-generated insights empower
                 healthcare providers to make informed decisions and
                 implement timely interventions. Furthermore, the IoMT
                 transmission model ensures efficient and secure data
                 transfer.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Walter:2024:DES,
  author =       "Markus Walter and J{\"o}rg Keller",
  title =        "Design and Evaluation of Steganographic Channels in
                 Fifth-Generation New Radio",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "410",
  day =          "6",
  month =        nov,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110410",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/410",
  abstract =     "Mobile communication is ubiquitous in everyday life.
                 The fifth generation of mobile networks (5G) introduced
                 5G New Radio as a radio access technology that meets
                 current bandwidth, quality, and application
                 requirements. Network steganographic channels that hide
                 secret message transfers in an innocent carrier
                 communication are a particular threat in mobile
                 communications as these channels are often used for
                 malware, ransomware, and data leakage. We
                 systematically analyze the protocol stack of the
                 5G--air interface for its susceptibility to network
                 steganography, addressing both storage and timing
                 channels. To ensure large coverage, we apply hiding
                 patterns that collect the essential ideas used to
                 create steganographic channels. Based on the results of
                 this analysis, we design and implement a network covert
                 storage channel, exploiting reserved bits in the header
                 of the Packet Data Convergence Protocol (PDCP). the
                 covert sender and receiver are located in a 5G base
                 station and mobile device, respectively. Furthermore,
                 we sketch a timing channel based on a recent
                 overshadowing attack. We evaluate our steganographic
                 storage channel both in simulation and real-world
                 experiments with respect to steganographic bandwidth,
                 robustness, and stealthiness. Moreover, we discuss
                 countermeasures. Our implementation demonstrates the
                 feasibility of a covert channel in 5G New Radio and the
                 possibility of achieving large steganographic bandwidth
                 for broadband transmissions. We also demonstrate that
                 the detection of the channel by a network analyzer is
                 possible, limiting its scope to application scenarios
                 where operators are unaware or ignorant of this
                 threat.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rajendran:2024:RTE,
  author =       "Venushini Rajendran and R Kanesaraj Ramasamy",
  title =        "Real-Time Evaluation of the Improved Eagle Strategy
                 Model in the {Internet of Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "409",
  day =          "6",
  month =        nov,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110409",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/409",
  abstract =     "With the rapid expansion of cloud computing and the
                 pervasive growth of IoT across industries and
                 educational sectors, the need for efficient remote data
                 management and service orchestration has become
                 paramount. Web services, facilitated by APIs, offer a
                 modular approach to integrating and streamlining
                 complex business processes. However, real-time
                 monitoring and optimal service selection within
                 large-scale, cloud-based repositories remain
                 significant challenges. This study introduces the novel
                 Improved Eagle Strategy (IES) hybrid model, which
                 uniquely integrates bio-inspired optimization with
                 clustering techniques to drastically reduce computation
                 time while ensuring highly accurate service selection
                 tailored to specific user requirements. Through
                 comprehensive NetLogo simulations, the IES model
                 demonstrates superior efficiency in service selection
                 compared to existing methodologies. Additionally, the
                 IES model's application through a web dashboard system
                 highlights its capability to manage both functional and
                 non-functional service attributes effectively. When
                 deployed on real-time IoT devices, the IES model not
                 only enhances computation speed but also ensures a more
                 responsive and user-centric service environment. This
                 research underscores the transformative potential of
                 the IES model, marking a significant advancement in
                 optimizing cloud computing processes, particularly
                 within the IoT ecosystem.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kamruzzaman:2024:MLB,
  author =       "Md Kamruzzaman and Nurul I. Sarkar and Jairo
                 Gutierrez",
  title =        "Machine Learning-Based Resource Allocation Algorithm
                 to Mitigate Interference in {D2D-Enabled} Cellular
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "408",
  day =          "6",
  month =        nov,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110408",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/408",
  abstract =     "Mobile communications have experienced exponential
                 growth both in connectivity and multimedia traffic in
                 recent years. To support this tremendous growth,
                 device-to-device (D2D) communications play a
                 significant role in 5G and beyond 5G networks. However,
                 enabling D2D communications in an underlay,
                 heterogeneous cellular network poses two major
                 challenges. First, interference management between D2D
                 and cellular users directly affects a system's
                 performance. Second, achieving an acceptable level of
                 link quality for both D2D and cellular networks is
                 necessary. An optimum resource allocation is required
                 to mitigate the interference and improve a system's
                 performance. In this paper, we provide a solution to
                 interference management with an acceptable quality of
                 services (QoS). To this end, we propose a machine
                 learning-based resource allocation method to maximize
                 throughput and achieve minimum QoS requirements for all
                 active D2D pairs and cellular users. We first solve a
                 resource optimization problem by allocating spectrum
                 resources and controlling power transmission on demand.
                 As resource optimization is an integer nonlinear
                 programming problem, we address this problem by
                 proposing a deep Q-network-based reinforcement learning
                 algorithm (DRL) to optimize the resource allocation
                 issue. The proposed DRL algorithm is trained with a
                 decision-making policy to obtain the best solution in
                 terms of spectrum efficiency, computational time, and
                 throughput. The system performance is validated by
                 simulation. The results show that the proposed method
                 outperforms the existing ones.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mudassar:2024:PPD,
  author =       "Bakhtawar Mudassar and Shahzaib Tahir and Fawad Khan
                 and Syed Aziz Shah and Syed Ikram Shah and Qammer
                 Hussain Abbasi",
  title =        "Privacy-Preserving Data Analytics in {Internet of
                 Medical Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "407",
  day =          "5",
  month =        nov,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110407",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/407",
  abstract =     "The healthcare sector has changed dramatically in
                 recent years due to depending more and more on big data
                 to improve patient care, enhance or improve operational
                 effectiveness, and forward medical research. Protecting
                 patient privacy in the era of digital health records is
                 a major challenge, as there could be a chance of
                 privacy leakage during the process of collecting
                 patient data. To overcome this issue, we propose a
                 secure, privacy-preserving scheme for healthcare data
                 to ensure maximum privacy of an individual while also
                 maintaining their utility and allowing for the
                 performance of queries based on sensitive attributes
                 under differential privacy. We implemented differential
                 privacy on two publicly available healthcare datasets,
                 the Breast Cancer Prediction Dataset and the Nursing
                 Home COVID-19 Dataset. Moreover, we examined the impact
                 of varying privacy parameter ( {\epsilon} ) values on
                 both the privacy and utility of the data. A significant
                 part of this study involved the selection of
                 {\epsilon}, which determines the degree of privacy
                 protection. We also conducted a computational time
                 comparison by performing multiple complex queries on
                 these datasets to analyse the computational overhead
                 introduced by differential privacy. The outcomes
                 demonstrate that, despite a slight increase in query
                 processing time, it remains within reasonable bounds,
                 ensuring the practicality of differential privacy for
                 real-time applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Owen:2024:VDI,
  author =       "Aron E. Owen and Jonathan C. Roberts",
  title =        "Visualisation Design Ideation with {AI}: a New
                 Framework, Vocabulary, and Tool",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "406",
  day =          "5",
  month =        nov,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110406",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/406",
  abstract =     "This paper introduces an innovative framework for
                 visualisation design ideation, which includes a
                 collection of terms for creative visualisation design,
                 the five-step process, and an implementation called
                 VisAlchemy. Throughout the visualisation ideation
                 process, individuals engage in exploring various
                 concepts, brainstorming, sketching ideas, prototyping,
                 and experimenting with different methods to visually
                 represent data or information. Sometimes, designers
                 feel incapable of sketching, and the ideation process
                 can be quite lengthy. In such cases, generative AI can
                 provide assistance. However, even with AI, it can be
                 difficult to know which vocabulary to use and how to
                 strategically approach the design process. Our strategy
                 prompts imaginative and structured narratives for
                 generative AI use, facilitating the generation and
                 refinement of visualisation design ideas. We aim to
                 inspire fresh and innovative ideas, encouraging
                 creativity and exploring unconventional concepts.
                 VisAlchemy is a five-step framework: a methodical
                 approach to defining, exploring, and refining prompts
                 to enhance the generative AI process. The framework
                 blends design elements and aesthetics with context and
                 application. In addition, we present a vocabulary set
                 of 300 words, underpinned from a corpus of
                 visualisation design and art papers, along with a
                 demonstration tool called VisAlchemy. The interactive
                 interface of the VisAlchemy tool allows users to adhere
                 to the framework and generate innovative visualisation
                 design concepts. It is built using the SDXL Turbo
                 language model. Finally, we demonstrate its use through
                 case studies and examples and show the transformative
                 power of the framework to create inspired and exciting
                 design ideas through refinement, re-ordering, weighting
                 of words and word rephrasing.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mana:2024:SAR,
  author =       "Antonio Ma{\~n}a and Francisco J. Jaime and Luc{\'\i}a
                 Guti{\'e}rrez",
  title =        "A Secure Auditable Remote Registry Pattern for {IoT}
                 Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "405",
  day =          "4",
  month =        nov,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110405",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/405",
  abstract =     "In software engineering, pattern papers serve the
                 purpose of providing a description of a generalized,
                 reusable solution to recurring design problems, based
                 on practical experience and established best practices.
                 This paper presents an architectural pattern for a
                 Secure Auditable Registry service based on
                 Message-Oriented Middleware to be used in large-scale
                 IoT systems that must provide auditing capabilities to
                 external entities. To prepare the pattern, the direct
                 experience in applying the pattern solution in an
                 industry-funded R\&D project has been a key aspect
                 because it has allowed us to gain a deep understanding
                 of the problem and the solution, and it has contributed
                 to the correctness and real-world applicability of the
                 pattern as described. To further improve the quality of
                 the paper, we have followed the commonly accepted
                 practices in pattern development (including peer
                 reviews) to ensure that the core aspects of the
                 solution are correctly represented and that the
                 description allows it to be applicable to similar
                 problems in other domains, such as healthcare,
                 autonomous devices, banking, food tracing or
                 manufacturing to name a few. The work done in applying
                 this pattern confirms that it solves a recurring
                 problem for IoT systems, but also that it can be
                 adopted in other domains, providing an effective
                 solution in order to achieve enhancement of the
                 auditability capabilities of the target systems. This
                 pattern will be part of a pattern language (i.e., a
                 family of related patterns) that we are developing for
                 transitioning from legacy systems to IoT with an
                 emphasis on security.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Vizzarri:2024:UCS,
  author =       "Alessandro Vizzarri and Franco Mazzenga",
  title =        "{6G} Use Cases and Scenarios: a Comparison Analysis
                 Between {ITU} and Other Initiatives",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "404",
  day =          "1",
  month =        nov,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110404",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/404",
  abstract =     "In the next decade, the amount of network traffic is
                 estimated to reach Zettabytes. The future International
                 Mobile Telecommunications-2030 (IMT-2030) standard of
                 mobile networks, known as 6G, introduces an important
                 paradigm shift in the context of wireless communication
                 systems thanks to capabilities such as low latency and
                 high data rates. Official documents on 6G
                 standardization have been released by the International
                 Telecommunication Union (ITU). However, other visions
                 and use cases of 6G have been proposed by industrial
                 stakeholders and research institutions, thus generating
                 a multitude of use cases and usage scenarios that are
                 only apparently different from each other. This paper
                 would contribute to providing a holistic vision of the
                 6G-enabled use cases and potentially impacted vertical
                 market sectors. The differences and similarities
                 between what has been proposed by ITU and other
                 initiatives are identified through a comparison based
                 on the technological characterization of use cases and
                 of the considered vertical market sectors. The main
                 findings presented in this paper demonstrate that many
                 of the use cases proposed by ITU and by the other
                 initiatives are almost identical in many cases.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wiessner:2024:UAT,
  author =       "Paul Wiessner and Grigor Bezirganyan and Sana Sellami
                 and Richard Chbeir and Hans-Joachim Bungartz",
  title =        "Uncertainty-Aware Time Series Anomaly Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "403",
  day =          "31",
  month =        oct,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110403",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/403",
  abstract =     "Traditional anomaly detection methods in time series
                 data often struggle with inherent uncertainties like
                 noise and missing values. Indeed, current approaches
                 mostly focus on quantifying epistemic uncertainty and
                 ignore data-dependent uncertainty. However,
                 consideration of noise in data is important as it may
                 have the potential to lead to more robust detection of
                 anomalies and a better capability of distinguishing
                 between real anomalies and anomalous patterns provoked
                 by noise. In this paper, we propose LSTMAE-UQ (Long
                 Short-Term Memory Autoencoder with Aleatoric and
                 Epistemic Uncertainty Quantification), a novel approach
                 that incorporates both aleatoric (data noise) and
                 epistemic (model uncertainty) uncertainties for more
                 robust anomaly detection. The model combines the
                 strengths of LSTM networks for capturing complex time
                 series relationships and autoencoders for unsupervised
                 anomaly detection and quantifies uncertainties based on
                 the Bayesian posterior approximation method Monte Carlo
                 (MC) Dropout, enabling a deeper understanding of noise
                 recognition. Our experimental results across different
                 real-world datasets show that consideration of
                 uncertainty effectively increases the robustness to
                 noise and point outliers, making predictions more
                 reliable for longer periodic sequential data.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Nikic:2024:LDR,
  author =       "Vladimir Niki{\'c} and Dusan Bortnik and Milan Luki{\'c} and
                 Dejan Vukobratovi{\'c} and Ivan Mezei",
  title =        "Lightweight Digit Recognition in Smart Metering System
                 Using Narrowband {Internet of Things} and Federated
                 Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "11",
  pages =        "402",
  day =          "31",
  month =        oct,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16110402",
  ISSN =         "1999-5903",
  bibdate =      "Sat Nov 30 05:39:07 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/11/402",
  abstract =     "Replacing mechanical utility meters with digital ones
                 is crucial due to the numerous benefits they offer,
                 including increased time resolution in measuring
                 consumption, remote monitoring capabilities for
                 operational efficiency, real-time data for informed
                 decision-making, support for time-of-use billing, and
                 integration with smart grids, leading to enhanced
                 customer service, reduced energy waste, and progress
                 towards environmental sustainability goals. However,
                 the cost associated with replacing mechanical meters
                 with their digital counterparts is a key factor
                 contributing to the relatively slow roll-out of such
                 devices. In this paper, we present a low-cost and
                 power-efficient solution for retrofitting the existing
                 metering infrastructure, based on state-of-the-art
                 communication and artificial intelligence technologies.
                 The edge device we developed contains a camera for
                 capturing images of a dial meter, a 32-bit
                 microcontroller capable of running the digit
                 recognition algorithm, and an NB-IoT module with
                 (E)GPRS fallback, which enables nearly ubiquitous
                 connectivity even in difficult radio conditions. Our
                 digit recognition methodology, based on the on-device
                 training and inference, augmented with federated
                 learning, achieves a high level of accuracy (97.01\%)
                 while minimizing the energy consumption and associated
                 communication overhead (87 {\mu} Wh per day on
                 average).",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{AlJamal:2024:RML,
  author =       "Mahmoud AlJamal and Rabee Alquran and Ayoub Alsarhan
                 and Mohammad Aljaidi and Mohammad Alhmmad and Wafa' Q.
                 Al-Jamal and Nasser Albalawi",
  title =        "A Robust Machine Learning Model for Detecting {XSS}
                 Attacks on {IoT} over {5G} Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "482",
  day =          "23",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120482",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/482",
  abstract =     "As the Internet of Things (IoT) expands rapidly and 5G
                 networks become more widespread, the need for strong
                 cybersecurity measures in IoT systems has become
                 increasingly critical. Traditional security methods are
                 no longer sufficient due to the shear volume,
                 diversity, and limited processing capabilities of IoT
                 devices. The high data transmission speeds of 5G
                 networks further intensify the potential risks, making
                 it essential to implement effective security measures.
                 One of the major threats to IoT systems is Cross-Site
                 Scripting (XSS) attacks. To address this issue, we
                 introduce a new machine learning (ML) approach designed
                 to detect and predict XSS attacks on IoT systems
                 operating over 5G networks. By using ML classifiers,
                 particularly the Random Forest classifier, our approach
                 achieves a high classification accuracy of 99.89\% in
                 identifying XSS attacks. This research enhances IoT
                 security by addressing the emerging challenges posed by
                 5G networks and XSS attacks, ensuring the safe
                 operation of IoT devices within the 5G ecosystem
                 through early detection and prevention of
                 vulnerabilities.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kamal:2024:AHT,
  author =       "Hesham Kamal and Maggie Mashaly",
  title =        "Advanced Hybrid Transformer-{CNN} Deep Learning Model
                 for Effective Intrusion Detection Systems with Class
                 Imbalance Mitigation Using Resampling Techniques",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "481",
  day =          "23",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120481",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/481",
  abstract =     "Network and cloud environments must be fortified
                 against a dynamic array of threats, and intrusion
                 detection systems (IDSs) are critical tools for
                 identifying and thwarting hostile activities. IDSs,
                 classified as anomaly-based or signature-based, have
                 increasingly incorporated deep learning models into
                 their framework. Recently, significant advancements
                 have been made in anomaly-based IDSs, particularly
                 those using machine learning, where attack detection
                 accuracy has been notably high. Our proposed method
                 demonstrates that deep learning models can achieve
                 unprecedented success in identifying both known and
                 unknown threats within cloud environments. However,
                 existing benchmark datasets for intrusion detection
                 typically contain more normal traffic samples than
                 attack samples to reflect real-world network traffic.
                 This imbalance in the training data makes it more
                 challenging for IDSs to accurately detect specific
                 types of attacks. Thus, our challenges arise from two
                 key factors, unbalanced training data and the emergence
                 of new, unidentified threats. To address these issues,
                 we present a hybrid transformer-convolutional neural
                 network (Transformer-CNN) deep learning model, which
                 leverages data resampling techniques such as adaptive
                 synthetic (ADASYN), synthetic minority oversampling
                 technique (SMOTE), edited nearest neighbors (ENN), and
                 class weights to overcome class imbalance. The
                 transformer component of our model is employed for
                 contextual feature extraction, enabling the system to
                 analyze relationships and patterns in the data
                 effectively. In contrast, the CNN is responsible for
                 final classification, processing the extracted features
                 to accurately identify specific attack types. The
                 Transformer-CNN model focuses on three primary
                 objectives to enhance detection accuracy and
                 performance: (1) reducing false positives and false
                 negatives, (2) enabling real-time intrusion detection
                 in high-speed networks, and (3) detecting zero-day
                 attacks. We evaluate our proposed model,
                 Transformer-CNN, using the NF-UNSW-NB15-v2 and
                 CICIDS2017 benchmark datasets, and assess its
                 performance with metrics such as accuracy, precision,
                 recall, and F1-score. The results demonstrate that our
                 method achieves an impressive 99.71\% accuracy in
                 binary classification and 99.02\% in multi-class
                 classification on the NF-UNSW-NB15-v2 dataset, while
                 for the CICIDS2017 dataset, it reaches 99.93\% in
                 binary classification and 99.13\% in multi-class
                 classification, significantly outperforming existing
                 models. This proves the enhanced capability of our IDS
                 in defending cloud environments against intrusions,
                 including zero-day attacks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2024:SSG,
  author =       "Ziyu Wang and Jing Ma and Edmund M-K Lai",
  title =        "A Survey of Scenario Generation for Automated Vehicle
                 Testing and Validation",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "480",
  day =          "23",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120480",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/480",
  abstract =     "This survey explores the evolution of test scenario
                 generation for autonomous vehicles (AVs),
                 distinguishing between non-adaptive and adaptive
                 scenario approaches. Non-adaptive scenarios, where
                 dynamic objects follow predetermined scripts, provide
                 repeatable and reliable tests but fail to capture the
                 complexity and unpredictability of real-world traffic
                 interactions. In contrast, adaptive scenarios, which
                 adapt in real time to environmental changes, offer a
                 more realistic simulation of traffic conditions,
                 enabling the assessment of an AV system's adaptability,
                 safety, and robustness. The shift from non-adaptive to
                 adaptive scenarios is increasingly emphasized in AV
                 research, to better evaluate system performance in
                 complex environments. However, generating adaptive
                 scenario is more complex and faces challenges. These
                 include the limited diversity in behaviors, low model
                 interpretability, and high resource requirements.
                 Future research should focus on enhancing the
                 efficiency of adaptive scenario generation and
                 developing comprehensive evaluation metrics to improve
                 the realism and effectiveness of AV testing.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Morales-Caporal:2024:IBL,
  author =       "Roberto Morales-Caporal and Rodolfo Eleazar
                 P{\'e}rez-Loaiza and Edmundo Bonilla-Huerta and Julio
                 Hern{\'a}ndez-P{\'e}rez and Jos{\'e} de Jes{\'u}s
                 Rangel-Magdaleno",
  title =        "{IoT}-Based {LPG} Level Sensor for Domestic Stationary
                 Tanks with Data Sharing to a Filling Plant to Optimize
                 Distribution Routes",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "479",
  day =          "21",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120479",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/479",
  abstract =     "This research presents the design and implementation
                 of an Internet of Things (IoT)-based solution to
                 measure the percentage of Liquefied Petroleum Gas (LPG)
                 inside domestic stationary tanks. The IoT-based sensor,
                 in addition to displaying the percentage of the LPG
                 level in the tank to the user through a mobile
                 application (app), has the advantage of simultaneously
                 sharing the acquired data with an LPG filling plant via
                 the Internet. The design process and calculations for
                 the selection of the electronic components of the
                 IoT-based sensor are presented. The methodology for
                 obtaining and calibrating the measurement of the tank
                 filling percentage from the magnetic level measurement
                 system is explained in detail. The operation of the
                 developed software, and the communication protocols
                 used are also explained so that the data can be queried
                 both in the user's app and on the gas company's web
                 platform safely. The use of the Clark and Wright
                 savings algorithm is proposed to sufficiently optimize
                 the distribution routes that tank trucks should follow
                 when serving different home refill requests from
                 customers located in different places in a city. The
                 experimental results confirm the functionality and
                 viability of the hardware and software developed. In
                 addition, by having the precise location of the tank,
                 the generation of optimized gas refill routes for
                 thirty customers using the heuristic algorithm and a
                 visualization of them on Google Maps is demonstrated.
                 This can lead to competitive advantages for home gas
                 distribution companies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhou:2024:CSU,
  author =       "Mengcai Zhou and Minglun Li and Kenta Ono and Makoto
                 Watanabe",
  title =        "A Comparative Study of the User Interaction Behavior
                 and Experience in a Home-Oriented Multi-User Interface
                 ({MUI}) During Family Collaborative Cooking",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "478",
  day =          "20",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120478",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/478",
  abstract =     "This study sought to ascertain the necessity of
                 crafting specialized multi-user interfaces for
                 scenarios involving multiple users and to provide
                 guidance for the design of multi-user human--computer
                 interactions by identifying the disparities in the
                 interaction behavior and user experience when employing
                 a conventional one-user interface (OUI) recipe versus a
                 multi-user interface (MUI) recipe in the context of
                 family collaborative cooking. To address this
                 objective, this study employed a before-and-after
                 comparison approach. Subsequently, adult users
                 submitted self-assessments of their experiences using
                 the OUI and MUI. The evaluation tools included a user
                 experience survey questionnaire and a Likert
                 seven-point scale, including aspects such as visual
                 confirmation, content, operation, and satisfaction.
                 Post-experiment interviews were also conducted with
                 family members. The MUI exhibited greater effectiveness
                 in terms of visual confirmation, with the ``layout''
                 assuming a role analogous to that of ``text'' in
                 facilitating visual confirmation. Moreover, the
                 operation of the MUI was found to be somewhat
                 enjoyable. Nevertheless, no significant disparities
                 were observed between the OUI group and the MUI group
                 concerning content readability and most operational
                 aspects. Furthermore, the users described their
                 satisfaction with the MUI to be superior to that of the
                 OUI, offering fun, convenience, and a clear appearance.
                 Findings from my research clearly demonstrate that it
                 is both valuable and essential to design a dedicated
                 MUI.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Attaran:2024:AHT,
  author =       "Sharmin Attaran and Mohsen Attaran",
  title =        "Advancing Healthcare Through the Integration of
                 Digital Twins Technology: Personalized {Medicine}'s
                 Next Frontier",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "477",
  day =          "20",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120477",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/477",
  abstract =     "The use of Digital Twin technology has been expanding
                 rapidly, and projections indicate that it will continue
                 to proliferate across various applications, use cases,
                 and industries, including healthcare. In recent years,
                 the healthcare sector has seen an acceleration in
                 digital transformation. This fast-paced change offers
                 both opportunities and risks, especially with emerging
                 technologies like digital twins, which are relatively
                 untested and still in the early stages of adoption in
                 medical care. This paper aims to conduct a literature
                 review to explore how digital twins facilitate
                 intelligent automation in healthcare. It defines the
                 concept, traces the technology's evolution and
                 development, reviews its key enabling technologies, and
                 examines current trends and challenges. The paper also
                 presents a range of application examples in
                 personalized medicine and public health, concluding
                 with a succinct discussion of the primary technical and
                 ancillary challenges, as well as the ethical issues
                 that arise when applying digital twin technology to
                 human subjects.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Augusto:2024:PRO,
  author =       "Gon{\c{c}}alo Augusto and Rui Duarte and Carlos Cunha
                 and Ana Matos",
  title =        "Pattern Recognition in Older Adults' Activities of
                 Daily Living",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "476",
  day =          "20",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120476",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/476",
  abstract =     "Monitoring daily activities and behaviors is essential
                 for improving quality of life in elderly care, where
                 early detection of behavioral anomalies can lead to
                 timely interventions and enhanced well-being. However,
                 monitoring systems often struggle with scalability,
                 high rates of false positives and negatives, and lack
                 of interpretability in understanding anomalies within
                 collected data. Addressing these limitations requires
                 an adaptable, accurate solution to detect patterns and
                 reliably identify outliers in elderly behavior data.
                 This work aims to design a scalable monitoring system
                 that identifies patterns and anomalies in elderly
                 activity data while prioritizing interpretability to
                 make well-informed decisions. The proposed system
                 employs pattern recognition to detect and analyze
                 outliers in behavior analysis, incorporating a service
                 worker generated with Crontab Guru for automated data
                 gathering and organization. Validation is conducted
                 through statistical measures such as accumulated
                 values, percentiles, and probability analyses to
                 minimize false detections and ensure reliable
                 performance. Experimental results indicate the system
                 achieves high accuracy, with an occupancy probability
                 across compartments and fewer outliers detected. The
                 system demonstrates effective scalability and robust
                 anomaly detection. By combining pattern recognition
                 with a focus on interpretability, the proposed system
                 provides actionable insights into elderly activity
                 patterns and behaviors. This approach enhances the
                 well-being of older adults, offering caregivers
                 reliable information to support timely interventions
                 and improve overall quality of life.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yang:2024:AFU,
  author =       "Jeong Yang and Anoop Abraham",
  title =        "Analyzing the Features, Usability, and Performance of
                 Deploying a Containerized Mobile {Web} Application on
                 Serverless Cloud Platforms",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "475",
  day =          "19",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120475",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/475",
  abstract =     "Serverless computing services are offered by major
                 cloud service providers such as Google Cloud Platform,
                 Amazon Web Services, and Microsoft Azure. The primary
                 purpose of the services is to offer efficiency and
                 scalability in modern software development and IT
                 operations while reducing overall costs and operational
                 complexity. However, prospective customers often
                 question which serverless service will best meet their
                 organizational and business needs. This study analyzed
                 the features, usability, and performance of three
                 serverless cloud computing platforms: Google Cloud's
                 Cloud Run, Amazon Web Service's App Runner, and
                 Microsoft Azure's Container Apps. The analysis was
                 conducted with a containerized mobile application
                 designed to track real-time bus locations for San
                 Antonio public buses on specific routes and provide
                 estimated arrival times for selected bus stops. The
                 study evaluated various system-related features,
                 including service configuration, pricing, and memory
                 and CPU capacity, along with performance metrics such
                 as container latency, distance matrix API response
                 time, and CPU utilization for each service. The results
                 of the analysis revealed that Google's Cloud Run
                 demonstrated better performance and usability than
                 AWS's App Runner and Microsoft Azure's Container Apps.
                 Cloud Run exhibited lower latency and faster response
                 time for distance matrix queries. These findings
                 provide valuable insights for selecting an appropriate
                 serverless cloud service for similar containerized web
                 applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Aragones:2024:TGP,
  author =       "Ra{\'u}l Aragon{\'e}s and Joan Oliver and Carles
                 Ferrer",
  title =        "Thermoelectric Generator-Powered Long-Range Wireless
                 Real-Time Steam Leak Detection in Steam Traps",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "474",
  day =          "19",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120474",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/474",
  abstract =     "This paper introduces a novel thermoelectric generator
                 (TEG)-powered Industrial Internet of Things (IIoT)
                 device that addresses key limitations in the detection
                 of steam leaks in industrial steam pipelines,
                 particularly in steam traps. Existing solutions often
                 rely on battery-powered or wired sensors, which are
                 limited by high maintenance costs, short lifespans, or
                 significant infrastructure investments. The proposed
                 device operates without batteries, using waste heat to
                 provide continuous power, and leverages LoRaWAN for
                 long-range wireless communication, minimizing reliance
                 on costly internal infrastructure. Additionally, the
                 device integrates temperature differential ({\Delta}T)
                 and ultrasonic sensors with edge computing capabilities
                 to enhance real-time leak detection and reduce
                 dependency on cloud computing. By enabling precise,
                 low-maintenance monitoring of steam systems in
                 energy-intensive industries (e.g., petrochemical,
                 pharmaceutical), this technology can significantly
                 reduce energy losses, operational costs, and greenhouse
                 gas emissions. Initial testing demonstrates the
                 device's ability to detect leaks accurately under
                 varying industrial conditions, offering a robust,
                 scalable solution for Industry 4.0 applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Cocco:2024:SSI,
  author =       "Luisanna Cocco and Roberto Tonelli",
  title =        "A Self-Sovereign Identity--Blockchain-Based Model
                 Proposal for Deep Digital Transformation in the
                 Healthcare Sector",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "473",
  day =          "19",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120473",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/473",
  abstract =     "The acceleration of the digital transformation process
                 imposed by the pandemic in all the countries of the
                 European Union, and in all sectors, has given way to a
                 revolution that up until a couple of years ago would
                 have been impossible even to imagine. Digital
                 innovation has become a factor of competitiveness in
                 all sectors. In this new scenario that has come to be,
                 the Blockchain technology, the Self-Sovereign Identity
                 paradigm, Internet of Things, and, in general, the new
                 technologies that will emerge, will constitute
                 enhancers of competitiveness and will have to aim for
                 interoperability. In this context, this article
                 develops and presents a model proposal in the
                 healthcare field that aims to highlight how the
                 combination of the Blockchain technology and the
                 Self-Sovereign Identity paradigm restores full control
                 over a person's identity and information, while
                 ensuring the integrity of all medical reports, enabling
                 secure communications between personal medical devices
                 and patient/doctor applications on devices exploiting
                 peer Decentralized Identifiers and ensuring data
                 privacy, exploiting Zero Knowledge Proofs. The proposal
                 relies on the Veramo platform, treating all medical
                 reports as verifiable credentials and storing them in
                 digital wallets owned by the patient. The article
                 concludes by presenting a prototype designed and
                 implemented for managing medication prescriptions,
                 their issuance, and their exchange.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tirziu:2024:EFD,
  author =       "Eugenia T{\^\i}rziu and Ana-Mihaela Vasilevschi and
                 Adriana Alexandru and Eleonora Tudora",
  title =        "Enhanced Fall Detection Using {YOLOv7-W6}-Pose for
                 Real-Time Elderly Monitoring",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "472",
  day =          "19",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120472",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/472",
  abstract =     "This study aims to enhance elderly fall detection
                 systems by using the YOLO (You Only Look Once) object
                 detection algorithm with pose estimation, improving
                 both accuracy and efficiency. Utilizing
                 YOLOv7-W6-Pose's robust real-time object detection and
                 pose estimation capabilities, the proposed system can
                 effectively identify falls in video feeds by using a
                 webcam and process them in real-time on a
                 high-performance computer equipped with a GPU to
                 accelerate object detection and pose estimation
                 algorithms. YOLO's single-stage detection mechanism
                 enables quick processing and analysis of video frames,
                 while pose estimation refines this process by analyzing
                 body positions and movements to accurately distinguish
                 falls from other activities. Initial validation was
                 conducted using several free videos sourced online,
                 depicting various types of falls. To ensure real-time
                 applicability, additional tests were conducted with
                 videos recorded live using a webcam, simulating dynamic
                 and unpredictable conditions. The experimental results
                 demonstrate significant advancements in detection
                 accuracy and robustness compared to traditional
                 methods. Furthermore, the approach ensures data privacy
                 by processing only skeletal points derived from pose
                 estimation, with no personal data stored. This
                 approach, integrated into the NeuroPredict platform
                 developed by our team, advances fall detection
                 technology, supporting better care and safety for older
                 adults.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Iordache:2024:EAV,
  author =       "Stefan Iordache and Catalina Camelia Patilea and
                 Ciprian Paduraru",
  title =        "Enhancing Autonomous Vehicle Safety with Blockchain
                 Technology: Securing Vehicle Communication and {AI}
                 Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "471",
  day =          "18",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120471",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/471",
  abstract =     "In recent years, the rapid development of autonomous
                 vehicles (AVs) has brought new challenges in terms of
                 data security, privacy, and communication integrity.
                 Our research investigates the potential of blockchain
                 technology to improve the security of AVs by securing
                 vehicle communication systems. By integrating
                 blockchain with AI-based predictive algorithms, this
                 approach aims to secure vehicle peer-to-peer
                 communication, reduce traffic congestion, and improve
                 safety for drivers and pedestrians. Blockchain's
                 decentralized ledger ensures the integrity of data
                 exchange between vehicles and smart city infrastructure
                 and mitigates the risks of cyberattacks such as data
                 manipulation and identity forgery. This paper also
                 examines recent advances in vehicular ad hoc networks
                 (VANETs) and vehicular social networks (VSNs), and it
                 demonstrates how the immutability and cryptographic
                 security of the blockchain can strengthen AV systems.
                 The proposed architecture not only protects user
                 privacy but also decentralizes access to critical data
                 needed for AI-driven decisions, ultimately promoting a
                 safer and more reliable environment for autonomous
                 vehicles.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kenyon:2024:CPE,
  author =       "Anthony Kenyon and Lipika Deka and David Elizondo",
  title =        "Characterising Payload Entropy in Packet Flows ---
                 Baseline Entropy Analysis for Network Anomaly
                 Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "470",
  day =          "16",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120470",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/470",
  abstract =     "The accurate and timely detection of cyber threats is
                 critical to keeping our online economy and data safe. A
                 key technique in early detection is the classification
                 of unusual patterns of network behaviour, often hidden
                 as low-frequency events within complex time-series
                 packet flows. One of the ways in which such anomalies
                 can be detected is to analyse the information entropy
                 of the payload within individual packets, since changes
                 in entropy can often indicate suspicious activity ---
                 such as whether session encryption has been
                 compromised, or whether a plaintext channel has been
                 co-opted as a covert channel. To decide whether
                 activity is anomalous, we need to compare real-time
                 entropy values with baseline values, and while the
                 analysis of entropy in packet data is not particularly
                 new, to the best of our knowledge, there are no
                 published baselines for payload entropy across commonly
                 used network services. We offer two contributions: (1)
                 we analyse several large packet datasets to establish
                 baseline payload information entropy values for
                 standard network services, and (2) we present an
                 efficient method for engineering entropy metrics from
                 packet flows from real-time and offline packet data.
                 Such entropy metrics can be included within feature
                 subsets, thus making the feature set richer for
                 subsequent analysis and machine learning
                 applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Vegas:2024:OCA,
  author =       "Jes{\'u}s Vegas and C{\'e}sar Llamas",
  title =        "Opportunities and Challenges of Artificial
                 Intelligence Applied to Identity and Access Management
                 in Industrial Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "469",
  day =          "16",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120469",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/469",
  abstract =     "The integration of artificial intelligence(AI)
                 technologies into identity and access management (IAM)
                 systems has greatly improved access control and
                 management, offering more robust, adaptive, and
                 intelligent solutions than traditional methods.
                 AI-driven IAM systems enhance security, operational
                 efficiency, and introduce new capabilities in
                 industrial environments. In this narrative review, we
                 present the state-of-the-art AI technologies in
                 industrial IAM, focusing on methods such as biometric,
                 comprising facial and voice recognition, and
                 multifactor authentication for robust security. It
                 addresses the challenges and solutions in implementing
                 AI-based IAM systems in industrial settings, including
                 security, privacy, evaluation, and continuous
                 improvement. We present also the emerging trends and
                 future directions, highlighting AI's potential to
                 transform industrial security measures. This review
                 aims to guide researchers and practitioners in
                 developing and implementing next-generation access
                 control systems, proposing future research directions
                 to address challenges and optimize AI applications in
                 this domain.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Trihinas:2024:EDM,
  author =       "Demetris Trihinas and Panagiotis Michael and Moysis
                 Symeonides",
  title =        "Evaluating {DL} Model Scaling Trade-Offs During
                 Inference via an Empirical Benchmark Analysis",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "468",
  day =          "13",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120468",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/468",
  abstract =     "With generative Artificial Intelligence (AI) capturing
                 public attention, the appetite of the technology sector
                 for larger and more complex Deep Learning (DL) models
                 is continuously growing. Traditionally, the focus in DL
                 model development has been on scaling the neural
                 network's foundational structure to increase
                 computational complexity and enhance the
                 representational expressiveness of the model. However,
                 with recent advancements in edge computing and 5G
                 networks, DL models are now aggressively being deployed
                 and utilized across the cloud--edge--IoT continuum for
                 the realization of in situ intelligent IoT services.
                 This paradigm shift introduces a growing need for AI
                 practitioners, as a focus on inference costs, including
                 latency, computational overhead, and energy efficiency,
                 is long overdue. This work presents a benchmarking
                 framework designed to assess DL model scaling across
                 three key performance axes during model inference:
                 classification accuracy, computational overhead, and
                 latency. The framework's utility is demonstrated
                 through an empirical study involving various model
                 structures and variants, as well as publicly available
                 datasets for three popular DL use cases covering
                 natural language understanding, object detection, and
                 regression analysis.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Xing:2024:SME,
  author =       "Weicheng Xing and Tianqing Zhu and Jenny Wang and Bo
                 Liu",
  title =        "A Survey on {MLLMs} in Education: Application and
                 Future Directions",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "467",
  day =          "13",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120467",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/467",
  abstract =     "This survey paper examines the applications,
                 methodologies, and future prospects of multimodal large
                 language models (MLLMs) within the educational
                 landscape. MLLMs, which integrate multiple data
                 modalities such as text, images, and audio, offer
                 innovative solutions that enhance learning experiences
                 across various educational domains, including language
                 acquisition, STEM education, interactive content
                 creation, and medical training. The paper highlights
                 how MLLMs contribute to improved engagement,
                 personalized learning paths, and enhanced comprehension
                 by leveraging their ability to process and generate
                 contextually relevant content. The key findings
                 underscore the transformative potential of MLLMs in
                 modern education, suggesting significant improvements
                 in both learner outcomes and pedagogical strategies.
                 The paper also explores emerging trends and
                 technological advancements that could shape the future
                 of education, advocating for continued research and
                 collaboration among stakeholders to fully harness the
                 capabilities of MLLMs. As the integration of MLLMs into
                 educational settings progresses, addressing ethical
                 considerations and ensuring equitable access remain
                 critical to maximizing their benefits.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Jin:2024:WFI,
  author =       "Shanyu Jin and Dongwoo Kim",
  title =        "{WiFi} Fingerprint Indoor Localization Employing
                 {Adaboost} and Probability-One Access Point Selection
                 for Multi-Floor Campus Buildings",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "466",
  day =          "13",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120466",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/466",
  abstract =     "Indoor positioning systems have become increasingly
                 important due to the rapid expansion of Internet of
                 Things (IoT) technologies, especially for providing
                 precise location-based services in complex environments
                 such as multi-floor campus buildings. This paper
                 presents a WiFi fingerprint indoor localization system
                 based on AdaBoost, combined with a new access point
                 (AP) filtering technique. The system comprises offline
                 and online phases. During the offline phase, a
                 fingerprint database is created using received signal
                 strength (RSS) values for two four-floor campus
                 buildings. In the online phase, the AdaBoost classifier
                 is used to accurately estimate locations. To improve
                 localization accuracy, APs that always appear in the
                 measurement data are selected for applying the AdaBoost
                 algorithm, aiming to eliminate noise from the
                 fingerprint database. The performance of the proposed
                 method is compared with other well-known machine
                 learning-based positioning algorithms in terms of
                 positioning accuracy and error distances. The results
                 indicate that the average positioning accuracy of the
                 proposed scheme reaches 95.55\%, which represents an
                 improvement of 5.55\% to 16.21\% over the other
                 methods. Additionally, the two-dimensional positioning
                 error can be reduced to 0.25 m.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chou:2024:CCH,
  author =       "Jerry Chou and Wu-Chun Chung",
  title =        "Cloud Computing and High Performance Computing ({HPC})
                 Advances for Next Generation {Internet}",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "465",
  day =          "12",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120465",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/465",
  abstract =     "Indoor positioning systems have become increasingly
                 important due to the rapid expansion of Internet of
                 Things (IoT) technologies, especially for providing
                 precise location-based services in complex environments
                 such as multi-floor campus buildings. This paper
                 presents a WiFi fingerprint indoor localization system
                 based on AdaBoost, combined with a new access point
                 (AP) filtering technique. The system comprises offline
                 and online phases. During the offline phase, a
                 fingerprint database is created using received signal
                 strength (RSS) values for two four-floor campus
                 buildings. In the online phase, the AdaBoost classifier
                 is used to accurately estimate locations. To improve
                 localization accuracy, APs that always appear in the
                 measurement data are selected for applying the AdaBoost
                 algorithm, aiming to eliminate noise from the
                 fingerprint database. The performance of the proposed
                 method is compared with other well-known machine
                 learning-based positioning algorithms in terms of
                 positioning accuracy and error distances. The results
                 indicate that the average positioning accuracy of the
                 proposed scheme reaches 95.55\%, which represents an
                 improvement of 5.55\% to 16.21\% over the other
                 methods. Additionally, the two-dimensional positioning
                 error can be reduced to 0.25 m.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liu:2024:RBM,
  author =       "Yuqi Liu and Rui Han and Xu Wang",
  title =        "A Reordering Buffer Management Method at Edge Gateway
                 in Hybrid {IP-ICN} Multipath Transmission System",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "464",
  day =          "11",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120464",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/464",
  abstract =     "Multipath transmission in ICN provides high
                 transmission efficiency and stability. In an IP-ICN
                 compatible network environment, unmodified IP terminal
                 devices can access ICN through gateways, benefiting
                 from these performance enhancements. This paper
                 proposes a gateway framework for hybrid IP-ICN
                 multipath transmission systems, enabling protocol
                 conversion and quality of service management. A packet
                 reordering module is integrated at the egress gateway
                 to address complex packet disorder issues caused by ICN
                 multipath transmission, thereby enhancing the service
                 quality provided to IP terminals. A Reordering Buffer
                 Management Method (RBMM) is introduced, consisting of
                 two key components. First, RBMM employs an improved
                 dynamic threshold scheme for reserved buffer
                 partitioning, efficiently identifying congestion and
                 optimizing buffer resource utilization. Second, a
                 flow-priority-based replacement strategy is designed to
                 enhance fairness in resource allocation by evicting
                 packets with lower delivery probability during
                 congestion. Experimental results demonstrate that RBMM
                 dynamically adapts to varying traffic conditions,
                 maintaining high transmission performance while
                 reducing buffer resource consumption. In comparison to
                 existing methods, RBMM significantly reduces queuing
                 delay and flow completion time, providing more balanced
                 resource allocation when multiple flows compete for
                 limited buffer capacity.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gerlach:2024:GXM,
  author =       "Bennet Gerlach and Hannes Hesse and Stefan Fischer and
                 Martin Leucker",
  title =        "{Gaia-X-Med}: Experiences with Building Dataspaces for
                 Medical Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "463",
  day =          "9",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120463",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/463",
  abstract =     "Gaia-X, a European initiative, aims to create a
                 digital sovereignty framework for service ecosystems in
                 the future Internet. Its applicability to the health
                 domain was explored in the Gaia-X-Med project, which
                 aimed to establish a common dataspace for various
                 medical use cases based on Gaia-X principles. This
                 paper presents a trust- and consent-based approach to
                 the secure authentication and digital contract
                 negotiation central to this endeavor and discusses the
                 challenges that arose during the adoption of the Gaia-X
                 framework, particularly relating to the strict
                 requirements of the European healthcare domain with
                 regards to privacy and consent regulations. By
                 exploring the practical implications of Gaia-X in the
                 healthcare context, this paper aims to contribute to
                 the ongoing discussions surrounding the digital
                 sovereignty of both citizens and corporations, as well
                 as its realization via future Internet technologies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhang:2024:GAM,
  author =       "Peng Zhang and Jiayu Shi and Maged N. Kamel Boulos",
  title =        "Generative {AI} in Medicine and Healthcare: Moving
                 Beyond the `Peak of Inflated Expectations'",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "462",
  day =          "9",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120462",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/462",
  abstract =     "The rapid development of specific-purpose Large
                 Language Models (LLMs), such as Med-PaLM, MEDITRON-70B,
                 and Med-Gemini, has significantly impacted healthcare,
                 offering unprecedented capabilities in clinical
                 decision support, diagnostics, and personalized health
                 monitoring. This paper reviews the advancements in
                 medicine-specific LLMs, the integration of
                 Retrieval-Augmented Generation (RAG) and prompt
                 engineering, and their applications in improving
                 diagnostic accuracy and educational utility. Despite
                 the potential, these technologies present challenges,
                 including bias, hallucinations, and the need for robust
                 safety protocols. The paper also discusses the
                 regulatory and ethical considerations necessary for
                 integrating these models into mainstream healthcare. By
                 examining current studies and developments, this paper
                 aims to provide a comprehensive overview of the state
                 of LLMs in medicine and highlight the future directions
                 for research and application. The study concludes that
                 while LLMs hold immense potential, their safe and
                 effective integration into clinical practice requires
                 rigorous testing, ongoing evaluation, and continuous
                 collaboration among stakeholders.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yuan:2024:ELT,
  author =       "Xinyang Yuan and Jiarong Wang and Haozhi Zhao and Tian
                 Yan and Fazhi Qi",
  title =        "Empowering {LLMs} with Toolkits: an Open-Source
                 Intelligence Acquisition Method",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "461",
  day =          "7",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120461",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/461",
  abstract =     "The acquisition of cybersecurity threat intelligence
                 is a critical task in the implementation of effective
                 security defense strategies. Recently, advancements in
                 large language model (LLM) technology have led to
                 remarkable capabilities in natural language processing
                 and understanding. In this paper, we introduce an
                 LLM-based approach for open-source intelligence (OSINT)
                 acquisition. This approach autonomously obtains OSINT
                 based on user requirements, eliminating the need for
                 manual scanning or querying, thus saving significant
                 time and effort. To further address the knowledge
                 limitations and timeliness challenges inherent in LLMs
                 when handling threat intelligence, we propose a
                 framework that integrates chain-of-thought techniques
                 to assist LLMs in utilizing tools to acquire OSINT.
                 Based on this framework, we have developed a threat
                 intelligence acquisition agent capable of decomposing
                 logical reasoning problems into multiple steps and
                 gradually solving them using appropriate tools, along
                 with a toolkit for the agent to dynamically access
                 during the problem-solving process. To validate the
                 effectiveness of our approach, we have designed four
                 evaluation metrics to assess the agent's performance
                 and constructed a test set. Experimental results
                 indicate that the agent achieves high accuracy rates in
                 OSINT acquisition tasks, with a substantial improvement
                 noted over its baseline large language model
                 counterpart in specific intelligence acquisition
                 scenarios.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Shoeibi:2024:NSD,
  author =       "Mehrdad Shoeibi and Anita Ershadi Oskouei and Masoud
                 Kaveh",
  title =        "A Novel Six-Dimensional Chimp Optimization Algorithm
                 --- Deep Reinforcement Learning-Based Optimization
                 Scheme for Reconfigurable Intelligent Surface-Assisted
                 Energy Harvesting in Batteryless {IoT} Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "460",
  day =          "6",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120460",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/460",
  abstract =     "The rapid advancement of Internet of Things (IoT)
                 networks has revolutionized modern connectivity by
                 integrating many low-power devices into various
                 applications. As IoT networks expand, the demand for
                 energy-efficient, batteryless devices becomes
                 increasingly critical for sustainable future networks.
                 These devices play a pivotal role in next-generation
                 IoT applications by reducing the dependence on
                 conventional batteries and enabling continuous
                 operation through energy harvesting capabilities.
                 However, several challenges hinder the widespread
                 adoption of batteryless IoT devices, including the
                 limited transmission range, constrained energy
                 resources, and low spectral efficiency in IoT
                 receivers. To address these limitations, reconfigurable
                 intelligent surfaces (RISs) offer a promising solution
                 by dynamically manipulating the wireless propagation
                 environment to enhance signal strength and improve
                 energy harvesting capabilities. In this paper, we
                 propose a novel deep reinforcement learning (DRL)
                 algorithm that optimizes the phase shifts of RISs to
                 maximize the network's achievable rate while satisfying
                 IoT devices' energy harvesting constraints. Our DRL
                 framework leverages a novel six-dimensional chimp
                 optimization algorithm (6DChOA) to fine-tune the
                 hyper-parameters, ensuring efficient and adaptive
                 learning. The proposed 6DChOA-DRL algorithm optimizes
                 RIS phase shifts to enhance the received power of IoT
                 devices while mitigating interference from direct and
                 RIS-cascaded links. The simulation results demonstrate
                 that our optimized RIS design significantly improves
                 energy harvesting and achievable data rates under
                 various system configurations. Compared to benchmark
                 algorithms, our approach achieves higher gains in
                 harvested power, an improvement in the data rate at a
                 transmit power of 20 dBm, and a significantly lower
                 root mean square error (RMSE) of 0.13 compared to 3.34
                 for standard RL and 6.91 for the DNN, indicating more
                 precise optimization of RIS phase shifts.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{vonSchwerin:2024:SCB,
  author =       "Magdalena von Schwerin and Manfred Reichert",
  title =        "A Systematic Comparison Between Open- and
                 Closed-Source Large Language Models in the Context of
                 Generating {GDPR}-Compliant Data Categories for
                 Processing Activity Records",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "459",
  day =          "5",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120459",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/459",
  abstract =     "This study investigates the capabilities of
                 open-source Large Language Models (LLMs) in automating
                 GDPR compliance documentation, specifically in
                 generating data categories --- types of personal data
                 (e.g., names, email addresses) --- for processing
                 activity records, a document required by the General
                 Data Protection Regulation (GDPR). By comparing four
                 state-of-the-art open-source models with the
                 closed-source GPT-4, we evaluate their performance
                 using benchmarks tailored to GDPR tasks: a
                 multiple-choice benchmark testing contextual knowledge
                 (evaluated by accuracy and F1 score) and a generation
                 benchmark evaluating structured data generation. In
                 addition, we conduct four experiments using
                 context-augmenting techniques such as few-shot
                 prompting and Retrieval-Augmented Generation (RAG). We
                 evaluate these on performance metrics such as latency,
                 structure, grammar, validity, and contextual
                 understanding. Our results show that open-source
                 models, particularly Qwen2-7B, achieve performance
                 comparable to GPT-4, demonstrating their potential as
                 cost-effective and privacy-preserving alternatives.
                 Context-augmenting techniques show mixed results, with
                 RAG improving performance for known categories but
                 struggling with categories not contained in the
                 knowledge base. Open-source models excel at structured
                 legal tasks, although challenges remain in handling
                 ambiguous legal language and unstructured scenarios.
                 These findings underscore the viability of open-source
                 models for GDPR compliance, while highlighting the need
                 for fine-tuning and improved context augmentation to
                 address complex use cases.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alshdadi:2024:BDD,
  author =       "Abdulrahman A. Alshdadi and Abdulwahab Ali Almazroi
                 and Nasir Ayub and Miltiadis D. Lytras and Eesa
                 Alsolami and Faisal S. Alsubaei",
  title =        "Big Data-Driven Deep Learning Ensembler for {DDoS}
                 Attack Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "458",
  day =          "5",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120458",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/458",
  abstract =     "The increasing threat of Distributed DDoS attacks
                 necessitates robust, big data-driven methods to detect
                 and mitigate complex Network and Transport Layer (NTL)
                 attacks. This paper proposes EffiGRU-GhostNet, a
                 deep-learning ensemble model for high-accuracy DDoS
                 detection with minimal resource consumption.
                 EffiGRU-GhostNet integrates Gated Recurrent Units (GRU)
                 with the GhostNet architecture, optimized through
                 Principal Component Analysis with Locality Preserving
                 Projections (PCA-LLP) to handle large-scale data
                 effectively. Our ensemble was tested on IoT-23,
                 APA-DDoS, and additional datasets created from popular
                 DDoS attack tools. Simulations demonstrate a
                 recognition rate of 98.99\% on IoT-23 with a 0.11\%
                 false positive rate and 99.05\% accuracy with a 0.01\%
                 error on APA-DDoS, outperforming SVM, ANN-GWO, GRU-RNN,
                 CNN, LSTM, and DBN baselines. Statistical validation
                 through Wilcoxon and Spearman's tests further verifies
                 EffiGRU-GhostNet's effectiveness across datasets, with
                 a Wilcoxon F-statistic of 7.632 ( p = 0.022) and a
                 Spearman correlation of 0.822 ( p = 0.005). This study
                 demonstrates that EffiGRU-GhostNet is a reliable,
                 scalable solution for dynamic DDoS detection, advancing
                 the field of big data-driven cybersecurity.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bray:2024:LCA,
  author =       "Nick Bray and Matthew Boeding and Michael Hempel and
                 Hamid Sharif and Tapio Heikkil{\"a} and Markku
                 Suomalainen and Tuomas Sepp{\"a}l{\"a}",
  title =        "A Latency Composition Analysis for Telerobotic
                 Performance Insights Across Various Network Scenarios",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "457",
  day =          "4",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120457",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/457",
  abstract =     "Telerobotics involves the operation of robots from a
                 distance, often using advanced communication
                 technologies combining wireless and wired technologies
                 and a variety of protocols. This application domain is
                 crucial because it allows humans to interact with and
                 control robotic systems safely and from a distance,
                 often performing activities in hazardous or
                 inaccessible environments. Thus, by enabling remote
                 operations, telerobotics not only enhances safety but
                 also expands the possibilities for medical and
                 industrial applications. In some use cases,
                 telerobotics bridges the gap between human skill and
                 robotic precision, making the completion of complex
                 tasks requiring high accuracy possible without being
                 physically present. With the growing availability of
                 high-speed networks around the world, especially with
                 the advent of 5G cellular technologies, applications of
                 telerobotics can now span a gamut of scenarios ranging
                 from remote control in the same room to robotic control
                 across the globe. However, there are a variety of
                 factors that can impact the control precision of the
                 robotic platform and user experience of the
                 teleoperator. One such critical factor is latency,
                 especially across large geographical areas or complex
                 network topologies. Consequently, military telerobotics
                 and remote operations, for example, rely on dedicated
                 communications infrastructure for such tasks. However,
                 this creates a barrier to entry for many other
                 applications and domains, as the cost of dedicated
                 infrastructure would be prohibitive. In this paper, we
                 examine the network latency of robotic control over
                 shared network resources in a variety of network
                 settings, such as a local network, access-controlled
                 networks through Wi-Fi and cellular, and a remote
                 transatlantic connection between Finland and the United
                 States. The aim of this study is to quantify and
                 evaluate the constituent latency components that
                 comprise the control feedback loop of this telerobotics
                 experience --- of a camera feed for an operator to
                 observe the telerobotic platform's environment in one
                 direction and the control communications from the
                 operator to the robot in the reverse direction. The
                 results show stable average round-trip latency of 6.6
                 ms for local network connection, 58.4 ms when
                 connecting over Wi-Fi, 115.4 ms when connecting through
                 cellular, and 240.7 ms when connecting from Finland to
                 the United States over a VPN access-controlled network.
                 These findings provide a better understanding of the
                 capabilities and performance limitations of conducting
                 telerobotics activities over commodity networks, and
                 lay the foundation of our future work to use these
                 insights for optimizing the overall user experience and
                 the responsiveness of this control loop.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Munoz:2024:MPA,
  author =       "Ernesto Cadena Mu{\~n}oz and Gustavo Chica Pedraza and
                 Alexander Aponte Moreno",
  title =        "Multiple {PUE} Attack Detection in Cooperative Mobile
                 Cognitive Radio Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "456",
  day =          "4",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120456",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/456",
  abstract =     "The Mobile Cognitive Radio Network (MCRN) are an
                 alternative to spectrum scarcity. However, like any
                 network, it comes with security issues to analyze. One
                 of the attacks to analyze is the Primary User Emulation
                 (PUE) attack, which leads the system to give the
                 attacker the service as a legitimate user and use the
                 Primary Users' (PUs) spectrum resources. This problem
                 has been addressed from perspectives like arrival time,
                 position detection, cooperative scenarios, and
                 artificial intelligence techniques (AI). Nevertheless,
                 it has been studied with one PUE attack at once. This
                 paper implements a countermeasure that can be applied
                 when several attacks simultaneously exist in a
                 cooperative network. A deep neural network (DNN) is
                 used with other techniques to determine the PUE's
                 existence and communicate it with other devices in the
                 cooperative MCRN. An algorithm to detect and share
                 detection information is applied, and the results show
                 that the system can detect multiple PUE attacks with
                 coordination between the secondary users (SUs).
                 Scenarios are implemented on software-defined radio
                 (SDR) with a cognitive protocol to protect the PU. The
                 probability of detection (PD) is measured for some
                 signal-to-noise ratio (SNR) values in the presence of
                 one PUE or more in the network, which shows high
                 detection values above 90\% for an SNR of -7dB. A
                 database is also created with the attackers' data and
                 shared with all the SUs.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Papazis:2024:HFM,
  author =       "Kon Papazis and Naveen Chilamkurti",
  title =        "{Hydrakon}, a Framework for Measuring Indicators of
                 Deception in Emulated Monitoring Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "455",
  day =          "4",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120455",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/455",
  abstract =     "The current cybersecurity ecosystem is proving
                 insufficient in today's increasingly sophisticated
                 cyber attacks. Malware authors and intruders have
                 pursued innovative avenues to circumvent emulated
                 monitoring systems (EMSs) such as honeypots, virtual
                 machines, sandboxes and debuggers to continue with
                 their malicious activities while remaining
                 inconspicuous. Cybercriminals are improving their
                 ability to detect EMS, by finding indicators of
                 deception (IoDs) to expose their presence and avoid
                 detection. It is proving a challenge for security
                 analysts to deploy and manage EMS to evaluate their
                 deceptive capability. In this paper, we introduce the
                 Hydrakon framework, which is composed of an EMS
                 controller and several Linux and Windows 10 clients.
                 The EMS controller automates the deployment and
                 management of the clients and EMS for the purpose of
                 measuring EMS deceptive capabilities. Experiments were
                 conducted by applying custom detection vectors to
                 client real machines, virtual machines and sandboxes,
                 where various artifacts were extracted and stored as
                 csv files on the EMS controller. The experiment
                 leverages the cosine similarity metric to compare and
                 identify similar artifacts between a real system and a
                 virtual machine or sandbox. Our results show that
                 Hydrakon offers a valid approach to assess the
                 deceptive capabilities of EMS without the need to
                 target specific IoD within the target system, thereby
                 fostering more robust and effective emulated monitoring
                 systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kim:2024:RBT,
  author =       "Heejoo Kim and Zhe Xiao and Xiaocai Zhang and Xiuju Fu
                 and Zheng Qin",
  title =        "Rethinking Blockchain Technologies for the Maritime
                 Industry: an Overview of the Current Landscape",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "454",
  day =          "3",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120454",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/454",
  abstract =     "This survey aims to provide an up-to-date and succinct
                 yet informative overview of the blockchain technologies
                 for the maritime industry. We synthesize the recent
                 advancements in blockchain development and its adoption
                 across maritime sectors, highlighting the key
                 blockchain use cases, including promoting maritime
                 sustainability and optimizing maritime supply chain
                 management through improved traceability, advancing
                 smart shipping with automated processes and fostering
                 collaboration among stakeholders by enhancing
                 transparency. Through an analysis of current
                 implementations, pilot projects, and case studies, we
                 especially focus on identifying the challenges and
                 barriers, reasoning on the status quo, and the
                 opportunities and future perspectives for blockchain in
                 maritime.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chajia:2024:CCP,
  author =       "Meryem Chajia and El Habib Nfaoui",
  title =        "Customer Churn Prediction Approach Based on {LLM}
                 Embeddings and Logistic Regression",
  journal =      j-FUTURE-INTERNET,
  volume =       "16",
  number =       "12",
  pages =        "453",
  day =          "3",
  month =        dec,
  year =         "2024",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi16120453",
  ISSN =         "1999-5903",
  bibdate =      "Tue Dec 31 12:05:17 MST 2024",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/16/12/453",
  abstract =     "Nowadays, predicting customer churn is essential for
                 the success of any company. Loyal customers generate
                 continuous revenue streams, resulting in long-term
                 success and growth. Moreover, companies are
                 increasingly prioritizing the retention of existing
                 customers due to the higher costs associated with
                 attracting new ones. Consequently, there has been a
                 growing demand for advanced methods aimed at enhancing
                 customer loyalty and satisfaction, as well as
                 predicting churners. In our work, we focused on
                 building a robust churn prediction model for the
                 telecommunications industry based on large embeddings
                 from large language models and logistic regression to
                 accurately identify churners. We conducted extensive
                 experiments using a range of embedding techniques,
                 including OpenAI Text-embedding, Google Gemini Text
                 Embedding, bidirectional encoder representations from
                 transformers (BERT), Sentence-Transformers, Sent2vec,
                 and Doc2vec, to extract meaningful features.
                 Additionally, we tested various classifiers, including
                 logistic regression, support vector machine, random
                 forest, K-nearest neighbors, multilayer perceptron,
                 naive Bayes, decision tree, and zero-shot
                 classification, to build a robust model capable of
                 making accurate predictions. The best-performing model
                 in our experiments is the logistic regression
                 classifier, which we trained using the extracted
                 feature from the OpenAI Text-embedding-ada-002 model,
                 achieving an accuracy of 89\%. The proposed model
                 demonstrates a high discriminative ability between
                 churning and loyal customers.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ramirez-Gordillo:2025:DIM,
  author =       "Tamai Ram{\'\i}rez-Gordillo and Antonio
                 Maci{\'a}-Lillo and Francisco A. Pujol and Nahuel
                 Garc{\'\i}a-D'Urso and Jorge Azor{\'\i}n-L{\'o}pez and
                 Higinio Mora",
  title =        "Decentralized Identity Management for {Internet of
                 Things} ({IoT}) Devices Using {IOTA} Blockchain
                 Technology",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "49",
  day =          "20",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010049",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/49",
  abstract =     "The exponential growth of the Internet of Things (IoT)
                 necessitates robust, scalable, and secure identity
                 management solutions to handle the vast number of
                 interconnected devices. Traditional centralized
                 identity systems are increasingly inadequate due to
                 their vulnerabilities, such as single points of
                 failure, scalability issues, and limited user control
                 over data. This study explores a decentralized identity
                 management model leveraging the IOTA Tangle, a Directed
                 Acyclic Graph (DAG)-based distributed ledger
                 technology, to address these challenges. By integrating
                 Decentralized Identifiers (DIDs), Verifiable
                 Credentials (VCs), and IOTA-specific technologies like
                 IOTA Identity, IOTA Streams, and IOTA Stronghold, we
                 propose a proof-of-concept framework that enhances
                 security, scalability, and privacy in IoT ecosystems.
                 Our implementation on resource-constrained IoT devices
                 demonstrates the feasibility of this approach,
                 highlighting significant improvements in transaction
                 efficiency, real-time data exchange, and cryptographic
                 key management. Furthermore, this research aligns with
                 Web 3.0 principles, emphasizing decentralization, user
                 autonomy, and data sovereignty. The findings suggest
                 that IOTA-based solutions can effectively advance
                 secure and user-centric identity management in IoT,
                 paving the way for broader applications in various
                 domains, including smart cities and healthcare.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{iPico:2025:TMF,
  author =       "Jan {Ferrer i Pic{\'o}} and Michelle Catta-Preta and
                 Alex {Trejo Ome{\~n}aca} and Marc Vidal and Josep Maria
                 {Monguet i Fierro}",
  title =        "The Time Machine: Future Scenario Generation Through
                 Generative {AI} Tools",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "48",
  day =          "20",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010048",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/48",
  abstract =     "Contemporary society faces unprecedented
                 challenges---from rapid technological evolution to
                 climate change and demographic tensions---compelling
                 organisations to anticipate the future for informed
                 decision-making. This case study aimed to design a
                 digital system for end-users called the Time Machine,
                 which enables a generative artificial intelligence
                 (GAI) system to produce prospective future scenarios
                 based on the input information automatically, proposing
                 hypotheses and prioritising trends to streamline and
                 make the formulation of future scenarios more
                 accessible. The system's design, development, and
                 testing progressed through three versions of prompts
                 for the OpenAI GPT-4 LLM, with six trials conducted
                 involving 222 participants. This iterative approach
                 allowed for gradual adjustment of instructions given to
                 the machine and encouraged refinement. Results from the
                 six trials demonstrated that the Time Machine is an
                 effective tool for generating future scenarios that
                 promote debate and stimulate new ideas in
                 multidisciplinary teams. Our trials proved that
                 GAI-generated scenarios could foster discussions on
                 +70\% of generated scenarios with appropriate
                 prompting, and more than half included new ideas. In
                 conclusion, large language models (LLMs) of GAI, with
                 suitable prompt engineering and architecture, have the
                 potential to generate useful future scenarios for
                 organisations, transforming future intelligence into a
                 more accessible and operational resource. However,
                 critical use of these scenarios is essential.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Aloqaily:2025:DLF,
  author =       "Ahmad Aloqaily and Emad E. Abdallah and Rahaf Al-Zyoud
                 and Esraa Abu Elsoud and Malak Al-Hassan and Alaa E.
                 Abdallah",
  title =        "Deep Learning Framework for Advanced De-Identification
                 of Protected Health Information",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "47",
  day =          "20",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010047",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/47",
  abstract =     "Electronic health records (EHRs) are widely used in
                 healthcare institutions worldwide, containing vast
                 amounts of unstructured textual data. However, the
                 sensitive nature of Protected Health Information (PHI)
                 embedded within these records presents significant
                 privacy challenges, necessitating robust
                 de-identification techniques. This paper introduces a
                 novel approach, leveraging a Bi-LSTM-CRF model to
                 achieve accurate and reliable PHI de-identification,
                 using the i2b2 dataset sourced from Harvard University.
                 Unlike prior studies that often unify Bi-LSTM and CRF
                 layers, our approach focuses on the individual design,
                 optimization, and hyperparameter tuning of both the
                 Bi-LSTM and CRF components, allowing for precise model
                 performance improvements. This rigorous approach to
                 architectural design and hyperparameter tuning, often
                 underexplored in the existing literature, significantly
                 enhances the model's capacity for accurate PHI tag
                 detection while preserving the essential clinical
                 context. Comprehensive evaluations are conducted across
                 23 PHI categories, as defined by HIPAA, ensuring
                 thorough security across critical domains. The
                 optimized model achieves exceptional performance
                 metrics, with a precision of 99\%, recall of 98\%, and
                 F1-score of 98\%, underscoring its effectiveness in
                 balancing recall and precision. By enabling the
                 de-identification of medical records, this research
                 strengthens patient confidentiality, promotes
                 compliance with privacy regulations, and facilitates
                 safe data sharing for research and analysis.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bayu:2025:AOA,
  author =       "Teguh Indra Bayu and Yung-Fa Huang and Jeang-Kuo Chen
                 and Cheng-Hsiung Hsieh and Budhi Kristianto and Erwien
                 Christianto and Suharyadi Suharyadi",
  title =        "Advanced Optimization Algorithm Combining a Fuzzy
                 Inference System for Vehicular Communications",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "46",
  day =          "20",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010046",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/46",
  abstract =     "The use of a static modulation coding scheme (MCS),
                 such as 7, and resource keep probability ( Prk ) value,
                 such as 0.8, was proven to be insufficient to achieve
                 the best packet reception ratio (PRR) performance.
                 Various adaptation techniques have been used in the
                 following years. This work introduces a novel
                 optimization algorithm approach called the fuzzy
                 inference reinforcement learning (FIRL) sequence for
                 adaptive parameter configuration in cellular
                 vehicle-to-everything (C-V2X) mode-4 communication
                 networks. This innovative method combines a Sugeno-type
                 fuzzy inference system (FIS) control system with a
                 Q-learning reinforcement learning algorithm to optimize
                 the PRR as the key metric for overall network
                 performance. The FIRL sequence generates adaptive
                 configuration parameters for Prk and MCS index values
                 each time the Long-Term Evolution (LTE) packet is
                 generated. Simulation results demonstrate the
                 effectiveness of this optimization algorithm approach,
                 achieving up to a 169.83\% improvement in performance
                 compared to static baseline parameters.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Qiao:2025:BAI,
  author =       "Yuansong Qiao",
  title =        "Blockchain and Artificial Intelligence for
                 Decentralized Edge Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "45",
  day =          "19",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010045",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/45",
  abstract =     "The use of a static modulation coding scheme (MCS),
                 such as 7, and resource keep probability ( Prk ) value,
                 such as 0.8, was proven to be insufficient to achieve
                 the best packet reception ratio (PRR) performance.
                 Various adaptation techniques have been used in the
                 following years. This work introduces a novel
                 optimization algorithm approach called the fuzzy
                 inference reinforcement learning (FIRL) sequence for
                 adaptive parameter configuration in cellular
                 vehicle-to-everything (C-V2X) mode-4 communication
                 networks. This innovative method combines a Sugeno-type
                 fuzzy inference system (FIS) control system with a
                 Q-learning reinforcement learning algorithm to optimize
                 the PRR as the key metric for overall network
                 performance. The FIRL sequence generates adaptive
                 configuration parameters for Prk and MCS index values
                 each time the Long-Term Evolution (LTE) packet is
                 generated. Simulation results demonstrate the
                 effectiveness of this optimization algorithm approach,
                 achieving up to a 169.83\% improvement in performance
                 compared to static baseline parameters.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Perez-Cano:2025:FDC,
  author =       "V{\'\i}ctor P{\'e}rez-Cano and Francisco Jurado",
  title =        "Fraud Detection in Cryptocurrency Networks --- an
                 Exploration Using Anomaly Detection and Heterogeneous
                 Graph Transformers",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "44",
  day =          "19",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010044",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/44",
  abstract =     "Blockchains are the backbone behind cryptocurrency
                 networks, which have developed rapidly in the last two
                 decades. However, this growth has brought several
                 challenges due to the features of these networks,
                 specifically anonymity and decentralization. One of
                 these challenges is the fight against fraudulent
                 activities performed in these networks, which, among
                 other things, involve financial schemes, phishing
                 attacks or money laundering. This article will address
                 the problem of identifying fraud cases among a large
                 set of transactions extracted from the Bitcoin network.
                 More specifically, our study's goal was to find
                 reliable techniques to label Bitcoin transactions,
                 taking into account their features. The approach
                 followed involved two kinds of Machine Learning
                 methods. On the one hand, anomaly detection algorithms
                 were applied to determine whether fraudulent activities
                 tend to show anomalous behaviour without resorting to
                 manually obtained labels. On the other hand,
                 Heterogeneous Graph Transformers were used to leverage
                 the heterogeneous relational nature of the
                 cryptocurrency information. As a result, the article
                 will provide reasonable conclusions to acknowledge that
                 unsupervised approaches can be useful for fraud
                 detection on blockchain networks. Furthermore, the
                 effectiveness of supervised graph methods was
                 revalidated, emphasizing the importance of data
                 heterogeneity.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kuo:2025:DKR,
  author =       "Chung-Wei Kuo and Wei Wei and Chun-Chang Lin and Yu-Yi
                 Hong and Jia-Ruei Liu and Kuo-Yu Tsai",
  title =        "Dynamic Key Replacement Mechanism for Lightweight
                 {Internet of Things} Microcontrollers to Resist
                 Side-Channel Attacks",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "43",
  day =          "18",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010043",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/43",
  abstract =     "5G technology and IoT devices are improving efficiency
                 and quality of life across many sectors. IoT devices
                 are often used in open environments where they handle
                 sensitive data. This makes them vulnerable to
                 side-channel attacks (SCAs), where attackers can
                 intercept and analyze the electromagnetic signals
                 emitted by microcontroller units (MCUs) to expose
                 encryption keys and compromise sensitive data. To
                 address this critical vulnerability, this study
                 proposes a novel dynamic key replacement mechanism
                 specifically designed for lightweight IoT
                 microcontrollers. The mechanism integrates Moving
                 Target Defense (MTD) with a lightweight Diffie--Hellman
                 (D-H) key exchange protocol and AES-128 encryption to
                 provide robust protection against SCAs. Unlike
                 traditional approaches, the proposed mechanism
                 dynamically updates encryption keys during each
                 cryptographic cycle, effectively mitigating the risk of
                 key reuse --- a primary vulnerability exploited in
                 SCAs. The lightweight D-H key exchange ensures that
                 even resource-constrained IoT devices can securely
                 perform key exchanges without significant computational
                 overhead. Experimental results demonstrate the
                 practicality and security of the proposed mechanism,
                 achieving key updates with minimal time overhead,
                 ranging from 12 to 50 milliseconds per encryption
                 transmission. Moreover, the approach shows strong
                 resilience against template attacks, with only two out
                 of sixteen AES-128 subkeys compromised after 20,000
                 attack attempts --- a notable improvement over existing
                 countermeasures. The key innovation of this study lies
                 in the seamless integration of MTD with lightweight
                 cryptographic protocols, striking a balance between
                 security and performance. This dynamic key replacement
                 mechanism offers an effective, scalable, and
                 resource-efficient solution for IoT applications,
                 particularly in scenarios that demand robust protection
                 against SCAs and low-latency performance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Amadeo:2025:ENC,
  author =       "Marica Amadeo and Giuseppe Ruggeri",
  title =        "Exploring In-Network Computing with
                 Information-Centric Networking: Review and Research
                 Opportunities",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "42",
  day =          "18",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010042",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/42",
  abstract =     "The advent of 6G networks and beyond calls for
                 innovative paradigms to address the stringent demands
                 of emerging applications, such as extended reality and
                 autonomous vehicles, as well as technological
                 frameworks like digital twin networks. Traditional
                 cloud computing and edge computing architectures fall
                 short in providing their required flexibility,
                 scalability, and ultra-low latency. Cloud computing
                 centralizes resources in distant data centers, leading
                 to high latency and increased network congestion, while
                 edge computing, though closer to data sources, lacks
                 the agility to dynamically adapt to fluctuating
                 workloads, user mobility, and real-time requirements.
                 In-network computing (INC) offers a transformative
                 solution by integrating computational capabilities
                 directly into the network fabric, enabling dynamic and
                 distributed task execution. This paper explores INC
                 through the lens of information-centric networking
                 (ICN), a revolutionary communication paradigm
                 implementing routing-by-name and in-network caching,
                 and thus emerging as a natural enabler for INC. We
                 review state-of-the-art advancements involving INC and
                 ICN, addressing critical topics such as service naming,
                 executor selection strategies, compute reuse, and
                 security. Furthermore, we discuss key challenges and
                 propose research directions for deploying INC via ICN,
                 thereby outlining a cohesive roadmap for future
                 investigation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fantozzi:2025:DTS,
  author =       "Italo Cesidio Fantozzi and Annalisa Santolamazza and
                 Giancarlo Loy and Massimiliano Maria Schiraldi",
  title =        "Digital Twins: Strategic Guide to Utilize Digital
                 Twins to Improve Operational Efficiency in {Industry
                 4.0}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "41",
  day =          "17",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010041",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/41",
  abstract =     "The Fourth Industrial Revolution, known as Industry
                 4.0, has transformed the manufacturing landscape by
                 integrating advanced digital technologies, fostering
                 automation, interconnectivity, and data-driven
                 decision-making. Among these innovations, Digital Twins
                 (DTs) have emerged as a pivotal tool, enabling
                 real-time monitoring, simulation, and optimization of
                 production processes. This paper provides a
                 comprehensive exploration of DT technology, offering a
                 strategic framework for its effective implementation
                 within Industry 4.0 environments to enhance operational
                 efficiency. The proposed methodology integrates key
                 enabling technologies such as the Internet of Things
                 (IoT), Artificial Intelligence (AI), and Machine
                 Learning to create accurate digital replicas of
                 manufacturing systems. Through a detailed case study,
                 this work demonstrates how DTs can optimize production
                 processes, reduce downtime, and improve maintenance
                 strategies. The findings highlight DTs' transformative
                 potential in achieving continuous improvement,
                 competitiveness, and operational excellence. This
                 research aims to provide organizations with actionable
                 insights and a roadmap to leverage DT technology for
                 sustainable industrial innovation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yang:2025:SBA,
  author =       "Yang Yang and Min Lin and Yangfei Lin and Chen Zhang
                 and Celimuge Wu",
  title =        "A Survey of Blockchain Applications for Management in
                 Agriculture and Livestock {Internet of Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "40",
  day =          "17",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010040",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/40",
  abstract =     "In the area of agriculture and livestock management,
                 the integration of the Internet of Things (IoT) has
                 emerged as a groundbreaking strategy to enhance
                 operational efficiency and advance intelligent process
                 management. However, this sector faces significant
                 challenges, including ambiguity in product origins and
                 limited regulatory oversight of IoT devices. This paper
                 explores the innovative integration of blockchain
                 technology within the agricultural and livestock IoT,
                 highlighting how this convergence significantly
                 enhances operational security and transparency. We
                 provide an in-depth review of the latest applications
                 and advancements of blockchain in these domains,
                 offering a comprehensive analysis of the current state
                 of technology and its implications. Furthermore, this
                 paper discusses the potential future development
                 trajectories in agricultural and livestock IoT,
                 emphasizing blockchain's role in addressing current
                 challenges and shaping future innovations. The findings
                 suggest that blockchain technology not only improves
                 data security and trustworthiness but also opens new
                 avenues for efficient and transparent management in
                 agriculture and animal husbandry.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Baruffa:2025:RAA,
  author =       "Giuseppe Baruffa and Luca Rugini",
  title =        "Resource Assignment Algorithms for Autonomous Mobile
                 Robots with Task Offloading",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "39",
  day =          "16",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010039",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/39",
  abstract =     "This paper deals with the optimization of the
                 operational efficiency of a fleet of mobile robots,
                 assigned with delivery-like missions in complex outdoor
                 scenarios. The robots, due to limited onboard
                 computation resources, need to offload some complex
                 computing tasks to an edge/cloud server, requiring
                 artificial intelligence and high computation loads. The
                 mobile robots also need reliable and efficient radio
                 communication with the network hosting edge/cloud
                 servers. The resource assignment aims at minimizing the
                 total latency and delay caused by the use of radio
                 links and computation nodes. This minimization is a
                 nonlinear integer programming problem, with high
                 complexity. In this paper, we present
                 reduced-complexity algorithms that allow to jointly
                 optimize the available radio and computation resources.
                 The original problem is reformulated and simplified, so
                 that it can be solved by also selfish and greedy
                 algorithms. For comparison purposes, a genetic
                 algorithm (GA) is used as the baseline for the proposed
                 optimization techniques. Simulation results in several
                 scenarios show that the proposed sequential
                 minimization (SM) algorithm achieves an almost optimal
                 solution with significantly reduced complexity with
                 respect to GA.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gifu:2025:AIV,
  author =       "Daniela Gifu and Covaci Silviu-Vasile",
  title =        "Artificial Intelligence vs. Human: Decoding Text
                 Authenticity with Transformers",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "38",
  day =          "16",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010038",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/38",
  abstract =     "This paper presents a comprehensive study on detecting
                 AI-generated text using transformer models. Our
                 research extends the existing RODICA dataset to create
                 the Enhanced RODICA for Human-Authored and AI-Generated
                 Text (ERH) dataset. We enriched RODICA by incorporating
                 machine-generated texts from various large language
                 models (LLMs), ensuring a diverse and representative
                 corpus. Methodologically, we fine-tuned several
                 transformer architectures, including BERT, RoBERTa, and
                 DistilBERT, on this dataset to distinguish between
                 human-written and AI-generated text. Our experiments
                 examined both monolingual and multilingual settings,
                 evaluating the model's performance across diverse
                 datasets such as M4, AICrowd, Indonesian Hoax News
                 Detection, TURNBACKHOAX, and ERH. The results
                 demonstrate that RoBERTa-large achieved superior
                 accuracy and F-scores of around 83\%, particularly in
                 monolingual contexts, while
                 DistilBERT-multilingual-cased excelled in multilingual
                 scenarios, achieving accuracy and F-scores of around
                 72\%. This study contributes a refined dataset and
                 provides insights into model performance, highlighting
                 the transformative potential of transformer models in
                 detecting AI-generated content.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Algarni:2025:EED,
  author =       "Sumaiah Algarni and Fathi E. Abd El-Samie",
  title =        "Energy-Efficient Distributed Edge Computing to Assist
                 Dense {Internet of Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "37",
  day =          "15",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010037",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/37",
  abstract =     "The Internet of Things (IoT) represents a rapidly
                 growing field, where billions of intelligent devices
                 are interconnected through the Internet, enabling the
                 seamless sharing of data and resources. These smart
                 devices are typically employed to sense various
                 environmental characteristics, including temperature,
                 motion of objects, and occupancy, and transfer their
                 values to the nearest access points for further
                 analysis. The exponential growth in sensor availability
                 and deployment, powered by recent advances in sensor
                 fabrication, has greatly increased the complexity of
                 IoT network architecture. As the market for these
                 sensors grows, so does the problem of ensuring that IoT
                 networks meet high requirements for network
                 availability, dependability, flexibility, and
                 scalability. Unlike traditional networks, IoT systems
                 must be able to handle massive amounts of data
                 generated by various and frequently-used
                 resource-constrained devices, while ensuring efficient
                 and dependable communication. This puts high
                 constraints on the design of IoT, mainly in terms of
                 the required network availability, reliability,
                 flexibility, and scalability. To this end, this work
                 considers deploying a recent technology of distributed
                 edge computing to enable IoT applications over dense
                 networks with the announced requirements. The proposed
                 network depends on distributed edge computing at two
                 levels: multiple access edge computing and fog
                 computing. The proposed structure increases network
                 scalability, availability, reliability, and
                 scalability. The network model and the energy model of
                 the distributed nodes are introduced. An
                 energy-offloading method is considered to manage IoT
                 data over the network energy, efficiently. The
                 developed network was evaluated using a developed IoT
                 testbed. Heterogeneous evaluation scenarios and metrics
                 were considered. The proposed model achieved a higher
                 energy efficiency by 19\%, resource utilization by
                 54\%, latency efficiency by 86\%, and reduced network
                 congestion by 92\% compared to traditional IoT
                 networks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Spyrou:2025:RAV,
  author =       "Orestis Spyrou and William Hurst and Caspar Krampe",
  title =        "A Reference Architecture for Virtual Human Integration
                 in the Metaverse: Enhancing the Galleries, Libraries,
                 Archives, and Museums ({GLAM}) Sector with {AI}-Driven
                 Experiences",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "36",
  day =          "15",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010036",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/36",
  abstract =     "The digital transformation of the GLAM (galleries,
                 libraries, archives, and museums) sector is a
                 multifaceted process that must address a range of
                 requirements and critical challenges, such as
                 traceability, long-term preservation, and
                 sustainability. The potential of disruptive
                 technologies to revolutionize this sector is
                 significant, offering new ways to overcome these
                 challenges and align with the broader objectives of
                 smart cities. While substantial research has been
                 conducted on the digital transformation of the GLAM
                 sector, many opportunities remain unexplored by various
                 stakeholders. This paper contributes to the field by
                 proposing a reference architecture rooted in a
                 design-oriented approach for developing and
                 implementing processes related to the digital
                 transformation within the context of smart cities. To
                 illustrate the practical application of the proposed
                 architecture, a proof of concept was developed in the
                 form of an immersive digital gallery, which features an
                 AI-powered virtual storyteller. The gallery, built
                 using the open, cross-platform, Unreal, incorporates
                 digitized physical art and a virtual metahuman tutor
                 who guides users through the gallery. This interactive
                 3D environment enables users to explore the space,
                 engage with artworks, and interact with a virtual
                 guide. The environment's performance was evaluated
                 using a keystroke-level model analysis. Key findings
                 from a pilot study involving 10 users showed that, when
                 directed by the AI storyteller, the average time to
                 locate an artwork was 16.5 s, while the average time to
                 ask a question was 15.8 s. By integrating such
                 technologies, the GLAM sector can contribute to the
                 cultural fabric of smart cities, fostering more
                 sustainable, accessible, and interactive public
                 spaces.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Qian:2025:SAI,
  author =       "Mian Qian and Abubakar Ahmad Musa and Milon Biswas and
                 Yifan Guo and Weixian Liao and Wei Yu",
  title =        "Survey of Artificial Intelligence Model Marketplace",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "35",
  day =          "14",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010035",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/35",
  abstract =     "The rapid advancement and widespread adoption of
                 artificial intelligence (AI) across diverse industries,
                 including healthcare, finance, manufacturing, and
                 retail, underscore the transformative potential of AI
                 technologies. This necessitates the development of
                 viable AI model marketplaces that facilitate the
                 development, trading, and sharing of AI models across
                 the pervasive industrial domains to harness and
                 streamline their daily activities. These marketplaces
                 act as centralized hubs, enabling stakeholders such as
                 developers, data owners, brokers, and buyers to
                 collaborate and exchange resources seamlessly. However,
                 existing AI marketplaces often fail to address the
                 demands of modern and next-generation application
                 domains. Limitations in pricing models,
                 standardization, and transparency hinder their
                 efficiency, leading to a lack of scalability and user
                 adoption. This paper aims to target researchers,
                 industry professionals, and policymakers involved in AI
                 development and deployment, providing actionable
                 insights for designing robust, secure, and transparent
                 AI marketplaces. By examining the evolving landscape of
                 AI marketplaces, this paper identifies critical gaps in
                 current practices, such as inadequate pricing schemes,
                 insufficient standardization, and fragmented policy
                 enforcement mechanisms. It further explores the AI
                 model life-cycle, highlighting pricing, trading,
                 tracking, security, and compliance challenges. This
                 detailed analysis is intended for an audience with a
                 foundational understanding of AI systems, marketplaces,
                 and their operational ecosystems. The findings aim to
                 inform stakeholders about the pressing need for
                 innovation and customization in AI marketplaces while
                 emphasizing the importance of balancing efficiency,
                 security, and trust. This paper serves as a blueprint
                 for the development of next-generation AI marketplaces
                 that meet the demands of both current and future
                 application domains, ensuring sustainable growth and
                 widespread adoption.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Boeding:2025:EEF,
  author =       "Matthew Boeding and Michael Hempel and Hamid Sharif",
  title =        "End-to-End Framework for Identifying Vulnerabilities
                 of Operational Technology Protocols and Their
                 Implementations in Industrial {IoT}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "34",
  day =          "14",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010034",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/34",
  abstract =     "The convergence of IT and OT networks has gained
                 significant attention in recent years, facilitated by
                 the increase in distributed computing capabilities, the
                 widespread deployment of Internet of Things devices,
                 and the adoption of Industrial Internet of Things. This
                 convergence has led to a drastic increase in external
                 access capabilities to previously air-gapped industrial
                 systems for process control and monitoring. To meet the
                 need for remote access to system information, protocols
                 designed for the OT space were extended to allow IT
                 networked communications. However, OT protocols often
                 lack the rigor of cybersecurity capabilities that have
                 become a critical characteristic of IT protocols.
                 Furthermore, OT protocol implementations on individual
                 devices can vary in performance, requiring the
                 comprehensive evaluation of a device's reliability and
                 capabilities before installation into a critical
                 infrastructure production network. In this paper, the
                 authors define a framework for identifying
                 vulnerabilities within these protocols and their
                 on-device implementations, utilizing formal modeling,
                 hardware in the loop-driven network emulation, and
                 fully virtual network scenario simulation. Initially,
                 protocol specifications are modeled to identify any
                 vulnerable states within the protocol, leveraging the
                 Construction and Analysis of Distributed Processes
                 (CADP) software (version 2022-d ``Kista'', which was
                 created by Inria, the French Institute for Research in
                 Computer Science and Automation, in France). Device
                 characteristics are then extracted through automated
                 real-time network emulation tests built on the OMNET++
                 framework, and all measured device characteristics are
                 then used as a virtual device representation for
                 network simulation tests within the OMNET++ software
                 (version 6.0.1., a public-source, open-architecture
                 software, initially developed by OpenSim Limited in
                 Budapest, Hungary), to verify the presence of any
                 potential vulnerabilities identified in the formal
                 modeling stage. With this framework, the authors have
                 thus defined an end-to-end process to identify and
                 verify the presence and impact of potential
                 vulnerabilities within a protocol, as shown by the
                 presented results. Furthermore, this framework can test
                 protocol compliance, performance, and security in a
                 controlled environment before deploying devices in live
                 production networks and addressing cybersecurity
                 concerns.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Corona-Fraga:2025:QAM,
  author =       "Pablo Corona-Fraga and Aldo Hernandez-Suarez and
                 Gabriel Sanchez-Perez and Linda Karina Toscano-Medina
                 and Hector Perez-Meana and Jose Portillo-Portillo and
                 Jesus Olivares-Mercado and Luis Javier Garc{\'\i}a
                 Villalba",
  title =        "Question--Answer Methodology for Vulnerable Source
                 Code Review via Prototype-Based Model-Agnostic
                 Meta-Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "33",
  day =          "14",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010033",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/33",
  abstract =     "In cybersecurity, identifying and addressing
                 vulnerabilities in source code is essential for
                 maintaining secure IT environments. Traditional static
                 and dynamic analysis techniques, although widely used,
                 often exhibit high false-positive rates, elevated
                 costs, and limited interpretability. Machine Learning
                 (ML)-based approaches aim to overcome these limitations
                 but encounter challenges related to scalability and
                 adaptability due to their reliance on large labeled
                 datasets and their limited alignment with the
                 requirements of secure development teams. These factors
                 hinder their ability to adapt to rapidly evolving
                 software environments. This study proposes an approach
                 that integrates Prototype-Based Model-Agnostic
                 Meta-Learning(Proto-MAML) with a Question-Answer (QA)
                 framework that leverages the Bidirectional Encoder
                 Representations from Transformers (BERT) model. By
                 employing Few-Shot Learning (FSL), Proto-MAML
                 identifies and mitigates vulnerabilities with minimal
                 data requirements, aligning with the principles of the
                 Secure Development Lifecycle (SDLC) and Development,
                 Security, and Operations (DevSecOps). The QA framework
                 allows developers to query vulnerabilities and receive
                 precise, actionable insights, enhancing its
                 applicability in dynamic environments that require
                 frequent updates and real-time analysis. The model
                 outputs are interpretable, promoting greater
                 transparency in code review processes and enabling
                 efficient resolution of emerging vulnerabilities.
                 Proto-MAML demonstrates strong performance across
                 multiple programming languages, achieving an average
                 precision of 98.49\%, recall of 98.54\%, F1-score of
                 98.78\%, and exact match rate of 98.78\% in PHP, Java,
                 C, and C++.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2025:AEI,
  author =       "Zhiyuan Wang and Yuezhi Zhou",
  title =        "Analysis and Evaluation of {Intel} Software Guard
                 Extension-Based Trusted Execution Environment Usage in
                 Edge Intelligence and {Internet of Things} Scenarios",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "32",
  day =          "13",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010032",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/32",
  abstract =     "With the extensive deployment and application of the
                 Internet of Things (IoT), 5G and 6G technologies and
                 edge intelligence, the volume of data generated by IoT
                 and the number of intelligence applications derived
                 from these data are rapidly growing. However, the
                 absence of effective mechanisms to safeguard the vast
                 data generated by IoT, along with the security and
                 privacy of edge intelligence applications, hinders
                 their further development and adoption. In recent
                 years, Trusted Execution Environment (TEE) has emerged
                 as a promising technology for securing cloud data
                 storage and cloud processing, demonstrating significant
                 potential for ensuring data and application
                 confidentiality in more scenarios. Nevertheless,
                 applying TEE technology to enhance security in IoT and
                 edge intelligence scenarios still presents several
                 challenges. This paper investigates the technical
                 challenges faced by current TEE solutions, such as
                 performance overhead and I/O security issues, in the
                 context of the resource constraints and data mobility
                 that are inherent to IoT and edge intelligence
                 applications. Using Intel Software Guard Extensions
                 (SGX) technology as a case study, this paper validates
                 these challenges through extensive experiments. The
                 results provide critical assessments and analyses
                 essential for advancing the development and usage of
                 TEE in IoT and edge intelligence scenarios.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ferone:2025:EBT,
  author =       "Alessio Ferone and Stefano Verrilli",
  title =        "Exploiting Blockchain Technology for Enhancing Digital
                 Twins' Security and Transparency",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "31",
  day =          "13",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010031",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/31",
  abstract =     "Blockchain technology has been applied in a wide range
                 of domains and has seen major developments in the last
                 years, notably when integrated with other emerging
                 technologies. In this paper, we focus on the
                 integration of blockchain and digital twins with the
                 aim of enhancing the capabilities of both technologies.
                 In particular, we demonstrate how blockchain can
                 improve critical aspects of the security and
                 transparency of digital twins by analyzing a real-world
                 scenario and evaluating produced experimental data.
                 This research identifies and addresses critical
                 vulnerabilities in digital twins, particularly data
                 integrity and transparency, through blockchain-based
                 validation mechanisms and smart-contract integration.
                 Various blockchain-related and digital twin-related
                 technologies are employed to enable the repeatability
                 of the suggested approach. Additionally, an in-depth
                 analysis of such integration is provided to facilitate
                 a symbiotic relationship between these technologies by
                 addressing key challenges, such as scalability,
                 interoperability, and performance, along with viable
                 solutions that could advance their co-evolution in both
                 academic research and industrial applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Dritsas:2025:SCI,
  author =       "Elias Dritsas and Maria Trigka",
  title =        "A Survey on Cybersecurity in {IoT}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "30",
  day =          "11",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010030",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/30",
  abstract =     "The proliferation of the Internet of Things (IoT) has
                 transformed the digital landscape, enabling a vast
                 array of interconnected devices to communicate and
                 share data seamlessly. However, the rapid expansion of
                 IoT networks has also introduced significant
                 cybersecurity challenges. This paper presents a
                 comprehensive survey of cybersecurity in the IoT
                 ecosystem, examining the current state of research,
                 identifying critical security vulnerabilities, and
                 exploring advanced strategies for mitigating threats.
                 The survey covers various facets of IoT security,
                 including device authentication, data integrity,
                 privacy, network security, and the emerging role of
                 artificial intelligence (AI) in bolstering
                 cybersecurity defenses. By synthesizing existing
                 research and highlighting ongoing challenges, this
                 survey aims to provide a holistic understanding of IoT
                 cybersecurity and to guide future research endeavors.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bono:2025:WAA,
  author =       "Francesco Morgan Bono and Alessio Polinelli and Luca
                 Radicioni and Lorenzo Benedetti and Francesco
                 Castelli-Dezza and Simone Cinquemani and Marco
                 Belloli",
  title =        "Wireless Accelerometer Architecture for Bridge {SHM}:
                 From Sensor Design to System Deployment",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "29",
  day =          "10",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010029",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/29",
  abstract =     "This paper introduces a framework to perform
                 operational modal analysis (OMA) for structural health
                 monitoring (SHM) by presenting the development and
                 validation of a low-power, solar-powered wireless
                 sensor network (WSN) tailored for bridge structures.
                 The system integrates accelerometers and temperature
                 sensors for dynamic structural assessment, all
                 interconnected through the energy-efficient message
                 queuing telemetry transport (MQTT) messaging protocol.
                 Moreover, it delves into the details of sensor
                 selection, calibration, and the design considerations
                 necessary to address the unique challenges associated
                 with bridge structures. Special attention is given to
                 the solar-powered aspect, allowing for extended
                 deployment periods without the need for frequent
                 maintenance or battery replacements. To validate the
                 proposed system, a comprehensive field deployment was
                 conducted on an actual bridge structure. The collected
                 data were transmitted through MQTT messages and
                 analyzed by means of OMA. Comparative studies with
                 traditional wired systems underscore the advantages of
                 the solar-powered wireless solution in terms of
                 sustainability, scalability, and ease of deployment.
                 Results from the validation phase demonstrate the
                 system's capability to provide accurate and real-time
                 data needed to assess the health state of the monitored
                 asset. This paper concludes with insights into the
                 practical implications of adopting such a solar-powered
                 WSN, emphasizing its potential to revolutionize bridge
                 health monitoring by offering a cost-effective and
                 energy-efficient solution for long-term infrastructure
                 resilience.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Roumeliotis:2025:FND,
  author =       "Konstantinos I. Roumeliotis and Nikolaos D. Tselikas
                 and Dimitrios K. Nasiopoulos",
  title =        "Fake News Detection and Classification: a Comparative
                 Study of Convolutional Neural Networks, Large Language
                 Models, and Natural Language Processing Models",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "28",
  day =          "9",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010028",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/28",
  abstract =     "In an era where fake news detection has become a
                 pressing issue due to its profound impacts on public
                 opinion, democracy, and social trust, accurately
                 identifying and classifying false information is a
                 critical challenge. In this study, the effectiveness is
                 investigated of advanced machine learning models ---
                 convolutional neural networks (CNNs), bidirectional
                 encoder representations from transformers (BERT), and
                 generative pre-trained transformers (GPTs) --- for
                 robust fake news classification. Each model brings
                 unique strengths to the task, from CNNs' pattern
                 recognition capabilities to BERT and GPTs' contextual
                 understanding in the embedding space. Our results
                 demonstrate that the fine-tuned GPT-4 Omni models
                 achieve 98.6\% accuracy, significantly outperforming
                 traditional models like CNNs, which achieved only
                 58.6\%. Notably, the smaller GPT-4o mini model
                 performed comparably to its larger counterpart,
                 highlighting the cost-effectiveness of smaller models
                 for specialized tasks. These findings emphasize the
                 importance of fine-tuning large language models (LLMs)
                 to optimize the performance for complex tasks such as
                 fake news classifier development, where capturing
                 subtle contextual relationships in text is crucial.
                 However, challenges such as computational costs and
                 suboptimal outcomes in zero-shot classification
                 persist, particularly when distinguishing fake content
                 from legitimate information. By highlighting the
                 practical application of fine-tuned LLMs and exploring
                 the potential of few-shot learning for fake news
                 detection, this research provides valuable insights for
                 news organizations seeking to implement scalable and
                 accurate solutions. Ultimately, this work contributes
                 to fostering transparency and integrity in journalism
                 through innovative AI-driven methods for fake news
                 classification and automated fake news classifier
                 systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mishra:2025:IWF,
  author =       "Lalan Mishra and Naima Kaabouch",
  title =        "Impact of Weather Factors on Unmanned Aerial Vehicles'
                 Wireless Communications",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "27",
  day =          "8",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010027",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/27",
  abstract =     "As the applications of unmanned aerial vehicles (UAV)
                 expand, reliable communication between UAVs and ground
                 control stations is crucial for successful missions.
                 However, adverse weather conditions caused by
                 atmospheric gases, clouds, fog, rain, and turbulence
                 pose challenges by degrading communication signals.
                 Although, some recent studies have explored the nature
                 of signal attenuation caused by atmospheric weather
                 variations, studies that compare the attenuation from
                 various weather conditions and analyze the effect on
                 available bandwidth are missing. This work aimed to
                 address this research gap by thoroughly investigating
                 the impact of atmospheric weather conditions on the
                 bandwidth available for UAV communications.
                 Quantitative and qualitative performance analyses were
                 performed for various weather conditions using metrics
                 such as attenuation and the bit error rate of the
                 received signals associated with different modulation
                 schemes and frequencies, using a linearly segmented
                 attenuation model. The results indicate that
                 atmospheric gases and clouds/fog affect wireless signal
                 propagation; however, the effect of rain on the
                 propagation distances and operating frequencies
                 considered in this study was the most severe. Based on
                 the influence of power transmission, operating
                 frequency, modulation schemes, distance, and adverse
                 weather conditions on the bit error rate and bandwidth
                 suboptimization, we propose an algorithm to select the
                 maximum operating frequency for reliable UAV link
                 operation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kalodanis:2025:HRA,
  author =       "Konstantinos Kalodanis and Panagiotis Rizomiliotis and
                 Georgios Feretzakis and Charalampos Papapavlou and
                 Dimosthenis Anagnostopoulos",
  title =        "High-Risk {AI} Systems --- Lie Detection Application",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "26",
  day =          "8",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010026",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/26",
  abstract =     "Integrating artificial intelligence into border
                 control systems may help to strengthen security and
                 make operations more efficient. For example, the
                 emerging application of artificial intelligence for lie
                 detection when inspecting passengers presents
                 significant opportunities for future implementation.
                 However, as it makes use of technology that is
                 associated with artificial intelligence, the system is
                 classified as high risk, in accordance with the EU AI
                 Act and, therefore, must adhere to rigorous regulatory
                 requirements to mitigate potential risks. This
                 manuscript distinctly amalgamates the technical,
                 ethical, and legal aspects, thereby offering an
                 extensive examination of the AI-based lie detection
                 systems utilized in border security. This academic
                 paper is uniquely set apart from others because it
                 undertakes a thorough investigation into the
                 categorization of these emerging technologies in terms
                 of the regulatory framework established by the EU AI
                 Act, which classifies them as high risk. It further
                 makes an assessment of practical case studies,
                 including notable examples such as iBorderCtrl and
                 AVATAR. This in-depth analysis seeks to emphasize not
                 only the enormous challenges ahead for practitioners
                 but also the progress made in this emerging field of
                 study. Furthermore, it seeks to investigate threats,
                 vulnerabilities, and privacy concerns associated with
                 AI, while providing security controls to address
                 difficulties related to lie detection. Finally, we
                 propose a framework that encompasses the EU AI Act's
                 principles and serves as a foundation for future
                 approaches and research projects. By analyzing current
                 methodologies and considering future directions, the
                 paper aims to provide a comprehensive understanding of
                 the viability and consequences of deploying AI lie
                 detection capabilities in border control.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mahmoud:2025:XIE,
  author =       "Maiada M. Mahmoud and Yasser Omar Youssef and Ayman A.
                 Abdel-Hamid",
  title =        "{XI2S-IDS}: an Explainable Intelligent 2-Stage
                 Intrusion Detection System",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "25",
  day =          "8",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010025",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/25",
  abstract =     "The rapid evolution of technologies such as the
                 Internet of Things (IoT), 5G, and cloud computing has
                 exponentially increased the complexity of cyber
                 attacks. Modern Intrusion Detection Systems (IDSs) must
                 be capable of identifying not only frequent, well-known
                 attacks but also low-frequency, subtle intrusions that
                 are often missed by traditional systems. The challenge
                 is further compounded by the fact that most IDS rely on
                 black-box machine learning (ML) and deep learning (DL)
                 models, making it difficult for security teams to
                 interpret their decisions. This lack of transparency is
                 particularly problematic in environments where quick
                 and informed responses are crucial. To address these
                 challenges, we introduce the XI2S-IDS framework --- an
                 Explainable, Intelligent 2-Stage Intrusion Detection
                 System. The XI2S-IDS framework uniquely combines a
                 two-stage approach with SHAP-based explanations,
                 offering improved detection and interpretability for
                 low-frequency attacks. Binary classification is
                 conducted in the first stage followed by multi-class
                 classification in the second stage. By leveraging SHAP
                 values, XI2S-IDS enhances transparency in
                 decision-making, allowing security analysts to gain
                 clear insights into feature importance and the model's
                 rationale. Experiments conducted on the UNSW-NB15 and
                 CICIDS2017 datasets demonstrate significant
                 improvements in detection performance, with a notable
                 reduction in false negative rates for low-frequency
                 attacks, while maintaining high precision, recall, and
                 F1-scores.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kim:2025:VAD,
  author =       "Daegyeom Kim and Sehwan O and Younghoon Ban and
                 Jungsoo Park and Kyungho Joo and Haehyun Cho",
  title =        "{Ventinel}: Automated Detection of {Android} Vishing
                 Apps Using Optical Character Recognition",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "24",
  day =          "7",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010024",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/unix.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/24",
  abstract =     "Vishing, a blend of ``voice'' and ``phishing'', has
                 evolved to include techniques like Call Redirection and
                 Display Overlay Attacks, causing significant financial
                 losses. Existing research has largely focused on user
                 behavior and awareness, leaving gaps in addressing
                 attacks originating from vishing applications. In this
                 work, we present Ventinel, an Android-based defense
                 system designed to detect these attacks without
                 requiring OS modifications. Ventinel employs Optical
                 Character Recognition (OCR) to compare phone numbers
                 during calls, effectively preventing Call Redirection
                 and Display Overlay Attacks. Additionally, it
                 safeguards against Duplicated Contacts Attacks by
                 cross-referencing call logs and SMS records. Ventinel
                 achieves 100\% detection accuracy, surpassing
                 commercial applications, and operates with minimal data
                 collection to ensure user privacy. We also describe
                 malicious API behavior and demonstrate that the same
                 behavior is possible for API levels 29 and higher.
                 Furthermore, we analyze the limitations of existing
                 solutions and propose new attack and defense
                 strategies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Marevac:2025:FDD,
  author =       "Elmin Marevac and Esad Kadusi{\'c} and Natasa
                 Zivi{\'c} and Nevzudin Buzadija and Samir Lemes",
  title =        "Framework Design for the Dynamic Reconfiguration of
                 {IoT}-Enabled Embedded Systems and ``On-the-Fly''
                 Code Execution",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "23",
  day =          "7",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010023",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/23",
  abstract =     "Embedded systems, particularly when integrated into
                 the Internet of Things (IoT) landscape, are critical
                 for projects requiring robust, energy-efficient
                 interfaces to collect real-time data from the
                 environment. As these systems become complex, the need
                 for dynamic reconfiguration, improved availability, and
                 stability becomes increasingly important. This paper
                 presents the design of a framework architecture that
                 supports dynamic reconfiguration and ``on-the-fly''
                 code execution in IoT-enabled embedded systems,
                 including a virtual machine capable of hot reloads,
                 ensuring system availability even during configuration
                 updates. A ``hardware-in-the-loop'' workflow manages
                 communication between the embedded components, while
                 low-level coding constraints are accessible through an
                 additional abstraction layer, with examples such as
                 MicroPython or Lua. The study results demonstrate the
                 VM's ability to handle serialization and
                 deserialization with minimal impact on system
                 performance, even under high workloads, with
                 serialization having a median time of 160 microseconds
                 and deserialization having a median of 964
                 microseconds. Both processes were fast and
                 resource-efficient under normal conditions, supporting
                 real-time updates with occasional outliers, suggesting
                 room for optimization and also highlighting the
                 advantages of VM-based firmware update methods, which
                 outperform traditional approaches like Serial and OTA
                 (Over-the-Air, the ability to update or configure
                 firmware, software, or devices via wireless connection)
                 updates by achieving lower latency and greater
                 consistency. With these promising results, however,
                 challenges like occasional deserialization time
                 outliers and the need for optimization in memory
                 management and network protocols remain for future
                 work. This study also provides a comparative analysis
                 of currently available commercial solutions,
                 highlighting their strengths and weaknesses.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fernando:2025:EFC,
  author =       "Niroshinie Fernando and Samir Shrestha and Seng W.
                 Loke and Kevin Lee",
  title =        "On Edge-Fog-Cloud Collaboration and Reaping Its
                 Benefits: a Heterogeneous Multi-Tier Edge Computing
                 Architecture",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "22",
  day =          "7",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010022",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/22",
  abstract =     "Edge, fog, and cloud computing provide complementary
                 capabilities to enable distributed processing of IoT
                 data. This requires offloading mechanisms,
                 decision-making mechanisms, support for the dynamic
                 availability of resources, and the cooperation of
                 available nodes. This paper proposes a novel 3-tier
                 architecture that integrates edge, fog, and cloud
                 computing to harness their collective strengths,
                 facilitating optimised data processing across these
                 tiers. Our approach optimises performance, reducing
                 energy consumption, and lowers costs. We evaluate our
                 architecture through a series of experiments conducted
                 on a purpose-built testbed. The results demonstrate
                 significant improvements, with speedups of up to 7.5
                 times and energy savings reaching 80\%, underlining the
                 effectiveness and practical benefits of our cooperative
                 edge-fog-cloud model in supporting the dynamic
                 computational needs of IoT ecosystems. We argue that a
                 multi-tier (e.g., edge-fog-cloud) dynamic task
                 offloading and management of heterogeneous devices will
                 be key to flexible edge computing, and that the
                 advantage of task relocation and offloading is not
                 straightforward but depends on the configuration of
                 devices and relative device capabilities.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Pazakou:2025:CVR,
  author =       "Antonia-Maria Pazakou and Stylianos Mystakidis and
                 Ioannis Kazanidis",
  title =        "Collaboration in a Virtual Reality Serious Escape Room
                 in the Metaverse Improves Academic Performance and
                 Learners' Experiences",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "21",
  day =          "6",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010021",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/21",
  abstract =     "The evolving potential of virtual reality and the
                 Metaverse to create immersive, engaging learning
                 experiences and of digital escape room games to provide
                 opportunities for active, autonomous, personalised
                 learning has brought both to the forefront for
                 educators seeking to transform traditional educational
                 settings. This study investigated the impact of
                 collaboration within a virtual reality serious escape
                 room game in the Metaverse that was designed for
                 English as a Foreign Language (EFL) learners to explore
                 how this approach influences their academic performance
                 and overall learning experience. A comparative research
                 approach was adopted using twenty (n = 20) adult
                 learners divided into two equal-sized groups; the
                 experimental group completed the virtual reality escape
                 room in pairs, while the control group completed it
                 individually. Mixed methods were employed, utilising a
                 pre- and post-test to measure academic performance, as
                 well as a questionnaire and two focus groups to
                 evaluate participants' learning experiences. Results
                 indicated a trend of learners working collaboratively
                 showing better learning outcomes and experience,
                 offering valuable insights regarding the integration of
                 serious Metaverse games in language-focused educational
                 contexts.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sharma:2025:CII,
  author =       "Aryan Sharma and Haoming Wang and Deepak Mishra and
                 Aruna Seneviratne",
  title =        "Conservative Interference Injection to Minimize
                 {Wi-Fi} Sensing Privacy Risks and Bandwidth Loss",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "1",
  pages =        "20",
  day =          "6",
  month =        jan,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17010020",
  ISSN =         "1999-5903",
  bibdate =      "Tue Feb 4 07:04:57 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/1/20",
  abstract =     "With the impending integration of sensing capabilities
                 into new wireless standards such as 6G and 802.11 bf,
                 there is a growing threat to public privacy. Recent
                 studies have revealed that even small-scale activities,
                 like keyboard typing, can be sensed by attackers using
                 Wi-Fi Channel State Information (CSI) as these devices
                 become more common in commercial spaces. This paper
                 aims to model the minimum CSI data rate required to
                 sense activities in the channel and quantifies the
                 detection accuracy of WiFi-based keystroke recognition
                 in relation to the CSI sensing data rate. Our
                 experimental findings using commercial-off-the-shelf
                 hardware suggest that interference can be used as a
                 defence strategy to degrade the CSI data rate and
                 prevent undesirable Wi-Fi sensing attacks. To achieve a
                 reduced data rate, we propose an extension to Bianchi's
                 model of CSMA/CA systems and establish a new
                 mathematical relationship between channel contention
                 and the available CSI. This proposed relationship was
                 empirically verified, and our contention-based defence
                 strategy was experimentally validated. Experiments show
                 that our contention-based defence strategy increases
                 the chances of evading undesired WiFi-based keystroke
                 recognition by around 70\%. By leveraging prior work
                 that shows a degradation in CSI quality with lower
                 transmission rates, we show that conservative
                 interference injection can sufficiently reduce sensing
                 accuracy whilst maintaining channel bandwidth.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Prenestino:2025:RSD,
  author =       "Francesco Bruni Prenestino and Enrico Barbierato and
                 Alice Gatti",
  title =        "Robust Synthetic Data Generation for Sequential
                 Financial Models Using Hybrid Variational
                 Autoencoder--{Markov} Chain {Monte Carlo}
                 Architectures",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "95",
  day =          "19",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020095",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/95",
  abstract =     "Generating high-quality synthetic data is essential
                 for advancing machine learning applications in
                 financial time series, where data scarcity and privacy
                 concerns often pose significant challenges. This study
                 proposes a novel hybrid architecture that combines
                 variational autoencoders (VAEs) with Markov Chain Monte
                 Carlo (MCMC) sampling to enhance the generation of
                 robust synthetic sequential data. The model leverages
                 Gated Recurrent Unit (GRU) layers for capturing
                 long-term temporal dependencies and MCMC sampling for
                 effective latent space exploration, ensuring high
                 variability and accuracy. Experimental evaluations on
                 datasets of Google, Tesla, and Nestl{\'e} stock prices
                 demonstrate the model's superior performance in
                 preserving statistical and temporal patterns, as
                 validated by quantitative metrics (discriminative and
                 predictive scores), statistical tests
                 (Kolmogorov--Smirnov), and t-Distributed Stochastic
                 Neighbour Embedding (t-SNE) visualisations. The
                 experiments reveal the model's scalability, maintaining
                 high fidelity even under augmented dataset sizes and
                 missing data scenarios. These findings position the
                 proposed framework as a computationally efficient and
                 structurally simple alternative to Generative
                 Adversarial Network (GAN)-based methods, suitable for
                 real-world applications in data-driven financial
                 modelling.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lakehal:2025:CCA,
  author =       "Abderrahim Lakehal and Adel Alti and Boubakeur
                 Annane",
  title =        "{CORES}: Context-Aware Emotion-Driven Recommendation
                 System-Based {LLM} to Improve Virtual Shopping
                 Experiences",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "94",
  day =          "18",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020094",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/94",
  abstract =     "In today's business landscape, artificial intelligence
                 (AI) plays a pivotal role in shopping processes and
                 customization. As the demand for customization grows,
                 virtual reality (VR) emerges as an innovative solution
                 to improve users' perception and decision making in
                 virtual shopping experiences (VSEs). Despite its
                 potential, limited research has explored the
                 integration of contextual information and emotions in
                 VR to deliver effective product recommendations. This
                 paper presents CORES (context-aware emotion-driven
                 recommendation system), a novel approach designed to
                 enrich users' experiences and to support decision
                 making in VR. CORES combines advanced large language
                 models (LLMs) and embedding-based context-aware
                 recommendation strategies to provide customized
                 products. Therefore, emotions are collected from social
                 platforms, and relevant contextual information is
                 matched to enable effective recommendation.
                 Additionally, CORES leverages transformers and
                 retrieval-augmented generation (RAG) capabilities to
                 explain recommended items, facilitate VR visualization,
                 and generate insights using various prompt templates.
                 CORES is applied to a VR shop of different items. An
                 empirical study validates the efficiency and accuracy
                 of this approach, achieving a significant average
                 accuracy of 97\% and an acceptable response time of
                 0.3267s in dynamic shopping scenarios.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Qawasmeh:2025:BFL,
  author =       "Saif Al-Dean Qawasmeh and Ali Abdullah S. AlQahtani",
  title =        "Beyond Firewall: Leveraging Machine Learning for
                 Real-Time Insider Threats Identification and User
                 Profiling",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "93",
  day =          "18",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020093",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/93",
  abstract =     "Insider threats pose a significant challenge to
                 organizational cybersecurity, often leading to
                 catastrophic financial and reputational damages.
                 Traditional tools such as firewalls and antivirus
                 systems lack the sophistication needed to detect and
                 mitigate these threats in real time. This paper
                 introduces a machine learning-based system that
                 integrates real-time anomaly detection with dynamic
                 user profiling, enabling the classification of
                 employees into categories of low, medium, and high
                 risk. The system was validated using a synthetic
                 dataset, achieving exceptional accuracy across machine
                 learning models, with XGBoost emerging as the most
                 effective.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Adda:2025:ISM,
  author =       "Mo Adda and Nancy Scheidt",
  title =        "Investigation of Smart Machines with {DNAs} in
                 {SpiderNet}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "92",
  day =          "17",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020092",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/92",
  abstract =     "The advancement of Internet of Things (IoT), robots,
                 drones, and vehicles signifies ongoing progress,
                 accompanied by increasing complexities and challenges
                 in forensic investigations. Globally, investigators
                 encounter obstacles when extracting evidence from these
                 vast landscapes, which include diverse devices,
                 networks, and cloud environments. Of particular concern
                 is the process of evidence collection, especially
                 regarding fingerprints and facial recognition within
                 the realm of vehicle forensics. Moreover, ensuring the
                 integrity of forensic evidence is a critical issue, as
                 it is vulnerable to attacks targeting data centres and
                 server farms. Mitigating these challenges, along with
                 addressing evidence mobility, presents additional
                 complexities. This paper introduces a groundbreaking
                 infrastructure known as SpiderNet, which is based on
                 cloud computing principles. We will illustrate how this
                 architecture facilitates the identification of devices,
                 secures the integrity of evidence both at its source
                 and during transit, and enables investigations into
                 individuals involved in criminal activities. Through
                 case studies, we will demonstrate the potential of
                 SpiderNet to assist law enforcement agencies in
                 addressing crimes perpetrated within IoT
                 environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zolfaghari:2025:BSS,
  author =       "Behrouz Zolfaghari and Jacob Krzciok and Khodakhast
                 Bibak",
  title =        "From Bottom of Sea to Space: Quo Vadis {IoT}? {So}
                 What About Security?",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "91",
  day =          "17",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020091",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/91",
  abstract =     "In recent years, we have witnessed the era of IoT.
                 Extensions of the IoT are found almost everywhere in
                 the modern world: under the ground, on the ground,
                 under the sea, in the sky, and in space. Such a rapid
                 proliferation has given rise to a variety of
                 requirements and challenges. As suggested by the recent
                 literature, security is the most critical challenge in
                 this area. A comprehensive survey in this area can pave
                 the way for further research by highlighting current
                 trends and shedding light on less-studied aspects of
                 the area. This paper provides a comprehensive review of
                 the current state of research on IoT extensions, with a
                 focus on security. We start with reviewing existing
                 relevant surveys, noting their shortcomings. We
                 highlight the lack of inclusiveness in existing
                 surveys. Moreover, we show that these surveys do not
                 look closely at security challenges and fail to develop
                 a taxonomy or a solid future roadmap. Then, we provide
                 an overview of the security challenges and mechanisms
                 of IoT extensions. We proceed to develop a taxonomy of
                 these extensions with a focus on security. Lastly, we
                 discuss what the future may hold for IoT extensions,
                 given the role of artificial intelligence in IoT and
                 the advancements of artificial intelligence on the
                 horizon.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Paolone:2025:SLS,
  author =       "Gaetanino Paolone and Romolo Paesani and Francesco
                 Pilotti and Jacopo Camplone and Andrea Piazza and
                 Paolino {Di Felice}",
  title =        "Smart Lighting Systems: State-of-the-Art in the
                 Adoption of the {EdgeML} Computing Paradigm",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "90",
  day =          "14",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020090",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/90",
  abstract =     "Lighting Systems (LSs) play a fundamental role in
                 almost every aspect of human activities. Since the
                 advent of lights, both academia and industry have been
                 engaged in raising the quality of the service offered
                 by these systems. The advent of Light Emitting Diode
                 (LED) lighting represented a giant step forward for
                 such systems in terms of light quality and energy
                 saving. To further raise the quality of the services
                 offered by LSs, increase the range of services they
                 offer, while at the same time consolidating their
                 reliability and security, we see the need to explore
                 the contribution that can be derived from the use of
                 the Artificial Intelligence of Things (AIoT) emerging
                 technology. This paper systematically reviews and
                 compares the state-of-the-art with regard to the impact
                 of the AIoT in the smart LS domain. The study reveals
                 that the field is relatively new, in fact the first
                 works date back to 2019. In addition to that, the
                 review delves into recent research works focusing on
                 the usage of Machine Learning (ML) algorithms in an
                 edge Cloud-based computing architecture. Our findings
                 reveal that this topic is almost unexplored. Finally,
                 the survey sheds light on future research opportunities
                 that can overcome the current gaps, with the final aim
                 of guiding scholars and practitioners in advancing the
                 field of smart LSs. The study is reported in full
                 detail, so it can be replicated.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sahnoun:2025:HST,
  author =       "Salwa Sahnoun and Mahdi Mnif and Bilel Ghoul and
                 Mohamed Jemal and Ahmed Fakhfakh and Olfa Kanoun",
  title =        "Hybrid Solution Through Systematic Electrical
                 Impedance Tomography Data Reduction and {CNN}
                 Compression for Efficient Hand Gesture Recognition on
                 Resource-Constrained {IoT} Devices",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "89",
  day =          "14",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020089",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/89",
  abstract =     "The rapid advancement of edge computing and Tiny
                 Machine Learning (TinyML) has created new opportunities
                 for deploying intelligence in resource-constrained
                 environments. With the growing demand for intelligent
                 Internet of Things (IoT) devices that can efficiently
                 process complex data in real-time, there is an urgent
                 need for innovative optimisation techniques that
                 overcome the limitations of IoT devices and enable
                 accurate and efficient computations. This study
                 investigates a novel approach to optimising
                 Convolutional Neural Network (CNN) models for Hand
                 Gesture Recognition (HGR) based on Electrical Impedance
                 Tomography (EIT), which requires complex signal
                 processing, energy efficiency, and real-time
                 processing, by simultaneously reducing input complexity
                 and using advanced model compression techniques. By
                 systematically reducing and halving the input
                 complexity of a 1D CNN from 40 to 20 Boundary Voltages
                 (BVs) and applying an innovative compression method, we
                 achieved remarkable model size reductions of 91.75\%
                 and 97.49\% for 40 and 20 BVs EIT inputs, respectively.
                 Additionally, the Floating-Point operations (FLOPs) are
                 significantly reduced, by more than 99\% in both cases.
                 These reductions have been achieved with a minimal loss
                 of accuracy, maintaining the performance of 97.22\% and
                 94.44\% for 40 and 20 BVs inputs, respectively. The
                 most significant result is the 20 BVs compressed model.
                 In fact, at only 8.73 kB and a remarkable 94.44\%
                 accuracy, our model demonstrates the potential of
                 intelligent design strategies in creating
                 ultra-lightweight, high-performance CNN-based solutions
                 for resource-constrained devices with near-full
                 performance capabilities specifically for the case of
                 HGR based on EIT inputs.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alshdadi:2025:FDL,
  author =       "Abdulrahman A. Alshdadi and Abdulwahab Ali Almazroi
                 and Nasir Ayub and Miltiadis D. Lytras and Eesa
                 Alsolami and Faisal S. Alsubaei and Riad Alharbey",
  title =        "Federated Deep Learning for Scalable and
                 Privacy-Preserving Distributed Denial-of-Service Attack
                 Detection in {Internet of Things} Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "88",
  day =          "13",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020088",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/88",
  abstract =     "Industry-wide IoT networks have altered operations and
                 increased vulnerabilities, notably DDoS attacks. IoT
                 systems are decentralised. Therefore, these attacks
                 flood networks with malicious traffic, creating
                 interruptions, financial losses, and availability
                 issues. We need scalable, privacy-preserving, and
                 resource-efficient IoT intrusion detection algorithms
                 to solve this essential problem. This paper presents a
                 Federated-Learning (FL) framework using ResVGG-SwinNet,
                 a hybrid deep-learning architecture, for multi-label
                 DDoS attack detection. ResNet improves feature
                 extraction, VGGNet optimises feature refining, and
                 Swin-Transformer captures contextual dependencies,
                 making the model sensitive to complicated attack
                 patterns across varied network circumstances. Using the
                 FL framework, decentralised training protects data
                 privacy and scales and adapts across diverse IoT
                 contexts. New preprocessing methods like Dynamic
                 Proportional Class Adjustment (DPCA) and Dual Adaptive
                 Selector (DAS) for feature optimisation improve system
                 efficiency and accuracy. The model performed well on
                 CIC-DDoS2019, UNSW-NB15, and IoT23 datasets, with
                 99.0\% accuracy, 2.5\% false alert rate, and 99.3\%
                 AUC. With a 93.0\% optimisation efficiency score, the
                 system balances computational needs with robust
                 detection. With advanced deep-learning models, FL
                 provides a scalable, safe, and effective DDoS detection
                 solution that overcomes significant shortcomings in
                 current systems. The framework protects IoT networks
                 from growing cyber threats and provides a complete
                 approach for current IoT-driven ecosystems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hu:2025:REE,
  author =       "Zhanyi Hu and Tianchen Zhou and Bingzhe Wu and Cen
                 Chen and Yanhao Wang",
  title =        "A Review and Experimental Evaluation on Split
                 Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "87",
  day =          "13",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020087",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/87",
  abstract =     "Training deep learning models collaboratively on
                 decentralized edge devices has attracted significant
                 attention recently. The two most prominent schemes for
                 this problem are Federated Learning (FL) and Split
                 Learning (SL). Although there have been several surveys
                 and experimental evaluations for FL in the literature,
                 SL paradigms have not yet been systematically reviewed
                 and evaluated. Due to the diversity of SL paradigms in
                 terms of label sharing, model aggregation, cut layer
                 selection, etc., the lack of a systematic survey makes
                 it difficult to fairly and conveniently compare the
                 performance of different SL paradigms. To address the
                 above issue, in this paper, we first provide a
                 comprehensive review for existing SL paradigms. Then,
                 we implement several typical SL paradigms and perform
                 extensive experiments to compare their performance in
                 different scenarios on four widely used datasets. The
                 experimental results provide extensive engineering
                 advice and research insights for SL paradigms. We hope
                 that our work can facilitate future research on SL by
                 establishing a fair and accessible benchmark for SL
                 performance evaluation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Asensio-Garriga:2025:ZFA,
  author =       "Rodrigo Asensio-Garriga and Alejandro Molina Zarca and
                 Jordi Ortiz and Ana Hermosilla and Hugo Ram{\'o}n
                 Pascual and Antonio Pastor and Antonio Skarmeta",
  title =        "{ZSM} Framework for Autonomous Security Service Level
                 Agreement Life-Cycle Management in {B5G} Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "86",
  day =          "12",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020086",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/86",
  abstract =     "In the rapidly evolving landscape of
                 telecommunications, the integration of commercial 5G
                 solutions and the rise of edge computing have reshaped
                 service delivery, emphasizing the customization of
                 requirements through network slices. However, the
                 heterogeneity of devices and technologies in 5G and
                 beyond networks poses significant challenges,
                 particularly in terms of security management.
                 Addressing this complexity, our work adopts the
                 Zero-touch network and Service Management (ZSM)
                 reference architecture to enable end-to-end automation
                 of security and service management in Beyond 5G
                 networks. This paper introduces the ZSM-based
                 framework, which harnesses software-defined networking,
                 network function virtualization, end-to-end slicing,
                 and orchestration paradigms to autonomously enforce and
                 preserve security service level agreements (SSLAs)
                 across multiple domains that make up a 5G network. The
                 framework autonomously manages end-to-end security
                 slices through intent-driven closed loops at various
                 logical levels, ensuring compliance with ETSI
                 end-to-end network slice management standards for 5G
                 communication services. The paper elaborates with an
                 SSLA-triggered use case comprising two phases:
                 proactive, wherein the framework deploys and configures
                 an end-to-end security slice tailored to the security
                 service level agreement specifications, and reactive,
                 where machine learning-trained security mechanisms
                 autonomously detect and mitigate novel beyond 5G
                 attacks exploiting open-sourced 5G core threat vectors.
                 Finally, the results of the implementation and
                 validation are presented, demonstrating the practical
                 application of this research. Interestingly, these
                 research results have been integrated into the ETSI ZSM
                 Proof of Concept \#6: 'Security SLA Assurance in 5G
                 Network Slices', highlighting the relevance and impact
                 of the study in the real world.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Baciu:2025:STM,
  author =       "Vlad-Eusebiu Baciu and An Braeken and Laurent Segers
                 and Bruno da Silva",
  title =        "Secure Tiny Machine Learning on Edge Devices: a
                 Lightweight Dual Attestation Mechanism for Machine
                 Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "85",
  day =          "12",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020085",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/85",
  abstract =     "Emerging edge devices are transforming the Internet of
                 Things (IoT) by enabling more responsive and efficient
                 interactions between physical objects and digital
                 networks. These devices support diverse applications,
                 from health-monitoring wearables to environmental
                 sensors, by moving data processing closer to the
                 source. Traditional IoT systems rely heavily on
                 centralized servers, but advances in edge computing and
                 Tiny Machine Learning (TinyML) now allow for on-device
                 processing, enhancing battery efficiency and reducing
                 latency. While this shift improves privacy, the
                 distributed nature of edge devices introduces new
                 security challenges, particularly regarding TinyML
                 models, which are designed for low-power environments
                 and may be vulnerable to tampering or unauthorized
                 access. Since other IoT entities depend on the data
                 generated by these models, ensuring trust in the
                 devices is essential. To address this, we propose a
                 lightweight dual attestation mechanism utilizing Entity
                 Attestation Tokens (EATs) to validate the device and ML
                 model integrity. This approach enhances security by
                 enabling verified device-to-device communication,
                 supports seamless integration with secure cloud
                 services, and allows for flexible, authorized ML model
                 updates, meeting modern IoT systems' scalability and
                 compliance needs.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Cuzzocrea:2025:CDP,
  author =       "Alfredo Cuzzocrea and Mst Shapna Akter and Hossain
                 Shahriar and Pablo Garc{\'\i}a Bringas",
  title =        "Cyberbullying Detection, Prevention, and Analysis on
                 Social Media via Trustable {LSTM}-Autoencoder Networks
                 over Synthetic Data: The {TLA-NET} Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "84",
  day =          "12",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020084",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/84",
  abstract =     "The plague of cyberbullying on social media exerts a
                 dangerous influence on human lives. Due to the fact
                 that online social networks continue to daily expand,
                 the proliferation of hate speech is also growing.
                 Consequentially, distressing content is often
                 implicated in the onset of depression and
                 suicide-related behaviors. In this paper, we propose an
                 innovative framework, named as the trustable
                 LSTM-autoencoder network (TLA NET), which is designed
                 for the detection of cyberbullying on social media by
                 employing synthetic data. We introduce a
                 state-of-the-art method for the automatic production of
                 translated data, which are aimed at tackling data
                 availability issues. Several languages, including Hindi
                 and Bangla, continue to face research limitations due
                 to the absence of adequate datasets. Experimental
                 identification of aggressive comments is carried out
                 via datasets in Hindi, Bangla, and English. By
                 employing TLA NET and traditional models, such as long
                 short-term memory (LSTM), bidirectional long short-term
                 memory (BiLSTM), the LSTM-autoencoder, Word2vec,
                 bidirectional encoder representations from transformers
                 (BERT), and the Generative Pre-trained Transformer 2
                 (GPT-2), we perform the experimental identification of
                 aggressive comments in datasets in Hindi, Bangla, and
                 English. In addition to this, we employ evaluation
                 metrics that include the F1-score, accuracy, precision,
                 and recall, to assess the performance of the models.
                 Our model demonstrates outstanding performance across
                 all the datasets by achieving a remarkable 99\%
                 accuracy and positioning itself as a frontrunner when
                 compared to previous works that make use of the dataset
                 featured in this research.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Pereira:2025:SPP,
  author =       "Carolina Pereira and Anabela Marto and Roberto Ribeiro
                 and Alexandrino Gon{\c{c}}alves and Nuno Rodrigues and
                 Carlos Rabad{\~a}o and Rog{\'e}rio Lu{\'\i}s de
                 Carvalho Costa and Leonel Santos",
  title =        "Security and Privacy in Physical--Digital
                 Environments: Trends and Opportunities",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "83",
  day =          "12",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020083",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/83",
  abstract =     "Over recent decades, internet-based communication has
                 grown exponentially, accompanied by a surge in cyber
                 threats from malicious actors targeting users and
                 organizations, heightening the demand for robust
                 security and privacy measures. With the emergence of
                 physical--digital environments based on Mixed Reality
                 (MR) and the Metaverse, new cybersecurity, privacy, and
                 confidentiality challenges have surfaced, requiring
                 innovative approaches. This work examines the current
                 landscape of cybersecurity concerns in MR and Metaverse
                 environments, focusing on their unique vulnerabilities
                 and the risks posed to users and their data. Key
                 challenges include authentication issues, data
                 breaches, and risks to user anonymity. The work also
                 explores advancements in secure design frameworks,
                 encryption techniques, and regulatory approaches to
                 safeguard these technologies. Additionally, it
                 identifies opportunities for further research and
                 innovation to strengthen data protection and ensure a
                 safe, trustworthy experience in these environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bastos:2025:FBP,
  author =       "Tiago Bastos and C{\'a}rmen Guimar{\~a}es and Leonor
                 Teixeira",
  title =        "Framework of Best Practices to Drive the Digital
                 Transition: Towards a 4.0 Paradigm Based on Evidence
                 from Case Studies",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "82",
  day =          "11",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020082",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/82",
  abstract =     "In a technology-driven world, the concepts of
                 digitalization and Industry 4.0 (I4.0) are an ever more
                 present reality for companies. The benefits which these
                 advancements offer, coupled with the market-driven
                 pressure to reduce response times, have placed
                 businesses in a technological ``wave'', where it is
                 imperative to adapt to avoid falling behind. While
                 numerous studies focus on technological
                 developments---such as definitions, capabilities, and
                 potential benefits---few provide a systematic approach
                 to best practices and recommendations for accelerating
                 digital transformation while mitigating adverse
                 impacts. In this study, case studies from 10 companies
                 are analyzed to identify and systematize the best
                 practices implemented in their digital transitions. The
                 findings culminate in a best-practice framework for
                 digital transition (DT), highlighting critical aspects
                 such as understanding a company's current state,
                 acquiring external knowledge, and addressing the
                 importance of cybersecurity and skilled staff.
                 Concerning originality, this work presents an artifact
                 based on manufacturing industry case studies,
                 emphasizing the practical vision concerning DT.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Piccininni:2025:MMU,
  author =       "Saverio Piccininni and Mine Dastan and Fabio Vangi and
                 Michele Fiorentino",
  title =        "{MAGIC}: Multi-User Advanced Graphic Immersive
                 Configurator for Sustainable Customization of Complex
                 Design Products --- a Sailing Yacht Case Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "81",
  day =          "11",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020081",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/81",
  abstract =     "Modern design products are increasingly complex and
                 emotionally significant, demanding versatile and
                 collaborative customization. However, a literature and
                 commercial review reveals a limited availability of
                 flexible, multi-user, photorealistic Virtual Reality
                 (VR) systems for product configuration. We introduce
                 MAGIC (Multi-user Advanced Graphic Immersive
                 Configurator), a collaborative platform combining
                 realistic graphics with ergonomic validation using
                 digital avatars, addressing the limitations of 2D
                 visualization and existing tools. MAGIC is evaluated in
                 a yacht design case study involving 30 participants in
                 an immersive, co-located configuration of a sailing
                 yacht to assess the system's usability and the
                 potential of VR for customizing complex products.
                 Results show MAGIC's feasibility in supporting
                 multi-user configuration (100\% success rate) and
                 achieving a strong usability score (SUS = 80.83). User
                 feedback highlights that high-quality graphics and
                 additional content significantly enhance immersion and
                 user engagement. However, encountered challenges with
                 navigation methods and spatial perception indicate
                 areas for improvement. MAGIC's collaborative and
                 immersive capabilities can be extended to other
                 industries demanding proactive customer engagement in
                 the customization of large, heavy products and
                 ergonomic design. Moreover, by promoting prototype
                 dematerialization and providing an interactive remote
                 tool for end users, MAGIC offers potential
                 environmental and economic benefits to boost the
                 competitiveness of small and medium enterprises
                 (SMEs).",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lee:2025:MLB,
  author =       "Cheng-Chi Lee and Dinh-Thuan Do and Agbotiname Lucky
                 Imoize",
  title =        "Machine Learning for Blockchain and {IoT} Systems in
                 Smart City",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "80",
  day =          "11",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020080",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/80",
  abstract =     "Modern design products are increasingly complex and
                 emotionally significant, demanding versatile and
                 collaborative customization. However, a literature and
                 commercial review reveals a limited availability of
                 flexible, multi-user, photorealistic Virtual Reality
                 (VR) systems for product configuration. We introduce
                 MAGIC (Multi-user Advanced Graphic Immersive
                 Configurator), a collaborative platform combining
                 realistic graphics with ergonomic validation using
                 digital avatars, addressing the limitations of 2D
                 visualization and existing tools. MAGIC is evaluated in
                 a yacht design case study involving 30 participants in
                 an immersive, co-located configuration of a sailing
                 yacht to assess the system's usability and the
                 potential of VR for customizing complex products.
                 Results show MAGIC's feasibility in supporting
                 multi-user configuration (100\% success rate) and
                 achieving a strong usability score (SUS = 80.83). User
                 feedback highlights that high-quality graphics and
                 additional content significantly enhance immersion and
                 user engagement. However, encountered challenges with
                 navigation methods and spatial perception indicate
                 areas for improvement. MAGIC's collaborative and
                 immersive capabilities can be extended to other
                 industries demanding proactive customer engagement in
                 the customization of large, heavy products and
                 ergonomic design. Moreover, by promoting prototype
                 dematerialization and providing an interactive remote
                 tool for end users, MAGIC offers potential
                 environmental and economic benefits to boost the
                 competitiveness of small and medium enterprises
                 (SMEs).",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bohra:2025:IBS,
  author =       "Navdeep Bohra and Ashish Kumari and Vikash Kumar
                 Mishra and Pramod Kumar Soni and Vipin Balyan",
  title =        "Intelligence-Based Strategies with
                 Vehicle-to-Everything Network: a Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "79",
  day =          "10",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020079",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/79",
  abstract =     "Advancements in intelligent vehicular networks and
                 computing systems have created new possibilities for
                 innovative approaches that enhance traffic safety,
                 comfort, and transportation performance. Machine
                 Learning (ML) has become widely employed for boosting
                 conventional data-driven methodologies in various
                 scientific study domains. The integration of a
                 Vehicle-to-Everything (V2X) system with ML enables the
                 acquisition of knowledge from multiple places, enhances
                 the operator's awareness, and predicts future crashes
                 to prevent them. The information serves multiple
                 functions, such as determining the most efficient
                 route, increasing the driver's knowledge, forecasting
                 movement strategy to avoid risky circumstances, and
                 eventually improving user convenience, security, and
                 overall highway experiences. This article thoroughly
                 examines Artificial Intelligence (AI) and ML methods
                 that are now investigated through different study
                 endeavors in vehicular ad hoc networks (VANETs).
                 Furthermore, it examines the benefits and drawbacks
                 accompanying such intelligent methods in the context of
                 the VANETs system and simulation tools. Ultimately,
                 this study pinpoints prospective domains for vehicular
                 network development that can utilize the capabilities
                 of AI and ML.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Cheminod:2025:LCS,
  author =       "Manuel Cheminod and Ivan Cibrario Bertolotti and
                 Adriano Valenzano and Luca Durante",
  title =        "Low-Cost Software Evaluation of Communication Delays
                 in Networked Industrial Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "78",
  day =          "10",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020078",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/78",
  abstract =     "Equipment to be installed in real-time industrial
                 control system networks must be carefully characterized
                 before commissioning to ensure it meets performance
                 requirements. However, performance analysis tools may
                 be expensive and come with stringent hardware and
                 software requirements that render them out of reach for
                 many small and medium enterprises. In this paper, we
                 propose a software tool that leverages inexpensive,
                 commonly available personal computer hardware and
                 Linux-based, user-level open source software to enhance
                 portability, flexibility, and ease of use without
                 sacrificing measurement accuracy. An extensive
                 evaluation of the tool's custom-designed traffic
                 generator shows that it compares favorably with related
                 work. At the same time, the measurement system is able
                 to achieve remarkable accuracy in determining the mean
                 delay and delay variance of the device under test, as
                 also demonstrated by a practical device evaluation
                 example.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Pohls:2025:SFS,
  author =       "Henrich C. P{\"o}hls and Fabian K{\"u}gler and Emiliia
                 Geloczi and Felix Klement",
  title =        "Segmentation and Filtering Are Still the Gold Standard
                 for Privacy in {IoT} --- an In-Depth {STRIDE} and
                 {LINDDUN} Analysis of Smart Homes",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "77",
  day =          "10",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020077",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/77",
  abstract =     "Every year, more and more electronic devices are used
                 in households, which certainly leads to an increase in
                 the total number of communications between devices.
                 During communication, a huge amount of information is
                 transmitted, which can be critical or even malicious.
                 To avoid the transmission of unnecessary information, a
                 filtering mechanism can be applied. Filtering is a
                 long-standing method used by network engineers to
                 segregate and thus block unwanted traffic from reaching
                 certain devices. In this work, we show how to apply
                 this to the Internet of Things (IoT) Smart Home domain
                 as it introduces numerous networked devices into our
                 daily lives. To analyse the positive influence of
                 filtering on security and privacy, we offer the results
                 from our in-depth STRIDE and LINDDUN analysis of
                 several Smart Home scenarios before and after the
                 application. To show that filtering can be applied to
                 other IoT domains, we offer a brief glimpse into the
                 domain of smart cars.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Carchiolo:2025:TCA,
  author =       "Vincenza Carchiolo and Michele Malgeri",
  title =        "Trends, Challenges, and Applications of Large Language
                 Models in Healthcare: a Bibliometric and Scoping
                 Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "76",
  day =          "8",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020076",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/76",
  abstract =     "The application of Large Language Models (LLMs) in
                 medicine represents an area of growing interest in
                 scientific research. This study presents a quantitative
                 review of the scientific literature aiming at analyzing
                 emerging trends in the use of LLMs in the medical
                 field. Through a systematic analysis of works extracted
                 from Scopus, the study examines the temporal evolution,
                 geographical distribution, and scientific
                 collaborations between research institutions and
                 nations. Furthermore, the main topics addressed in the
                 most cited papers are identified, and the most recent
                 and relevant reviews are explored in depth. The
                 quantitative approach enables mapping the development
                 of research, highlighting both opportunities and open
                 challenges. This study presents a comprehensive
                 analysis of research articles and review-type articles
                 across several years, focusing on temporal,
                 geographical, and thematic trends. The temporal
                 analysis reveals significant shifts in research
                 activity, including periods of increased or decreased
                 publication output and the emergence of new areas of
                 interest. Geographically, the results identify regions
                 and countries with higher concentrations of
                 publications, as well as regions experiencing growing
                 or stagnant international collaboration. The thematic
                 analysis highlights the key research areas addressed in
                 the reviewed papers, tracking evolving topics and
                 changes in research focus over time. Additionally, the
                 collaborative analysis sheds light on key networks of
                 international collaboration, revealing changes in the
                 distribution of affiliations across subperiods and
                 publication types. Finally, an investigation of the
                 most cited papers highlights the works that have had
                 the greatest impact on the scientific community,
                 identifying enduring themes and methodologies that
                 continue to shape the field of study. The results
                 provide a clear overview of current trends and future
                 perspectives for the application of LLMs in medicine,
                 offering a valuable reference for researchers and
                 professionals in the field.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liu:2025:PSE,
  author =       "Peng Liu and Lili Jia and Yang Xiao",
  title =        "Participant Selection for Efficient and Trusted
                 Federated Learning in Blockchain-Assisted Hierarchical
                 Federated Learning Architectures",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "75",
  day =          "8",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020075",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/75",
  abstract =     "Federated learning has attracted widespread attention
                 due to its strong capabilities of privacy protection,
                 making it a powerful supporting technology for
                 addressing data silos in the future. However, federated
                 learning still lags significantly behind traditional
                 centralized learning in terms of learning efficiency
                 and system security. In this paper, we first construct
                 a hierarchical federated learning architecture
                 integrated with blockchain based on the cooperation of
                 the cloud, edge, and terminal, which has the ability to
                 enhance the security of federated learning while
                 reducing the introduction costs of blockchain. Under
                 this architecture, we propose a semi-asynchronous
                 aggregation scheme at the edge layer and introduce a
                 hierarchical aggregation scheme that combines it with
                 synchronous aggregation at the cloud end to improve
                 system efficiency. Furthermore, we present a
                 multi-objective node selection scheme that considers
                 various influencing factors such as security and
                 efficiency. We formulate the node selection problem as
                 a Markov Decision Process (MDP) and propose a solution
                 based on deep reinforcement learning to address it more
                 efficiently. The experimental results show that the
                 proposed scheme can effectively improve system
                 efficiency and enhance system security. In addition,
                 the proposed DQN-based node selection algorithm can
                 efficiently realize the selection of the optimal
                 policy.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Abdulla:2025:EDA,
  author =       "Hemin Sardar Abdulla and Aso M. Aladdin",
  title =        "Enhancing Design and Authentication Performance Model:
                 a Multilevel Secure Database Management System",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "74",
  day =          "8",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020074",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/74",
  abstract =     "Multilevel security (MLS) is particularly intended to
                 secure information against unauthorized access. An MLS
                 security DBMS allows users with different security
                 levels to access and share a database. For this
                 purpose, the study creates a model that includes a
                 restricted access authentication prototype with
                 multilevel security in a database management system
                 (MLS/DBMS). Accordingly, the model has been designed to
                 emphasize the highest level of authorized security. The
                 system ensures that users can only access information
                 that they are permitted to view, fully adhering to the
                 newly established MLS framework. In addition, the model
                 also integrates cryptographic algorithms, such as RSA
                 and AES, to enhance its functionality and demonstrate
                 the scalability and security of the model. These
                 criteria are defined based on the perspective of the
                 database provided to users, determined by their
                 respective authorization levels. An informal security
                 framework for a multilevel secure DBMS is defined. It
                 includes a classification strategy and explains the
                 implementation of operations like insertion and
                 deletion, addressing the complexity of models with
                 novel methods. The metric evaluation of this model
                 assesses the performance of the authentication process
                 and how operations are implemented across three
                 authentication group types. It also calculates the key
                 generation time and encryption types in cryptographic
                 algorithms. The results confirm that the RSA model
                 requires less time for evaluation while maintaining
                 multilevel security. Furthermore, the type 2
                 authentication group is more complex and requires more
                 memory and time for generation. Based on the
                 classification, the results highlight notable
                 differences, which designers should consider when
                 selecting authentication methods. Lastly, the study
                 presents various conclusions, explores possible future
                 directions, and discusses its limitations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yang:2025:TDV,
  author =       "Ran Yang and Zhaonan Li and Junhao Qian and Zhihua
                 Li",
  title =        "Task-Driven Virtual Machine Optimization Placement
                 Model and Algorithm",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "73",
  day =          "7",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020073",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/73",
  abstract =     "In cloud data centers, determining how to balance the
                 interests of the user and the cloud service provider is
                 a challenging issue. In this study, a
                 task-loading-oriented virtual machine (VM) optimization
                 placement model and algorithm is proposed integrating
                 consideration of both VM placement and the user's
                 computing requirements. First, the VM placement is
                 modeled as a multi-objective optimization problem to
                 minimize the makespan of the loading tasks, user rental
                 costs, and energy consumption of cloud data centers;
                 then, an improved chaos-elite NSGA-III (CE-NSGAIII)
                 algorithm is presented by casting the logistic
                 mapping-based population initialization (LMPI) and the
                 elite-guided algorithm in NSGA-III; finally, the
                 presented CE-NSGAIII is employed to solve the
                 aforementioned optimization model, and further, through
                 combination of the above sub-algorithms, a
                 CE-NSGAIII-based VM placement method is developed. The
                 experiment results show that the Pareto solution set
                 obtained using the CE-NSGAIII exhibits better
                 convergence and diversity than those of the compared
                 algorithms and yields an optimized VM placement scheme
                 with shorter makespan, less user rental costs, and
                 lower energy consumption.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kuznetsov:2025:OMP,
  author =       "Oleksandr Kuznetsov and Emanuele Frontoni and Kateryna
                 Kuznetsova and Marco Arnesano",
  title =        "Optimizing {Merkle} Proof Size Through Path Length
                 Analysis: a Probabilistic Framework for Efficient
                 Blockchain State Verification",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "72",
  day =          "7",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020072",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/72",
  abstract =     "This study addresses a critical challenge in modern
                 blockchain systems: the excessive size of Merkle proofs
                 in state verification, which significantly impacts
                 scalability and efficiency. As highlighted by
                 Ethereum's founder, Vitalik Buterin, current Merkle
                 Patricia Tries (MPTs) are highly inefficient for
                 stateless clients, with worst-case proofs reaching
                 approximately 300 MB. We present a comprehensive
                 probabilistic analysis of path length distributions in
                 MPTs to optimize proof size while maintaining security
                 guarantees. Our novel mathematical model characterizes
                 the distribution of path lengths in tries containing
                 random blockchain addresses and validates it through
                 extensive computational experiments. The findings
                 reveal logarithmic scaling of average path lengths with
                 respect to the number of addresses, with unprecedented
                 precision in predicting structural properties across
                 scales from 100 to 300 million addresses. The research
                 demonstrates remarkable accuracy, with discrepancies
                 between theoretical and experimental results not
                 exceeding 0.01 across all tested scales. By identifying
                 and verifying the right-skewed nature of path length
                 distributions, we provide critical insights for
                 optimizing Merkle proof generation and size reduction.
                 Our practical implementation guidelines demonstrate
                 potential proof size reductions of up to 70\% through
                 optimized path structuring and node layout. This work
                 bridges the gap between theoretical computer science
                 and practical blockchain engineering, offering
                 immediate applications for blockchain client
                 optimization and efficient state-proof generation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Marti:2025:CMA,
  author =       "Patrizia Marti and Giulia Teverini and Cecilia Goracci
                 and Lorenzo Franchi",
  title =        "Correction: {Marti et al. Gamification of Orthodontic
                 Treatment with Personalised Facemasks: Enhancing
                 Patient Compliance Through Playful Engagement. Future
                 Internet 2024, {\bf 16}, 446}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "71",
  day =          "7",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020071",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/71",
  abstract =     "This study addresses a critical challenge in modern
                 blockchain systems: the excessive size of Merkle proofs
                 in state verification, which significantly impacts
                 scalability and efficiency. As highlighted by
                 Ethereum's founder, Vitalik Buterin, current Merkle
                 Patricia Tries (MPTs) are highly inefficient for
                 stateless clients, with worst-case proofs reaching
                 approximately 300 MB. We present a comprehensive
                 probabilistic analysis of path length distributions in
                 MPTs to optimize proof size while maintaining security
                 guarantees. Our novel mathematical model characterizes
                 the distribution of path lengths in tries containing
                 random blockchain addresses and validates it through
                 extensive computational experiments. The findings
                 reveal logarithmic scaling of average path lengths with
                 respect to the number of addresses, with unprecedented
                 precision in predicting structural properties across
                 scales from 100 to 300 million addresses. The research
                 demonstrates remarkable accuracy, with discrepancies
                 between theoretical and experimental results not
                 exceeding 0.01 across all tested scales. By identifying
                 and verifying the right-skewed nature of path length
                 distributions, we provide critical insights for
                 optimizing Merkle proof generation and size reduction.
                 Our practical implementation guidelines demonstrate
                 potential proof size reductions of up to 70\% through
                 optimized path structuring and node layout. This work
                 bridges the gap between theoretical computer science
                 and practical blockchain engineering, offering
                 immediate applications for blockchain client
                 optimization and efficient state-proof generation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Delwar:2025:RTF,
  author =       "Tahesin Samira Delwar and Sayak Mukhopadhyay and
                 Akshay Kumar and Mangal Singh and Yang-won Lee and
                 Jee-Youl Ryu and A. S. M. Sanwar Hosen",
  title =        "Real-Time Farm Surveillance Using {IoT} and {YOLOv8}
                 for Animal Intrusion Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "70",
  day =          "6",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020070",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/70",
  abstract =     "This research proposes a ground-breaking technique for
                 protecting agricultural fields against animal invasion,
                 addressing a key challenge in the agriculture industry.
                 The suggested system guarantees real-time intrusion
                 detection and quick reactions by combining cutting-edge
                 sensor technologies, image processing capabilities, and
                 the Internet of Things (IoT), successfully safeguarding
                 crops and reducing agricultural losses. This study
                 involves a thorough examination of five
                 models---Inception, Xception, VGG16, AlexNet, and
                 YoloV8---against three different datasets. The YoloV8
                 model emerged as the most promising, with exceptional
                 accuracy and precision, exceeding 99\% in both
                 categories. Following that, the YoloV8 model's
                 performance was compared to previous study findings,
                 confirming its excellent capabilities in terms of
                 intrusion detection in agricultural settings. Using the
                 capabilities of the YoloV8 model, an IoT device was
                 designed to provide real-time intrusion alarms on
                 farms. The ESP32cam module was used to build this
                 gadget, which smoothly integrated this cutting-edge
                 model to enable efficient farm security measures. The
                 incorporation of this technology has the potential to
                 transform farm monitoring by providing farmers with
                 timely, actionable knowledge to prevent possible
                 threats and protect agricultural production.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Efunogbon:2025:ONS,
  author =       "Abimbola Efunogbon and Enjie Liu and Renxie Qiu and
                 Taiwo Efunogbon",
  title =        "Optimal {5G} Network Sub-Slicing Orchestration in a
                 Fully Virtualised Smart Company Using Machine
                 Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "69",
  day =          "6",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020069",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/69",
  abstract =     "This paper introduces Optimal 5G Network Sub-Slicing
                 Orchestration (ONSSO), a novel machine learning
                 framework for dynamic and autonomous 5G network slice
                 orchestration. The framework leverages the LazyPredict
                 module to automatically select optimal supervised
                 learning algorithms based on real-time network
                 conditions and historical data. We propose Enhanced
                 Sub-Slice (eSS), a machine learning pipeline that
                 enables granular resource allocation through network
                 sub-slicing, reducing service denial risks and
                 enhancing user experience. This leads to the
                 introduction of Company Network as a Service (CNaaS), a
                 new enterprise service model for mobile network
                 operators (MNOs). The framework was evaluated using
                 Google Colab for machine learning implementation and
                 MATLAB/Simulink for dynamic testing. The results
                 demonstrate that ONSSO improves MNO collaboration
                 through real-time resource information sharing,
                 reducing orchestration delays and advancing adaptive 5G
                 network management solutions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Pourghasem:2025:MLD,
  author =       "Azita Pourghasem and Raimund Kirner and Athanasios
                 Tsokanos and Iosif Mporas and Alexios Mylonas",
  title =        "Machine Learning and Deep Learning-Based
                 Multi-Attribute Physical-Layer Authentication for
                 Spoofing Detection in {LoRaWAN}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "68",
  day =          "6",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020068",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/68",
  abstract =     "The use of wireless sensor networks (WSNs) in critical
                 applications such as environmental monitoring, smart
                 agriculture, and industrial automation has created
                 significant security concerns, particularly due to the
                 broadcasting nature of wireless communication. The
                 absence of physical-layer authentication mechanisms
                 exposes these networks to threats like spoofing,
                 compromising data authenticity. This paper introduces a
                 multi-attribute physical layer authentication (PLA)
                 scheme to enhance WSN security by using physical
                 attributes such as received signal strength indicator
                 (RSSI), battery level (BL), and altitude. The LoRaWAN
                 join procedure, a key risk due to plain text
                 transmission without encryption during initial
                 communication, is addressed in this study. To evaluate
                 the proposed approach, a partially synthesized dataset
                 was developed. Real-world RSSI values were sourced from
                 the LoRa at the Edge Dataset, while BL and altitude
                 columns were added to simulate realistic sensor
                 behavior in a forest fire detection scenario. Machine
                 learning (ML) models, including Logistic Regression
                 (LR), Random Forest (RF), and K-Nearest Neighbors
                 (KNN), were compared with deep learning (DL) models,
                 such as Multi-Layer Perceptron (MLP) and Convolutional
                 Neural Networks (CNN). The results showed that RF
                 achieved the highest accuracy among machine learning
                 models, while MLP and CNN delivered competitive
                 performance with higher resource demands.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Stelea:2025:WCM,
  author =       "George Alex Stelea and Livia Sangeorzan and Nicoleta
                 Enache-David",
  title =        "When Cybersecurity Meets Accessibility: a Holistic
                 Development Architecture for Inclusive Cyber-Secure
                 {Web} Applications and {Websites}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "67",
  day =          "5",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020067",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/67",
  abstract =     "In today's technology-centric era, digital
                 transformation has made accessibility and cybersecurity
                 critical components for developing inclusive web
                 applications that are essential in daily operations.
                 However, current development models often treat
                 accessibility and cybersecurity separately, leading to
                 solutions that may excel in one area while lacking in
                 the other. This paper addresses this gap by proposing
                 the Holistic Security and Accessibility Layered
                 Architecture (HSALA), a novel architectural model that
                 integrates accessibility and cybersecurity throughout
                 the development process. HSALA consists of five
                 interconnected layers, each paired with a corresponding
                 security layer, ensuring that both accessibility and
                 security are embedded at every level. We conduct a
                 theoretical and analytical case study comparing HSALA
                 with the traditional three-layered architecture,
                 demonstrating HSALA's superiority in addressing
                 contemporary challenges related to accessibility,
                 cybersecurity, scalability, and user experience. The
                 findings indicate that HSALA provides a robust
                 framework for developing secure and inclusive web
                 applications, promoting a more equitable digital
                 ecosystem. We outline a roadmap for future work,
                 including empirical validation and practical
                 implementation strategies. HSALA represents a
                 significant advancement in web application development,
                 fostering inclusivity and trust in an increasingly
                 digital society.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Maciel:2025:UMO,
  author =       "Kilbert Amorim Maciel and David Martins Leite and
                 Guilherme Alves de Ara{\'u}jo and Flavia C. Delicato
                 and Atslands R. Rocha",
  title =        "{Ubunye}: an {MEC} Orchestration Service Based on
                 {QoE}, {QoS}, and Service Classification Using Machine
                 Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "2",
  pages =        "66",
  day =          "5",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17020066",
  ISSN =         "1999-5903",
  bibdate =      "Fri Feb 28 06:11:52 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/2/66",
  abstract =     "The increasing adoption of Internet of Things devices
                 has led to a significant demand for cloud services,
                 where latency and bandwidth play a crucial role in
                 shaping users' perception of network service quality.
                 However, the use of cloud services with the desired
                 quality is not always available to all users.
                 Furthermore, uneven network coverage in urban and rural
                 areas has created ``digital deserts'', which are
                 characterized by a lack of connectivity resources,
                 complicating access to cloud services. In this
                 scenario, edge computing emerges as a promising
                 alternative for service provision. Edge computing
                 leverages data processing at or near the source where
                 it is generated rather than sending it to the cloud for
                 processing. It can lead to several advantages, such as
                 reduced latency and lower bandwidth usage. This paper
                 addresses the need to ensure consistent quality of
                 experience (QoE) and quality of service (QoS) in
                 dynamic network environments, particularly in remote
                 regions with limited infrastructure. We propose an
                 orchestration service called Ubunye, which operates at
                 the network edge and selects the most appropriate edge
                 node to fulfill a given application request while
                 satisfying its quality requirements. Ubunye considers
                 factors such as latency and available bandwidth when
                 selecting a node to execute the requested service. It
                 implements a service classification system based on
                 machine learning (ML) techniques. The ideal edge node
                 is chosen through a multi-faceted evaluation, which
                 includes current CPU load, memory availability, and
                 other relevant parameters. Experiment results show that
                 Ubunye effectively orchestrates resources at the
                 network edge, enhancing QoE and QoS for services that
                 demand low latency and high bandwidth. Additionally, it
                 showcases the ability to classify services and allocate
                 resources under challenging network conditions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zheng:2025:FNF,
  author =       "Qizhong Zheng and Xiujie Huang",
  title =        "{FedRecI2C}: a Novel Federated Recommendation
                 Framework Integrating Communication and Computation to
                 Accelerate Convergence Under Communication
                 Constraints",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "132",
  day =          "20",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030132",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/132",
  abstract =     "The federated recommender system (FRS) employs
                 federated learning methodologies to create a
                 recommendation model in a distributed environment,
                 where clients share locally updated data with the
                 server without exposing raw data and achieving privacy
                 preservation. However, varying communication
                 capabilities among devices restrict the participation
                 of only a subset of clients in each round of federated
                 training, resulting in slower convergence and requiring
                 additional training rounds. In this work, we propose a
                 novel federated recommendation framework, called
                 FedRecI2C, which integrates communication and
                 computation resources in the system. This framework
                 accelerates convergence by utilizing not only
                 communication-capable clients for federated training
                 but also communication-constrained clients to leverage
                 their computation and limited communication resources
                 for further local training. This framework offers
                 simplicity and flexibility, providing a plug-and-play
                 architecture that effectively enhances the convergence
                 speed in FRSs. It has demonstrated remarkable
                 effectiveness in a wide range of FRSs when operating
                 under diverse communication conditions. Extensive
                 experiments are conducted to validate the effectiveness
                 of FedRecI2C. Moreover, we provide in-depth analyses of
                 the FedRecI2C framework, offering novel insights into
                 the training patterns of FRSs.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alnami:2025:DML,
  author =       "Hani Alnami and Imad Mahgoub and Hamzah Al-Najada and
                 Easa Alalwany",
  title =        "A Distributed Machine Learning-Based Scheme for
                 Real-Time Highway Traffic Flow Prediction in {Internet}
                 of Vehicles",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "131",
  day =          "19",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030131",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/131",
  abstract =     "Abnormal traffic flow prediction is crucial for
                 reducing traffic congestion. Most recent studies
                 utilized machine learning models in traffic flow
                 detection systems. However, these detection systems do
                 not support real-time analysis. Centralized machine
                 learning methods face a number of challenges due to the
                 sheer volume of traffic data that needs to be processed
                 in real-time. Thus, it is not scalable and lacks fault
                 tolerance and data privacy. This study designs and
                 evaluates a scalable distributed machine learning-based
                 scheme to predict highway traffic flows in real-time.
                 The proposed system is segment-based where the vehicles
                 in each segment form a cluster. We train and validate a
                 local Random Forest Regression (RFR) model for each
                 vehicle's cluster (highway-segment) using six different
                 hyper parameters. Due to the variance of traffic flow
                 patterns between segments, we build a global
                 Distributed Machine Learning Random Forest (DMLRF)
                 regression model to improve the system performance for
                 abnormal traffic flows. Kappa Architecture is utilized
                 to enable real-time prediction. The proposed model is
                 evaluated and compared to other base-line models,
                 Linear Regression (LR), Logistic Regression (LogR), and
                 K Nearest Neighbor (KNN) regression in terms of Mean
                 Square Error (MSE), Root Mean Square Error (RMSE), Mean
                 Absolute Error (MAE), R-squared (R 2 ), and Adjusted
                 R-Squared (AR 2 ). The proposed scheme demonstrates
                 high accuracy in predicting abnormal traffic flows
                 while maintaining scalability and data privacy.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Islam:2025:RAE,
  author =       "Mohammad Munzurul Islam and Mohammed Alawad",
  title =        "Resource-Aware {ECG} Classification with Heterogeneous
                 Models in Federated Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "130",
  day =          "19",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030130",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/130",
  abstract =     "In real-world scenarios, ECG data are collected from a
                 diverse range of heterogeneous devices, including
                 high-end medical equipment and consumer-grade wearable
                 devices, each with varying computational capabilities
                 and constraints. This heterogeneity presents
                 significant challenges in developing a highly accurate
                 deep learning (DL) global model for ECG classification,
                 as traditional centralized approaches struggle to
                 address privacy concerns, scalability issues, and model
                 inconsistencies arising from diverse device
                 characteristics. Federated Learning (FL) has emerged as
                 a promising solution by enabling collaborative model
                 training without sharing raw data, thus preserving
                 privacy and security. However, standard FL assumes
                 uniform device capabilities and model architectures,
                 which is impractical given the varied nature of ECG
                 data collection devices. Although heterogeneity has
                 been explored in other domains, its impact on ECG
                 classification and the classification of similar time
                 series physiological signals remains underexplored. In
                 this study, we adopted HeteroFL, a technique that
                 enables model heterogeneity to reflect real-world
                 resource constraints. By allowing local models to vary
                 in complexity while aggregating their updates, HeteroFL
                 accommodates the computational diversity of different
                 devices. This study evaluated the applicability of
                 HeteroFL for ECG classification using the MIT-BIH
                 Arrhythmia dataset, identifying both its strengths and
                 limitations. Our findings establish a foundation for
                 future research on improving FL strategies for
                 heterogeneous medical data, highlighting areas for
                 further optimization and adaptation in real-world
                 deployments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Papanikou:2025:HMS,
  author =       "Vasiliki Papanikou and Panagiotis Papadakos and
                 Theodora Karamanidou and Thanos G. Stavropoulos and
                 Evaggelia Pitoura and Panayiotis Tsaparas",
  title =        "Health Misinformation in Social Networks: a Survey of
                 Information Technology Approaches",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "129",
  day =          "15",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030129",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/129",
  abstract =     "In this paper, we present a comprehensive survey on
                 the pervasive issue of medical misinformation in social
                 networks from the perspective of information
                 technology. The survey aims at providing a systematic
                 review of related research and helping researchers and
                 practitioners navigate through this fast-changing
                 field. Research on misinformation spans multiple
                 disciplines, but technical surveys rarely focus on the
                 medical domain. Existing medical misinformation surveys
                 provide broad insights for various stakeholders but
                 lack a deep dive into computational methods. This
                 survey fills that gap by examining how fact-checking
                 and fake news detection techniques are adapted to the
                 medical field from a computer engineering perspective.
                 Specifically, we first present manual and automatic
                 approaches for fact-checking, along with publicly
                 available fact-checking tools. We then explore fake
                 news detection methods, using content, propagation
                 features, or source features, as well as mitigation
                 approaches for countering the spread of misinformation.
                 We also provide a detailed list of several datasets on
                 health misinformation. While this survey primarily
                 serves researchers and technology experts, it can also
                 provide valuable insights for policymakers working to
                 combat health misinformation. We conclude the survey
                 with a discussion on the open challenges and future
                 research directions in the battle against health
                 misinformation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kang:2025:GGB,
  author =       "Yulin Kang and Wuzheng Tan and Linlin Fan and Yinuo
                 Chen and Xinbin Lai and Jian Weng",
  title =        "{GHEFL}: Grouping Based on Homomorphic Encryption
                 Validates Federated Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "128",
  day =          "15",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030128",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/128",
  abstract =     "Federated learning is a powerful tool for securing
                 participants' private data due to its ability to make
                 data ``available but not visible''. In recent years,
                 federated learning has been enhanced by the emergence
                 of multi-weight aggregation protocols, which minimize
                 the impact of erroneous parameters, and verifiable
                 protocols, which prevent server misbehavior. However,
                 it still faces significant security and performance
                 challenges. Malicious participants may infer the
                 private data of others or carry out poisoning attacks
                 to compromise the model's correctness. Similarly,
                 malicious servers may return incorrect aggregation
                 results, undermining the model's convergence.
                 Furthermore, substantial communication overhead caused
                 by interactions between participants or between
                 participants and servers hinders the development of
                 federated learning. In response to this, this paper
                 proposes GHEFL, a group-based, verifiable, federated
                 learning method based on homomorphic encryption that
                 aims to prevent servers from maliciously stealing
                 participant privacy data or performing malicious
                 aggregation. While ensuring the usability of the
                 aggregated model, it strives to minimize the workload
                 on the server as much as possible. Finally, we
                 experimentally evaluate the performance of GHEFL.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2025:DNN,
  author =       "Li Wang and Heming Zhang and Changyuan Wang",
  title =        "Deep Neural Network-Based Modeling of Multimodal
                 Human-Computer Interaction in Aircraft Cockpits",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "127",
  day =          "13",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030127",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/127",
  abstract =     "Improving the performance of human-computer
                 interaction systems is an essential indicator of
                 aircraft intelligence. To address the limitations of
                 single-modal interaction methods, a multimodal
                 interaction model based on gaze and EEG target
                 selection is proposed using deep learning technology.
                 This model consists of two parts: target classification
                 and intention recognition. The target classification
                 model based on long short-term memory networks is
                 established and trained by combining the eye movement
                 information of the operator. The intention recognition
                 model based on transformers is constructed and trained
                 by combining the operator's EEG information. In the
                 application scenario of the aircraft radar page system,
                 the highest accuracy of the target classification model
                 is 98\%. The intention recognition rate obtained by
                 training the 32-channel EEG information in the
                 intention recognition model is 98.5\%, which is higher
                 than other compared models. In addition, we validated
                 the model on a simulated flight platform, and the
                 experimental results show that the proposed multimodal
                 interaction framework outperforms the single gaze
                 interaction in terms of performance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ye:2025:USS,
  author =       "Shaoyu Ye and Kevin K. W. Ho",
  title =        "University Students' Subjective Well-Being in {Japan}
                 Between 2021 and 2023: Its Relationship with Social
                 Media Use",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "126",
  day =          "12",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030126",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/126",
  abstract =     "This study investigated whether young adults' social
                 media use and subjective well-being (SWB) changed
                 during the COVID-19 pandemic. It examined the possible
                 relationships between social media use, SWB, and
                 personality traits. It included generalized trust,
                 self-consciousness, friendship, and desire for
                 self-presentation and admiration, in relation to
                 different patterns of social media use and genders.
                 Data were collected from university students in Japan
                 from 2021 to 2023 and were analyzed based on different
                 social media use patterns. The conceptual model was
                 based on the cognitive bias and social network
                 mediation models. Data were analyzed using ANOVA and
                 regression analyses. The findings revealed that, over
                 time, young adults' anxiety toward COVID-19 decreased,
                 while their SWB improved and their social support
                 increased. Depression tendencies showed a negative
                 association, whereas social support was positively
                 related to improvement of SWB for all three patterns of
                 social media use. Furthermore, online communication
                 skills had a positive relationship with improvements in
                 students' SWB in Patterns 1 (LINE + Twitter +
                 Instagram) and 2 (LINE + Twitter + Instagram + TikTok).
                 The self-indeterminate factor had a positive
                 relationship with students' SWB for all patterns in
                 2022 and 2023, and the praise acquisition factor had a
                 positive relationship with improvements in students'
                 SWB in Patterns 1 and 2. These results suggest that
                 young adults maintained their mental health through
                 different social media usage patterns, considering
                 their personality traits and social situations
                 associated with COVID-19. Particularly, receiving
                 social support, decreasing people's depression
                 tendencies, and displaying different aspects of the
                 ``self'' online can improve SWB. This study elucidates
                 the mental health situations of university students in
                 Japan and will help public health authorities develop
                 new support programs that help digital natives improve
                 their mental health in the context of social
                 environmental changes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{ALDabbas:2025:ATA,
  author =       "Ashraf ALDabbas and Zaid Mustafa and Zoltan Gal",
  title =        "Advanced Trajectory Analysis of {NASA}'s {Juno
                 Mission} Using Unsupervised Machine Learning: Insights
                 into {Jupiter}'s Orbital Dynamics",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "125",
  day =          "11",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030125",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/125",
  abstract =     "NASA's Juno mission, involving a pioneering spacecraft
                 the size of a basketball court, has been instrumental
                 in observing Jupiter's atmosphere and surface from
                 orbit since it reached the intended orbit. Over its
                 first decade of operation, Juno has provided
                 unprecedented insights into the solar system's origins
                 through advanced remote sensing and technological
                 innovations. This study focuses on change detection in
                 terms of Juno's trajectory, leveraging cutting-edge
                 data computing techniques to analyze its orbital
                 dynamics. Utilizing 3D position and velocity time
                 series data from NASA, spanning 11 years and 5 months
                 (August 2011 to January 2023), with 5.5 million samples
                 at 1 min accuracy, we examine the spacecraft's
                 trajectory modifications. The instantaneous average
                 acceleration, jerk, and snap are computed as
                 approximations of the first, second, and third
                 derivatives of velocity, respectively. The Hilbert
                 transform is employed to visualize the spectral
                 properties of Juno's non-stationary 3D movement,
                 enabling the detection of extreme events caused by
                 varying forces. Two unsupervised machine learning
                 algorithms, DBSCAN and OPTICS, are applied to cluster
                 the sampling events in two 3D state spaces: (velocity,
                 acceleration, jerk) and (acceleration, jerk, snap). Our
                 results demonstrate that the OPTICS algorithm
                 outperformed DBSCAN in terms of the outlier detection
                 accuracy across all three operational phases (OP1, OP2,
                 and OP3), achieving accuracies of 99.3\%, 99.1\%, and
                 98.9\%, respectively. In contrast, DBSCAN yielded
                 accuracies of 98.8\%, 98.2\%, and 97.4\%. These
                 findings highlight OPTICS as a more effective method
                 for identifying outliers in elliptical orbit data,
                 albeit with higher computational resource requirements
                 and longer processing times. This study underscores the
                 significance of advanced machine learning techniques in
                 enhancing our understanding of complex orbital dynamics
                 and their implications for planetary exploration.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Santoso:2025:FPP,
  author =       "Andri Santoso and Samsul Huda and Yuta Kodera and
                 Yasuyuki Nogami",
  title =        "Facial Privacy Protection with Dynamic Multi-User
                 Access Control for Online Photo Platforms",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "124",
  day =          "11",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030124",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/124",
  abstract =     "In the digital age, sharing moments through photos has
                 become a daily habit. However, every face captured in
                 these photos is vulnerable to unauthorized
                 identification and potential misuse through AI-powered
                 synthetic content generation. Previously, we introduced
                 SnapSafe, a secure system for enabling selective image
                 privacy focusing on facial regions for single-party
                 scenarios. Recognizing that group photos with multiple
                 subjects are a more common scenario, we extend SnapSafe
                 to support multi-user facial privacy protection with
                 dynamic access control designed for online photo
                 platforms. Our approach introduces key splitting for
                 access control, an owner-centric permission system for
                 granting and revoking access to facial regions, and a
                 request-based mechanism allowing subjects to initiate
                 access permissions. These features ensure that facial
                 regions remain protected while maintaining the
                 visibility of non-facial content for general viewing.
                 To ensure reproducibility and isolation, we implemented
                 our solution using Docker containers. Our experimental
                 assessment covered diverse scenarios, categorized as
                 ``Single'', ``Small'', ``Medium'', and ``Large'', based
                 on the number of faces in the photos. The results
                 demonstrate the system's effectiveness across all test
                 scenarios, consistently performing face encryption
                 operations in under 350 ms and achieving average face
                 decryption times below 286 ms across various group
                 sizes. The key-splitting operations maintained a 100\%
                 100\% 100\% success rate across all group
                 configurations, while revocation operations were
                 executed efficiently with server processing times
                 remaining under 16 ms. These results validate the
                 system's capability in managing facial privacy while
                 maintaining practical usability in online photo sharing
                 contexts.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2025:HDD,
  author =       "Yanxuan Li and Vatcharapol Sukhotu",
  title =        "How Does Digital Capability Shape Resilient Supply
                 Chains? --- Evidence from {China}'s Electric Vehicle
                 Manufacturing Industry",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "123",
  day =          "11",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030123",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/123",
  abstract =     "In recent years, the rapid advancement of digital
                 technologies and the growing demand for sustainability
                 have driven unprecedented transformations in the
                 automotive industry, particularly toward electric
                 vehicles (EVs) and renewable energy. The EV supply
                 chain, a complex global network, has become
                 increasingly vulnerable to globalization and frequent
                 ``black swan'' events. The purpose of this study,
                 grounded in organizational information processing
                 theory, aims to systematically examine the role of
                 digital capability in strengthening supply chain
                 resilience (SCR) through improved risk management
                 effectiveness. Specifically, it explores the
                 multidimensional nature of digital capability,
                 clarifies its distinct impact on SCR, and addresses
                 existing research gaps in this domain. To achieve this,
                 this study develops a theoretical framework and
                 validates it using survey data collected from 249 EV
                 supply chain enterprises in China. Partial Least
                 Squares Structural Equation Modeling (PLS-SEM) is
                 employed to empirically test the proposed
                 relationships. The findings provide valuable
                 theoretical insights and actionable guidance for EV
                 manufacturers seeking to leverage digital
                 transformation to mitigate risks effectively and
                 enhance supply chain resilience. However, as the study
                 focuses on Chinese EV supply chain enterprises, caution
                 is needed when generalizing the findings to other
                 regions. Future research could extend this
                 investigation to different markets, such as to Europe
                 and the United States, to explore potential
                 variations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chaudhari:2025:ETI,
  author =       "Bharat S. Chaudhari",
  title =        "Enabling Tactile {Internet} via {6G}: Application
                 Characteristics, Requirements, and Design
                 Considerations",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "122",
  day =          "11",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030122",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/122",
  abstract =     "With the emergence of artificial intelligence and
                 advancements in network technologies, the imminent
                 arrival of 6G is not very far away. The 6G technology
                 will introduce unique and innovative applications of
                 the Tactile Internet in the near future. This paper
                 highlights the evolution towards the Tactile Internet
                 enabled by 6G technology, along with the details of 6G
                 capabilities. It emphasizes the stringent requirements
                 for emerging Tactile Internet applications and the
                 critical role of parameters, such as latency,
                 reliability, data rate, and others. The study
                 identifies the important characteristics of future
                 Tactile Internet applications, interprets them into
                 explicit requirements, and then discusses the
                 associated design considerations. The study focuses on
                 the role of application characteristics of various
                 applications, like virtual reality/augmented reality,
                 remote surgery, gaming, smart cities, autonomous
                 vehicles, industrial automation, brain-machine
                 interface, telepresence/holography, and requirements in
                 the design of 6G and the Tactile Internet. Furthermore,
                 we discuss the exclusive parameters and other
                 requirements of Tactile Internet to realize real-time
                 haptic interactions with the help of 6G and artificial
                 intelligence. The study deliberates and examines the
                 important performance parameters for the given
                 applications. It also discusses various types of
                 sensors that are required for Tactile Internet
                 applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bompotas:2025:CMP,
  author =       "Agorakis Bompotas and Nikitas-Rigas Kalogeropoulos and
                 Christos Makris",
  title =        "{CommC}: a Multi-Purpose {COMModity} Hardware
                 Cluster",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "121",
  day =          "11",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030121",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/121",
  abstract =     "The high costs of acquiring and maintaining
                 high-performance computing (HPC) resources pose
                 significant barriers for medium-sized enterprises and
                 educational institutions, often forcing them to rely on
                 expensive cloud-based solutions with recurring costs.
                 This paper introduces CommC, a multi-purpose commodity
                 hardware cluster designed to reduce operational
                 expenses and extend hardware lifespan by repurposing
                 underutilized computing resources. By integrating
                 virtualization (KVM and Proxmox) and containerization
                 (Kubernetes and Docker), CommC creates a scalable,
                 secure, and cost-efficient computing environment. The
                 proposed system enables seamless resource sharing,
                 ensuring high availability and fault tolerance for both
                 containerized and virtualized workloads. To demonstrate
                 its versatility, we deploy big data engines like Apache
                 Spark alongside traditional web services, showcasing
                 CommC's ability to support diverse workloads
                 efficiently. Our cost analysis reveals that CommC
                 reduces computing expenses by up to 77.93\% compared to
                 cloud-based alternatives while also mitigating e-waste
                 accumulation by extending the lifespan of existing
                 hardware. This significantly improves environmental
                 sustainability compared to cloud providers, where
                 frequent hardware turnover contributes to rising carbon
                 emissions. This research contributes to the fields of
                 cloud computing, resource management, and sustainable
                 IT infrastructure by providing a replicable, adaptable,
                 and financially viable alternative to traditional
                 cloud-based solutions. Future work will focus on
                 automating resource allocation, enhancing real-time
                 monitoring, and integrating advanced security
                 mechanisms to further optimize performance and
                 usability.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Thomson:2025:NTB,
  author =       "Amanda Thomson and Leandros Maglaras and Naghmeh
                 Moradpoor",
  title =        "A Novel {TLS}-Based Fingerprinting Approach That
                 Combines Feature Expansion and Similarity Mapping",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "120",
  day =          "7",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030120",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/120",
  abstract =     "Malicious domains are part of the landscape of the
                 internet but are becoming more prevalent and more
                 dangerous both to companies and to individuals. They
                 can be hosted on various technologies and serve an
                 array of content, including malware, command and
                 control and complex phishing sites that are designed to
                 deceive and expose. Tracking, blocking and detecting
                 such domains is complex, and very often it involves
                 complex allowlist or denylist management or SIEM
                 integration with open-source TLS fingerprinting
                 techniques. Many fingerprinting techniques, such as
                 JARM and JA3, are used by threat hunters to determine
                 domain classification, but with the increase in TLS
                 similarity, particularly in CDNs, they are becoming
                 less useful. The aim of this paper was to adapt and
                 evolve open-source TLS fingerprinting techniques with
                 increased features to enhance granularity and to
                 produce a similarity-mapping system that would enable
                 the tracking and detection of previously unknown
                 malicious domains. This was achieved by enriching TLS
                 fingerprints with HTTP header data and producing a
                 fine-grain similarity visualisation that represented
                 high-dimensional data using MinHash and
                 Locality-Sensitive Hashing. Influence was taken from
                 the chemistry domain, where the problem of
                 high-dimensional similarity in chemical fingerprints is
                 often encountered. An enriched fingerprint was
                 produced, which was then visualised across three
                 separate datasets. The results were analysed and
                 evaluated, with 67 previously unknown malicious domains
                 being detected based on their similarity to known
                 malicious domains and nothing else. The
                 similarity-mapping technique produced demonstrates
                 definite promise in the arena of early detection of
                 malware and phishing domains.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Giotopoulos:2025:DWM,
  author =       "Konstantinos C. Giotopoulos and Dimitrios
                 Michalopoulos and Gerasimos Vonitsanos and Dimitris
                 Papadopoulos and Ioanna Giannoukou and Spyros Sioutas",
  title =        "Dynamic Workload Management System in the Public
                 Sector: a Comparative Analysis",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "119",
  day =          "6",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030119",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/119",
  abstract =     "Efficient human resource management is critical to
                 public sector performance, particularly in dynamic
                 environments where traditional systems struggle to
                 adapt to fluctuating workloads. The increasing
                 complexity of public sector operations and the need for
                 equitable task allocation highlight the limitations of
                 conventional evaluation methods, which often fail to
                 account for variations in employee performance and
                 workload demands. This study addresses these challenges
                 by optimizing load distribution through predicting
                 employee capability using data-driven approaches,
                 ensuring efficient resource utilization and enhanced
                 productivity. Using a dataset encompassing
                 public/private sector experience, educational history,
                 and age, we evaluate the effectiveness of seven machine
                 learning algorithms: Linear Regression, Artificial
                 Neural Networks (ANNs), Adaptive Neuro-Fuzzy Inference
                 System (ANFIS), Support Vector Machine (SVM), Gradient
                 Boosting Machine (GBM), Bagged Decision Trees, and
                 XGBoost in predicting employee capability and
                 optimizing task allocation. Performance is assessed
                 through ten evaluation metrics, including Mean Squared
                 Error (MSE), Root Mean Squared Error (RMSE), Mean
                 Absolute Error (MAE), and Mean Absolute Percentage
                 Error (MAPE), ensuring a comprehensive assessment of
                 accuracy, robustness, and bias. The results demonstrate
                 ANFIS as the superior model, consistently outperforming
                 other algorithms across all metrics. By synergizing
                 fuzzy logic's capacity to model uncertainty with neural
                 networks' adaptive learning, ANFIS effectively captures
                 non-linear relationships and variations in employee
                 performance, enabling precise capability predictions in
                 dynamic environments. This research highlights the
                 transformative potential of machine learning in public
                 sector workforce management, underscoring the role of
                 data-driven decision-making in improving task
                 allocation, operational efficiency, and resource
                 utilization.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Trigka:2025:ECC,
  author =       "Maria Trigka and Elias Dritsas",
  title =        "Edge and Cloud Computing in Smart Cities",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "118",
  day =          "6",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030118",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/118",
  abstract =     "The evolution of smart cities is intrinsically linked
                 to advancements in computing paradigms that support
                 real-time data processing, intelligent decision-making,
                 and efficient resource utilization. Edge and cloud
                 computing have emerged as fundamental pillars that
                 enable scalable, distributed, and latency-aware
                 services in urban environments. Cloud computing
                 provides extensive computational capabilities and
                 centralized data storage, whereas edge computing
                 ensures localized processing to mitigate network
                 congestion and latency. This survey presents an
                 in-depth analysis of the integration of edge and cloud
                 computing in smart cities, highlighting architectural
                 frameworks, enabling technologies, application domains,
                 and key research challenges. The study examines
                 resource allocation strategies, real-time analytics,
                 and security considerations, emphasizing the synergies
                 and trade-offs between cloud and edge computing
                 paradigms. The present survey also notes future
                 directions that address critical challenges, paving the
                 way for sustainable and intelligent urban
                 development.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Avila-Cortes:2025:EMS,
  author =       "Ojilvie Avila-Cort{\'e}s and Sa{\'u}l E. Pomares
                 Hern{\'a}ndez and Julio C{\'e}sar P{\'e}rez-Sansalvador
                 and Lil Mar{\'\i}a Xibai
                 Rodr{\'\i}guez-Henr{\'\i}quez",
  title =        "Emergency Messaging System for Urban Vehicular
                 Networks Inspired by Social Insects' Stigmergic
                 Communication",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "117",
  day =          "6",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030117",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/117",
  abstract =     "For occupant safety in vehicular networks, emergency
                 messages derived from vehicular incidents should be
                 exchanged only during their validity period and in
                 zones containing involved entities. Problems arise for
                 mobile entities in vehicular networks that change their
                 location over time, where data may be further
                 communicated in out-of-context space and time. Current
                 solutions extend from the naive assumption of notifying
                 every entity in the network about emergencies with data
                 flooding and clusters and by means of specific
                 communication only in the affected zones-geo-routing-of
                 incidents' relative data. However, delivering useless
                 data to uninvolved entities results in wasted resources
                 and more overheads in the former cases and the work of
                 obtaining knowledge and secondary site services from
                 neighbors in the latter. In this paper, we propose that
                 the common task of disseminating emergency messages for
                 occupant safety among entities should only be
                 communicated only where and when useful, namely, if
                 spatio-temporal constraints apply regarding those
                 incidents. Our solution is inspired by the
                 communication of working social insects that exchange
                 data through pheromones regardless of closeness or
                 knowledge among colony members for food retrieval. The
                 results show that communication based on space-time
                 constraints makes better use of resources than other
                 solutions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Messina:2025:NSA,
  author =       "Fabrizio Messina and Domenico Rosaci and Giuseppe M.
                 L. Sarn{\`e}",
  title =        "A Neural-Symbolic Approach to Extract Trust Patterns
                 in {IoT} Scenarios",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "116",
  day =          "6",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030116",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/116",
  abstract =     "Trust and reputation relationships among objects
                 represent key aspects of smart IoT object communities
                 with social characteristics. In this context, several
                 trustworthiness models have been presented in the
                 literature that could be applied to IoT scenarios;
                 however, most of these approaches use scalar measures
                 to represent different dimensions of trust, which are
                 then integrated into a single global trustworthiness
                 value. Nevertheless, this scalar approach within the
                 IoT context holds a few limitations that emphasize the
                 need for models that can capture complex trust
                 relationships beyond vector-based representations. To
                 overcome these limitations, we already proposed a novel
                 trust model where the trust perceived by one object
                 with respect to another is represented by a directed,
                 weighted graph. In this model, called T-pattern, the
                 vertices represent individual trust dimensions, and the
                 arcs capture the relationships between these
                 dimensions. This model allows the IoT community to
                 represent scenarios where an object may lack direct
                 knowledge of a particular trust dimension, such as
                 reliability, but can infer it from another dimension,
                 like honesty. The proposed model can represent trust
                 structures of the type described, where multiple trust
                 dimensions are interdependent. This work represents a
                 further contribution by presenting the first real
                 implementation of the T-pattern model, where a
                 neural-symbolic approach has been adopted as inference
                 engine. We performed experiments that demonstrate the
                 capability in inferring trust of both the T-pattern and
                 this specific implementation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ranasinghe:2025:CEC,
  author =       "Daneesha Ranasinghe and Nayomi Kankanamge and Chathura
                 {De Silva} and Nuwani Kangana and Rifat Mahamood and
                 Tan Yigitcanlar",
  title =        "{CityBuildAR}: Enhancing Community Engagement in
                 Placemaking Through Mobile Augmented Reality",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "115",
  day =          "6",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030115",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/115",
  abstract =     "Mostly, public places are planned and designed by
                 professionals rather engaging the community in the
                 design process. Even if the community engaged, the
                 engagement process was limited to hand drawings, manual
                 mappings, or public discussions, which limited the
                 general public to visualize and well-communicate their
                 aspirations with the professionals. Against this
                 backdrop, this study intends to develop a mobile
                 application called ``CityBuildAR'', which uses
                 Augmented Reality technology that allows the end user
                 to visualize their public spaces in a way they want.
                 CityBuildAR was developed by the authors using the
                 Unity Real-Time Development Platform, and the app was
                 developed for an Android Operating System. The app was
                 used to assess community interests in designing open
                 spaces by categorizing participants into three groups:
                 those with limited, average, and professional knowledge
                 of space design. The open cafeteria of the University
                 of Moratuwa, Sri Lanka served as the testbed for this
                 study. The study findings revealed that: (a) Mobile
                 Augmented Reality is an effective way to engage people
                 with limited knowledge in space design to express their
                 design thinking, (b) Compared to professionals, the
                 general public wanted to have more green elements in
                 the public space; (c) Compared to the professionals,
                 the general public who were not conversant with the
                 designing skills found the app more useful to express
                 their ideas. The study guides urban authorities in
                 their placemaking efforts by introducing a novel
                 approach to effectively capture community ideas for
                 creating inclusive public spaces.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Xi:2025:SNI,
  author =       "Tieqi Xi and Qiuhua Zheng and Chuanhui Cheng and Ting
                 Wu and Guojie Xie and Xuebiao Qian and Haochen Ye and
                 Zhenyu Sun",
  title =        "{SwiftSession}: a Novel Incremental and Adaptive
                 Approach to Rapid Traffic Classification by Leveraging
                 Local Features",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "114",
  day =          "3",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030114",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/114",
  abstract =     "Network traffic classification is crucial for
                 effective security management. However, the increasing
                 prevalence of encrypted traffic and the confidentiality
                 of protocol details have made this task more
                 challenging. To address this issue, we propose a
                 progressive, adaptive traffic classification method
                 called SwiftSession, designed to achieve real-time and
                 accurate classification. SwiftSession extracts
                 statistical and sequential features from the first K
                 packets of traffic. Statistical features capture
                 overall characteristics, while sequential features
                 reflect communication patterns. An initial
                 classification is conducted based on the first K
                 packets during the classification process. If the
                 prediction meets the predefined probability threshold,
                 processing stops; otherwise, additional packets are
                 received. This progressive approach dynamically adjusts
                 the required packets, enhancing classification
                 efficiency. Experimental results show that traffic can
                 be effectively classified by using only the initial K
                 packets. Moreover, on most datasets, the classification
                 time is reduced by more than 70\%. Unlike existing
                 methods, SwiftSession enhances the classification speed
                 while ensuring classification accuracy.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Jones:2025:CTB,
  author =       "Nicholas Jones and Md Whaiduzzaman and Tony Jan and
                 Amr Adel and Ammar Alazab and Afnan Alkreisat",
  title =        "A {CIA} Triad-Based Taxonomy of Prompt Attacks on
                 Large Language Models",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "113",
  day =          "3",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030113",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/113",
  abstract =     "The rapid proliferation of Large Language Models
                 (LLMs) across industries such as healthcare, finance,
                 and legal services has revolutionized modern
                 applications. However, their increasing adoption
                 exposes critical vulnerabilities, particularly through
                 adversarial prompt attacks that compromise LLM
                 security. These prompt-based attacks exploit weaknesses
                 in LLMs to manipulate outputs, leading to breaches of
                 confidentiality, corruption of integrity, and
                 disruption of availability. Despite their significance,
                 existing research lacks a comprehensive framework to
                 systematically understand and mitigate these threats.
                 This paper addresses this gap by introducing a taxonomy
                 of prompt attacks based on the Confidentiality,
                 Integrity, and Availability (CIA) triad, an important
                 cornerstone of cybersecurity. This structured taxonomy
                 lays the foundation for a unique framework of prompt
                 security engineering, which is essential for
                 identifying risks, understanding their mechanisms, and
                 devising targeted security protocols. By bridging this
                 critical knowledge gap, the present study provides
                 actionable insights that can enhance the resilience of
                 LLM to ensure their secure deployment in high-stakes
                 and real-world environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Stoyanov:2025:RMA,
  author =       "Stanimir Stoyanov and Emil Doychev and Asya
                 Stoyanova-Doycheva and Veneta Tabakova-Komsalova and
                 Ivan Stoyanov and Iliya Nedelchev",
  title =        "A Regional Multi-Agent Air Monitoring Platform",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "112",
  day =          "3",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030112",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/112",
  abstract =     "Plovdiv faces significant air pollution challenges due
                 to geographic, climatic, and industrial factors, making
                 accurate air quality assessment critical. This study
                 presents a hybrid multi-agent platform that integrates
                 symbolic and sub-symbolic artificial intelligence to
                 improve the reliability of air quality monitoring. The
                 platform features a BDI agent, developed using JaCaMo,
                 for processing real-time sensor measurements and a
                 ReAct agent, implemented with LangChain, to incorporate
                 external data sources and perform advanced analytics.
                 By combining these AI approaches, the platform enhances
                 data integration, detects anomalies, and resolves
                 discrepancies between conflicting air quality reports.
                 Furthermore, its scalable and adaptable architecture
                 lays the foundation for future advancements in
                 environmental monitoring. This research represents the
                 first stage in developing an AI-powered system that
                 supports more objective and data-driven decision-making
                 for air quality management in Plovdiv.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Memon:2025:FAS,
  author =       "Shuaib K. Memon and Md Akbar Hossain and Nurul I.
                 Sarkar",
  title =        "Frame Aggregation with Simple Block Acknowledgement
                 Mechanism to Provide Strict Quality of Service
                 Guarantee to Emergency Traffic in Wireless Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "111",
  day =          "3",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030111",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/111",
  abstract =     "This paper proposes a frame aggregation with a simple
                 block acknowledgement (FASBA) mechanism to provide a
                 strict QoS guarantee to life-saving emergency traffic
                 in wireless local area networks. This work builds on
                 our previous work on a multi-preemptive enhanced
                 distributed channel access protocol called MP-EDCA. The
                 main difference between FASBA and MP-EDCA is that
                 MP-EDCA does not provide a strict QoS guarantee to
                 life-saving emergency traffic (e.g., ambulance calls),
                 especially in high-load conditions. Our proposed FASBA
                 protocol solves the problems of achieving a strict QoS
                 guarantee to life-saving emergency traffic. The strict
                 QoS guarantee is achieved by aggregating multiple
                 frames with a two-bit block acknowledgement for
                 transmissions. FASBA assures guaranteed network
                 services by reducing MAC overheads; consequently, it
                 offers higher throughput, lower packet delays, and
                 accommodates a larger number of life-saving emergency
                 nodes during emergencies. The performance of the
                 proposed FASBA is validated by Riverbed Modeler and
                 MATLAB 2024a-based simulation. Results obtained show
                 that the proposed FASBA offers about 30\% lower delays,
                 17\% higher throughput, and 60\% lower retransmission
                 attempts than MP-EDCA under high-traffic loads.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Barrile:2025:DUD,
  author =       "Vincenzo Barrile and Emanuela Genovese and Clemente
                 Maesano and Sonia Calluso and Maurizio Pasquale Manti",
  title =        "Developing an Urban Digital Twin for Environmental and
                 Risk Assessment: a Case Study on Public Lighting and
                 Hydrogeological Risk",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "110",
  day =          "1",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030110",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/110",
  abstract =     "Improvements in immersive technology are opening up
                 new opportunities for land management and urban
                 planning, enabling the creation of detailed virtual
                 models for examining and simulating real-world short-,
                 medium-, and long-term scenarios. The goal of this
                 research is to present the creation of an urban digital
                 twin based on a virtual reality city replica, that
                 models and visualizes the urban environment in three
                 dimensions using advanced geomatics techniques and IoT
                 technologies. The methodology focuses on two case
                 studies that utilize environmental analysis and virtual
                 simulation: assessing hydrogeological risk and
                 evaluating public light pollution. The Cesium platform
                 was employed to build high-precision 3D models based on
                 topographic, meteorological, and infrastructure data.
                 The proposed methodology calculated a correlation
                 between light pollution and CO 2 equal to 0.51 and a
                 correlation between precipitation, slope, and risk area
                 higher than 0.80. The most critical and high-risk
                 classes are as follows: Dense Discontinuous Urban
                 Fabric, Roads and Associated Lands, Pastures, and
                 Forests. Results show how an urban digital twin can be
                 a powerful tool for monitoring and territorial
                 planning, with concrete applications in the public and
                 risk management fields. This study also highlights the
                 importance of geomatics technologies in the creation of
                 realistic and functional virtual environments for the
                 assessment and sustainable management of urban
                 resources.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Albelaihi:2025:MPR,
  author =       "Rana Albelaihi",
  title =        "Mobility Prediction and Resource-Aware Client
                 Selection for Federated Learning in {IoT}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "109",
  day =          "1",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030109",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/109",
  abstract =     "This paper presents the Mobility-Aware Client
                 Selection (MACS) strategy, developed to address the
                 challenges associated with client mobility in Federated
                 Learning (FL). FL enables decentralized machine
                 learning by allowing collaborative model training
                 without sharing raw data, preserving privacy. However,
                 client mobility and limited resources in IoT
                 environments pose significant challenges to the
                 efficiency and reliability of FL. MACS is designed to
                 maximize client participation while ensuring timely
                 updates under computational and communication
                 constraints. The proposed approach incorporates a
                 Mobility Prediction Model to forecast client
                 connectivity and resource availability and a
                 Resource-Aware Client Evaluation mechanism to assess
                 eligibility based on predicted latencies. MACS
                 optimizes client selection, improves convergence rates,
                 and enhances overall system performance by employing
                 these predictive capabilities and a dynamic resource
                 allocation strategy. The evaluation includes
                 comparisons with advanced baselines such as
                 Reinforcement Learning-based FL (RL-based) and Deep
                 Learning-based FL (DL-based), in addition to Static and
                 Random selection methods. For the CIFAR dataset, MACS
                 achieved a final accuracy of 95\%, outperforming Static
                 selection (85\%), Random selection (80\%), RL-based FL
                 (90\%), and DL-based FL (93\%). Similarly, for the
                 MNIST dataset, MACS reached 98\% accuracy, surpassing
                 Static selection (92\%), Random selection (88\%),
                 RL-based FL (94\%), and DL-based FL (96\%).
                 Additionally, MACS consistently required fewer
                 iterations to achieve target accuracy levels,
                 demonstrating its efficiency in dynamic IoT
                 environments. This strategy provides a scalable and
                 adaptable solution for sustainable federated learning
                 across diverse IoT applications, including smart
                 cities, healthcare, and industrial automation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Reina:2025:DSB,
  author =       "J. D. Morillo Reina and T. J. Mateo Sanguino",
  title =        "Decentralized and Secure Blockchain Solution for
                 Tamper-Proof Logging Events",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "108",
  day =          "1",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030108",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/108",
  abstract =     "Log files are essential assets for IT engineers
                 engaged in the security of server and computer systems.
                 They provide crucial information for identifying
                 malicious events, conducting cybersecurity incident
                 analyses, performing audits, system maintenance, and
                 ensuring compliance with security regulations.
                 Nevertheless, there is still the possibility of
                 deliberate data manipulation by own personnel,
                 especially with regard to system access and
                 configuration changes, where error tracking or
                 debugging traces are vital. To address tampering of log
                 files, this work proposes a solution to ensure data
                 integrity, immutability, and non-repudiation through
                 different blockchain-based public registry systems.
                 This approach offers an additional layer of security
                 through a decentralized, tamper-resistant ledger. To
                 this end, this manuscript aims to provide a solid
                 guideline for creating secure log storage systems. For
                 this purpose, methodologies and experiments using two
                 different blockchains are presented to demonstrate
                 their effectiveness in various contexts, such as
                 transactions with and without metadata. The findings
                 suggest that Solana's response times make it well
                 suited for environments with moderately critical
                 records requiring certification. In contrast, Cardano
                 shows higher response times, thus making it suitable
                 for less frequent events with metadata that requires
                 legitimacy.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mulo:2025:NCH,
  author =       "John Mulo and Hengshuo Liang and Mian Qian and Milon
                 Biswas and Bharat Rawal and Yifan Guo and Wei Yu",
  title =        "Navigating Challenges and Harnessing Opportunities:
                 Deep Learning Applications in {Internet of Medical
                 Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "107",
  day =          "1",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030107",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/107",
  abstract =     "Integrating deep learning (DL) with the Internet of
                 Medical Things (IoMT) is a paradigm shift in modern
                 healthcare, offering enormous opportunities for patient
                 care, diagnostics, and treatment. Implementing DL with
                 IoMT has the potential to deliver better diagnosis,
                 treatment, and patient management. However, the
                 practical implementation has challenges, including data
                 quality, privacy, interoperability, and limited
                 computational resources. This survey article provides a
                 conceptual IoMT framework for healthcare, synthesizes
                 and identifies the state-of-the-art solutions that
                 tackle the challenges of the current applications of
                 DL, and analyzes existing limitations and potential
                 future developments. Through an analysis of case
                 studies and real-world implementations, this work
                 provides insights into best practices and lessons
                 learned, including the importance of robust data
                 preprocessing, integration with legacy systems, and
                 human-centric design. Finally, we outline future
                 research directions, emphasizing the development of
                 transparent, scalable, and privacy-preserving DL models
                 to realize the full potential of IoMT in healthcare.
                 This survey aims to serve as a foundational reference
                 for researchers and practitioners seeking to navigate
                 the challenges and harness the opportunities in this
                 rapidly evolving field.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Martinez-Morfa:2025:FLS,
  author =       "Mario Mart{\'\i}nez-Morfa and Carlos Ruiz de Mendoza
                 and Cristina Cervell{\'o}-Pastor and Sebastia
                 Sallent-Ribes",
  title =        "Federated Learning System for Dynamic Radio\slash
                 {MEC} Resource Allocation and Slicing Control in Open
                 Radio Access Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "106",
  day =          "26",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030106",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/106",
  abstract =     "The evolution of cellular networks from
                 fifth-generation (5G) architectures to beyond 5G (B5G)
                 and sixth-generation (6G) systems necessitates
                 innovative solutions to overcome the limitations of
                 traditional Radio Access Network (RAN) infrastructures.
                 Existing monolithic and proprietary RAN components
                 restrict adaptability, interoperability, and optimal
                 resource utilization, posing challenges in meeting the
                 stringent requirements of next-generation applications.
                 The Open Radio Access Network (O-RAN) and Multi-Access
                 Edge Computing (MEC) have emerged as transformative
                 paradigms, enabling disaggregation, virtualization, and
                 real-time adaptability-which are key to achieving
                 ultra-low latency, enhanced bandwidth efficiency, and
                 intelligent resource management in future cellular
                 systems. This paper presents a Federated Deep
                 Reinforcement Learning (FDRL) framework for dynamic
                 radio and edge computing resource allocation and
                 slicing management in O-RAN environments. An Integer
                 Linear Programming (ILP) model has also been developed,
                 resulting in the proposed FDRL solution drastically
                 reducing the system response time. On the other hand,
                 unlike centralized Reinforcement Learning (RL)
                 approaches, the proposed FDRL solution leverages
                 Federated Learning (FL) to optimize performance while
                 preserving data privacy and reducing communication
                 overhead. Comparative evaluations against centralized
                 models demonstrate that the federated approach improves
                 learning efficiency and reduces bandwidth consumption.
                 The system has been rigorously tested across multiple
                 scenarios, including multi-client O-RAN environments
                 and loss-of-synchronization conditions, confirming its
                 resilience in distributed deployments. Additionally, a
                 case study simulating realistic traffic profiles
                 validates the proposed framework's ability to
                 dynamically manage radio and computational resources,
                 ensuring efficient and adaptive O-RAN slicing for
                 diverse and high-mobility scenarios.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ramos:2025:UGC,
  author =       "Eva Correia Ramos and C{\'e}lia M. Q. Ramos",
  title =        "User-Generated Content and Its Impact on Purchase
                 Intent for Tourism Products: a Comparative Analysis of
                 Millennials and Centennials on {TikTok}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "105",
  day =          "25",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030105",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/105",
  abstract =     "In an increasingly technological society, online
                 social networks are essential to support consumer
                 purchasing decisions, primarily through User Generated
                 Content (UGC). In this research, we look at the
                 influence of UGC on purchase intent applied to the
                 tourism product on the TikTok social network. In this
                 sense, a survey was applied to TikTok users aged
                 between 18 and 42 to compare their behaviour with that
                 of the two generations: Millennials and Centennials.
                 The results indicate a relationship of influence
                 between credibility and the usefulness of information
                 and between usefulness and social influence on the
                 intention to buy tourism products and services. In
                 addition, a comparison was made between the results of
                 the sample of individuals belonging to the Millennial
                 Generation and the sample of individuals belonging to
                 the Centennial Generation, with the main discrepancy in
                 the results being the relationship between the need for
                 information and the usefulness of information. These
                 insights pave the way for further research aimed at
                 establishing more robust conclusions in this area.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chalyi:2025:ABS,
  author =       "Oleksii Chalyi and Kestutis Driaunys and Vytautas
                 Rudzionis",
  title =        "Assessing Browser Security: a Detailed Study Based on
                 {CVE} Metrics",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "104",
  day =          "25",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030104",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/104",
  abstract =     "This study systematically evaluates the
                 vulnerabilities of modern web browsers using developed
                 indices derived from the CVE database, including I CVE,
                 I CVSS, I R and I T. These indices incorporate metrics
                 such as vulnerability severity and risks, along with
                 browser popularity, to enable a balanced comparison of
                 browser security. The results highlight significant
                 differences in browser security: while Google Chrome
                 and Samsung Internet exhibited lower threat indices,
                 Mozilla Firefox demonstrated consistently higher
                 scores, indicating greater exposure to risks. These
                 observations a slightly contradict widespread opinion.
                 The findings emphasize the importance of timely
                 software updates in mitigating vulnerabilities, as many
                 incidents were linked to outdated browser versions.
                 This study also introduces a robust methodology for
                 assessing browser threats, providing a framework for
                 future research. Potential applications include
                 developing browser-based penetration testing systems to
                 simulate phishing and data extraction scenarios,
                 offering insights into user-specific risks and broader
                 organizational impacts. By combining theoretical
                 analysis with practical implications, this work
                 contributes to advancing browser security and lays the
                 foundation for future applied research in
                 cybersecurity.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Swacha:2025:GGL,
  author =       "Jakub Swacha and Artur Kulpa",
  title =        "{Gamitest}: a Game-like Online Student Assessment
                 System",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "103",
  day =          "24",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030103",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/103",
  abstract =     "The widespread availability of mobile devices has led
                 to the emergence of multiple gamified web and mobile
                 applications for online assessment of students during
                 classes. Their common weak side is that they focus
                 mostly on positive reinforcement, without exploiting
                 the pedagogical potential of loss and failure
                 experience; thus, they are far from an actual game-like
                 experience. In this paper, we present Gamitest, a
                 course-subject-agnostic web application for student
                 assessment that features an original game-like scheme
                 to improve students' perception of engagement and fun,
                 as well as to reduce their examination stress. The
                 results of the survey-based evaluation of the tool
                 indicate that its design goals have been met and allow
                 us to recommend it for consideration in various forms
                 of student assessment, as well as provide grounds for
                 future work on analyzing the tool's effects on
                 learning.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Muralinath:2025:MSE,
  author =       "Rashmi N. Muralinath and Vishwambhar Pathak and
                 Prabhat K. Mahanti",
  title =        "Metastable Substructure Embedding and Robust
                 Classification of Multichannel {EEG} Data Using
                 Spectral Graph Kernels",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "102",
  day =          "23",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030102",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/102",
  abstract =     "Classification of neurocognitive states from
                 Electroencephalography (EEG) data is complex due to
                 inherent challenges such as noise, non-stationarity,
                 non-linearity, and the high-dimensional and sparse
                 nature of connectivity patterns. Graph-theoretical
                 approaches provide a powerful framework for analysing
                 the latent state dynamics using connectivity measures
                 across spatio-temporal-spectral dimensions. This study
                 applies the graph Koopman embedding kernels (GKKE)
                 method to extract latent neuro-markers of seizures from
                 epileptiform EEG activity. EEG-derived graphs were
                 constructed using correlation and mean phase locking
                 value (mPLV), with adjacency matrices generated via
                 threshold-binarised connectivity. Graph kernels,
                 including Random Walk, Weisfeiler-Lehman (WL), and
                 spectral-decomposition (SD) kernels, were evaluated for
                 latent space feature extraction by approximating
                 Koopman spectral decomposition. The potential of graph
                 Koopman embeddings in identifying latent metastable
                 connectivity structures has been demonstrated with
                 empirical analyses. The robustness of these features
                 was evaluated using classifiers such as Decision Trees,
                 Support Vector Machine (SVM), and Random Forest, on
                 Epilepsy-EEG from the Children's Hospital Boston's
                 (CHB)-MIT dataset and cognitive-load-EEG datasets from
                 online repositories. The classification workflow
                 combining mPLV connectivity measure, WL graph Koopman
                 kernel, and Decision Tree (DT) outperformed the
                 alternative combinations, particularly considering the
                 accuracy (91.7\%) and F1-score (88.9\%), The
                 comparative investigation presented in results section
                 convinces that employing cost-sensitive learning
                 improved the F1-score for the mPLV-WL-DT workflow to
                 91\% compared to 88.9\% without cost-sensitive
                 learning. This work advances EEG-based neuro-marker
                 estimation, facilitating reliable assistive tools for
                 prognosis and cognitive training protocols.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhou:2025:EIE,
  author =       "Yuezhi Zhou and Xu Chen",
  title =        "Edge Intelligence: Edge Computing for {5G} and the
                 {Internet of Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "101",
  day =          "23",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030101",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/101",
  abstract =     "Classification of neurocognitive states from
                 Electroencephalography (EEG) data is complex due to
                 inherent challenges such as noise, non-stationarity,
                 non-linearity, and the high-dimensional and sparse
                 nature of connectivity patterns. Graph-theoretical
                 approaches provide a powerful framework for analysing
                 the latent state dynamics using connectivity measures
                 across spatio-temporal-spectral dimensions. This study
                 applies the graph Koopman embedding kernels (GKKE)
                 method to extract latent neuro-markers of seizures from
                 epileptiform EEG activity. EEG-derived graphs were
                 constructed using correlation and mean phase locking
                 value (mPLV), with adjacency matrices generated via
                 threshold-binarised connectivity. Graph kernels,
                 including Random Walk, Weisfeiler-Lehman (WL), and
                 spectral-decomposition (SD) kernels, were evaluated for
                 latent space feature extraction by approximating
                 Koopman spectral decomposition. The potential of graph
                 Koopman embeddings in identifying latent metastable
                 connectivity structures has been demonstrated with
                 empirical analyses. The robustness of these features
                 was evaluated using classifiers such as Decision Trees,
                 Support Vector Machine (SVM), and Random Forest, on
                 Epilepsy-EEG from the Children's Hospital Boston's
                 (CHB)-MIT dataset and cognitive-load-EEG datasets from
                 online repositories. The classification workflow
                 combining mPLV connectivity measure, WL graph Koopman
                 kernel, and Decision Tree (DT) outperformed the
                 alternative combinations, particularly considering the
                 accuracy (91.7\%) and F1-score (88.9\%), The
                 comparative investigation presented in results section
                 convinces that employing cost-sensitive learning
                 improved the F1-score for the mPLV-WL-DT workflow to
                 91\% compared to 88.9\% without cost-sensitive
                 learning. This work advances EEG-based neuro-marker
                 estimation, facilitating reliable assistive tools for
                 prognosis and cognitive training protocols.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gonzalez-Cancelas:2025:IBT,
  author =       "Nicoletta Gonz{\'a}lez-Cancelas and Javier
                 Vaca-Cabrero and Alberto Camarero-Orive",
  title =        "{IoV} and Blockchain for Traffic Optimization in
                 {Ro-Ro} Terminals: a Case Study in the {Spanish} Port
                 System",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "99",
  day =          "22",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030099",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/99",
  abstract =     "This study examines the integration of the Internet of
                 Vehicles (IoV) and blockchain as tools to optimize
                 traffic management in Roll-on/Roll-off (Ro-Ro)
                 terminals within the Spanish port system. Faced with
                 increasing operational complexity, these technologies
                 present innovative solutions to enhance efficiency,
                 reduce waiting times, and ensure transparency in data
                 management. The methodology follows five main phases:
                 analysis of the current scenario, establishment of a
                 baseline, calculations to evaluate key outcomes,
                 analysis of blockchain implementation, and discussion
                 of results. Key variables include waiting times,
                 vehicular flow, CO 2 emissions, and operational costs,
                 comparing manual and automated scenarios. The findings
                 reveal that the combined use of IoV and blockchain can
                 increase vehicular flow by up to 70\%, reduce waiting
                 times by 2.56 min, and decrease CO 2 emissions by 57.74
                 kg per hour. Additionally, automation significantly
                 reduces operational costs, yielding average savings of
                 over EUR 500 per hour. This study concludes that
                 adopting these technologies transforms port operations
                 by fostering sustainability, efficiency, and safety.
                 However, challenges remain, including high initial
                 implementation costs and system interoperability
                 issues. This work underscores the need for strategic
                 approaches to overcome these barriers and positions
                 Spanish ports as potential leaders in logistics
                 innovation, aligning with global demands for
                 sustainable, efficient, and transparent port
                 operations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2025:ALL,
  author =       "Jinying Li and Ananda Maiti",
  title =        "Applying Large Language Model Analysis and Backend
                 {Web} Services in Regulatory Technologies for
                 Continuous Compliance Checks",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "100",
  day =          "22",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030100",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/100",
  abstract =     "Regulatory technologies (RegTechs) are a set of
                 electronic and digital technologies applied to check
                 compliance in industrial processes. Such applications
                 also aim to simplify the process of data collection and
                 exchange according to the expected format over the
                 cloud or the internet. Industrial processes are
                 required to meet basic regulatory requirements
                 according to law and follow a set of industry
                 practices. Industry practices must be compliant with
                 the basic regulatory requirements. Such applications
                 also need a high level of privacy to protect the
                 individual participant's data from competitors but are
                 revealed to the relevant regulatory agencies. However,
                 there cannot be a standard data procurement method, as
                 the industrial processes are different for individual
                 businesses and often involve various stages of data
                 collection with different aims. Also, the regulatory
                 requirements may be changed over time. These challenges
                 can be addressed over an online system that uses large
                 language models (LLM) to perform continuous compliance
                 checks. With LLMs, RegTech can be easily scaled up to
                 meet new requirements. It can also help with data
                 analysis and reformatting for different stakeholders in
                 RegTech, such as producers, supply chains, regulators,
                 and financial institutions. It can check for acceptable
                 values with regards to RegTech through either numeric
                 comparisons or enumerations matching. In this paper, we
                 propose a comprehensive RegTech framework backed by LLM
                 and web services. We propose a method to measure the
                 accuracy of LLM in returning appropriate responses for
                 RegTech queries and herein analyze several LLMs to
                 conclude that they are satisfactory for basic tasks,
                 but a dedicated LLM is needed for RegTech. Furthermore,
                 we test the LLM's tool-calling capabilities to identify
                 and use dedicated functions in the form of web services
                 to enhance the analytical accuracy and consistency of
                 RegTech-related prompts.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kanjanapruthipong:2025:BBD,
  author =       "Wata Kanjanapruthipong and Sirapat Boonkrong",
  title =        "Blockchain-Based Decentralised Authentication in
                 Closed Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "98",
  day =          "21",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030098",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/98",
  abstract =     "Traditional authentication systems with an
                 authentication server that handles authentication
                 requests from many clients have a major weakness, i.e.,
                 a single point of failure. This study presents an
                 authentication paradigm based on blockchain, which
                 provides a decentralised and distributed mechanism for
                 processing authentication. The security of the proposed
                 design of the decentralised authentication protocol was
                 evaluated using Gong-Needham-Yahalom (GNY) logic. The
                 results indicated that the protocol was secure against
                 various attacks. This protocol has significant
                 potential for enhancing secure identity management in
                 sectors where privacy and data integrity are most
                 important.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gaon:2025:OEV,
  author =       "Tal Gaon and Yovel Gabay and Miri Weiss Cohen",
  title =        "Optimizing Electric Vehicle Routing Efficiency Using
                 {$K$}-Means Clustering and Genetic Algorithms",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "97",
  day =          "20",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030097",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/97",
  abstract =     "Route planning for electric vehicles (EVs) is a
                 critical challenge in sustainable transportation, as it
                 directly addresses concerns about greenhouse gas
                 emissions and energy efficiency. This study presents a
                 novel approach that combines K-means clustering and GA
                 optimization to create dynamic, real-world applicable
                 routing solutions. This framework incorporates
                 practical challenges, such as charging station queue
                 lengths, which significantly influence travel time and
                 energy consumption. Using K-means clustering, the
                 methodology groups charging stations based on
                 geographical proximity, allowing for optimal stop
                 selection and minimizing unnecessary detours. GA
                 optimization is used to refine these routes by
                 evaluating key factors, including travel distance,
                 queue dynamics, and time, to determine paths with the
                 fewest charging stops while maintaining efficiency. By
                 integrating these two techniques, the proposed
                 framework achieves a balance between computational
                 simplicity and adaptability to changing conditions. A
                 series of experiments have demonstrated the framework's
                 ability to identify the shortest and least congested
                 routes with strategically placed charging stops. The
                 dynamic nature of the model ensures adaptability to
                 evolving real-world scenarios, such as fluctuating
                 queue lengths and travel demands. This research
                 demonstrates the effectiveness of this approach for
                 identifying the shortest, least congested routes with
                 the most optimal charging stations, resulting in
                 significant advancements in sustainable transportation
                 and EV route optimization.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{deCurto:2025:ITF,
  author =       "J. de Curt{\`o} and I. de Zarz{\`a} and Leandro
                 Sebasti{\'a}n Fervier and Victoria Sanagust{\'\i}n-Fons
                 and Carlos T. Calafate",
  title =        "An Institutional Theory Framework for Leveraging Large
                 Language Models for Policy Analysis and Intervention
                 Design",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "3",
  pages =        "96",
  day =          "20",
  month =        feb,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17030096",
  ISSN =         "1999-5903",
  bibdate =      "Fri Mar 28 06:12:07 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/3/96",
  abstract =     "This study proposes a comprehensive framework for
                 integrating data-driven approaches into policy analysis
                 and intervention strategies. The methodology is
                 structured around five critical components: data
                 collection, historical analysis, policy impact
                 assessment, predictive modeling, and intervention
                 design. Leveraging data-driven approaches capabilities,
                 the line of work enables advanced multilingual data
                 processing, advanced statistics in population trends,
                 evaluation of policy outcomes, and the development of
                 evidence-based interventions. A key focus is on the
                 theoretical integration of social order mechanisms,
                 including communication modes as institutional
                 structures, token optimization as an efficiency
                 mechanism, and institutional memory adaptation. A mixed
                 methods approach was used that included sophisticated
                 visualization techniques and use cases in the
                 hospitality sector, in global food security, and in
                 educational development. The framework demonstrates its
                 capacity to inform government and industry policies by
                 leveraging statistics, visualization, and AI-driven
                 decision support. We introduce the concept of
                 ``institutional intelligence''-the synergistic
                 integration of human expertise, AI capabilities, and
                 institutional theory-to create adaptive yet stable
                 policy-making systems. This research highlights the
                 transformative potential of data-driven approaches
                 combined with large language models in supporting
                 sustainable and inclusive policy-making processes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yang:2025:MQE,
  author =       "Jaewoo Yang and Hayun Kim and Junyung Ji and Younghoon
                 Kim",
  title =        "Mitigating Quantization Errors Due to Activation
                 Spikes in Gated Linear Unit-Based Large Language
                 Models",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "185",
  day =          "21",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040185",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/185",
  abstract =     "Modern large language models (LLMs) achieve
                 state-of-the-art performance through architectural
                 advancements but require high computational costs for
                 inference. Post-training quantization is a widely
                 adopted approach to reduce these costs by quantizing
                 weights and activations to lower precision, such as
                 INT8. However, we identify a critical challenge in
                 activation quantization for GLU (Gated Linear Unit)
                 variants, which are commonly used in the feed-forward
                 networks of modern LLMs like the LLaMA family.
                 Specifically, severe local quantization errors arise
                 due to excessively large activation magnitudes, which
                 we refer to as activation spikes, leading to
                 significant degradation in model performance. Our
                 analysis reveals a systematic pattern of these spikes:
                 they predominantly occur in the FFN (feed-forward
                 network) layers at the early and late layers of the
                 model and are concentrated on a small subset of tokens
                 rather than being uniformly distributed across a token
                 sequence. To mitigate this issue, we propose two
                 empirical methods: Quantization-free Module (QFeM) and
                 Quantization-free Prefix (QFeP), which isolate
                 activation spikes during quantization. Extensive
                 experiments demonstrated that our methods effectively
                 improve activation quantization, particularly in
                 coarse-grained quantization schemes, enhancing the
                 performance of LLMs with GLU variants and addressing
                 the limitations of existing quantization techniques.
                 The code for implementing our methods and reproducing
                 the experiments is publicly available our GitHub
                 repository.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bagchi:2025:BDE,
  author =       "Swarnadeep Bagchi and Ruair{\'\i} de Fr{\'e}in",
  title =        "Big-Delay Estimation for Speech Separation in Assisted
                 Living Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "184",
  day =          "21",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040184",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/184",
  abstract =     "Phase wraparound due to large inter-sensor spacings in
                 multi-channel demixing renders the DUET and AdRess
                 source separation algorithms-known for their low
                 computational complexity and effective speech demixing
                 performance-unsuitable for hearing-assisted living
                 applications, where such configurations are needed.
                 DUET is limited to relative delays of up to 7 samples,
                 given a sampling rate of Fs=16 Fs=16 Fs=16 kHz in
                 anechoic scenarios, while the AdRess algorithm is
                 constrained to instantaneous mixing problems. The task
                 of this paper is to improve the performance of
                 DUET-type time-frequency (TF) masks when microphones
                 are placed far apart. A significant challenge in
                 assistive hearing scenarios is phase wraparound caused
                 by large relative delays. We evaluate the performance
                 of a large relative delay estimation method, called the
                 Elevatogram, in the presence of significant phase
                 wraparound. We present extensions of DUET and AdRess,
                 termed Elevato-DUET and Elevato-AdRess, which are
                 effective in scenarios with relative delays of up to
                 200 samples. The findings demonstrate that
                 Elevato-AdRess not only outperforms Elevato-DUET in
                 terms of objective separation quality metrics-BSS\_Eval
                 and PEASS-but also achieves higher intelligibility
                 scores, as measured by the Perceptual Evaluation of
                 Speech Quality (PESQ) Mean Opinion Score (MOS) scores.
                 These findings suggest that the phase wraparound
                 limitations of DUET and AdRess algorithms in assistive
                 hearing scenarios involving large inter-microphone
                 spacing can be addressed by introducing the
                 Elevatogram-based Elevato-DUET and Elevato-AdRess
                 algorithms. These algorithms improve separation quality
                 and intelligibility, with Elevato-AdRess demonstrating
                 the best overall performance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Siam:2025:SDE,
  author =       "Md Kamrul Siam and Bilash Saha and Md Mehedi Hasan and
                 Md Jobair Hossain Faruk and Nafisa Anjum and Sharaban
                 Tahora and Aiasha Siddika and Hossain Shahriar",
  title =        "Securing Decentralized Ecosystems: a Comprehensive
                 Systematic Review of Blockchain Vulnerabilities,
                 Attacks, and Countermeasures and Mitigation
                 Strategies",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "183",
  day =          "21",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040183",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/183",
  abstract =     "Blockchain technology has emerged as a transformative
                 innovation, providing a transparent, immutable, and
                 decentralized platform that underpins critical
                 applications across industries such as
                 cryptocurrencies, supply chain management, healthcare,
                 and finance. Despite their promise of enhanced security
                 and trust, the increasing sophistication of
                 cyberattacks has exposed vulnerabilities within
                 blockchain ecosystems, posing severe threats to their
                 integrity, reliability, and adoption. This study
                 presents a comprehensive and systematic review of
                 blockchain vulnerabilities by categorizing and
                 analyzing potential threats, including network-level
                 attacks, consensus-based exploits, smart contract
                 vulnerabilities, and user-centric risks. Furthermore,
                 the research evaluates existing countermeasures and
                 mitigation strategies by examining their effectiveness,
                 scalability, and adaptability to diverse blockchain
                 architectures and use cases. The study highlights the
                 critical need for context-aware security solutions that
                 address the unique requirements of various blockchain
                 applications and proposes a framework for advancing
                 proactive and resilient security designs. By bridging
                 gaps in the existing literature, this research offers
                 valuable insights for academics, industry
                 practitioners, and policymakers, contributing to the
                 ongoing development of robust and secure decentralized
                 ecosystems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Atoum:2025:CIT,
  author =       "Mohammed Salem Atoum and Ala Abdulsalam Alarood and
                 Eesa Alsolami and Adamu Abubakar and Ahmad K. {Al
                 Hwaitat} and Izzat Alsmadi",
  title =        "Cybersecurity Intelligence Through Textual Data
                 Analysis: a Framework Using Machine Learning and
                 Terrorism Datasets",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "182",
  day =          "21",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040182",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/182",
  abstract =     "This study examines multi-lexical data sources,
                 utilizing an extracted dataset from an open-source
                 corpus and the Global Terrorism Datasets (GTDs), to
                 predict lexical patterns that are directly linked to
                 terrorism. This is essential as specific patterns
                 within a textual context can facilitate the
                 identification of terrorism-related content. The
                 research methodology focuses on generating a corpus
                 from various published works and extracting texts
                 pertinent to ``terrorism''. Afterwards, we extract
                 additional lexical contexts of GTDs that directly
                 relate to terrorism. The integration of multi-lexical
                 data sources generates lexical patterns linked to
                 terrorism. Machine learning models were used to train
                 the dataset. We conducted two primary experiments and
                 analyzed the results. The analysis of data obtained
                 from open sources reveals that while the Extra Trees
                 model achieved the highest accuracy at 94.31\%, the
                 XGBoost model demonstrated superior overall performance
                 with a higher recall (81.32\%) and F1-Score (83.06\%)
                 after tuning, indicating a better balance between
                 sensitivity and precision. Similarly, on the GTD
                 dataset, XGBoost consistently outperformed other models
                 in recall and the F1-score, making it a more suitable
                 candidate for tasks where minimizing false negatives is
                 critical. This implies that we can establish a specific
                 co-occurrence and context within the terrorism dataset
                 from multiple lexical data sources in effectively
                 identifying certain multi-lexical patterns such as
                 ``Suicide Attack/Casualty'', ``Civilians/Victims'', and
                 ``Hostage Taking/Abduction'' across various
                 applications or contexts. This will facilitate the
                 development of a framework for understanding the
                 lexical patterns associated with terrorism.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gautam:2025:AUD,
  author =       "Abhilasha Gautam and Prabhat Thakur and Ghanshyam
                 Singh",
  title =        "Analysis of Universal Decoding Techniques for {6G}
                 Ultra-Reliable and Low-Latency Communication Scenario",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "181",
  day =          "21",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040181",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/181",
  abstract =     "Ultra-reliable and low-latency communication (URLLC)
                 in 6G networks is characterized by very high
                 reliability and very low latency to enable
                 mission-critical applications. The ability of a coding
                 scheme to support diverse use cases requires
                 flexibility on the part of the decoder. High
                 reliability and low latency require decoders with
                 improved error rate performance and reduced complexity.
                 This article investigates candidate universal decoding
                 algorithms for 6G communication scenarios. Universal
                 decoders work on a wide range of error-correcting
                 codes, making them scalable for different communication
                 protocols. This article undertakes the comparative
                 analysis and performance evaluation of the
                 code-agnostic decoding schemes, including automorphism
                 ensemble (AED), guessing random additive noise (GRAND),
                 ordered statistics (OSD), belief propagation (BPD), bit
                 flipping (BFD), and their variants. Simulations are
                 carried out in MATLAB (R2024a) for the error rate
                 performance of decoders, and plots are provided for the
                 comparative analysis from the results of inferred data.
                 The key findings in this paper highlight the
                 competitive advantage of universal decoding techniques
                 in comparison to the standardized CA-SCL decoding of
                 polar code. Consequently, this work will help in
                 identifying more efficient decoding algorithms for
                 potential 6G URLLC applications. We aim to provide an
                 insight into the scalability of universal decoding
                 techniques by exploring their key performance metrics
                 and comparing their performances.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alti:2025:AMU,
  author =       "Adel Alti and Abderrahim Lakehal",
  title =        "{AI-MDD-UX}: Revolutionizing E-Commerce User
                 Experience with Generative {AI} and Model-Driven
                 Development",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "180",
  day =          "20",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040180",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/180",
  abstract =     "E-commerce applications have emerged as key drivers of
                 digital transformation, reshaping consumer behavior and
                 driving demand for seamless online transactions.
                 Despite the growth of smart mobile technologies,
                 existing methods rely on fixed UI content that cannot
                 adjust to local cultural preferences and fluctuating
                 user behaviors. This paper explores the combination of
                 generative Artificial Intelligence (AI) technologies
                 with Model-Driven Development (MDD) to enhance
                 personalization, engagement, and adaptability in
                 e-commerce. Unlike static adaptation approaches,
                 generative AI enables real-time, adaptive interactions
                 tailored to individual needs, providing a more engaging
                 and adaptable user experience. The proposed framework
                 follows a three-tier architecture: first, it collects
                 and analyzes user behavior data from UI interactions;
                 second, it leverages MDD to model and personalize user
                 personas and interactions and third, AI techniques,
                 including generative AI and multi-agent reinforcement
                 learning, are applied to refine and optimize UI/UX
                 design. This automation-driven approach uses a
                 multi-agent system to continuously enhance AI-generated
                 layouts. Technical validation demonstrated strong user
                 engagement across diverse platforms and superior
                 performance in UI optimization, achieving an average
                 user satisfaction improvement of 2.3\% compared to
                 GAN-based models, 18.6\% compared to Bootstrap-based
                 designs, and 11.8\% compared to rule-based UI
                 adaptation. These results highlight generative
                 AI-driven MDD tools as a promising tool for e-commerce,
                 enhancing engagement, personalization, and
                 efficiency.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Reis:2025:EAR,
  author =       "Manuel J. C. S. Reis and Carlos Ser{\^o}dio",
  title =        "Edge {AI} for Real-Time Anomaly Detection in Smart
                 Homes",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "179",
  day =          "18",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040179",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/179",
  abstract =     "The increasing adoption of smart home technologies has
                 intensified the demand for real-time anomaly detection
                 to improve security, energy efficiency, and device
                 reliability. Traditional cloud-based approaches
                 introduce latency, privacy concerns, and network
                 dependency, making Edge AI a compelling alternative for
                 low-latency, on-device processing. This paper presents
                 an Edge AI-based anomaly detection framework that
                 combines Isolation Forest (IF) and Long Short-Term
                 Memory Autoencoder (LSTM-AE) models to identify
                 anomalies in IoT sensor data. The system is evaluated
                 on both synthetic and real-world smart home datasets,
                 including temperature, motion, and energy consumption
                 signals. Experimental results show that LSTM-AE
                 achieves higher detection accuracy (up to 93.6\%) and
                 recall but requires more computational resources. In
                 contrast, IF offers faster inference and lower power
                 consumption, making it suitable for constrained
                 environments. A hybrid architecture integrating both
                 models is proposed to balance accuracy and efficiency,
                 achieving sub-50 ms inference latency on embedded
                 platforms such as Raspberry Pi and NVIDEA Jetson Nano.
                 Optimization strategies such as quantization reduced
                 LSTM-AE inference time by 76\% and power consumption by
                 35\%. Adaptive learning mechanisms, including federated
                 learning, are also explored to minimize cloud
                 dependency and enhance data privacy. These findings
                 demonstrate the feasibility of deploying real-time,
                 privacy-preserving, and energy-efficient anomaly
                 detection directly on edge devices. The proposed
                 framework can be extended to other domains such as
                 smart buildings and industrial IoT. Future work will
                 investigate self-supervised learning, transformer-based
                 detection, and deployment in real-world operational
                 settings.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ljubi:2025:DDC,
  author =       "Igor Ljubi and Zdravko Grgi{\'c} and Marin Vukovi{\'c}
                 and Gordan Gledec",
  title =        "Detecting Disinformation in {Croatian} Social Media
                 Comments",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "178",
  day =          "17",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040178",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/178",
  abstract =     "The frequency with which fake news or misinformation
                 is published on social networks is constantly
                 increasing. Users of social networks are confronted
                 with many different posts every day, often with
                 sensationalist titles and content of dubious veracity.
                 The problem is particularly common in times of
                 sensitive social or political situations, such as
                 epidemics of contagious diseases or elections. As such
                 messages can have an impact on democratic processes or
                 cause panic among the population, many countries and
                 the European Commission itself have recently stepped up
                 their activities to combat disinformation campaigns on
                 social networks. Since previous research has shown that
                 there are no tools available to combat disinformation
                 in the Croatian language, we proposed a framework to
                 detect potentially misinforming content in the comments
                 on social media. The case study was conducted with real
                 public comments published on Croatian Facebook pages.
                 The initial results of this framework were encouraging
                 as it can successfully classify and detect
                 disinformation content.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Falevai:2025:ETC,
  author =       "Ilaisaane Falevai and Farkhondeh Hassandoust",
  title =        "Enhancing Transplantation Care with {eHealth}:
                 Benefits, Challenges, and Key Considerations for the
                 Future",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "177",
  day =          "17",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040177",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/177",
  abstract =     "eHealth has transformed transplantation care by
                 enhancing communication between patients and clinics,
                 supporting self-management, and improving adherence to
                 medical advice. However, existing research on eHealth
                 in transplantation remains fragmented, lacking a
                 comprehensive understanding of its diverse users,
                 associated benefits and challenges, and key
                 considerations for intervention development. This
                 systematic review, conducted following the PRISMA
                 guidelines, analyzed the literature on eHealth in
                 transplantation published between 2018 and September
                 2023 across multiple databases. A total of 60 studies
                 were included, highlighting benefits such as improved
                 patient engagement, accessibility, empowerment, and
                 cost-efficiency. Three primary categories of barriers
                 were identified: knowledge and access barriers,
                 usability and implementation challenges, and trust
                 issues. Additionally, patient-centered design and
                 readiness were found to be crucial factors in
                 developing effective eHealth solutions. These findings
                 underscore the need for tailored, patient-centric
                 interventions to maximize the potential of eHealth in
                 transplantation care. Moreover, the success of eHealth
                 interventions in transplantation is increasingly
                 dependent on robust networking infrastructure,
                 cloud-based telemedicine systems, and secure
                 data-sharing platforms. These technologies facilitate
                 real-time communication between transplant teams and
                 patients, ensuring continuous care and monitoring.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zaidani:2025:ACR,
  author =       "Hajar Zaidani and Rim Koulali and Abderrahim Maizate
                 and Mohamed Ouzzif",
  title =        "Augmentation and Classification of Requests in
                 {Moroccan} Dialect to Improve Quality of Public
                 Service: a Comparative Study of Algorithms",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "176",
  day =          "17",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040176",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/176",
  abstract =     "Moroccan Law 55.19 aims to streamline administrative
                 procedures, fostering trust between citizens and public
                 administrations. To implement this law effectively and
                 enhance public service quality, it is essential to use
                 the Moroccan dialect to involve a wide range of people
                 by leveraging Natural Language Processing (NLP)
                 techniques customized to its specific linguistic
                 characteristics. It is worth noting that the Moroccan
                 dialect presents a unique linguistic landscape, marked
                 by the coexistence of multiple texts. Though it has
                 emerged as the preferred medium of communication on
                 social media, reaching wide audiences, its perceived
                 difficulty of comprehension remains unaddressed. This
                 article introduces a new approach to addressing these
                 challenges. First, we compiled and processed a dataset
                 of Moroccan dialect requests for public administration
                 documents, employing a new augmentation technique to
                 enhance its size and diversity. Second, we conducted
                 text classification experiments using various machine
                 learning algorithms, ranging from traditional methods
                 to advanced large language models (LLMs), to categorize
                 the requests into three classes. The results indicate
                 promising outcomes, with an accuracy of more than 80\%
                 for LLMs. Finally, we propose a chatbot system
                 architecture for deploying the most efficient
                 classification algorithm. This solution also contains a
                 voice assistant system that can contribute to the
                 social inclusion of illiterate people. The article
                 concludes by outlining potential avenues for future
                 research.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sheikh:2025:SEC,
  author =       "Abdul Manan Sheikh and Md. Rafiqul Islam and Mohamed
                 Hadi Habaebi and Suriza Ahmad Zabidi and Athaur Rahman
                 {Bin Najeeb} and Adnan Kabbani",
  title =        "A Survey on Edge Computing {(EC)} Security Challenges:
                 Classification, Threats, and Mitigation Strategies",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "175",
  day =          "16",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040175",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/175",
  abstract =     "Edge computing (EC) is a distributed computing
                 approach to processing data at the network edge, either
                 by the device or a local server, instead of centralized
                 data centers or the cloud. EC proximity to the data
                 source can provide faster insights, response time, and
                 bandwidth utilization. However, the distributed
                 architecture of EC makes it vulnerable to data security
                 breaches and diverse attack vectors. The edge paradigm
                 has limited availability of resources like memory and
                 battery power. Also, the heterogeneous nature of the
                 hardware, diverse communication protocols, and
                 difficulty in timely updating security patches exist. A
                 significant number of researchers have presented
                 countermeasures for the detection and mitigation of
                 data security threats in an EC paradigm. However, an
                 approach that differs from traditional data security
                 and privacy-preserving mechanisms already used in cloud
                 computing is required. Artificial Intelligence (AI)
                 greatly improves EC security through advanced threat
                 detection, automated responses, and optimized resource
                 management. When combined with Physical Unclonable
                 Functions (PUFs), AI further strengthens data security
                 by leveraging PUFs' unique and unclonable attributes
                 alongside AI's adaptive and efficient management
                 features. This paper investigates various edge security
                 strategies and cutting-edge solutions. It presents a
                 comparison between existing strategies, highlighting
                 their benefits and limitations. Additionally, the paper
                 offers a detailed discussion of EC security threats,
                 including their characteristics and the classification
                 of different attack types. The paper also provides an
                 overview of the security and privacy needs of the EC,
                 detailing the technological methods employed to address
                 threats. Its goal is to assist future researchers in
                 pinpointing potential research opportunities.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Almani:2025:DRA,
  author =       "Dimah Almani and Tim Muller and Steven Furnell",
  title =        "Distributed Reputation for Accurate Vehicle
                 Misbehavior Reporting {(DRAMBR)}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "174",
  day =          "15",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040174",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/174",
  abstract =     "Vehicle-to-Vehicle (V2V) communications technology
                 offers enhanced road safety, traffic efficiency, and
                 connectivity. In V2V, vehicles cooperate by
                 broadcasting safety messages to quickly detect and
                 avoid dangerous situations on time or to avoid and
                 reduce congestion. However, vehicles might misbehave,
                 creating false information and sharing it with
                 neighboring vehicles, such as, for example, failing to
                 report an observed accident or falsely reporting one
                 when none exists. If other vehicles detect such
                 misbehavior, they can report it. However, false
                 accusations also constitute misbehavior. In
                 disconnected areas with limited infrastructure, the
                 potential for misbehavior increases due to the scarcity
                 of Roadside Units (RSUs) necessary for verifying the
                 truthfulness of communications. In such a situation,
                 identifying malicious behavior using a standard
                 misbehaving management system is ineffective in areas
                 with limited connectivity. This paper presents a novel
                 mechanism, Distributed Reputation for Accurate
                 Misbehavior Reporting (DRAMBR), offering a fully
                 integrated reputation solution that utilizes reputation
                 to enhance the accuracy of the reporting system by
                 identifying misbehavior in rural networks. The system
                 operates in two phases: offline, using the Local
                 Misbehavior Detection Mechanism (LMDM), where vehicles
                 detect misbehavior and store reports locally, and
                 online, where these reports are sent to a central
                 reputation server. DRAMBR aggregates the reports and
                 integrates DBSCAN for clustering spatial and temporal
                 misbehavior reports, Isolation Forest for anomaly
                 detection, and Gaussian Mixture Models for
                 probabilistic classification of reports. Additionally,
                 Random Forest and XGBoost models are combined to
                 improve decision accuracy. DRAMBR distinguishes between
                 honest mistakes, intentional deception, and malicious
                 reporting. Using an existing mechanism, the updated
                 reputation is available even in an offline environment.
                 Through simulations, we evaluate our proposed
                 reputation system's performance, demonstrating its
                 effectiveness in achieving a reporting accuracy of
                 approximately 98\%. The findings highlight the
                 potential of reputation-based strategies to minimize
                 misbehavior and improve the reliability and security of
                 V2V communications, particularly in rural areas with
                 limited infrastructure, ultimately contributing to
                 safer and more reliable transportation systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Shin:2025:MFD,
  author =       "Jungpil Shin and Abu Saleh Musa Miah and Rei Egawa and
                 Najmul Hassan and Koki Hirooka and Yoichi Tomioka",
  title =        "Multimodal Fall Detection Using Spatial-Temporal
                 Attention and {Bi-LSTM}-Based Feature Fusion",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "173",
  day =          "15",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040173",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/173",
  abstract =     "Human fall detection is a significant healthcare
                 concern, particularly among the elderly, due to its
                 links to muscle weakness, cardiovascular issues, and
                 locomotive syndrome. Accurate fall detection is crucial
                 for timely intervention and injury prevention, which
                 has led many researchers to work on developing
                 effective detection systems. However, existing unimodal
                 systems that rely solely on skeleton or sensor data
                 face challenges such as poor robustness, computational
                 inefficiency, and sensitivity to environmental
                 conditions. While some multimodal approaches have been
                 proposed, they often struggle to capture long-range
                 dependencies effectively. In order to address these
                 challenges, we propose a multimodal fall detection
                 framework that integrates skeleton and sensor data. The
                 system uses a Graph-based Spatial-Temporal
                 Convolutional and Attention Neural Network (GSTCAN) to
                 capture spatial and temporal relationships from
                 skeleton and motion data information in stream-1, while
                 a Bi-LSTM with Channel Attention (CA) processes sensor
                 data in stream-2, extracting both spatial and temporal
                 features. The GSTCAN model uses AlphaPose for skeleton
                 extraction, calculates motion between consecutive
                 frames, and applies a graph convolutional network (GCN)
                 with a CA mechanism to focus on relevant features while
                 suppressing noise. In parallel, the Bi-LSTM with CA
                 processes inertial signals, with Bi-LSTM capturing
                 long-range temporal dependencies and CA refining
                 feature representations. The features from both
                 branches are fused and passed through a fully connected
                 layer for classification, providing a comprehensive
                 understanding of human motion. The proposed system was
                 evaluated on the Fall Up and UR Fall datasets,
                 achieving a classification accuracy of 99.09\% and
                 99.32\%, respectively, surpassing existing methods.
                 This robust and efficient system demonstrates strong
                 potential for accurate fall detection and continuous
                 healthcare monitoring.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chatzoglou:2025:CLN,
  author =       "Efstratios Chatzoglou and Georgios Kambourakis",
  title =        "{C3}: Leveraging the Native Messaging Application
                 Programming Interface for Covert Command and Control",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "172",
  day =          "14",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040172",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/172",
  abstract =     "Traditional command and control (C2) frameworks
                 struggle with evasion, automation, and resilience
                 against modern detection techniques. This paper
                 introduces covert C2 (C3), a novel C2 framework
                 designed to enhance operational security and minimize
                 detection. C3 employs a decentralized architecture,
                 enabling independent victim communication with the C2
                 server for covert persistence. Its adaptable design
                 supports diverse post-exploitation and lateral movement
                 techniques for optimized results across various
                 environments. Through optimized performance and the use
                 of the native messaging API, C3 agents achieve a
                 demonstrably low detection rate against prevalent
                 Endpoint Detection and Response (EDR) solutions. A
                 publicly available proof-of-concept implementation
                 demonstrates C3's effectiveness in real-world
                 adversarial simulations, specifically in direct code
                 execution for privilege escalation and lateral
                 movement. Our findings indicate that integrating novel
                 techniques, such as the native messaging API, and a
                 decentralized architecture significantly improves the
                 stealth, efficiency, and reliability of offensive
                 operations. The paper further analyzes C3's
                 post-exploitation behavior, explores relevant defense
                 strategies, and compares it with existing C2 solutions,
                 offering practical insights for enhancing network
                 security.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alexandrescu:2025:DAD,
  author =       "Adrian Alexandrescu and Delia-Elena Barbuta and
                 Cristian Nicolae Butincu and Alexandru Archip and
                 Silviu-Dumitru Paval and Catalin Mironeanu and
                 Gabriel-Alexandru Sc{\^\i}nteie",
  title =        "Design Analysis for a Distributed Business Innovation
                 System Employing Generated Expert Profiles,
                 Matchmaking, and Blockchain Technology",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "171",
  day =          "14",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040171",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/171",
  abstract =     "Innovation ecosystems often face challenges such as
                 inadequate coordination, insufficient protection of
                 intellectual property, limited access to quality
                 expertise, and inefficient matchmaking between
                 innovators and experts. This paper provides an in-depth
                 design analysis of SPARK-IT, a novel business
                 innovation platform specifically addressing these
                 challenges. The platform leverages advanced AI to
                 precisely match innovators with suitable mentors,
                 supported by a distributed web scraper that constructs
                 expert profiles from reliable sources (e.g., LinkedIn
                 and BrainMap). Data privacy and security are
                 prioritized through robust encryption that restricts
                 sensitive content exclusively to innovators and
                 mentors, preventing unauthorized access even by
                 platform administrators. Additionally, documents are
                 stored encrypted on decentralized storage, with their
                 cryptographic hashes anchored on blockchain to ensure
                 transparency, traceability, non-repudiation, and
                 immutability. To incentivize active participation,
                 SPARK-IT utilizes a dual-token approach comprising
                 reward and reputation tokens. The reward tokens,
                 SparkCoins, are wrapped stablecoins with tangible
                 monetary value, enabling seamless internal transactions
                 and external exchanges. Finally, the paper discusses
                 key design challenges and critical architectural
                 trade-offs and evaluates the socio-economic impacts of
                 implementing this innovative solution.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Filho:2025:ESM,
  author =       "Edson Ramiro Lucas Filho and George Savva and Lun Yang
                 and Kebo Fu and Jianqiang Shen and Herodotos
                 Herodotou",
  title =        "Employing Streaming Machine Learning for Modeling
                 Workload Patterns in Multi-Tiered Data Storage
                 Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "170",
  day =          "11",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040170",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/170",
  abstract =     "Modern multi-tiered data storage systems optimize file
                 access by managing data across a hybrid composition of
                 caches and storage tiers while using policies whose
                 decisions can severely impact the storage system's
                 performance. Recently, different Machine-Learning (ML)
                 algorithms have been used to model access patterns from
                 complex workloads. Yet, current approaches train their
                 models offline in a batch-based approach, even though
                 storage systems are processing a stream of file
                 requests with dynamic workloads. In this manuscript, we
                 advocate the streaming ML paradigm for modeling access
                 patterns in multi-tiered storage systems as it
                 introduces various advantages, including high
                 efficiency, high accuracy, and high adaptability.
                 Moreover, representative file access patterns,
                 including temporal, spatial, length, and frequency
                 patterns, are identified for individual files,
                 directories, and file formats, and used as features.
                 Streaming ML models are developed, trained, and tested
                 on different file system traces for making two types of
                 predictions: the next offset to be read in a file and
                 the future file hotness. An extensive evaluation is
                 performed with production traces provided by Huawei
                 Technologies, showing that the models are practical,
                 with low memory consumption ({$<$1}.3 MB) and low
                 training delay ({$<$1}.8 ms per training instance), and
                 can make accurate predictions online (0.98 F1 score and
                 0.07 MAE on average).",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Vaziri:2025:EES,
  author =       "Ali Vaziri and Pardis Sadatian Moghaddam and Mehrdad
                 Shoeibi and Masoud Kaveh",
  title =        "Energy-Efficient Secure Cell-Free Massive {MIMO} for
                 {Internet} of Things: a Hybrid {CNN-LSTM}-Based
                 Deep-Learning Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "169",
  day =          "11",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040169",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/169",
  abstract =     "The Internet of Things (IoT) has revolutionized modern
                 communication systems by enabling seamless connectivity
                 among low-power devices. However, the increasing demand
                 for high-performance wireless networks necessitates
                 advanced frameworks that optimize both energy
                 efficiency (EE) and security. Cell-free massive
                 multiple-input multiple-output (CF m-MIMO) has emerged
                 as a promising solution for IoT networks, offering
                 enhanced spectral efficiency, low-latency
                 communication, and robust connectivity. Nevertheless,
                 balancing EE and security in such systems remains a
                 significant challenge due to the stringent power and
                 computational constraints of IoT devices. This study
                 employs secrecy energy efficiency (SEE) as a key
                 performance metric to evaluate the trade-off between
                 power consumption and secure communication efficiency.
                 By jointly considering energy consumption and secrecy
                 rate, our analysis provides a comprehensive assessment
                 of security-aware energy efficiency in CF m-MIMO-based
                 IoT networks. To enhance SEE, we introduce a hybrid
                 deep-learning (DL) framework that integrates
                 convolutional neural networks (CNN) and long short-term
                 memory (LSTM) networks for joint EE and security
                 optimization. The CNN extracts spatial features, while
                 the LSTM captures temporal dependencies, enabling a
                 more robust and adaptive modeling of dynamic IoT
                 communication patterns. Additionally, a multi-objective
                 improved biogeography-based optimization (MOIBBO)
                 algorithm is utilized to optimize hyperparameters,
                 ensuring an improved balance between convergence speed
                 and model performance. Extensive simulation results
                 demonstrate that the proposed MOIBBO-CNN-LSTM framework
                 achieves superior SEE performance compared to benchmark
                 schemes. Specifically, MOIBBO-CNN-LSTM attains an SEE
                 gain of up to 38\% compared to LSTM and 22\% over CNN
                 while converging significantly faster at early training
                 epochs. Furthermore, our results reveal that SEE
                 improves with increasing AP transmit power up to a
                 saturation point (approximately 9.5 Mb/J at PmaxAP=500
                 PAPmax=500 PAPmax=500 mW), beyond which excessive power
                 consumption limits efficiency gains. Additionally, SEE
                 decreases as the number of APs increases, underscoring
                 the need for adaptive AP selection strategies to
                 mitigate static power consumption in backhaul links.
                 These findings confirm that MOIBBO-CNN-LSTM offers an
                 effective solution for optimizing SEE in CF
                 m-MIMO-based IoT networks, paving the way for more
                 energy-efficient and secure IoT communications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2025:NNU,
  author =       "Peng Li and Chen Qing and Hao Liu",
  title =        "{NUDIF}: a Non-Uniform Deployment Framework for
                 Distributed Inference in Heterogeneous Edge Clusters",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "168",
  day =          "11",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040168",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/168",
  abstract =     "Distributed inference in resource-constrained
                 heterogeneous edge clusters is fundamentally limited by
                 disparities in device capabilities and load imbalance
                 issues. Existing methods predominantly focus on
                 optimizing single-pipeline allocation schemes for
                 partitioned sub-models. However, such approaches often
                 lead to load imbalance and suboptimal resource
                 utilization under concurrent batch processing
                 scenarios. To address these challenges, we propose a
                 non-uniform deployment inference framework (NUDIF),
                 which achieves high-throughput distributed inference
                 service by adapting to heterogeneous resources and
                 balancing inter-stage processing capabilities.
                 Formulated as a mixed-integer nonlinear programming
                 (MINLP) problem, NUDIF is responsible for planning the
                 number of instances for each sub-model and determining
                 the specific devices for deploying these instances,
                 while considering computational capacity, memory
                 constraints, and communication latency. This
                 optimization minimizes inter-stage processing
                 discrepancies and maximizes resource utilization.
                 Experimental evaluations demonstrate that NUDIF
                 enhances system throughput by an average of 9.95\%
                 compared to traditional single-pipeline optimization
                 methods under various scales of cluster device
                 configurations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bertolotti:2025:AIS,
  author =       "Ivan Cibrario Bertolotti and Luca Durante and Enrico
                 Cambiaso",
  title =        "Analyzing Impact and Systemwide Effects of the
                 {SlowROS} Attack in an Industrial Automation Scenario",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "167",
  day =          "11",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040167",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/167",
  abstract =     "The ongoing adoption of Robot Operating Systems (ROSs)
                 not only for research-oriented projects but also for
                 industrial applications demands a more thorough
                 assessment of its security than in the past. This paper
                 highlights that a key ROS component-the ROS Master-is
                 indeed vulnerable to a novel kind of Slow Denial of
                 Service (slow DoS) attack, the root reason of this
                 vulnerability being an extremely high idle connection
                 timeout. The effects of vulnerability exploitation have
                 been evaluated in detail by means of a realistic test
                 bed, showing how it leads to a systemwide and
                 potentially dangerous disruption of ROS system
                 operations. Moreover, it has been shown how some basic
                 forms of built-in protection of the Linux kernel can be
                 easily circumvented, and are therefore ineffective
                 against this kind of threat.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Troussas:2025:RLB,
  author =       "Christos Troussas and Akrivi Krouska and Phivos
                 Mylonas and Cleo Sgouropoulou",
  title =        "Reinforcement Learning-Based Dynamic Fuzzy Weight
                 Adjustment for Adaptive User Interfaces in Educational
                 Software",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "166",
  day =          "9",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040166",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/166",
  abstract =     "Adaptive educational systems are essential for
                 addressing the diverse learning needs of students by
                 dynamically adjusting instructional content and user
                 interfaces (UI) based on real-time performance.
                 Traditional adaptive learning environments often rely
                 on static fuzzy logic rules, which lack the flexibility
                 to evolve with learners' changing behaviors. To address
                 this limitation, this paper presents an adaptive UI
                 system for educational software in Java programming,
                 integrating fuzzy logic and reinforcement learning (RL)
                 to personalize learning experiences. The system
                 consists of two main modules: (a) the Fuzzy Inference
                 Module, which classifies learners into Fast, Moderate,
                 or Slow categories based on triangular membership
                 functions, and (b) the Reinforcement Learning
                 Optimization Module, which dynamically adjusts the
                 fuzzy membership function thresholds to enhance
                 personalization over time. By refining the timing and
                 necessity of UI modifications, the system optimizes
                 hints, difficulty levels, and structured guidance,
                 ensuring interventions are neither premature nor
                 delayed. The system was evaluated in educational
                 software for Java programming, with 100 postgraduate
                 students. The evaluation, based on learning efficiency,
                 engagement, and usability metrics, demonstrated
                 promising results, particularly for slow and moderate
                 learners, confirming that reinforcement learning-driven
                 fuzzy weight adjustments significantly improve adaptive
                 UI effectiveness.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2025:CCE,
  author =       "Junchao Wang and Honglin Li and Yan Sun and Chris
                 Phillips and Alexios Mylonas and Dimitris Gritzalis",
  title =        "{CPCROK}: a Communication-Efficient and
                 Privacy-Preserving Scheme for Low-Density Vehicular Ad
                 Hoc Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "165",
  day =          "9",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040165",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/165",
  abstract =     "The mix-zone method is effective in preserving
                 real-time vehicle identity and location privacy in
                 Vehicular Ad Hoc Networks (VANETs). However, it has
                 limitations in low-vehicle-density scenarios, where
                 adversaries can still identify the real trajectories of
                 the victim vehicle. To address this issue, researchers
                 often generate numerous fake beacons to deceive
                 attackers, but this increases transmission overhead
                 significantly. Therefore, we propose the
                 Communication-Efficient Pseudonym-Changing Scheme
                 within the Restricted Online Knowledge Scheme (CPCROK)
                 to protect vehicle privacy without causing significant
                 communication overhead in low-density VANETs by
                 generating highly authentic fake beacons to form a
                 single fabricated trajectory. Specifically, the CPCROK
                 consists of three main modules: firstly, a special
                 Kalman filter module that provides real-time,
                 coarse-grained vehicle trajectory estimates to reduce
                 the need for real-time vehicle state information;
                 secondly, a Recurrent Neural Network (RNN) module that
                 enhances predictions within the mix zone by
                 incorporating offline data engineering and considering
                 online vehicle steering angles; and finally, a
                 trajectory generation module that collaborates with the
                 first two to generate highly convincing fake
                 trajectories outside the mix zone. The experimental
                 results confirm that CPCROK effectively reduces the
                 attack success rate by over 90\%, outperforming the
                 plain mix-zone scheme and beating other fake beacon
                 schemes by more than 60\%. Additionally, CPCROK
                 effectively minimizes transmission overhead by 67\%,
                 all while ensuring a high level of protection.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Haque:2025:TBA,
  author =       "Ahshanul Haque and Hamdy Soliman",
  title =        "A Transformer-Based Autoencoder with Isolation Forest
                 and {XGBoost} for Malfunction and Intrusion Detection
                 in Wireless Sensor Networks for Forest Fire
                 Prediction",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "164",
  day =          "9",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040164",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/164",
  abstract =     "Wireless Sensor Networks (WSNs) play a critical role
                 in environmental monitoring and early forest fire
                 detection. However, they are susceptible to sensor
                 malfunctions and network intrusions, which can
                 compromise data integrity and lead to false alarms or
                 missed detections. This study presents a hybrid anomaly
                 detection framework that integrates a Transformer-based
                 Autoencoder, Isolation Forest, and XGBoost to
                 effectively classify normal sensor behavior,
                 malfunctions, and intrusions. The Transformer
                 Autoencoder models spatiotemporal dependencies in
                 sensor data, while adaptive thresholding dynamically
                 adjusts sensitivity to anomalies. Isolation Forest
                 provides unsupervised anomaly validation, and XGBoost
                 further refines classification, enhancing detection
                 precision. Experimental evaluation using real-world
                 sensor data demonstrates that our model achieves 95\%
                 accuracy, with high recall for intrusion detection,
                 minimizing false negatives. The proposed approach
                 improves the reliability of WSN-based fire monitoring
                 by reducing false alarms, adapting to dynamic
                 environmental conditions, and distinguishing between
                 hardware failures and security threats.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kostadimas:2025:SRC,
  author =       "Dimitris Kostadimas and Vlasios Kasapakis and
                 Konstantinos Kotis",
  title =        "A Systematic Review on the Combination of {VR}, {IoT}
                 and {AI} Technologies, and Their Integration in
                 Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "163",
  day =          "7",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040163",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/163",
  abstract =     "The convergence of Virtual Reality (VR), Artificial
                 Intelligence (AI), and the Internet of Things (IoT)
                 offers transformative potential across numerous
                 sectors. However, existing studies often examine these
                 technologies independently or in limited pairings,
                 which overlooks the synergistic possibilities of their
                 combined usage. This systematic review adheres to the
                 PRISMA guidelines in order to critically analyze
                 peer-reviewed literature from highly recognized
                 academic databases related to the intersection of VR,
                 AI, and IoT, and identify application domains,
                 methodologies, tools, and key challenges. By focusing
                 on real-life implementations and working prototypes,
                 this review highlights state-of-the-art advancements
                 and uncovers gaps that hinder practical adoption, such
                 as data collection issues, interoperability barriers,
                 and user experience challenges. The findings reveal
                 that digital twins (DTs), AIoT systems, and immersive
                 XR environments are promising as emerging technologies
                 (ET), but require further development to achieve
                 scalability and real-world impact, while in certain
                 fields a limited amount of research is conducted until
                 now. This review bridges theory and practice, providing
                 a targeted foundation for future interdisciplinary
                 research aimed at advancing practical, scalable
                 solutions across domains such as healthcare, smart
                 cities, industry, education, cultural heritage, and
                 beyond. The study found that the integration of VR, AI,
                 and IoT holds significant potential across various
                 domains, with DTs, IoT systems, and immersive XR
                 environments showing promising applications, but
                 challenges such as data interoperability, user
                 experience limitations, and scalability barriers hinder
                 widespread adoption.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Palma:2025:MCI,
  author =       "{\'A}gata Palma and M{\'a}rio Antunes and Jorge
                 Bernardino and Ana Alves",
  title =        "Multi-Class Intrusion Detection in {Internet} of
                 Vehicles: Optimizing Machine Learning Models on
                 Imbalanced Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "162",
  day =          "7",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040162",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/162",
  abstract =     "The Internet of Vehicles (IoV) presents complex
                 cybersecurity challenges, particularly against
                 Denial-of-Service (DoS) and spoofing attacks targeting
                 the Controller Area Network (CAN) bus. This study
                 leverages the CICIoV2024 dataset, comprising six
                 distinct classes of benign traffic and various types of
                 attacks, to evaluate advanced machine learning
                 techniques for intrusion detection systems (IDS). The
                 models XGBoost, Random Forest, AdaBoost, Extra Trees,
                 Logistic Regression, and Deep Neural Network were
                 tested under realistic, imbalanced data conditions,
                 ensuring that the evaluation reflects real-world
                 scenarios where benign traffic dominates. Using
                 hyperparameter optimization with Optuna, we achieved
                 significant improvements in detection accuracy and
                 robustness. Ensemble methods such as XGBoost and Random
                 Forest consistently demonstrated superior performance,
                 achieving perfect accuracy and macro-average F1-scores,
                 even when detecting minority attack classes, in
                 contrast to previous results for the CICIoV2024
                 dataset. The integration of optimized hyperparameter
                 tuning and a broader methodological scope culminated in
                 an IDS framework capable of addressing diverse attack
                 scenarios with exceptional precision.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Singh:2025:EGC,
  author =       "Radheshyam Singh and Line M. P. Larsen and Eder Ollora
                 Zaballa and Michael St{\"u}bert Berger and Christian
                 Kloch and Lars Dittmann",
  title =        "Enabling Green Cellular Networks: a Review and
                 Proposal Leveraging Software-Defined Networking,
                 Network Function Virtualization, and Cloud-Radio Access
                 Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "161",
  day =          "5",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040161",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/161",
  abstract =     "The increasing demand for enhanced communication
                 systems, driven by applications such as real-time video
                 streaming, online gaming, critical operations, and
                 Internet-of-Things (IoT) services, has necessitated the
                 optimization of cellular networks to meet evolving
                 requirements while addressing power consumption
                 challenges. In this context, various initiatives
                 undertaken by industry, academia, and researchers to
                 reduce the power consumption of cellular network
                 systems are comprehensively reviewed. Particular
                 attention is given to emerging technologies, including
                 Software-Defined Networking (SDN), Network Function
                 Virtualization (NFV), and Cloud-Radio Access Network
                 (C-RAN), which are identified as key enablers for
                 reshaping cellular infrastructure. Their collective
                 potential to enhance energy efficiency while addressing
                 convergence challenges is analyzed, and solutions for
                 sustainable network evolution are proposed. A
                 conceptual architecture based on SDN, NFV, and C-RAN is
                 presented as an illustrative example of integrating
                 these technologies to achieve significant power
                 savings. The proposed framework outlines an approach to
                 developing energy-efficient cellular networks, capable
                 of reducing power consumption by approximately 40 to
                 50\% through the optimal placement of virtual network
                 functions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2025:CFG,
  author =       "Jiayi Wang and Tianyou Zheng and Yang Zhang and Tianli
                 Zheng and Weiwei Fu",
  title =        "Comparative Feature-Guided Regression Network with a
                 Model-Eye Pretrained Model for Online Refractive Error
                 Screening",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "160",
  day =          "3",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040160",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/160",
  abstract =     "With the development of the internet, the incidence of
                 myopia is showing a trend towards younger ages, making
                 routine vision screening increasingly essential. This
                 paper designs an online refractive error screening
                 solution centered on the CFGN (Comparative
                 Feature-Guided Network), a refractive error screening
                 network based on the eccentric photorefraction method.
                 Additionally, a training strategy incorporating an
                 objective model-eye pretraining model is introduced to
                 enhance screening accuracy. Specifically, we obtain
                 six-channel infrared eccentric photorefraction pupil
                 images to enrich image information and design a
                 comparative feature-guided module and a multi-channel
                 information fusion module based on the characteristics
                 of each channel image to enhance network performance.
                 Experimental results show that CFGN achieves an
                 accuracy exceeding 92\% within a \pm 1.00 D refractive
                 error range across datasets from two regions, with mean
                 absolute errors (MAEs) of 0.168 D and 0.108 D,
                 outperforming traditional models and meeting vision
                 screening requirements. The pretrained model helps
                 achieve better performance with small samples. The
                 vision screening scheme proposed in this study is more
                 efficient and accurate than existing networks, and the
                 cost-effectiveness of the pretrained model with
                 transfer learning provides a technical foundation for
                 subsequent rapid online screening and routine tracking
                 via networking.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Simisterra-Batallas:2025:ITD,
  author =       "Chrisbel Simisterra-Batallas and Pablo Pico-Valencia
                 and Jaime Sayago-Heredia and Xavier
                 Qui{\~n}{\'o}nez-Ku",
  title =        "{Internet of Things} and Deep Learning for Citizen
                 Security: a Systematic Literature Review on Violence
                 and Crime",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "159",
  day =          "3",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040159",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/159",
  abstract =     "This study conducts a systematic literature review
                 following the PRISMA framework and the guidelines of
                 Kitchenham and Charters to analyze the application of
                 Internet of Things (IoT) technologies and deep learning
                 models in monitoring violent actions and criminal
                 activities in smart cities. A total of 45 studies
                 published between 2010 and 2024 were selected,
                 revealing that most research, primarily from India and
                 China, focuses on cybersecurity in IoT networks (76\%),
                 while fewer studies address the surveillance of
                 physical violence and crime-related events (17\%).
                 Advanced neural network models, such as Convolutional
                 Neural Networks (CNNs), Long Short-Term Memory (LSTM)
                 networks, and hybrid approaches, have demonstrated high
                 accuracy rates, averaging over 97.44\%, in detecting
                 suspicious behaviors. These models perform well in
                 identifying anomalies in IoT security; however, they
                 have primarily been tested in simulation environments
                 (91\% of analyzed studies), most of which incorporate
                 real-world data. From a legal perspective, existing
                 proposals mainly emphasize security and privacy. This
                 study contributes to the development of smart cities by
                 promoting IoT-based security methodologies that enhance
                 surveillance and crime prevention in cities in
                 developing countries.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2025:ARQ,
  author =       "Sunan Wang and Rong Song and Xiangyu Zheng and Wanwei
                 Huang and Hongchang Liu",
  title =        "{A3C-R}: a {QoS}-Oriented Energy-Saving Routing
                 Algorithm for Software-Defined Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "158",
  day =          "3",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040158",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/158",
  abstract =     "With the rapid growth of Internet applications and
                 network traffic, existing routing algorithms are
                 usually difficult to guarantee the quality of service
                 (QoS) indicators such as delay, bandwidth, and packet
                 loss rate as well as network energy consumption for
                 various data flows with business characteristics. They
                 have problems such as unbalanced traffic scheduling and
                 unreasonable network resource allocation. Aiming at the
                 above problems, this paper proposes a QoS-oriented
                 energy-saving routing algorithm A3C-R in the
                 software-defined network (SDN) environment. Based on
                 the asynchronous update advantages of the asynchronous
                 advantage Actor-Critic (A3C) algorithm and the
                 advantages of independent interaction between multiple
                 agents and the environment, the A3C-R algorithm can
                 effectively improve the convergence of the routing
                 algorithm. The process of the A3C-R algorithm first
                 takes QoS indicators such as delay, bandwidth, and
                 packet loss rate and the network energy consumption of
                 the link as input. Then, it creates multiple agents to
                 start asynchronous training, through the continuous
                 updating of Actors and Critics in each agent and
                 periodically synchronizes the model parameters to the
                 global model. After the algorithm training converges,
                 it can output the link weights of the network topology
                 to facilitate the calculation of intelligent routing
                 strategies that meet QoS requirements and lower network
                 energy consumption. The experimental results indicate
                 that the A3C-R algorithm, compared to the baseline
                 algorithms ECMP, I-DQN, and DDPG-EEFS, reduces delay by
                 approximately 9.4\%, increases throughput by
                 approximately 7.0\%, decreases the packet loss rate by
                 approximately 9.5\%, and improves energy-saving
                 percentage by approximately 10.8\%.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Anagnostakis:2025:NCT,
  author =       "Aristidis G. Anagnostakis and Euripidis Glavas",
  title =        "The New {CAP} Theorem on Blockchain Consensus
                 Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "157",
  day =          "2",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040157",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/157",
  abstract =     "One of the most emblematic theorems in the theory of
                 distributed databases is Eric Brewer's CAP theorem. It
                 stresses the tradeoffs between Consistency,
                 Availability, and Partition and states that it is
                 impossible to guarantee all three of them
                 simultaneously. Inspired by this, we introduce the new
                 CAP theorem for autonomous consensus systems, and we
                 demonstrate that, at most, two of the three elementary
                 properties, Consensus achievement (C), Autonomy (A),
                 and entropic Performance (P) can be optimized
                 simultaneously in the generic case. This provides a
                 theoretical limit to Blockchain systems'
                 decentralization, impacting their scalability,
                 security, and real-world adoption. To formalize and
                 analyze this tradeoff, we utilize the IoT
                 micro-Blockchain as a universal, minimal,
                 consensus-enabling framework. We define a set of
                 quantitative functions relating each of the properties
                 to the number of event witnesses in the system. We
                 identify the existing mutual exclusions, and formally
                 prove for one homogeneous system consideration, that
                 (A), (C), and (P) cannot be optimized simultaneously.
                 This suggests that a requirement for concurrent
                 optimization of the three properties cannot be
                 satisfied in the generic case and reveals an intrinsic
                 limitation on the design and the optimization of
                 distributed Blockchain consensus mechanisms. Our
                 findings are formally proved utilizing the IoT
                 micro-Blockchain framework and validated through the
                 empirical data benchmarking of large-scale Blockchain
                 systems, i.e., Bitcoin, Ethereum, and Hyperledger
                 Fabric.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ajasa:2025:DSP,
  author =       "Ade Dotun Ajasa and Hassan Chizari and Abu Alam",
  title =        "Database Security and Performance: a Case of {SQL}
                 Injection Attacks Using {Docker}-Based Virtualisation
                 and Its Effect on Performance",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "156",
  day =          "2",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040156",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/156",
  abstract =     "Modern database systems are critical for storing
                 sensitive information but are increasingly targeted by
                 cyber threats, including SQL injection (SQLi) attacks.
                 This research proposes a robust security framework
                 leveraging Docker-based virtualisation to enhance
                 database security and mitigate the impact of SQLi
                 attacks. A controlled experimental methodology
                 evaluated the framework's effectiveness using Damn
                 Vulnerable Web Application (DVWA) and Acunetix
                 databases. The findings reveal that Docker
                 significantly reduces the vulnerability to SQLi attacks
                 by isolating database instances, thereby safeguarding
                 user data and system integrity. While Docker introduces
                 a significant increase in CPU utilisation during
                 high-traffic scenarios, the trade-off ensures enhanced
                 security and reliability for real-world applications.
                 This study highlights Docker's potential as a practical
                 solution for addressing evolving database security
                 challenges in distributed and cloud environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Khalili:2025:BPA,
  author =       "Hamed Khalili and Hannes Frey and Maria A. Wimmer",
  title =        "Balancing Prediction Accuracy and Explanation Power of
                 Path Loss Modeling in a {University} Campus Environment
                 via Explainable {AI}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "155",
  day =          "31",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040155",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/155",
  abstract =     "For efficient radio network planning, empirical path
                 loss (PL) prediction models are utilized to predict
                 signal attenuation in different environments.
                 Alternatively, machine learning (ML) models are
                 proposed to predict path loss. While empirical models
                 are transparent and require less computational
                 capacity, their predictions are not able to generate
                 accurate forecasting in complex environments. While ML
                 models are precise and can cope with complex terrains,
                 their opaque nature hampers building trust and relying
                 assertively on their predictions. To fill the gap
                 between transparency and accuracy, in this paper, we
                 utilize glass box ML using Microsoft research's
                 explainable boosting machines (EBM) together with the
                 PL data measured for a university campus environment.
                 Moreover, polar coordinate transformation is applied in
                 our paper, which unravels the superior explanation
                 capacity of the feature transmitting angle beyond the
                 feature distance. PL predictions of glass box ML are
                 compared with predictions of black box ML models as
                 well as those generated by empirical models. The glass
                 box EBM exhibits the highest performance. The glass box
                 ML, furthermore, sheds light on the important
                 explanatory features and the magnitude of their effects
                 on signal attenuation in the underlying propagation
                 environment.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mukherjee:2025:GAE,
  author =       "Madhav Mukherjee and John Le and Yang-Wai Chow",
  title =        "Generative {AI}-Enhanced Intelligent Tutoring System
                 for Graduate Cybersecurity Programs",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "154",
  day =          "31",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040154",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/154",
  abstract =     "Due to the widespread applicability of generative
                 artificial intelligence, we have seen it adopted across
                 many areas of education, providing universities with
                 new opportunities, particularly in cybersecurity
                 education. With the industry facing a skills shortage,
                 this paper explores the use of generative artificial
                 intelligence in higher cybersecurity education as an
                 intelligent tutoring system to enhance factors leading
                 to positive student outcomes. Despite its success in
                 content generation and assessment within cybersecurity,
                 the field's multidisciplinary nature presents
                 additional challenges to scalability and
                 generalisability. We propose a solution using agents to
                 orchestrate specialised large language models and to
                 demonstrate its applicability in graduate level
                 cybersecurity topics offered at a leading Australian
                 university. We aim to show a generalisable and scalable
                 solution to diversified educational paradigms,
                 highlighting its relevant features, and a method to
                 evaluate the quality of content as well as the general
                 effectiveness of the intelligent tutoring system on
                 subjective factors aligned with positive student
                 outcomes. We further explore areas for future research
                 in model efficiency, privacy, security, and
                 scalability.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Manolov:2025:PCB,
  author =       "Vladislav Manolov and Daniela Gotseva and Nikolay
                 Hinov",
  title =        "Practical Comparison Between the {CI\slash CD}
                 Platforms {Azure DevOps} and {GitHub}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "153",
  day =          "31",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040153",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/153",
  abstract =     "Continuous integration and delivery are essential for
                 modern software development, enabling teams to automate
                 testing, streamline deployments, and deliver
                 high-quality software more efficiently. As DevOps
                 adoption grows, selecting the right CI/CD platform is
                 essential for optimizing workflows. Azure DevOps and
                 GitHub, both under Microsoft, are leading solutions
                 with distinct features and target audiences. This paper
                 compares Azure DevOps and GitHub, evaluating their
                 CI/CD capabilities, scalability, security, pricing, and
                 usability. It explores their integration with cloud
                 environments, automation workflows, and suitability for
                 teams of varying sizes. Security features, including
                 access controls, vulnerability scanning, and
                 compliance, are analyzed to assess their suitability
                 for organizational needs. Cost-effectiveness is also
                 examined through licensing models and total ownership
                 costs. This study leverages real-world case studies and
                 industry trends to guide organizations in selecting the
                 right CI/CD tools. Whether seeking a fully managed
                 DevOps suite or a flexible, Git-native platform,
                 understanding the strengths and limitations of Azure
                 DevOps and GitHub is crucial for optimizing development
                 and meeting long-term scalability goals.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Neumayer:2025:EM,
  author =       "Bernhard Neumayer and Stefan Sauermann and Sten
                 Hanke",
  title =        "{eHealth} and {mHealth}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "152",
  day =          "31",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040152",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/152",
  abstract =     "Continuous integration and delivery are essential for
                 modern software development, enabling teams to automate
                 testing, streamline deployments, and deliver
                 high-quality software more efficiently. As DevOps
                 adoption grows, selecting the right CI/CD platform is
                 essential for optimizing workflows. Azure DevOps and
                 GitHub, both under Microsoft, are leading solutions
                 with distinct features and target audiences. This paper
                 compares Azure DevOps and GitHub, evaluating their
                 CI/CD capabilities, scalability, security, pricing, and
                 usability. It explores their integration with cloud
                 environments, automation workflows, and suitability for
                 teams of varying sizes. Security features, including
                 access controls, vulnerability scanning, and
                 compliance, are analyzed to assess their suitability
                 for organizational needs. Cost-effectiveness is also
                 examined through licensing models and total ownership
                 costs. This study leverages real-world case studies and
                 industry trends to guide organizations in selecting the
                 right CI/CD tools. Whether seeking a fully managed
                 DevOps suite or a flexible, Git-native platform,
                 understanding the strengths and limitations of Azure
                 DevOps and GitHub is crucial for optimizing development
                 and meeting long-term scalability goals.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Feretzakis:2025:GLL,
  author =       "Georgios Feretzakis and Evangelia Vagena and
                 Konstantinos Kalodanis and Paraskevi Peristera and
                 Dimitris Kalles and Athanasios Anastasiou",
  title =        "{GDPR} and Large Language Models: Technical and Legal
                 Obstacles",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "151",
  day =          "28",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040151",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/151",
  abstract =     "Large Language Models (LLMs) have revolutionized
                 natural language processing but present significant
                 technical and legal challenges when confronted with the
                 General Data Protection Regulation (GDPR). This paper
                 examines the complexities involved in reconciling the
                 design and operation of LLMs with GDPR requirements. In
                 particular, we analyze how key GDPR
                 provisions-including the Right to Erasure, Right of
                 Access, Right to Rectification, and restrictions on
                 Automated Decision-Making-are challenged by the opaque
                 and distributed nature of LLMs. We discuss issues such
                 as the transformation of personal data into
                 non-interpretable model parameters, difficulties in
                 ensuring transparency and accountability, and the risks
                 of bias and data over-collection. Moreover, the paper
                 explores potential technical solutions such as machine
                 unlearning, explainable AI (XAI), differential privacy,
                 and federated learning, alongside strategies for
                 embedding privacy-by-design principles and automated
                 compliance tools into LLM development. The analysis is
                 further enriched by considering the implications of
                 emerging regulations like the EU's Artificial
                 Intelligence Act. In addition, we propose a four-layer
                 governance framework that addresses data governance,
                 technical privacy enhancements, continuous compliance
                 monitoring, and explainability and oversight, thereby
                 offering a practical roadmap for GDPR alignment in LLM
                 systems. Through this comprehensive examination, we aim
                 to bridge the gap between the technical capabilities of
                 LLMs and the stringent data protection standards
                 mandated by GDPR, ultimately contributing to more
                 responsible and ethical AI practices.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ahmadzadeh:2025:GOD,
  author =       "Danial Ahmadzadeh and Mehrdad Jalali and Reza Ghaemi
                 and Maryam Kheirabadi",
  title =        "{GraphDBSCAN}: Optimized {DBSCAN} for Noise-Resistant
                 Community Detection in Graph Clustering",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "150",
  day =          "28",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040150",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/150",
  abstract =     "Community detection in complex networks remains a
                 significant challenge due to noise, outliers, and the
                 dependency on predefined clustering parameters. This
                 study introduces GraphDBSCAN, an adaptive community
                 detection framework that integrates an optimized
                 density-based clustering method with an enhanced graph
                 partitioning approach. The proposed method refines
                 clustering accuracy through three key innovations: (1)
                 a K-nearest neighbor (KNN)-based strategy for automatic
                 parameter tuning in density-based clustering,
                 eliminating the need for manual selection; (2) a
                 proximity-based feature extraction technique that
                 enhances node representations while preserving network
                 topology; and (3) an improved edge removal strategy in
                 graph partitioning, incorporating additional centrality
                 measures to refine community structures. GraphDBSCAN is
                 evaluated on real-world and synthetic datasets,
                 demonstrating improvements in modularity, noise
                 reduction, and clustering robustness. Compared to
                 existing methods, GraphDBSCAN consistently enhances
                 structural coherence, reduces sensitivity to outliers,
                 and improves community separation without requiring
                 fixed parameter assumptions. The proposed method offers
                 a scalable, data-driven approach to community
                 detection, making it suitable for large-scale and
                 heterogeneous networks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Belcaid:2025:CCB,
  author =       "Saad Belcaid and Mostapha Zbakh and Siham Aouad and
                 Abdellah Touhafi and An Braeken",
  title =        "A Cross-Chain-Based Access Control Framework for Cloud
                 Environment",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "149",
  day =          "27",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040149",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/149",
  abstract =     "Cloud computing presents itself as one of the leading
                 technologies in the IT solutions field, providing a
                 variety of services and capabilities. Meanwhile,
                 blockchain-based solutions emerge as advantageous as
                 they permit data immutability, transaction efficiency,
                 transparency, and trust due to decentralization and the
                 use of smart contracts. In this paper, we are
                 consolidating these two technologies into a secure
                 framework for access control in cloud environments. A
                 cross-chain-based methodology is used, in which
                 transactions and interactions between multiple
                 blockchains and cloud computing systems are supported,
                 such that no separate third-party certificates are
                 required in the authentication and authorization
                 processes. This paper presents a cross-chain-based
                 framework that integrates a full, fine-grained,
                 attribute-based access control (ABAC) mechanism that
                 evaluates cloud user access transaction attributes. It
                 grants or denies access to the cloud resources by
                 inferring knowledge about the attributes received using
                 semantic reasoning based on ontologies, resulting in a
                 more reliable method for information sharing over the
                 cloud network. Our implemented cross-chain framework on
                 the Cosmos ecosystem with the integrated semantic ABAC
                 scored an overall access control (AC) processing time
                 of 9.72 ms.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Qamar:2025:TSP,
  author =       "Saad Qamar and Nesar Ahmad and Parvez Mahmood Khan",
  title =        "Task Scheduling for Public Clouds Using a Fuzzy
                 Controller-Based Priority- and Deadline-Aware
                 Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "148",
  day =          "27",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040148",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/148",
  abstract =     "With the increasing predominance of public cloud
                 computing, managing the cost of usage for end users has
                 become vital in importance. Task scheduling has emerged
                 as an important target of research in this area. The
                 present work considers the problem of assigning tasks
                 with different priorities to clouds, with the main
                 requirement being to ensure the meeting of deadlines
                 for high-priority tasks at all costs. The idea is to
                 use as many public cloud resources as needed to satisfy
                 this constraint, even if it means incurring more cost.
                 To solve this problem, the present work proposes a
                 two-stage approach that uses a fuzzy logic controller
                 and heuristic-based task rearrangement. The proposed
                 approach is compared with the FCFS-EDF, SJF-EDF, and
                 Random-EDF approaches using synthetic and GoCJ
                 datasets, and it demonstrates the ability to meet all
                 the primary constraints. The experiments also
                 demonstrate that the required constraints do not
                 necessarily require a higher cost expenditure. It is
                 also shown that if a higher expenditure does occur for
                 a particular task set, the proposed approach is able to
                 keep the rise in cost minimal.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Maffezzoni:2025:DDD,
  author =       "Deborah Maffezzoni and Enrico Barbierato and Alice
                 Gatti",
  title =        "Data-Driven Diagnostics for Pediatric Appendicitis:
                 Machine Learning to Minimize Misdiagnoses and
                 Unnecessary Surgeries",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "147",
  day =          "26",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040147",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/147",
  abstract =     "Pediatric appendicitis remains a challenging condition
                 to diagnose accurately due to its varied clinical
                 presentations and the non-specific nature of symptoms,
                 particularly in younger patients. Traditional
                 diagnostic approaches often result in delayed
                 treatments or unnecessary surgical interventions,
                 highlighting the need for more robust diagnostic tools.
                 In this study, we explore the potential of machine
                 learning (ML) algorithms to improve the diagnosis,
                 management, and prediction of appendicitis severity in
                 pediatric patients. Using a dataset of pediatric
                 patients with suspected appendicitis, we developed and
                 compared several ML models, including logistic
                 regression (LR), random forests (RFs), gradient
                 boosting machines (GBMs), and Multilayer Perceptrons
                 (MLPs). These models were trained using clinical,
                 laboratory, and imaging data to predict three key
                 outcomes: diagnosis accuracy, management strategy, and
                 the likelihood of negative appendectomies. Our results
                 demonstrate that the RF model achieved the highest
                 overall performance with an Area Under the Receiver
                 Operating Characteristic curve (AUC-ROC) score of 0.94
                 for diagnosing appendicitis, 0.92 for determining the
                 appropriate management strategy, and 0.70 for
                 predicting appendicitis severity. Furthermore, by
                 employing advanced feature selection techniques, the
                 models were able to reduce the number of unnecessary
                 surgical interventions by up to 17\%, highlighting
                 their potential for clinical application. The findings
                 of this study suggest that ML models can significantly
                 enhance diagnostic accuracy and provide valuable
                 insights for managing pediatric appendicitis,
                 potentially reducing unnecessary surgeries and
                 improving patient outcomes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mesa-Montoya:2025:IDT,
  author =       "Carlos Andr{\'e}s Mesa-Montoya and N{\'e}stor Iv{\'a}n
                 Mar{\'\i}n Pel{\'a}ez and Kevin David
                 Ortega-Qui{\~n}ones and German Andr{\'e}s
                 Holgu{\'\i}n-Londo{\~n}o and Libardo Vicente
                 Vanegas-Useche and Gian Carlo Daravi{\~n}a-Pe{\~n}a and
                 Edwan Anderson Ariza-Echeverri and Diego Vergara",
  title =        "Integration of a Digital Twin Framework for Trajectory
                 Control of a {2RRR} Planar Parallel Manipulator Using
                 {ROS\slash Gazebo} and {MATLAB}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "146",
  day =          "26",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040146",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/matlab.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/146",
  abstract =     "Digital twin (DT) technology is transforming
                 industrial automation by enabling the real-time
                 simulation, predictive control, and optimization of
                 complex systems. This study presents a DT-based
                 kinematic control method designed for trajectory
                 planning and execution in a 2RRR planar parallel
                 manipulator. The framework utilizes ROS/Gazebo for
                 virtual modeling and MATLAB's Guide tool for a
                 human-machine interface, establishing a synchronized
                 virtual-physical environment. By dynamically bridging
                 design and manufacturing phases, the DT model enhances
                 operational insight through real-time data exchange and
                 control flexibility. Statistical analyses, including
                 the comparative hypothesis testing of angular positions
                 and velocities with a 95\% confidence level, validate
                 the model's precision, demonstrating a high degree of
                 fidelity between the virtual model and the physical
                 system. These findings confirm the DT's reliability as
                 an effective tool for trajectory programming,
                 highlighting its potential in industrial robotics where
                 adaptability and data-driven decision making are
                 essential. This approach contributes to the evolving
                 landscape of Industry 4.0 by supporting intelligent
                 manufacturing systems with improved accuracy and
                 efficiency.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Branda:2025:RAB,
  author =       "Francesco Branda and Massimo Stella and Cecilia
                 Ceccarelli and Federico Cabitza and Giancarlo
                 Ceccarelli and Antonello Maruotti and Massimo Ciccozzi
                 and Fabio Scarpa",
  title =        "The Role of {AI}-Based Chatbots in Public Health
                 Emergencies: a Narrative Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "145",
  day =          "26",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040145",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/145",
  abstract =     "The rapid emergence of infectious disease outbreaks
                 has underscored the urgent need for effective
                 communication tools to manage public health crises.
                 Artificial Intelligence (AI)-based chatbots have become
                 increasingly important in these situations, serving as
                 critical resources to provide immediate and reliable
                 information. This review examines the role of AI-based
                 chatbots in public health emergencies, particularly
                 during infectious disease outbreaks. By providing
                 real-time responses to public inquiries, these chatbots
                 help disseminate accurate information, correct
                 misinformation, and reduce public anxiety. Furthermore,
                 AI chatbots play a vital role in supporting healthcare
                 systems by triaging inquiries, offering guidance on
                 symptoms and preventive measures, and directing users
                 to appropriate health services. This not only enhances
                 public access to critical information but also helps
                 alleviate the workload of healthcare professionals,
                 allowing them to focus on more complex tasks. However,
                 the implementation of AI-based chatbots is not without
                 challenges. Issues such as the accuracy of information,
                 user trust, and ethical considerations regarding data
                 privacy are critical factors that need to be addressed
                 to optimize their effectiveness. Additionally, the
                 adaptability of these chatbots to rapidly evolving
                 health scenarios is essential for their sustained
                 relevance. Despite these challenges, the potential of
                 AI-driven chatbots to transform public health
                 communication during emergencies is significant. This
                 review highlights the importance of continuous
                 development and the integration of AI chatbots into
                 public health strategies to enhance preparedness and
                 response efforts during infectious disease outbreaks.
                 Their role in providing accessible, accurate, and
                 timely information makes them indispensable tools in
                 modern public health emergency management.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rusho:2025:KSS,
  author =       "Yonit Rusho and Daphne Ruth Raban and David Simantov
                 and Gilad Ravid",
  title =        "Knowledge Sharing in Security-Sensitive Communities",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "144",
  day =          "26",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040144",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/144",
  abstract =     "Collective intelligence inherently relies on knowledge
                 sharing. In security-sensitive organizations, tension
                 arises between the need to develop collective knowledge
                 and organizational culture, which requires secrecy.
                 Drawing on the effects of trust on social behavior,
                 this study examines knowledge-sharing in
                 security-sensitive organizations compared to
                 non-sensitive organizations dealing with the same
                 subject matter. Methodology-We use Social Network
                 Analysis (SNA) to analyze data from 18 communities: 7
                 security-sensitive and 9 non-sensitive. This
                 comparative analysis explores the impact of
                 organizational culture on communication structures and
                 knowledge-sharing patterns. Findings-(1) The
                 communication structure of security-sensitive
                 communities differs from the structure of non-sensitive
                 communities; (2) Security-sensitive communities have a
                 higher density than non-sensitive communities. (3) When
                 two security-sensitive organizations join together,
                 knowledge sharing decreases. (4) Characteristics of the
                 organizational culture of security-sensitive
                 communities affect their network structure, which in
                 turn affects knowledge sharing. This study provides
                 valuable insights into the complex relationship between
                 organizational culture, trust, and knowledge sharing in
                 security-sensitive contexts. It highlights how secrecy
                 and trust dynamics shape communication patterns and
                 collective intelligence, contributing to a deeper
                 understanding of knowledge-sharing practices in
                 environments where security concerns are paramount. The
                 findings are particularly relevant for improving
                 knowledge-sharing strategies in both security-sensitive
                 and non-sensitive organizations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lee:2025:EUE,
  author =       "Jaehwan Lee and Youngjun Sim and Jinyou Kim and
                 Young-Joo Suh",
  title =        "{EmoSDS}: Unified Emotionally Adaptive Spoken Dialogue
                 System Using Self-Supervised Speech Representations",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "143",
  day =          "25",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040143",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/143",
  abstract =     "In recent years, advancements in artificial
                 intelligence, speech, and natural language processing
                 technology have enhanced spoken dialogue systems
                 (SDSs), enabling natural, voice-based human-computer
                 interaction. However, discrete, token-based LLMs in
                 emotionally adaptive SDSs focus on lexical content
                 while overlooking essential paralinguistic cues for
                 emotion expression. Existing methods use external
                 emotion predictors to compensate for this but introduce
                 computational overhead and fail to fully integrate
                 paralinguistic features with linguistic context.
                 Moreover, the lack of high-quality emotional speech
                 datasets limits models' ability to learn expressive
                 emotional cues. To address these challenges, we propose
                 EmoSDS, a unified SDS framework that integrates speech
                 and emotion recognition by leveraging self-supervised
                 learning (SSL) features. Our three-stage training
                 pipeline enables the LLM to learn both discrete
                 linguistic content and continuous paralinguistic
                 features, improving emotional expressiveness and
                 response naturalness. Additionally, we construct EmoSC,
                 a dataset combining GPT-generated dialogues with
                 emotional voice conversion data, ensuring greater
                 emotional diversity and a balanced sample distribution
                 across emotion categories. The experimental results
                 show that EmoSDS outperforms existing models in
                 emotional alignment and response generation, achieving
                 a minimum 2.9\% increase in text generation metrics,
                 enhancing the LLM's ability to interpret emotional and
                 textual cues for more expressive and contextually
                 appropriate responses.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Scalise:2025:SCN,
  author =       "Paul Scalise and Michael Hempel and Hamid Sharif",
  title =        "A Survey of {5G} Core Network User Identity
                 Protections, Concerns, and Proposed Enhancements for
                 Future {6G} Technologies",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "142",
  day =          "25",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040142",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/142",
  abstract =     "Fifth-Generation (5G) cellular networks extensively
                 utilize subscriber identifiers throughout the protocol
                 stack, thereby linking subscribers to their activities
                 on the network. With the inherent use of linked
                 identifiers comes the potential capability to track
                 subscribers' location and behavior, which poses
                 critical challenges for user identity protections and
                 privacy in sensitive applications like military or
                 healthcare operating over public 5G infrastructure. The
                 reliance on such personal identifiers threatens a
                 user's right to privacy and brings to light the
                 importance of proper mechanisms to mitigate these risks
                 for current and future cellular network technologies.
                 In this paper, we explore the 5G specifications to
                 understand the most important list of identifiers and
                 their use across Virtual Network Functions (VNF), and
                 points of exposure within the Core Network (CN). We
                 also examine the existing literature regarding identity
                 protections and efforts to mitigate privacy concerns
                 targeted in the CN. Findings include the need for a
                 trust relationship between users and their network
                 providers to protect and safeguard their identity.
                 While 5G technology has greater user identity
                 protections compared to previous cellular generations,
                 our analysis shows that several areas of concern
                 remain, particularly in the exchange of subscriber
                 metadata. This work also finds that new technologies
                 adopted in 5G networks add further complexity to
                 maintaining a strict posture for safeguarding user
                 identity and privacy protections. This paper also
                 reviews the scientific community's proposed
                 enhancements for future 6G networks' user identity and
                 privacy protections, with a focus on emerging
                 Artificial Intelligence (AI) and Machine Learning (ML)
                 applications. The ethical implications of private or
                 anonymous communications are also carefully weighed and
                 examined to understand the multifaceted nature of this
                 topic. Our work is concluded by proposing important
                 further research to reduce the prevalence and reliance
                 on personal identifiers such as the SUPI (Subscription
                 Permanent Identifier) within 5G Core operations to help
                 better protect user identity. We also propose replacing
                 the widespread use of the SUPI between VNFs with
                 ephemeral identifiers, building upon efforts by 3GPP
                 aiming for 5G to protect the SUPI from eavesdroppers.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Dechouniotis:2025:SDC,
  author =       "Dimitrios Dechouniotis and Ioannis Dimolitsas",
  title =        "Scalable and Distributed Cloud Continuum Orchestration
                 for Next-Generation {IoT} Applications: Latest Advances
                 and Prospects",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "141",
  day =          "25",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040141",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/141",
  abstract =     "Fifth-Generation (5G) cellular networks extensively
                 utilize subscriber identifiers throughout the protocol
                 stack, thereby linking subscribers to their activities
                 on the network. With the inherent use of linked
                 identifiers comes the potential capability to track
                 subscribers' location and behavior, which poses
                 critical challenges for user identity protections and
                 privacy in sensitive applications like military or
                 healthcare operating over public 5G infrastructure. The
                 reliance on such personal identifiers threatens a
                 user's right to privacy and brings to light the
                 importance of proper mechanisms to mitigate these risks
                 for current and future cellular network technologies.
                 In this paper, we explore the 5G specifications to
                 understand the most important list of identifiers and
                 their use across Virtual Network Functions (VNF), and
                 points of exposure within the Core Network (CN). We
                 also examine the existing literature regarding identity
                 protections and efforts to mitigate privacy concerns
                 targeted in the CN. Findings include the need for a
                 trust relationship between users and their network
                 providers to protect and safeguard their identity.
                 While 5G technology has greater user identity
                 protections compared to previous cellular generations,
                 our analysis shows that several areas of concern
                 remain, particularly in the exchange of subscriber
                 metadata. This work also finds that new technologies
                 adopted in 5G networks add further complexity to
                 maintaining a strict posture for safeguarding user
                 identity and privacy protections. This paper also
                 reviews the scientific community's proposed
                 enhancements for future 6G networks' user identity and
                 privacy protections, with a focus on emerging
                 Artificial Intelligence (AI) and Machine Learning (ML)
                 applications. The ethical implications of private or
                 anonymous communications are also carefully weighed and
                 examined to understand the multifaceted nature of this
                 topic. Our work is concluded by proposing important
                 further research to reduce the prevalence and reliance
                 on personal identifiers such as the SUPI (Subscription
                 Permanent Identifier) within 5G Core operations to help
                 better protect user identity. We also propose replacing
                 the widespread use of the SUPI between VNFs with
                 ephemeral identifiers, building upon efforts by 3GPP
                 aiming for 5G to protect the SUPI from eavesdroppers.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kanzouai:2025:EIS,
  author =       "Chaimae Kanzouai and Soukaina Bouarourou and
                 Abderrahim Zannou and Abdelhak Boulaalam and El Habib
                 Nfaoui",
  title =        "Enhancing {IoT} Scalability and Interoperability
                 Through Ontology Alignment and {FedProx}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "140",
  day =          "25",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040140",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/140",
  abstract =     "The rapid expansion of IoT devices has introduced
                 major challenges in ensuring data interoperability,
                 enabling real-time processing, and achieving
                 scalability, especially in decentralized edge computing
                 environments. In this paper, an advanced framework of
                 FedProx with ontology-driven data standardization is
                 proposed, which can meet such challenges
                 comprehensively. On the one hand, it can guarantee
                 semantic consistency across different kinds of IoT
                 devices using unified ontology, so that data from
                 multiple sources could be seamlessly integrated; on the
                 other hand, it solves the non-IID issues of data and
                 limited resources in edge servers by FedProx.
                 Experimental findings indicate that FedProx outperforms
                 FedAvg, with a remarkable accuracy level of 89.4\%,
                 having higher convergence rates, and attaining a 30\%
                 saving on communication overhead through gradient
                 compression. In addition, the ontology alignment
                 procedure yielded a 95\% success rate, thereby ensuring
                 uniform data preprocessing across domains, including
                 traffic monitoring and parking management. The model
                 demonstrates outstanding scalability and flexibility to
                 new devices, while maintaining high performance during
                 ontology evolution. These findings highlight its great
                 potential for deployment in smart cities, environmental
                 monitoring, and other IoT-based ecosystems, thereby
                 enabling the creation of more efficient and integrated
                 solutions in these areas.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Nedyalkov:2025:SIU,
  author =       "Ivan Nedyalkov",
  title =        "Studying the Impact of a {UDP} {DoS} Attack on the
                 Parameters of {VoIP} Voice and Video Streams",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "139",
  day =          "24",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040139",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/139",
  abstract =     "This work studies the hypothesis of whether the UDP
                 DoS attack affects voice and video flows in a VoIP
                 network. It is a continuation of a previous work that
                 studied the same hypothesis, but the VoIP server was
                 under different types of TCP DoS attacks. The studied
                 VoIP platform is the Asterisk FreePBX. A simple IP
                 network model was developed for the purpose of the
                 study. The used platform for the modeling of IP
                 networks is GNS3. The study is conventionally divided
                 into two parts: in the first part, only voice streams
                 are exchanged in the network, and the server is
                 subjected to a UDP DoS attack, and in the second part,
                 only video streams are exchanged in the network, and
                 again, Asterisk is subjected to a UDP DoS attack. The
                 obtained results confirm the results of the previous
                 study-the performance of the Asterisk FreePBX is not
                 affected by the UDP DoS attack. Although the server is
                 flooded with UDP packets, it works and is not blocked,
                 and different types of VoIP calls are realized without
                 problems. The UDP DoS attack does not affect the
                 parameters of voice and video VoIP streams.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Nemati:2025:BLL,
  author =       "Ali Nemati and Mohammad Assadi Shalmani and Qiang Lu
                 and Jake Luo",
  title =        "Benchmarking Large Language Models from Open and
                 Closed Source Models to Apply Data Annotation for
                 Free-Text Criteria in Healthcare",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "138",
  day =          "24",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040138",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/138",
  abstract =     "Large language models (LLMs) hold the potential to
                 significantly enhance data annotation for free-text
                 healthcare records. However, ensuring their accuracy
                 and reliability is critical, especially in clinical
                 research applications requiring the extraction of
                 patient characteristics. This study introduces a novel
                 evaluation framework based on Multi-Criteria Decision
                 Analysis (MCDA) and the Order of Preference by
                 Similarity to Ideal Solution (TOPSIS) technique,
                 designed to benchmark LLMs on their annotation quality.
                 The framework defines ten evaluation metrics across key
                 criteria such as age, gender, BMI, disease presence,
                 and blood markers (e.g., white blood count and
                 platelets). Using this methodology, we assessed leading
                 open source and commercial LLMs, achieving accuracy
                 scores of 0.59, 1, 0.84, 0.56, and 0.92, respectively,
                 for the specified criteria. Our work not only provides
                 a rigorous framework for evaluating LLM capabilities in
                 healthcare data annotation but also highlights their
                 current performance limitations and strengths. By
                 offering a comprehensive benchmarking approach, we aim
                 to support responsible adoption and decision-making in
                 healthcare applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ninos:2025:MBA,
  author =       "Fragkiskos Ninos and Konstantinos Karalas and
                 Dimitrios Dechouniotis and Michael Polemis",
  title =        "On Microservice-Based Architecture for Digital
                 Forensics Applications: a Competition Policy
                 Perspective",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "137",
  day =          "23",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040137",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/137",
  abstract =     "Digital forensics systems are complex applications
                 consisting of numerous individual components that
                 demand substantial computing resources. By adopting the
                 concept of microservices, forensics applications can be
                 divided into smaller, independently managed services.
                 In this context, cloud resource orchestration platforms
                 like Kubernetes provide augmented functionalities, such
                 as resource scaling, load balancing, and monitoring,
                 supporting every stage of the application's lifecycle.
                 This article explores the deployment of digital
                 forensics applications over a microservice-based
                 architecture. Leveraging resource scaling and
                 persistent storage mechanisms, we introduce a vertical
                 scaling mechanism for compute-intensive forensics
                 applications. A practical evaluation of digital
                 forensics applications in competition investigations
                 was performed using datasets from the private cloud of
                 the Hellenic Competition Commission. The numerical
                 results illustrate that the processing time of
                 CPU-intensive tasks is reduced significantly using
                 dynamic resource scaling, while data integrity and
                 security requirements are fulfilled.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zaman:2025:DDS,
  author =       "Ali Zaman and Salman A. Khan and Nazeeruddin Mohammad
                 and Abdelhamied A. Ateya and Sadique Ahmad and Mohammed
                 A. ElAffendi",
  title =        "Distributed Denial of Service Attack Detection in
                 Software-Defined Networks Using Decision Tree
                 Algorithms",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "136",
  day =          "22",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040136",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/136",
  abstract =     "A software-defined network (SDN) is a new architecture
                 approach for constructing and maintaining networks with
                 the main goal of making the network open and
                 programmable. This allows the achievement of specific
                 network behavior by updating and installing software,
                 instead of making physical changes to the network.
                 Thus, SDNs allow far more flexibility and
                 maintainability compared to conventional
                 device-dependent architectures. Unfortunately, like
                 their predecessors, SDNs are prone to distributed
                 denial of service (DDoS) attacks. These attack paralyze
                 networks by flooding the controller with bogus
                 requests. The answer to this problem is to ignore
                 machines in the network sending these requests. This
                 can be achieved by incorporating classification
                 algorithms that can distinguish between genuine and
                 bogus requests. There is abundant literature on the
                 application of such algorithms on conventional
                 networks. However, because SDNs are relatively new,
                 they lack such abundance both in terms of novel
                 algorithms and effective datasets when it comes to DDoS
                 attack detection. To address these issues, the present
                 study analyzes several variants of the decision tree
                 algorithm for detection of DDoS attacks while using two
                 recently proposed datasets for SDNs. The study finds
                 that a decision tree constructed with a hill climbing
                 approach, termed the greedy decision tree, iteratively
                 adds features on the basis of model performance and
                 provides a simpler and more effective strategy for the
                 detection of DDoS attacks in SDNs when compared with
                 recently proposed schemes in the literature.
                 Furthermore, stability analysis of the greedy decision
                 tree provides useful insights about the performance of
                 the algorithm. One edge that greedy decision tree has
                 over several other methods is its enhanced
                 interpretability in conjunction with higher accuracy.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Joshi:2025:EIS,
  author =       "Akhil Joshi and Sai Teja Erukude and Lior Shamir",
  title =        "Explainable Identification of Similarities Between
                 Entities for Discovery in Large Text",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "135",
  day =          "22",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040135",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/135",
  abstract =     "With the availability of a virtually infinite number
                 of text documents in digital format, automatic
                 comparison of textual data is essential for extracting
                 meaningful insights that are difficult to identify
                 manually. Many existing tools, including AI and large
                 language models, struggle to provide precise and
                 explainable insights into textual similarities. In many
                 cases, they determine the similarity between documents
                 as reflected by the text, rather than the similarities
                 between the subjects being discussed in these
                 documents. This study addresses these limitations by
                 developing an n-gram analysis framework designed to
                 compare documents automatically and uncover explainable
                 similarities. A scoring formula is applied to assigns
                 each of the n-grams with a weight, where the weight is
                 higher when the n-grams are more frequent in both
                 documents, but is penalized when the n-grams are more
                 frequent in the English language. Visualization tools
                 like word clouds enhance the representation of these
                 patterns, providing clearer insights. The findings
                 demonstrate that this framework effectively uncovers
                 similarities between text documents, offering
                 explainable insights that are often difficult to
                 identify manually. This non-parametric approach
                 provides a deterministic solution for identifying
                 similarities across various fields, including
                 biographies, scientific literature, historical texts,
                 and more. Code for the method is publicly available.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Norbu:2025:UCA,
  author =       "Tenzin Norbu and Joo Yeon Park and Kok Wai Wong and
                 Hui Cui",
  title =        "Understanding Consumer Acceptance for Blockchain-Based
                 Digital Payment Systems in {Bhutan}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "134",
  day =          "21",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040134",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/134",
  abstract =     "Blockchain is a secure, digital ledger that enables
                 faster transactions, reduces fraud, lowers costs, and
                 enhances transparency. The blockchain is capable of
                 changing the face of digital payments by providing
                 greater opportunities for transformation. Consumer
                 acceptance in emerging markets such as Bhutan depends
                 on a number of key factors. This paper explores the
                 impact of performance expectancy, effort expectancy,
                 social influence, and facilitating conditions on
                 consumer acceptance of blockchain-based digital payment
                 systems in Bhutan. Sustained by the Unified Theory of
                 Acceptance and Use of Technology (UTAUT), the study
                 uses PLS-SEM to analyze survey data from 302
                 respondents. The results show that performance
                 expectancy, the expectation of blockchain's usefulness,
                 is the most influential factor determining customer
                 acceptance. Effort expectancy and facilitating
                 conditions are equally important. Social influences,
                 although rather marginal, play an important role in
                 Bhutan's collectivist culture. The paper sheds light on
                 factors for consumer acceptance of blockchain adoption.
                 The findings add to the literature on blockchain
                 adoption in burgeoning economies and provide the
                 foundation for further research on blockchain adoption
                 in multi-cultural contexts.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Afolalu:2025:ENO,
  author =       "Oladele Afolalu and Mohohlo Samuel Tsoeu",
  title =        "Enterprise Networking Optimization: a Review of
                 Challenges, Solutions, and Technological
                 Interventions",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "4",
  pages =        "133",
  day =          "21",
  month =        mar,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17040133",
  ISSN =         "1999-5903",
  bibdate =      "Mon Apr 28 09:37:50 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/4/133",
  abstract =     "Enterprise networking optimization has become crucial
                 recently due to increasing demand for a secure,
                 adaptable, reliable, and interoperable network
                 infrastructure. Novel techniques to optimize network
                 security and to improve scalability and efficiency are
                 constantly being developed by network enablers,
                 particularly in more challenging multi-cloud and edge
                 scenarios. This paper, therefore, presents a
                 comprehensive review of the traditional and most recent
                 developments in enterprise networking. We structure the
                 paper with particular emphasis on the adoption of state
                 of-the-art technologies, such as software-defined wide
                 area network(SD-WAN), secure access service edge (SASE)
                 architecture, and network automation, driven by
                 artificial intelligence (AI). The review also
                 identifies various challenges associated with the
                 adoption of the aforementioned technologies. These
                 include operational complexity, cybersecurity threats,
                 and trade-offs between cost-effectiveness and high
                 performance requirements. Furthermore, the paper
                 examines how different organizations are addressing a
                 plethora of challenges by exploiting these
                 technological innovations to drive robust and agile
                 business interconnectivity. The review is concluded
                 with an outline of possible solutions and future
                 prospects, capable of promoting digital transformation
                 and enhancing seamless connectivity within the
                 enterprise networking environment.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gegov:2025:HFA,
  author =       "Alexander Gegov and Boriana Vatchova and Yordanka
                 Boneva and Alexandar Ichtev",
  title =        "Heuristic Fuzzy Approach to Traffic Flow Modelling and
                 Control on Urban Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "227",
  day =          "20",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050227",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/227",
  abstract =     "Computer-aided transport modelling is essential for
                 testing different control strategies for traffic
                 lights. One approach to modelling traffic control is by
                 heuristically defining fuzzy rules for the control of
                 traffic light systems and applying them to a network of
                 hierarchically dependent crossroads. In this paper,
                 such a network is investigated through modelling the
                 geometry of the network in the simulation environment
                 Aimsun. This environment is based on real-world traffic
                 data and is used in this paper with the MATLAB
                 R2019a-Fuzzy toolbox. It focuses on the development of
                 a network of intersections, as well as four fuzzy
                 models and the behaviour of these models on the
                 investigated intersections. The transport network
                 consists of four intersections. The novelty of the
                 proposed approach is in the application of heuristic
                 fuzzy rules to the modelling and control of traffic
                 flow through these intersections. The motivation behind
                 the use of this approach is to address inherent
                 uncertainties using a fuzzy method and analyse its main
                 findings in relation to a classical deterministic
                 approach.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kaur:2025:EAA,
  author =       "Navneet Kaur and Lav Gupta",
  title =        "Explainable {AI} Assisted {IoMT} Security in Future
                 {6G} Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "226",
  day =          "20",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050226",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/226",
  abstract =     "The rapid integration of the Internet of Medical
                 Things (IoMT) is transforming healthcare through
                 real-time monitoring, AI-driven diagnostics, and remote
                 treatment. However, the growing reliance on IoMT
                 devices, such as robotic surgical systems, life-support
                 equipment, and wearable health monitors, has expanded
                 the attack surface, exposing healthcare systems to
                 cybersecurity risks like data breaches, device
                 manipulation, and potentially life-threatening
                 disruptions. While 6G networks offer significant
                 benefits for healthcare, such as ultra-low latency,
                 extensive connectivity, and AI-native capabilities, as
                 highlighted in the ITU 6G (IMT-2030) framework, they
                 are expected to introduce new and potentially more
                 severe security challenges. These advancements put
                 critical medical systems at greater risk, highlighting
                 the need for more robust security measures. This study
                 leverages AI techniques to systematically identify
                 security vulnerabilities within 6G-enabled healthcare
                 environments. Additionally, the proposed approach
                 strengthens AI-driven security through use of multiple
                 XAI techniques cross-validated against each other.
                 Drawing on the insights provided by XAI, we tailor our
                 mitigation strategies to the ITU-defined 6G usage
                 scenarios, with a focus on their applicability to
                 medical IoT networks. We propose that these strategies
                 will effectively address potential vulnerabilities and
                 enhance the security of medical systems leveraging IoT
                 and 6G networks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Shen:2025:TOU,
  author =       "Lingfeng Shen and Jiangtao Nie and Ming Li and
                 Guanghui Wang and Qiankun Zhang and Xin He",
  title =        "Trajectory Optimization for {UAV}-Aided {IoT} Secure
                 Communication Against Multiple Eavesdroppers",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "225",
  day =          "19",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050225",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/225",
  abstract =     "This study concentrates on physical layer security
                 (PLS) in UAV-aided Internet of Things (IoT) networks
                 and proposes an innovative approach to enhance security
                 by optimizing the trajectory of unmanned aerial
                 vehicles (UAVs). In an IoT system with multiple
                 eavesdroppers, formulating the optimal UAV trajectory
                 poses a non-convex and non-differentiable optimization
                 challenge. The paper utilizes the successive convex
                 approximation (SCA) method in conjunction with
                 hypograph theory to address this challenge. First, a
                 set of trajectory increment variables is introduced to
                 replace the original UAV trajectory coordinates,
                 thereby converting the original non-convex problem into
                 a sequence of convex subproblems. Subsequently,
                 hypograph theory is employed to convert these
                 non-differentiable subproblems into standard convex
                 forms, which can be solved using the CVX toolbox.
                 Simulation results demonstrate the UAV's trajectory
                 fluctuations under different parameters, affirming that
                 trajectory optimization significantly improves PLS
                 performance in IoT systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Takahashi:2025:RAR,
  author =       "Tomoroh Takahashi and Gia Khanh Tran",
  title =        "Research on Advancing Radio Wave Source Localization
                 Technology Through {UAV} Path Optimization",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "224",
  day =          "16",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050224",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/224",
  abstract =     "With an increasing number of illegal radio stations,
                 connected cars, and IoT devices, high-accuracy radio
                 source localization techniques are in demand.
                 Traditional methods such as GPS positioning and
                 triangulation suffer from accuracy degradation in NLOS
                 (non-line-of-sight) environments due to obstructions.
                 In contrast, the fingerprinting method builds a
                 database of pre-collected radio information and
                 estimates the source location via pattern matching,
                 maintaining relatively high accuracy in NLOS
                 environments. This study aims to improve the accuracy
                 of fingerprinting-based localization by optimizing UAV
                 flight paths. Previous research mainly relied on
                 RSSI-based localization, but we introduce an AOA model
                 considering AOA (angle of arrival) and EOA (elevation
                 of arrival), as well as a HYBRID model that integrates
                 multiple radio features with weighting. Using Wireless
                 Insite, we conducted ray-tracing simulations based on
                 the Institute of Science Tokyo's Ookayama campus and
                 optimized UAV flight paths with PSO (Particle Swarm
                 Optimization). Results show that the HYBRID model
                 achieved the highest accuracy, limiting the maximum
                 error to 20 m. Sequential estimation improved accuracy
                 for high-error sources, particularly when RSSI was used
                 first, followed by AOA or HYBRID. Future work includes
                 estimating unknown frequency sources, refining
                 sequential estimation, and implementing cooperative
                 localization.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mahmud:2025:RTI,
  author =       "Bahar Uddin Mahmud and Guanyue Hong and Virinchi
                 Ravindrakumar Lalwani and Nicholas Brown and Zachary D.
                 Asher",
  title =        "Real-Time Identification of Look-Alike Medical Vials
                 Using Mixed Reality-Enabled Deep Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "223",
  day =          "16",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050223",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/223",
  abstract =     "The accurate identification of look-alike medical
                 vials is essential for patient safety, particularly
                 when similar vials contain different substances,
                 volumes, or concentrations. Traditional methods, such
                 as manual selection or barcode-based identification,
                 are prone to human error or face reliability issues
                 under varying lighting conditions. This study addresses
                 these challenges by introducing a real-time deep
                 learning-based vial identification system, leveraging a
                 Lightweight YOLOv4 model optimized for edge devices.
                 The system is integrated into a Mixed Reality (MR)
                 environment, enabling the real-time detection and
                 annotation of vials with immediate operator feedback.
                 Compared to standard barcode-based methods and the
                 baseline YOLOv4-Tiny model, the proposed approach
                 improves identification accuracy while maintaining low
                 computational overhead. The experimental evaluations
                 demonstrate a mean average precision (mAP) of 98.76
                 percent, with an inference speed of 68 milliseconds per
                 frame on HoloLens 2, achieving real-time performance.
                 The results highlight the model's robustness in diverse
                 lighting conditions and its ability to mitigate
                 misclassifications of visually similar vials. By
                 combining deep learning with MR, this system offers a
                 more reliable and efficient alternative for
                 pharmaceutical and medical applications, paving the way
                 for AI-driven MR-assisted workflows in critical
                 healthcare environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bala:2025:PNM,
  author =       "Raju Sethupatu Bala and Salaheddin Hosseinzadeh and
                 Farhad Sadeghineko and Craig Scott Thomson and Rohinton
                 Emmanuel",
  title =        "A Portable Non-Motorized Smart {IoT} Weather Station
                 Platform for Urban Thermal Comfort Studies",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "222",
  day =          "15",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050222",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/222",
  abstract =     "Smart cities are widely regarded as a promising
                 solution to urbanization challenges; however,
                 environmental aspects such as outdoor thermal comfort
                 and urban heat island are often less addressed than
                 social and economic dimensions of sustainability. To
                 address this gap, we developed and evaluated an
                 affordable, scalable, and cost-effective weather
                 station platform, consisting of a centralized server
                 and portable edge devices to facilitate urban heat
                 island and outdoor thermal comfort studies. This edge
                 device is designed in accordance with the ISO 7726
                 (1998) standards and further enhanced with a
                 positioning system. The device can regularly log
                 parameters such as air temperature, relative humidity,
                 globe temperature, wind speed, and geographical
                 coordinates. Strategic selection of components allowed
                 for a low-cost device that can perform data
                 manipulation, pre-processing, store the data, and
                 exchange data with a centralized server via the
                 internet. The centralized server facilitates
                 scalability, processing, storage, and live monitoring
                 of data acquisition processes. The edge devices'
                 electrical and shielding design was evaluated against a
                 commercial weather station, showing Mean Absolute Error
                 and Root Mean Square Error values of 0.1 and 0.33,
                 respectively, for air temperature. Further, empirical
                 test campaigns were conducted under two scenarios:
                 ``stop-and-go'' and ``on-the-move''. These tests
                 provided an insight into transition and response times
                 required for urban heat island and thermal comfort
                 studies, and evaluated the platform's overall
                 performance, validating it for nuanced human-scale
                 thermal comfort, urban heat island, and
                 bio-meteorological studies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kumar:2025:SHA,
  author =       "Anubhav Kumar and Rajamani Radhakrishnan and Mani
                 Sumithra and Prabu Kaliyaperumal and Balamurugan
                 Balusamy and Francesco Benedetto",
  title =        "A Scalable Hybrid Autoencoder-Extreme Learning Machine
                 Framework for Adaptive Intrusion Detection in
                 High-Dimensional Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "221",
  day =          "15",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050221",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/221",
  abstract =     "The rapid expansion of network environments has
                 introduced significant cybersecurity challenges,
                 particularly in handling high-dimensional traffic and
                 detecting sophisticated threats. This study presents a
                 novel, scalable Hybrid Autoencoder-Extreme Learning
                 Machine (AE-ELM) framework for Intrusion Detection
                 Systems (IDS), specifically designed to operate
                 effectively in dynamic, cloud-supported IoT
                 environments. The scientific novelty lies in the
                 integration of an Autoencoder for deep feature
                 compression with an Extreme Learning Machine for rapid
                 and accurate classification, enhanced through adaptive
                 thresholding techniques. Evaluated on the
                 CSE-CIC-IDS2018 dataset, the proposed method
                 demonstrates a high detection accuracy of 98.52\%,
                 outperforming conventional models in terms of
                 precision, recall, and scalability. Additionally, the
                 framework exhibits strong adaptability to emerging
                 threats and reduced computational overhead, making it a
                 practical solution for real-time, scalable IDS in
                 next-generation network infrastructures.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lu:2025:NCA,
  author =       "Rui Lu and Lei Shi and Yinlong Liu and Zhongkai Dang",
  title =        "A Novel Crowdsourcing-Assisted {5G} Wireless Signal
                 Ranging Technique in {MEC} Architecture",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "220",
  day =          "14",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050220",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/220",
  abstract =     "In complex indoor and outdoor scenarios, traditional
                 GPS-based ranging technology faces limitations in
                 availability due to signal occlusion and user privacy
                 issues. Wireless signal ranging technology based on 5G
                 base stations has emerged as a potential alternative.
                 However, existing methods are limited by low efficiency
                 in constructing static signal databases, poor
                 environmental adaptability, and high resource overhead,
                 restricting their practical application. This paper
                 proposes a 5G wireless signal ranging framework that
                 integrates mobile edge computing (MEC) and crowdsourced
                 intelligence to systematically address the
                 aforementioned issues. This study designs a progressive
                 solution by (1) building a crowdsourced data collection
                 network, using mobile terminals equipped with GPS
                 technology to automatically collect device signal
                 features, replacing inefficient manual drive tests; (2)
                 developing a progressive signal update algorithm that
                 integrates real-time crowdsourced data and historical
                 signals to optimize the signal fingerprint database in
                 dynamic environments; (3) establishing an edge service
                 architecture to offload signal matching and trajectory
                 estimation tasks to MEC nodes, using lightweight
                 computing engines to reduce the load on the core
                 network. Experimental results demonstrate a mean
                 positioning error of 5 m, with 95\% of devices
                 achieving errors within 10 m, as well as building and
                 floor prediction error rates of 0.5\% and 1\%,
                 respectively. The proposed framework outperforms
                 traditional static methods by $ 3 \times i $ n ranging
                 accuracy while maintaining computational efficiency,
                 achieving significant improvements in environmental
                 adaptability and service scalability.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kalodanis:2025:CKA,
  author =       "Konstantinos Kalodanis and Panagiotis Rizomiliotis and
                 Georgios Feretzakis and Charalampos Papapavlou and
                 Dimosthenis Anagnostopoulos",
  title =        "Correction: {Kalodanis et al. High-Risk AI Systems-Lie
                 Detection Application. Future Internet 2025, {\bf 17},
                 26}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "219",
  day =          "14",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050219",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/219",
  abstract =     "In complex indoor and outdoor scenarios, traditional
                 GPS-based ranging technology faces limitations in
                 availability due to signal occlusion and user privacy
                 issues. Wireless signal ranging technology based on 5G
                 base stations has emerged as a potential alternative.
                 However, existing methods are limited by low efficiency
                 in constructing static signal databases, poor
                 environmental adaptability, and high resource overhead,
                 restricting their practical application. This paper
                 proposes a 5G wireless signal ranging framework that
                 integrates mobile edge computing (MEC) and crowdsourced
                 intelligence to systematically address the
                 aforementioned issues. This study designs a progressive
                 solution by (1) building a crowdsourced data collection
                 network, using mobile terminals equipped with GPS
                 technology to automatically collect device signal
                 features, replacing inefficient manual drive tests; (2)
                 developing a progressive signal update algorithm that
                 integrates real-time crowdsourced data and historical
                 signals to optimize the signal fingerprint database in
                 dynamic environments; (3) establishing an edge service
                 architecture to offload signal matching and trajectory
                 estimation tasks to MEC nodes, using lightweight
                 computing engines to reduce the load on the core
                 network. Experimental results demonstrate a mean
                 positioning error of 5 m, with 95\% of devices
                 achieving errors within 10 m, as well as building and
                 floor prediction error rates of 0.5\% and 1\%,
                 respectively. The proposed framework outperforms
                 traditional static methods by $ 3 \times i $ n ranging
                 accuracy while maintaining computational efficiency,
                 achieving significant improvements in environmental
                 adaptability and service scalability.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ye:2025:USU,
  author =       "Jiawei Ye and Ming Yan and Shenglin Wu and Jingxuan
                 Tan and Jie Wu",
  title =        "{U-SCAD}: an Unsupervised Method of System Call-Driven
                 Anomaly Detection for Containerized Edge Clouds",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "218",
  day =          "14",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050218",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/218",
  abstract =     "Container technology is currently one of the
                 mainstream technologies in the field of cloud
                 computing, yet its adoption in resource-constrained,
                 latency-sensitive edge environments introduces unique
                 security challenges. While existing system call-based
                 anomaly-detection methods partially address these
                 issues, they suffer from high false positive rates and
                 excessive computational overhead. To achieve security
                 and observability in edge-native containerized
                 environments and lower the cost of computing resources,
                 we propose an unsupervised anomaly-detection method
                 based on system calls. This method filters out
                 unnecessary system call data through automatic rule
                 generation and an unsupervised classification model. To
                 increase the accuracy of anomaly detection and reduce
                 the false positive rates, this method embeds system
                 calls into sequences using the proposed Syscall2vec and
                 processes the remain sequences in favor of the anomaly
                 detection model's analysis. We conduct experiments
                 using our method with a background based on modern
                 containerized cloud microservices. The results show
                 that the detection part of our method improves the F1
                 score by 23.88\% and 41.31\%, respectively, as compared
                 to HIDS and LSTM-VAE. Moreover, our method can
                 effectively reduce the original processing data to
                 13\%, which means that it significantly lowers the cost
                 of computing resources.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Karampakakis:2025:WBA,
  author =       "Panagiotis Karampakakis and Despoina Ioakeimidou and
                 Periklis Chatzimisios and Konstantinos A. Tsintotas",
  title =        "A {Web}-Based Application for Smart City Data Analysis
                 and Visualization",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "217",
  day =          "13",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050217",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/217",
  abstract =     "Smart cities are urban areas that use contemporary
                 technology to improve citizens' overall quality of
                 life. These modern digital civil hubs aim to manage
                 environmental conditions, traffic flow, and
                 infrastructure through interconnected and data-driven
                 decision-making systems. Today, many applications
                 employ intelligent sensors for real-time data
                 acquisition, leveraging visualization to derive
                 actionable insights. However, despite the proliferation
                 of such platforms, challenges like high data volume,
                 noise, and incompleteness continue to hinder practical
                 visual analysis. As missing data is a frequent issue in
                 visualizing those urban sensing systems, our approach
                 prioritizes their correction as a fundamental step. We
                 deploy a hybrid imputation strategy combining SARIMAX,
                 k -nearest neighbors, and random forest regression to
                 address this. Building on this foundation, we propose
                 an interactive web-based pipeline that processes,
                 analyzes, and presents the sensor data provided by
                 Basel's `` Smarte Strasse ``. Our platform receives and
                 projects environmental measurements, i.e., NO 2, O 3,
                 PM 2.5, and traffic noise, as well as mobility
                 indicators such as vehicle speed and type, parking
                 occupancy, and electric vehicle charging behavior. By
                 resolving gaps in the data, we provide a solid
                 foundation for high-fidelity and quality visual
                 analytics. Built on the Flask web framework, the
                 platform incorporates performance optimizations through
                 Flask-Caching. Concerning the user's dashboard, it
                 supports interactive exploration via dynamic charts and
                 spatial maps. This way, we demonstrate how future
                 internet technologies permit the accessibility of
                 complex urban sensor data for research, planning, and
                 public engagement. Lastly, our open-source web-based
                 application keeps reproducible, privacy-aware urban
                 analytics.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2025:MCI,
  author =       "Jing Li and Wei Zong and Yang-Wai Chow and Willy
                 Susilo",
  title =        "Mitigating Class Imbalance in Network Intrusion
                 Detection with Feature-Regularized {GANs}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "216",
  day =          "13",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050216",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/216",
  abstract =     "Network Intrusion Detection Systems (NIDS) often
                 suffer from severe class imbalance, where minority
                 attack types are underrepresented, leading to degraded
                 detection performance. To address this challenge, we
                 propose a novel augmentation framework that integrates
                 Soft Nearest Neighbor Loss (SNNL) into Generative
                 Adversarial Networks (GANs), including WGAN, CWGAN, and
                 WGAN-GP. Unlike traditional oversampling methods (e.g.,
                 SMOTE, ADASYN), our approach improves feature-space
                 alignment between real and synthetic samples, enhancing
                 classifier generalization on rare classes. Experiments
                 on NSL-KDD, CSE-CIC-IDS2017, and CSE-CIC-IDS2018 show
                 that SNNL-augmented GANs consistently improve
                 minority-class F1-scores without degrading overall
                 accuracy or majority-class performance. UMAP
                 visualizations confirm that SNNL produces more compact
                 and class-consistent sample distributions. We also
                 evaluate the computational overhead, finding the added
                 cost moderate. These results demonstrate the
                 effectiveness and practicality of SNNL as a general
                 enhancement for GAN-based data augmentation in
                 imbalanced NIDS tasks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tynchenko:2025:MCG,
  author =       "Valeriya V. Tynchenko and Ivan Malashin and Sergei O.
                 Kurashkin and Vadim Tynchenko and Andrei Gantimurov and
                 Vladimir Nelyub and Aleksei Borodulin",
  title =        "Multi-Criteria Genetic Algorithm for Optimizing
                 Distributed Computing Systems in Neural Network
                 Synthesis",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "215",
  day =          "13",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050215",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/215",
  abstract =     "Artificial neural networks (ANNs) are increasingly
                 effective in addressing complex scientific and
                 technological challenges. However, challenges persist
                 in synthesizing neural network models and defining
                 their structural parameters. This study investigates
                 the use of parallel evolutionary algorithms on
                 distributed computing systems (DCSs) to optimize energy
                 consumption and computational time. New mathematical
                 models for DCS performance and reliability are
                 proposed, based on a mass service system framework,
                 along with a multi-criteria optimization model designed
                 for resource-intensive computational problems. This
                 model employs a multi-criteria GA to generate a diverse
                 set of Pareto-optimal solutions. Additionally, a
                 decision-support system is developed, incorporating the
                 multi-criteria GA, allowing for customization of the
                 genetic algorithm (GA) and the construction of
                 specialized ANNs for specific problem domains. The
                 application of the decision-support system (DSS)
                 demonstrated performance of 1220.745 TFLOPS and an
                 availability factor of 99.03\%. These findings
                 highlight the potential of the proposed DCS framework
                 to enhance computational efficiency in relevant
                 applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bua:2025:LCM,
  author =       "Cristian Bua and Francesco Fiorini and Michele Pagano
                 and Davide Adami and Stefano Giordano",
  title =        "Low-Complexity Microclimate Classification in Smart
                 Greenhouses: a Fuzzy-Neural Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "214",
  day =          "13",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050214",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/214",
  abstract =     "Maintaining optimal microclimatic conditions within
                 greenhouses represents a significant challenge in
                 modern agricultural contexts, where prediction systems
                 play a crucial role in regulating temperature and
                 humidity, thereby enabling timely interventions to
                 prevent plant diseases or adverse growth conditions. In
                 this work, we propose a novel approach which integrates
                 a cascaded Feed-Forward Neural Network (FFNN) with the
                 Granular Computing paradigm to achieve accurate
                 microclimate forecasting and reduced computational
                 complexity. The experimental results demonstrate that
                 the accuracy of our approach is the same as that of the
                 FFNN-based approach but the complexity is reduced,
                 making this solution particularly well suited for
                 deployment on edge devices with limited computational
                 capabilities. Our innovative approach has been
                 validated using a real-world dataset collected from
                 four greenhouses and integrated into a distributed
                 network architecture. This setup supports the execution
                 of predictive models both on sensors deployed within
                 the greenhouse and at the network edge, where more
                 computationally intensive models can be utilized to
                 enhance decision-making accuracy.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liu:2025:IIT,
  author =       "Zhihao Liu and Franco Davoli and Davide Borsatti",
  title =        "{Industrial Internet of Things (IIoT)}: Trends and
                 Technologies",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "213",
  day =          "13",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050213",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/213",
  abstract =     "Maintaining optimal microclimatic conditions within
                 greenhouses represents a significant challenge in
                 modern agricultural contexts, where prediction systems
                 play a crucial role in regulating temperature and
                 humidity, thereby enabling timely interventions to
                 prevent plant diseases or adverse growth conditions. In
                 this work, we propose a novel approach which integrates
                 a cascaded Feed-Forward Neural Network (FFNN) with the
                 Granular Computing paradigm to achieve accurate
                 microclimate forecasting and reduced computational
                 complexity. The experimental results demonstrate that
                 the accuracy of our approach is the same as that of the
                 FFNN-based approach but the complexity is reduced,
                 making this solution particularly well suited for
                 deployment on edge devices with limited computational
                 capabilities. Our innovative approach has been
                 validated using a real-world dataset collected from
                 four greenhouses and integrated into a distributed
                 network architecture. This setup supports the execution
                 of predictive models both on sensors deployed within
                 the greenhouse and at the network edge, where more
                 computationally intensive models can be utilized to
                 enhance decision-making accuracy.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ahmad:2025:EPD,
  author =       "Pir Noman Ahmad and Adnan Muhammad Shah and KangYoon
                 Lee",
  title =        "Enhanced Propaganda Detection in Public Social Media
                 Discussions Using a Fine-Tuned Deep Learning Model: a
                 Diffusion of Innovation Perspective",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "212",
  day =          "12",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050212",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/212",
  abstract =     "During the COVID-19 pandemic, social media platforms
                 emerged as both vital information sources and conduits
                 for the rapid spread of propaganda and misinformation.
                 However, existing studies often rely on single-label
                 classification, lack contextual sensitivity, or use
                 models that struggle to effectively capture nuanced
                 propaganda cues across multiple categories. These
                 limitations hinder the development of robust,
                 generalizable detection systems in dynamic online
                 environments. In this study, we propose a novel deep
                 learning (DL) framework grounded in fine-tuning the
                 RoBERTa model for a multi-label, multi-class (ML-MC)
                 classification task, selecting RoBERTa due to its
                 strong contextual representation capabilities and
                 demonstrated superiority in complex NLP tasks. Our
                 approach is rigorously benchmarked against traditional
                 and neural methods, including, TF-IDF with n -grams,
                 Conditional Random Fields (CRFs), and long short-term
                 memory (LSTM) networks. While LSTM models show strong
                 performance in capturing sequential patterns, our
                 RoBERTa-based model achieves the highest overall
                 accuracy at 88\%, outperforming state-of-the-art
                 baselines. Framed within the diffusion of innovations
                 theory, the proposed model offers clear relative
                 advantages-including accuracy, scalability, and
                 contextual adaptability-that support its early adoption
                 by Information Systems researchers and practitioners.
                 This study not only contributes a high-performing
                 detection model but also delivers methodological and
                 theoretical insights for combating propaganda in
                 digital discourse, enhancing resilience in online
                 information ecosystems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Talabani:2025:DHT,
  author =       "Hardi Sabah Talabani and Zrar Khalid Abdul and Hardi
                 Mohammed Mohammed Saleh",
  title =        "{DNS} over {HTTPS} Tunneling Detection System Based on
                 Selected Features via Ant Colony Optimization",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "211",
  day =          "7",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050211",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/211",
  abstract =     "DNS over HTTPS (DoH) is an advanced version of the
                 traditional DNS protocol that prevents eavesdropping
                 and man-in-the-middle attacks by encrypting queries and
                 responses. However, it introduces new challenges such
                 as encrypted traffic communication, masking malicious
                 activity, tunneling attacks, and complicating intrusion
                 detection system (IDS) packet inspection. In contrast,
                 unencrypted packets in the traditional Non-DoH version
                 remain vulnerable to eavesdropping, privacy breaches,
                 and spoofing. To address these challenges, an optimized
                 dual-path feature selection approach is designed to
                 select the most efficient packet features for binary
                 class (DoH-Normal, DoH-Malicious) and multiclass
                 (Non-DoH, DoH-Normal, DoH-Malicious) classification.
                 Ant Colony Optimization (ACO) is integrated with
                 machine learning algorithms such as XGBoost, K-Nearest
                 Neighbors (KNN), Random Forest (RF), and Convolutional
                 Neural Networks (CNNs) using CIRA-CIC-DoHBrw-2020 as
                 the benchmark dataset. Experimental results show that
                 the proposed model selects the most effective features
                 for both scenarios, achieving the highest detection and
                 outperforming previous studies in IDS. The highest
                 accuracy obtained for binary and multiclass
                 classifications was 0.9999 and 0.9955, respectively.
                 The optimized feature set contributed significantly to
                 reducing computational costs and processing time across
                 all utilized classifiers. The results provide a robust,
                 fast, and accurate solution to challenges associated
                 with encrypted DNS packets.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Marletta:2025:BBS,
  author =       "Daniele Marletta and Alessandro Midolo and Emiliano
                 Tramontana",
  title =        "A Blockchain-Based Strategy for Certifying Timestamps
                 in a Distributed Healthcare Emergency Response
                 Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "210",
  day =          "7",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050210",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/210",
  abstract =     "A high level of data integrity is a strong requirement
                 in systems where the life of people depends on accurate
                 and timely responses. In healthcare emergency response
                 systems, a centralized authority that handles data
                 related to occurring events is prone to challenges,
                 such as, e.g., disputes over event timestamps and data
                 authenticity. To address both the potential lack of
                 trust among collaborating parties and the inability of
                 an authority to clearly certify events by itself, this
                 paper proposes a blockchain-based framework designed to
                 provide proof of integrity and authenticity of data in
                 healthcare emergency response systems. The proposed
                 solution integrates blockchain technology to certify
                 the accuracy of events throughout their incident
                 lifecycle. Critical events are timestamped and hashed
                 using SHA-256; then, such hashes are stored immutably
                 on an EVM-compatible blockchain via smart contracts.
                 The system combines blockchain technology with cloud
                 storage to ensure scalability, security, and
                 transparency. Blockchain technology provides the
                 advantage of eliminating a trusted server, providing
                 timestamping and reducing costs by forgoing such a
                 service. The experimental results, using publicly
                 available incident data, demonstrated the feasibility
                 and effectiveness of this approach. The system provides
                 a cost-effective, scalable solution for managing
                 incident data while keeping a proof of their integrity.
                 The proposed blockchain-based framework offers a
                 reliable, transparent mechanism for certifying
                 incident-related data. This fosters trust among
                 healthcare emergency response system actors.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gayathri:2025:ATM,
  author =       "R. G. Gayathri and Atul Sajjanhar and Yong Xiang",
  title =        "Adversarial Training for Mitigating Insider-Driven
                 {XAI}-Based Backdoor Attacks",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "209",
  day =          "6",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050209",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/209",
  abstract =     "The study investigates how adversarial training
                 techniques can be used to introduce backdoors into deep
                 learning models by an insider with privileged access to
                 training data. The research demonstrates an
                 insider-driven poison-label backdoor approach in which
                 triggers are introduced into the training dataset.
                 These triggers misclassify poisoned inputs while
                 maintaining standard classification on clean data. An
                 adversary can improve the stealth and effectiveness of
                 such attacks by utilizing XAI techniques, which makes
                 the detection of such attacks more difficult. The study
                 uses publicly available datasets to evaluate the
                 robustness of the deep learning models in this
                 situation. Our experiments show that adversarial
                 training considerably reduces backdoor attacks. These
                 results are verified using various performance metrics,
                 revealing model vulnerabilities and possible
                 countermeasures. The findings demonstrate the
                 importance of robust training techniques and effective
                 adversarial defenses to improve the security of deep
                 learning models against insider-driven backdoor
                 attacks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ye:2025:NTC,
  author =       "Jiawei Ye and Yanting Chen and Aierpanjiang Simayi and
                 Yu Liu and Zhihui Lu and Jie Wu",
  title =        "A Network Traffic Characteristics Reconstruction
                 Method for Mitigating the Impact of Packet Loss in Edge
                 Computing Scenarios",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "208",
  day =          "5",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050208",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/208",
  abstract =     "This paper presents TCReC, an innovative model
                 designed for reconstructing network traffic
                 characteristics in the presence of packet loss. With
                 the rapid expansion of wireless networks driven by edge
                 computing, IoT, and 5G technologies, challenges such as
                 transmission instability, channel competition, and
                 environmental interference have led to significant
                 packet loss rates, adversely impacting deep
                 learning-based network traffic analysis tasks. To
                 address this issue, TCReC leverages masked autoencoder
                 techniques to reconstruct missing traffic features,
                 ensuring reliable input for downstream tasks in edge
                 computing scenarios. Experimental results demonstrate
                 that TCReC maintains detection model accuracy within
                 10\% of the original data, even under packet loss rates
                 as high as 70\%. For instance, on the ISCX-VPN-2016
                 dataset, TCReC achieves a Reconstruction Ability Index
                 (RAI) of 94.02\%, while on the CIC-IDS-2017 dataset, it
                 achieves an RAI of 94.99\% when combined with LSTM,
                 significantly outperforming other methods such as
                 Transformer, KNN, and RNN. Additionally, TCReC exhibits
                 robustness across various packet loss scenarios,
                 consistently delivering high-quality feature
                 reconstruction for both attack traffic and common
                 Internet application data. TCReC provides a robust
                 solution for network traffic analysis in high-loss edge
                 computing scenarios, offering practical value for
                 real-world deployment.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Giannilias:2025:CHP,
  author =       "Theodoros Giannilias and Andreas Papadakis and
                 Nikolaos Nikolaou and Theodore Zahariadis",
  title =        "Classification of Hacker's Posts Based on Zero-Shot,
                 Few-Shot, and Fine-Tuned {LLMs} in Environments with
                 Constrained Resources",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "207",
  day =          "5",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050207",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/207",
  abstract =     "This paper investigates, applies, and evaluates
                 state-of-the-art Large Language Models (LLMs) for the
                 classification of posts from a dark web hackers' forum
                 into four cyber-security categories. The LLMs applied
                 included Mistral-7B-Instruct-v0.2, Gemma-1.1-7B,
                 Llama-3-8B-Instruct, and Llama-2-7B, with zero-shot
                 learning, few-shot learning, and fine-tuning. The four
                 cyber-security categories consisted of ``Access Control
                 and Management'', ``Availability Protection and
                 Security by Design Mechanisms'', ``Software and
                 Firmware Flaws'', and ``not relevant''. The hackers'
                 posts were also classified and labelled by a human
                 cyber-security expert, allowing a detailed evaluation
                 of the classification accuracy per each LLM and
                 customization/learning method. We verified LLM
                 fine-tuning as the most effective mechanism to enhance
                 the accuracy and reliability of the classifications.
                 The results include the methodology applied and the
                 labelled hackers' posts dataset.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liu:2025:XBD,
  author =       "Liang Liu and Weiqing Yu and Zhijun Wu and Silin
                 Peng",
  title =        "{XGBoost}-Based Detection of {DDoS} Attacks in Named
                 Data Networking",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "206",
  day =          "4",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050206",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/206",
  abstract =     "Named Data Networking (NDN) is highly susceptible to
                 Distributed Denial of Service (DDoS) attacks, such as
                 Interest Flooding Attack (IFA) and Cache Pollution
                 Attack (CPA). These attacks exploit the inherent data
                 retrieval and caching mechanisms of NDN, leading to
                 severe disruptions in data availability and network
                 efficiency, thereby undermining the overall performance
                 and reliability of the system. In this paper, an attack
                 detection method based on an improved XGBoost is
                 proposed and applied to the hybrid attack pattern of
                 IFA and CPA. Through experiments, the performance of
                 the new attacks and the efficacy of the detection
                 algorithm are analyzed. In comparison with other
                 algorithms, the proposed method is demonstrated to have
                 advantages in terms of the advanced nature of the
                 proposed classifier, which is confirmed by the
                 AUC-score.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Islam:2025:SBS,
  author =       "Mohammad Jaminur Islam and Saminur Islam and Mahmud
                 Hossain and Shahid Noor and S. M. Riazul Islam",
  title =        "Securing Blockchain Systems: a Layer-Oriented Survey
                 of Threats, Vulnerability Taxonomy, and Detection
                 Methods",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "205",
  day =          "3",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050205",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/205",
  abstract =     "Blockchain technology is emerging as a pivotal
                 framework to enhance the security of internet-based
                 systems, especially as advancements in machine learning
                 (ML), artificial intelligence (AI), and cyber-physical
                 systems such as smart grids and IoT applications in
                 healthcare continue to accelerate. Although these
                 innovations promise significant improvements, security
                 remains a critical challenge. Blockchain offers a
                 secure foundation for integrating diverse technologies;
                 however, vulnerabilities-including adversarial
                 exploits-can undermine performance and compromise
                 application reliability. To address these risks
                 effectively, it is essential to comprehensively analyze
                 the vulnerability landscape of blockchain systems. This
                 paper contributes in two key ways. First, it presents a
                 unique layer-based framework for analyzing and
                 illustrating security attacks within blockchain
                 architectures. Second, it introduces a novel taxonomy
                 that classifies existing research on blockchain
                 vulnerability detection. Our analysis reveals that
                 while ML and deep learning offer promising approaches
                 for detecting vulnerabilities, their effectiveness
                 often depends on access to extensive and high-quality
                 datasets. Additionally, the layer-based framework
                 demonstrates that vulnerabilities span all layers of a
                 blockchain system, with attacks frequently targeting
                 the consensus process, network integrity, and smart
                 contract code. Overall, this paper provides a
                 comprehensive overview of blockchain security threats
                 and detection methods, emphasizing the need for a
                 multifaceted approach to safeguard these evolving
                 systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Narigina:2025:APS,
  author =       "Marta Narigina and Agris Vindecs and Dusanka
                 Boskovi{\'c} and Yuri Merkuryev and Andrejs Romanovs",
  title =        "{AI}-Powered Stroke Diagnosis System: Methodological
                 Framework and Implementation",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "204",
  day =          "2",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050204",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/204",
  abstract =     "This study introduces an AI-based framework for stroke
                 diagnosis that merges clinical data and curated imaging
                 data. The system utilizes traditional machine learning
                 and advanced deep learning techniques to tackle dataset
                 imbalances and variability in stroke presentations. Our
                 approach involves rigorous data preprocessing, feature
                 engineering, and ensemble techniques to optimize the
                 predictive performance. Comprehensive evaluations
                 demonstrate that gradient-boosted models outperform in
                 accuracy, while CNNs enhance stroke detection rates.
                 Calibration and threshold optimization are utilized to
                 align predictions with clinical requirements, ensuring
                 diagnostic reliability. This multi-modal framework
                 highlights the capacity of AI to accelerate stroke
                 diagnosis and aid clinical decision making, ultimately
                 enhancing patient outcomes in critical care.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Artioli:2025:CHP,
  author =       "Marcello Artioli and Andrea Borghesi and Marta
                 Chinnici and Anna Ciampolini and Michele Colonna and
                 Davide {De Chiara} and Daniela Loreti",
  title =        "{C6EnPLS}: a High-Performance Computing Job Dataset
                 for the Analysis of Linear Solvers' Power Consumption",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "203",
  day =          "30",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050203",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/203",
  abstract =     "In recent decades, driven by global efforts towards
                 sustainability, the priorities of HPC facilities have
                 changed to include maximising energy efficiency besides
                 computing performance. In this regard, a crucial open
                 question is how to accurately predict the contribution
                 of each parallel job to the system's energy
                 consumption. Accurate estimations in this sense could
                 offer an initial insight into the overall power
                 requirements of the system, and provide meaningful
                 information for, e.g., power-aware scheduling, load
                 balancing, infrastructure design, etc. While ML-based
                 attempts employing large training datasets of past
                 executions may suffer from the high variability of HPC
                 workloads, a more specific knowledge of the nature of
                 the jobs can improve prediction accuracy. In this work,
                 we restrict our attention to the rather pervasive task
                 of linear system resolution. We propose a methodology
                 to build a large dataset of runs (including the
                 measurements coming from physical sensors deployed on a
                 large HPC cluster), and we report a statistical
                 analysis and preliminary evaluation of the efficacy of
                 the obtained dataset when employed to train
                 well-established ML methods aiming to predict the
                 energy footprint of specific software.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Geloczi:2025:SDS,
  author =       "Emiliia Geloczi and Felix Klement and Patrick Struck
                 and Stefan Katzenbeisser",
  title =        "{SoK}: Delegated Security in the {Internet of
                 Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "202",
  day =          "30",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050202",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/202",
  abstract =     "The increased use of electronic devices in the
                 Internet of Things (IoT) leads not only to an improved
                 comfort of living but also to an increased risk of
                 attacks. IoT security has thus become an important
                 research field. However, due to limits on performance
                 and bandwidth, IoT devices are often not powerful
                 enough to execute, e.g., costly cryptographic
                 algorithms or protocols. This limitation can be solved
                 through a delegation concept. By delegating certain
                 operations to devices with sufficient resources, it is
                 possible to achieve a high level of security without
                 overloading a device that needs protection. In this
                 paper, we give an overview of current approaches for
                 security delegation in the context of IoT, formalise
                 security notions, discuss the security of existing
                 approaches, and identify further research questions.
                 Furthermore, a mathematical formalisation of the CIA
                 triad (confidentiality, integrity, and availability) is
                 proposed for the predefined application areas, in order
                 to evaluate the different approaches.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{BenRjeb:2025:OIT,
  author =       "Hanen {Ben Rjeb} and Layth Sliman and Hela Zorgati and
                 Raoudha {Ben Djemaa} and Amine Dhraief",
  title =        "Optimizing {Internet of Things} Services Placement in
                 Fog Computing Using Hybrid Recommendation System",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "201",
  day =          "30",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050201",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/201",
  abstract =     "Fog Computing extends Cloud computing capabilities by
                 providing computational resources closer to end users.
                 Fog Computing has gained considerable popularity in
                 various domains such as drones, autonomous vehicles,
                 and smart cities. In this context, the careful
                 selection of suitable Fog resources and the optimal
                 assignment of services to these resources (the service
                 placement problem (SPP)) is essential. Numerous studies
                 have attempted to tackle this issue. However, to the
                 best of our knowledge, none of the previously proposed
                 works took into consideration the dynamic context
                 awareness and the user preferences for IoT service
                 placement. To deal with this issue, we propose a hybrid
                 recommendation system for service placement that
                 combines two techniques: collaborative filtering and
                 content-based recommendation. By considering user and
                 service context, user preferences, service needs, and
                 resource availability, the proposed recommendation
                 system provides optimal placement suggestions for each
                 IoT service. To assess the efficiency of the proposed
                 system, a validation scenario based on Internet of
                 Drones (IoD) was simulated and tested. The results show
                 that the proposed approach leads to a considerable
                 reduction in waiting time and a substantial improvement
                 in resource utilization and the number of executed
                 services.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Stefan:2025:IPA,
  author =       "Ioana-Livia Stefan and Andrei Mateescu and Ionut
                 Lentoiu and Silviu Raileanu and Florin Daniel Anton and
                 Dragos Constantin Popescu and Ioan Stefan Sacala",
  title =        "Implementation and Performance Analysis of an
                 Industrial Robot's Vision System Based on Cloud Vision
                 Services",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "200",
  day =          "30",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050200",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/200",
  abstract =     "With its fast advancements, cloud computing opens many
                 opportunities for research in various applications from
                 the robotics field. In our paper, we further explore
                 the prospect of integrating Cloud AI object recognition
                 services into an industrial robotics sorting task.
                 Starting from our previously implemented solution on a
                 digital twin, we are now putting our proposed
                 architecture to the test in the real world, on an
                 industrial robot, where factors such as illumination,
                 shadows, different colors, and textures of the
                 materials influence the performance of the vision
                 system. We compare the results of our suggested method
                 with those from an industrial machine vision software,
                 indicating promising performance and opening additional
                 application perspectives in the robotics field,
                 simultaneously with the continuous improvement of Cloud
                 and AI technology.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tina:2025:IAT,
  author =       "Fahmida Wazed Tina and Nasrin Afsarimanesh and Anindya
                 Nag and Md Eshrat E. Alahi",
  title =        "Integrating {AIoT} Technologies in Aquaculture: a
                 Systematic Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "199",
  day =          "30",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050199",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/199",
  abstract =     "The increasing global demand for seafood underscores
                 the necessity for sustainable aquaculture practices.
                 However, several challenges, including rising
                 operational costs, variable environmental conditions,
                 and the threat of disease outbreaks, impede progress in
                 this field. This review explores the transformative
                 role of the Artificial Intelligence of Things (AIoT) in
                 mitigating these challenges. We analyse current
                 research on AIoT applications in aquaculture, with a
                 strong emphasis on the use of IoT sensors for real-time
                 data collection and AI algorithms for effective data
                 analysis. Our focus areas include monitoring water
                 quality, implementing smart feeding strategies,
                 detecting diseases, analysing fish behaviour, and
                 employing automated counting techniques. Nevertheless,
                 several research gaps remain, particularly regarding
                 the integration of AI in broodstock management, the
                 development of multimodal AI systems, and challenges
                 regarding model generalization. Future advancements in
                 AIoT should prioritise real-time adaptability,
                 cost-effectiveness, and sustainability while
                 emphasizing the importance of multimodal systems,
                 advanced biosensing capabilities, and digital twin
                 technologies. In conclusion, while AIoT presents
                 substantial opportunities for enhancing aquaculture
                 practices, successful implementation will depend on
                 overcoming challenges related to scalability, cost, and
                 technical expertise, improving models' adaptability,
                 and ensuring environmental sustainability.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Jahanbakhsh:2025:LRA,
  author =       "Negin Jahanbakhsh and Mario Vega-Barbas and Iv{\'a}n
                 Pau and Lucas Elvira-Mart{\'\i}n and Hirad Moosavi and
                 Carolina Garc{\'\i}a-V{\'a}zquez",
  title =        "Leveraging Retrieval-Augmented Generation for
                 Automated Smart Home Orchestration",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "198",
  day =          "29",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050198",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/198",
  abstract =     "The rapid growth of smart home technologies, driven by
                 the expansion of the Internet of Things (IoT), has
                 introduced both opportunities and challenges in
                 automating daily routines and orchestrating device
                 interactions. Traditional rule-based automation systems
                 often fall short in adapting to dynamic conditions,
                 integrating heterogeneous devices, and responding to
                 evolving user needs. To address these limitations, this
                 study introduces a novel smart home orchestration
                 framework that combines generative Artificial
                 Intelligence (AI), Retrieval-Augmented Generation
                 (RAG), and the modular OSGi framework. The proposed
                 system allows users to express requirements in natural
                 language, which are then interpreted and transformed
                 into executable service bundles by large language
                 models (LLMs) enhanced with contextual knowledge
                 retrieved from vector databases. These AI-generated
                 service bundles are dynamically deployed via OSGi,
                 enabling real-time service adaptation without system
                 downtime. Manufacturer-provided device capabilities are
                 seamlessly integrated into the orchestration pipeline,
                 ensuring compatibility and extensibility. The framework
                 was validated through multiple use-case scenarios
                 involving dynamic device discovery, on-demand code
                 generation, and adaptive orchestration based on user
                 preferences. Results highlight the system's ability to
                 enhance automation efficiency, personalization, and
                 resilience. This work demonstrates the feasibility and
                 advantages of AI-driven orchestration in realising
                 intelligent, flexible, and scalable smart home
                 environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Regueiro:2025:LBT,
  author =       "Cristina Regueiro and Santiago de Diego and Borja
                 Urkizu",
  title =        "Leveraging Blockchain Technology for Secure {5G}
                 Offloading Processes",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "197",
  day =          "29",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050197",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/197",
  abstract =     "This paper presents a secure 5G offloading mechanism
                 leveraging Blockchain technology and Self-Sovereign
                 Identity (SSI). The advent of 5G has significantly
                 enhanced the capabilities of all sectors, enabling
                 innovative applications and improving security and
                 efficiency. However, challenges such as limited
                 infrastructure, signal interference, and high upgrade
                 costs persist. Offloading processes already address
                 these issues but they require more transparency and
                 security. This paper proposes a Blockchain-based
                 marketplace using Hyperledger Fabric to optimize
                 resource allocation and enhance security. This
                 marketplace facilitates the exchange of services and
                 resources among operators, promoting competition and
                 flexibility. Additionally, the paper introduces an
                 SSI-based authentication system to ensure privacy and
                 security during the offloading process. The
                 architecture and components of the marketplace and
                 authentication system are detailed, along with their
                 data models and operations. Performance evaluations
                 indicate that the proposed solutions do not
                 significantly degrade offloading times, making them
                 suitable for everyday applications. As a result, the
                 integration of Blockchain and SSI technologies enhances
                 the security and efficiency of 5G offloading.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Haywood:2025:ENI,
  author =       "Gregor Tamati Haywood and Saleem Noel Bhatti",
  title =        "Ephemeral Node Identifiers for Enhanced Flow Privacy",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "196",
  day =          "28",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050196",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/196",
  abstract =     "The Internet Protocol (IP) uses numerical address
                 values carried in IP packets at the network layer to
                 allow correct forwarding of packets between source and
                 destination. Those address values must be kept visible
                 in all parts of the network. By definition, those
                 addresses must carry enough information to identify the
                 source and destination for the communication. This
                 means that successive flows of IP packets can be
                 correlated -it is possible for an observer of the flows
                 to easily link them to an individual source and so,
                 potentially, to an individual user. To alleviate this
                 privacy concern, it is desirable to have ephemeral
                 address values-values that have a limited lifespan and
                 so make flow correlation more difficult for an
                 attacker. However, the IP address is also used in the
                 end-to-end communication state for transport layer
                 flows so must remain consistent to allow correct
                 operation at the transport layer. We present a solution
                 to this tension in requirements by the use of ephemeral
                 Node Identifier (eNID) values in IP packets as part of
                 the address value. We have implemented our approach as
                 an extension to IPv6 in the FreeBSD14 operating system
                 kernel. We have evaluated the implementation with
                 existing applications over both a testbed network in a
                 controlled environment, as well as with global IPv6
                 network connectivity. Our results show that eNIDs work
                 with existing applications and over existing IPv6
                 networks. Our analyses shows that using eNIDs creates a
                 disruption to the correlation of flows and so
                 effectively perturbs linkability. As our approach is a
                 network layer (layer 3) mechanism, it is usable by any
                 transport layer (layer 4) protocol, improving privacy
                 for all applications and all users.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fahrudin:2025:IRP,
  author =       "Tresna Maulana Fahrudin and Nobuo Funabiki and Komang
                 Candra Brata and Inzali Naing and Soe Thandar Aung and
                 Amri Muhaimin and Dwi Arman Prasetya",
  title =        "An Improved Reference Paper Collection System Using
                 {Web} Scraping with Three Enhancements",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "195",
  day =          "28",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050195",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/195",
  abstract =     "Nowadays, accessibility to academic papers has been
                 significantly improved with electric publications on
                 the internet, where open access has become common. At
                 the same time, it has increased workloads in literature
                 surveys for researchers who usually manually download
                 PDF files and check their contents. To solve this
                 drawback, we have proposed a reference paper collection
                 system using a web scraping technology and natural
                 language models. However, our previous system often
                 finds a limited number of relevant reference papers
                 after taking long time, since it relies on one paper
                 search website and runs on a single thread at a
                 multi-core CPU. In this paper, we present an improved
                 reference paper collection system with three
                 enhancements to solve them: (1) integrating the APIs
                 from multiple paper search web sites, namely, the bulk
                 search endpoint in the Semantic Scholar API, the
                 article search endpoint in the DOAJ API, and the search
                 and fetch endpoint in the PubMed API to retrieve
                 article metadata, (2) running the program on multiple
                 threads for multi-core CPU, and (3) implementing
                 Dynamic URL Redirection, Regex-based URL Parsing, and
                 HTML Scraping with URL Extraction for fast checking of
                 PDF file accessibility, along with sentence embedding
                 to assess relevance based on semantic similarity. For
                 evaluations, we compare the number of obtained
                 reference papers and the response time between the
                 proposal, our previous work, and common literature
                 search tools in five reference paper queries. The
                 results show that the proposal increases the number of
                 relevant reference papers by 64.38\% and reduces the
                 time by 59.78\% on average compared to our previous
                 work, while outperforming common literature search
                 tools in reference papers. Thus, the effectiveness of
                 the proposed system has been demonstrated in our
                 experiments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Huang:2025:BGB,
  author =       "Wanwei Huang and Huicong Yu and Yingying Li and Xi He
                 and Rui Chen",
  title =        "{BPDM-GCN}: Backup Path Design Method Based on Graph
                 Convolutional Neural Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "194",
  day =          "27",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050194",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/194",
  abstract =     "To address the problems of poor applicability of
                 existing fault link recovery algorithms in network
                 topology migration and backup path congestion, this
                 paper proposes a backup path algorithm based on graph
                 convolutional neural to improve deep deterministic
                 policy gradient. First, the BPDM-GCN backup path
                 algorithm is constructed within a deep deterministic
                 policy gradient training framework. It uses graph
                 convolutional networks to detect changes in network
                 topology, aiming to optimize data transmission delay
                 and bandwidth occupancy within the network topology.
                 After iterative training of the BPDM-GCN algorithm, the
                 comprehensive link weights within the network topology
                 are generated. Then, according to the comprehensive
                 link weight and taking the shortest path as the
                 optimization objective, a backup path implementation
                 method based on the incremental shortest path tree is
                 designed to reduce the phasor data transmission delay
                 in the backup path. In conclusion, the experimental
                 results show that the backup path formulated by this
                 algorithm exhibits reduced data transmission delay,
                 minimal path extension, and a high success rate in
                 recovering failed links. Compared to the superior
                 NRLF-RL algorithm, the BPDM-GCN algorithm achieves a
                 reduction of approximately 14.29\% in the average
                 failure link recovery delay and an increase of
                 approximately 5.24\% in the failure link recovery
                 success rate.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Xu:2025:DQT,
  author =       "Guobin Xu and Oluwole Adetifa and Jianzhou Mao and
                 Eric Sakk and Shuangbao Wang",
  title =        "Developing Quantum Trusted Platform Module {(QTPM)} to
                 Advance {IoT} Security",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "193",
  day =          "26",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050193",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/193",
  abstract =     "Randomness is integral to computer security,
                 influencing fields such as cryptography and machine
                 learning. In the context of cybersecurity, particularly
                 for the Internet of Things (IoT), high levels of
                 randomness are essential to secure cryptographic
                 protocols. Quantum computing introduces significant
                 risks to traditional encryption methods. To address
                 these challenges, we propose investigating a
                 quantum-safe solution for IoT-trusted computing.
                 Specifically, we implement the first lightweight,
                 practical integration of a quantum random number
                 generator (QRNG) with a software-based trusted platform
                 module (TPM) to create a deployable quantum trusted
                 platform module (QTPM) prototype for IoT systems to
                 improve cryptographic capabilities. The proposed
                 quantum entropy as a service (QEaaS) framework further
                 extends quantum entropy access to legacy and
                 resource-constrained devices. Through the evaluation,
                 we compare the performance of QRNG with traditional
                 Pseudo-random Number Generators (PRNGs), demonstrating
                 the effectiveness of the quantum TPM. Our paper
                 highlights the transformative potential of integrating
                 quantum technology to bolster IoT security.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Atanasov:2025:RCR,
  author =       "Ivaylo Atanasov and Dragomira Dimitrova and Evelina
                 Pencheva and Ventsislav Trifonov",
  title =        "Railway Cloud Resource Management as a Service",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "192",
  day =          "24",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050192",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/192",
  abstract =     "Cloud computing has the potential to accelerate the
                 digital journey of railways. Railway systems are big
                 and complex, involving a lot of parts, like trains,
                 tracks, signaling systems, and control systems, among
                 others. The application of cloud computing technologies
                 in the railway industry has the potential to enhance
                 operational efficiency, data management, and overall
                 system performance. Cloud management is essential for
                 complex systems, and the automation of management
                 services can speed up the provisioning, deployment, and
                 maintenance of cloud infrastructure and applications by
                 enabling visibility across the environment. It can
                 provide consistent and unified management over resource
                 allocation, streamline security processes, and automate
                 the monitoring of key performance indicators. Key
                 railway cloud management challenges include the lack of
                 open interfaces and standardization, which are related
                 to the vendor lock-in problem. In this paper, we
                 propose an approach to design the railway cloud
                 resource management as a service. Based on typical use
                 cases, the requirements to fault and performance
                 management of the railway cloud resources are
                 identified. The main functionality is designed as
                 RESTful services. The approach feasibility is proved by
                 formal verification of the cloud resource management
                 models supported by cloud management application and
                 services. The proposed approach is open, in contrast to
                 any proprietary solutions and feature scalability and
                 interoperability.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Garroppo:2025:TAF,
  author =       "Rosario G. Garroppo and Pietro Giuseppe Giardina and
                 Giada Landi and Marco Ruta",
  title =        "Trustworthy {AI} and Federated Learning for Intrusion
                 Detection in {6G}-Connected Smart Buildings",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "191",
  day =          "23",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050191",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/191",
  abstract =     "Smart building applications require robust security
                 measures to ensure system functionality, privacy, and
                 security. To this end, this paper proposes a Federated
                 Learning Intrusion Detection System (FL-IDS) composed
                 of two convolutional neural network (CNN) models to
                 detect network and IoT device attacks simultaneously.
                 Collaborative training across multiple cooperative
                 smart buildings enables model development without
                 direct data sharing, ensuring privacy by design.
                 Furthermore, the design of the proposed method
                 considers three key principles: sustainability,
                 adaptability, and trustworthiness. The proposed data
                 pre-processing and engineering system significantly
                 reduces the amount of data to be processed by the CNN,
                 helping to limit the processing load and associated
                 energy consumption towards more sustainable Artificial
                 Intelligence (AI) techniques. Furthermore, the data
                 engineering process, which includes sampling, feature
                 extraction, and transformation of data into images, is
                 designed considering its adaptability to integrate new
                 sensor data and to fit seamlessly into a zero-touch
                 system, following the principles of Machine Learning
                 Operations (MLOps). The designed CNNs allow for the
                 investigation of AI reasoning, implementing eXplainable
                 AI (XAI) techniques such as the correlation map
                 analyzed in this paper. Using the ToN-IoT dataset, the
                 results show that the proposed FL-IDS achieves
                 performance comparable to that of its centralized
                 counterpart. To address the specific vulnerabilities of
                 FL, a secure and robust aggregation method is
                 introduced, making the system resistant to poisoning
                 attacks from up to 20\% of the participating clients.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Malde:2025:MLA,
  author =       "Avnish Malde and Vishnunarayan Girishan Prabhu and
                 Dishant Banga and Michael Hsieh and Chaithanya
                 Renduchintala and Ronald Pirrallo",
  title =        "A Machine Learning Approach for Predicting Maternal
                 Health Risks in Lower-Middle-Income Countries Using
                 Sparse Data and Vital Signs",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "190",
  day =          "22",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050190",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/190",
  abstract =     "According to the World Health Organization, maternal
                 mortality rates remain a critical public health issue,
                 with 94\% of maternal deaths occurring in low- and
                 middle-income countries (LMICs), where the rates
                 reached 430 per 100,000 live births in 2020 compared to
                 13 in high-income countries. Despite this difference,
                 only a few studies have investigated whether sparse
                 data and features such as vital signs can effectively
                 predict maternal health risks. This study addresses
                 this gap by evaluating the predictive capability of
                 vital sign data using machine learning models trained
                 on a dataset of 1014 pregnant women from rural
                 Bangladesh. This study developed multiple machine
                 learning models using a dataset containing age, blood
                 pressure, temperature, heart rate, and blood glucose of
                 1014 pregnant women from rural Bangladesh. The models'
                 performance were evaluated using regular, random and
                 stratified sampling techniques. Additionally, we
                 developed a stacking ensemble machine learning model
                 combining multiple methods to evaluate predictive
                 accuracy. A key contribution of this study is
                 developing a stacking ensemble model combined with
                 stratified sampling, an approach not previously
                 considered in maternal health risk prediction. The
                 ensemble model using stratified sampling achieved the
                 highest accuracy (87.2\%), outperforming CatBoost
                 (84.7\%), XGBoost (84.2\%), random forest (81.3\%) and
                 decision trees (80.3\%) without stratified sampling.
                 Observations from our study demonstrate the feasibility
                 of using sparse data and features for maternal health
                 risk prediction using algorithms. By focusing on data
                 from resource-constrained settings, we show that
                 machine learning offers a convenient and accessible
                 solution to improve prenatal care and reduce maternal
                 deaths in LMICs.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2025:ABE,
  author =       "Mingjun Wang and Xuezhi Zhang and Feng Jing and Mei
                 Gao",
  title =        "{Ad-BBR}: Enhancing Round-Trip Time Fairness and
                 Transmission Stability in {TCP-BBR}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "189",
  day =          "22",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050189",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/189",
  abstract =     "The rapid development of wireless network technology
                 and the continuous evolution of network service demands
                 have raised higher requirements for congestion control
                 algorithms. In 2016, Google proposed the Bottleneck
                 Bandwidth and Round-trip propagation time (BBR)
                 congestion control algorithm based on the Transmission
                 Control Protocol (TCP) protocol. While BBR offers lower
                 latency and higher throughput compared to traditional
                 congestion control algorithms, it still faces
                 challenges. These include the periodic triggering of
                 the ProbeRTT phase, which impairs data transmission
                 efficiency, data over-injection caused by the
                 congestion window (CWND) value-setting policy, and the
                 difficulty of coordinating resource allocation across
                 multiple concurrent flows. These limitations make BBR
                 less effective in multi-stream competition scenarios in
                 high-speed wireless networks. This paper analyzes the
                 design limitations of the BBR algorithm from a
                 theoretical perspective and proposes the Adaptive-BBR
                 (Ad-BBR) algorithm. The Ad-BBR algorithm incorporates
                 real-time RTT and link queue-state information,
                 introduces a new RTprop determination mechanism, and
                 implements a finer-grained, RTT-based adaptive
                 transmission rate adjustment mechanism to reduce data
                 over-injection and improve RTT fairness. Additionally,
                 the ProbeRTT phase-triggering mechanism is updated to
                 ensure more stable and smoother data transmission. In
                 the NS3, 5G, and Wi-Fi simulation experiments, Ad-BBR
                 outperformed all comparison algorithms by effectively
                 mitigating data over-injection and minimizing
                 unnecessary entries into the ProbeRTT phase. Compared
                 to the BBRv1 algorithm, Ad-BBR achieved a 17\% increase
                 in throughput and a 30\% improvement in RTT fairness,
                 along with a 13\% reduction in the retransmission rate
                 and an approximate 20\% decrease in latency.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Raju:2025:FEW,
  author =       "Anand Raju and Sathishkumar Samiappan",
  title =        "Feature Extraction in {5G} Wireless Systems: a Quantum
                 Cat Swarm and Wavelet-Based Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "188",
  day =          "22",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050188",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/188",
  abstract =     "This paper represents a new method for the extraction
                 of features from 5G signals using spectrogram and
                 quantum cat swarm optimization (QCSO). The proposed
                 approach uses a discrete wavelet transform (DWT)-based
                 convolutional neural network (W-CNN) to enhance the
                 extracted features and improve the signal
                 classification. The combination of QCSO and W-CNN is
                 designed to enable improved signal recognition and
                 dimension reduction. Our results demonstrate an
                 improvement in the 5G signal feature extraction
                 performance with the use of this novel approach. The
                 QCSO shows improvement in seven out of eight parameters
                 studied when compared to five other state-of-the-art
                 optimization methods.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rakin:2025:TSC,
  author =       "Raiyen Z. Rakin and Mahmudur Rahman and Kanij F. Borsa
                 and Fahmid {Al Farid} and Shakila Rahman and Jia Uddin
                 and Hezerul Abdul Karim",
  title =        "Towards Safer Cities: {AI}-Powered Infrastructure
                 Fault Detection Based on {YOLOv11}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "187",
  day =          "22",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050187",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/187",
  abstract =     "The current infrastructure is crucial to metropolitan
                 improvement. Natural factors, aging, and overuse cause
                 these structures to deteriorate, introducing dangers to
                 public well-being. Timely detection of infrastructure
                 failures requires an effective solution. A
                 YOLOv11-based deep learning model has been proposed
                 which analyzes infrastructure and detects faults in
                 civil architecture. The focus of this study is on an
                 image-based approach to infrastructure assessment,
                 which is an alternative to manual visual inspections.
                 Despite not explicitly modeling infrastructure
                 deterioration, the proposed method is designed to
                 automate defect identification based on visual cues. A
                 customized dataset was created with 9116 images
                 collected from various platforms. The dataset was
                 pre-processed, i.e., annotated, and after
                 pre-processing, the proposed model was trained. After
                 training, our proposed model finds defects with greater
                 precision and speed than conventional defect detection
                 techniques. It achieves high performance with
                 precision, recall, F1 score, and mAP in 100 epochs, and
                 is therefore reliable for applications in civil
                 engineering and urban infrastructure monitoring.
                 Finally, the detection results show that the proposed
                 YOLOv11 model works better than other baseline
                 algorithms (YOLOv8, YOLOv9, and YOLOv10) and is more
                 accurate at finding infrastructure problems in
                 real-world scenarios.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Johnstone:2025:UML,
  author =       "Michael N. Johnstone and Wencheng Yang and Mohiuddin
                 Ahmed",
  title =        "Using Machine Learning to Detect Vault (Anti-Forensic)
                 Apps",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "5",
  pages =        "186",
  day =          "22",
  month =        apr,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17050186",
  ISSN =         "1999-5903",
  bibdate =      "Thu May 29 11:43:40 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/5/186",
  abstract =     "Content hiding, or vault applications (apps), are
                 designed with a secondary, often concealed purpose,
                 such as encrypting and storing files. While these apps
                 may serve legitimate functions, they unequivocally
                 present significant challenges for law enforcement.
                 Conventional methods for tackling this issue, whether
                 static or dynamic, prove inadequate when
                 devices-typically smartphones-cannot be modified.
                 Additionally, these methods frequently require prior
                 knowledge of which apps are classified as vault apps.
                 This research decisively demonstrates that a
                 non-invasive method of app analysis, combined with
                 machine learning, can effectively identify vault apps.
                 Our findings reveal that it is entirely possible to
                 detect an Android vault app with 98\% accuracy using a
                 random forest classifier. This clearly indicates that
                 our approach can be instrumental for law enforcement in
                 their efforts to address this critical issue.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bertolotti:2025:CBF,
  author =       "Ivan Cibrario Bertolotti",
  title =        "A {C}-Based Framework for Low-Cost Real-Time Embedded
                 Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "269",
  day =          "19",
  month =        jun,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060269",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/269",
  abstract =     "This paper presents a framework that enables
                 programmers to deploy embedded real-time firmware of
                 Internet of Things (IoT) devices more conveniently than
                 using plain C/C++-language programming, by abstracting
                 away from low-level details and the ad hoc management
                 of multiple, diverse network technologies. Moreover,
                 unlike other proposals, the framework is able to
                 accommodate both time and event-driven applications.
                 Experimental results show that for Modbus-CAN
                 communication, the worst-case time overhead of the
                 framework is less than 6\% of the total combined
                 processing and communication time. Its memory
                 requirement is less than 5\% and 4\% of the Flash
                 memory and RAM available on a typical IoT
                 microcontroller. The framework also compares favorably
                 with respect to two other approaches in terms of the
                 sustainable minimum cycle time, memory overhead, and
                 level of programming abstraction when tested on a
                 simple real-time algorithm.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hussain:2025:BAV,
  author =       "Iftikhar Hussain and Manuel J. C. S. Reis and Carlos
                 Ser{\^o}dio and Frederico Branco",
  title =        "A Bibliometric Analysis and Visualization of
                 In-Vehicle Communication Protocols",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "268",
  day =          "19",
  month =        jun,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060268",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/268",
  abstract =     "This research examined the domain of intelligent
                 transportation systems (ITS) by analyzing the impact of
                 scholarly work and thematic prevalence, as well as
                 focusing attention on vehicles, their technologies,
                 cybersecurity, and related scholarly technologies. This
                 was performed by examining the scientific literature
                 indexed in the Scopus database. This study analysed
                 2919 documents published between 2018 and 2025. The
                 findings indicated that the highest and most
                 significant journal was derived from IEEE Transactions
                 on Vehicular Technology, with significant standing to
                 the growth of communication and computing on vehicles
                 with edge computing and AI optimization of vehicular
                 systems. In addition, important PST research
                 conferences highlighted the growing interest in
                 academic research in cybersecurity for vehicle
                 networks. Sensor networks, pose forensics, and
                 privacy-preserving communication frameworks were some
                 of the significant contributing fields marking the
                 significance of the interdisciplinary nature of this
                 research. Employing bibliometric analysis, the
                 literature illustrated the multiple channels
                 integrating knowledge creation and innovation in ITS
                 through citation analysis. The outcome suggested an
                 increasingly sophisticated research area, weighing
                 technical progress and increasing concern about
                 security and privacy measures. Further studies must
                 investigate edge computing integrated with AI, advanced
                 privacy-preserving linguistic protocols, and new
                 vehicular network intrusion detection systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bagui:2025:DCT,
  author =       "Sikha S. Bagui and Germano {Correa Silva De Carvalho}
                 and Asmi Mishra and Dustin Mink and Subhash C. Bagui
                 and Stephanie Eager",
  title =        "Detecting Cyber Threats in {UWF-ZeekDataFall22} Using
                 {$K$}-Means Clustering in the Big Data Environment",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "267",
  day =          "18",
  month =        jun,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060267",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/267",
  abstract =     "In an era marked by the rapid growth of the Internet
                 of Things (IoT), network security has become
                 increasingly critical. Traditional Intrusion Detection
                 Systems, particularly signature-based methods, struggle
                 to identify evolving cyber threats such as Advanced
                 Persistent Threats (APTs)and zero-day attacks. Such
                 threats or attacks go undetected with supervised
                 machine-learning methods. In this paper, we apply
                 K-means clustering, an unsupervised clustering
                 technique, to a newly created modern network attack
                 dataset, UWF-ZeekDataFall22. Since this dataset
                 contains labeled Zeek logs, the dataset was de-labeled
                 before using this data for {$K$}-means clustering. The
                 labeled data, however, was used in the evaluation
                 phase, to determine the attack clusters
                 post-clustering. In order to identify APTs as well as
                 zero-day attack clusters, three different labeling
                 heuristics were evaluated to determine the attack
                 clusters. To address the challenges faced by Big Data,
                 the Big Data framework, that is, Apache Spark and
                 PySpark, were used for our development environment. In
                 addition, the uniqueness of this work is also in using
                 connection-based features. Using connection-based
                 features, an in-depth study is done to determine the
                 effect of the number of clusters, seeds, as well as
                 features, for each of the different labeling
                 heuristics. If the objective is to detect every single
                 attack, the results indicate that 325 clusters with a
                 seed of 200, using an optimal set of features, would be
                 able to correctly place 99\% of attacks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alenezi:2025:SML,
  author =       "Mohammed N. Alenezi",
  title =        "Significance of Machine Learning-Driven Algorithms for
                 Effective Discrimination of {DDoS} Traffic Within {IoT}
                 Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "266",
  day =          "18",
  month =        jun,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060266",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/266",
  abstract =     "As digital infrastructure continues to expand,
                 networks, web services, and Internet of Things (IoT)
                 devices become increasingly vulnerable to distributed
                 denial of service (DDoS) attacks. Remarkably, IoT
                 devices have become attracted to DDoS attacks due to
                 their common deployment and limited applied security
                 measures. Therefore, attackers take advantage of the
                 growing number of unsecured IoT devices to reflect
                 massive traffic that overwhelms networks and disrupts
                 necessary services, making protection of IoT devices
                 against DDoS attacks a major concern for organizations
                 and administrators. In this paper, the effectiveness of
                 supervised machine learning (ML) classification and
                 deep learning (DL) algorithms in detecting DDoS attacks
                 on IoT networks was investigated by conducting an
                 extensive analysis of network traffic dataset
                 (legitimate and malicious). The performance of the
                 models and data quality improved when emphasizing the
                 impact of feature selection and data pre-processing
                 approaches. Five machine learning models were evaluated
                 by utilizing the Edge-IIoTset dataset: Random Forest
                 (RF), Support Vector Machine (SVM), Long Short-Term
                 Memory (LSTM), and K-Nearest Neighbors (KNN) with
                 multiple K values, and Convolutional Neural Network
                 (CNN). Findings revealed that the RF model outperformed
                 other models by delivering optimal detection speed and
                 remarkable performance across all evaluation metrics,
                 while KNN (K = 7) emerged as the most efficient model
                 in terms of training time.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Cisneros-Gonzalez:2025:JIA,
  author =       "Jorge Cisneros-Gonz{\'a}lez and Natalia Gordo-Herrera
                 and Iv{\'a}n Barcia-Santos and Javier
                 S{\'a}nchez-Soriano",
  title =        "{JorGPT}: Instructor-Aided Grading of Programming
                 Assignments with Large Language Models ({LLMs})",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "265",
  day =          "18",
  month =        jun,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060265",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/265",
  abstract =     "This paper explores the application of large language
                 models (LLMs) to automate the evaluation of programming
                 assignments in an undergraduate ``Introduction to
                 Programming'' course. This study addresses the
                 challenges of manual grading, including time
                 constraints and potential inconsistencies, by proposing
                 a system that integrates several LLMs to streamline the
                 assessment process. The system utilizes a graphic
                 interface to process student submissions, allowing
                 instructors to select an LLM and customize the grading
                 rubric. A comparative analysis, using LLMs from OpenAI,
                 Google, DeepSeek and ALIBABA to evaluate student code
                 submissions, revealed a strong correlation between
                 LLM-generated grades and those assigned by human
                 instructors. Specifically, the reduced model using
                 statistically significant variables demonstrates a high
                 explanatory power, with an adjusted R 2 of 0.9156 and a
                 Mean Absolute Error of 0.4579, indicating that LLMs can
                 effectively replicate human grading. The findings
                 suggest that LLMs can automate grading when paired with
                 human oversight, drastically reducing the instructor
                 workload, transforming a task estimated to take more
                 than 300 h of manual work into less than 15 min of
                 automated processing and improving the efficiency and
                 consistency of assessment in computer science
                 education.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kiouvrekis:2025:EML,
  author =       "Yiannis Kiouvrekis and Katerina Gkirtzou and Sotiris
                 Zikas and Dimitris Kalatzis and Theodor
                 Panagiotakopoulos and Zoran Lajic and Dimitris
                 Papathanasiou and Ioannis Filippopoulos",
  title =        "An Explainable Machine Learning Approach for
                 {IoT}-Supported Shaft Power Estimation and Performance
                 Analysis for Marine Vessels",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "264",
  day =          "17",
  month =        jun,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060264",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/264",
  abstract =     "In the evolving landscape of green shipping, the
                 accurate estimation of shaft power is critical for
                 reducing fuel consumption and greenhouse gas emissions.
                 This study presents an explainable machine learning
                 framework for shaft power prediction, utilising
                 real-world Internet of Things (IoT) sensor data
                 collected from nine (9) Very Large Crude Carriers
                 (VLCCs) over a 36-month period. A diverse set of
                 models---ranging from traditional algorithms such as
                 Decision Trees and Support Vector Machines to advanced
                 ensemble methods like XGBoost and LightGBM---were
                 developed and evaluated. Model performance was assessed
                 using the coefficient of determination ( R2 ) and RMSE,
                 with XGBoost achieving the highest accuracy (
                 R2=0.9490, RMSE 888) and LightGBM being close behind (
                 R2=0.9474, RMSE 902), with both substantially exceeding
                 the industry baseline model ( R2=0.9028, RMSE 1500).
                 Explainability was integrated through SHapley Additive
                 exPlanations (SHAP), offering detailed insights into
                 the influence of each input variable. Features such as
                 draft, GPS speed, and time since last dry dock
                 consistently emerged as key predictors. The results
                 demonstrate the robustness and interpretability of
                 tree-based methods, offering a data-driven alternative
                 to traditional performance estimation techniques and
                 supporting the maritime industry's transition toward
                 more efficient and sustainable operations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chen:2025:GSB,
  author =       "Tzung-Her Chen",
  title =        "A {Grover} Search-Based Quantum Key Agreement Protocol
                 for Secure {Internet of Medical Things} Communication",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "263",
  day =          "17",
  month =        jun,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060263",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/263",
  abstract =     "The rapid integration of the Internet of Medical
                 Things (IoMT) into healthcare systems raises urgent
                 demands for secure communication mechanisms capable of
                 protecting sensitive patient data. Quantum key
                 agreement (QKA), a collaborative approach to key
                 generation based on quantum principles, provides an
                 attractive alternative to traditional quantum key
                 distribution (QKD), as it eliminates dependence on a
                 trusted authority and ensures equal participation from
                 all users. QKA demonstrates particular suitability for
                 IoMT's decentralized medical networks by eliminating
                 trusted authority dependence while ensuring equitable
                 participation among all participants. This addresses
                 fundamental challenges where centralized trust models
                 introduce vulnerabilities and asymmetric access
                 patterns that compromise egalitarian principles
                 essential for medical data sharing. However, practical
                 QKA applications in IoMT remain limited, particularly
                 for schemes that avoid complex entanglement operations
                 and authenticated classical channels. Among the few QKA
                 protocols employing Grover's search algorithm (GSA),
                 existing proposals potentially suffer from limitations
                 in fairness and security. In this paper, the author
                 proposes an improved GSA-based QKA protocol that
                 ensures fairness, security, and correctness without
                 requiring an authenticated classical communication
                 channel. The proposed scheme guarantees that each
                 participant's input equally contributes to the final
                 key, preventing manipulation by any user subgroup. The
                 scheme combines Grover's algorithm with the decoy
                 photon technique to ensure secure quantum transmission.
                 Security analysis confirms resistance to external
                 attacks, including intercept-resend, entanglement
                 probes, and device-level exploits, as well as insider
                 threats such as parameter manipulation. Fairness is
                 achieved through a symmetric protocol design rooted in
                 quantum mechanical principles. Efficiency evaluation
                 shows a theoretical efficiency of approximately 25\%,
                 while eliminating the need for quantum memory. These
                 results position the proposed protocol as a practical
                 and scalable solution for future secure quantum
                 communication systems, particularly within distributed
                 IoMT environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Atlam:2025:EHS,
  author =       "Hany F. Atlam and Yifu Yang",
  title =        "Enhancing Healthcare Security: a Unified {RBAC} and
                 {ABAC} Risk-Aware Access Control Approach",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "262",
  day =          "14",
  month =        jun,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060262",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/262",
  abstract =     "Healthcare systems are increasingly vulnerable to
                 security threats due to their reliance on digital
                 platforms. Traditional access control models like
                 Role-Based Access Control (RBAC) and Attribute-Based
                 Access Control (ABAC) have limitations in mitigating
                 evolving risks in these systems. Despite their unique
                 features, these models face limitations in mitigating
                 evolving risks in healthcare systems. Traditional
                 models are primarily oriented towards allocating
                 permissions according to predetermined roles or
                 policies, which results in challenges in effectively
                 adapting to the dynamic complexities of modern
                 healthcare ecosystems. Therefore, this paper proposes a
                 novel risk-aware RBAC and ABAC access control model to
                 enhance the flexibility, adaptability and security
                 issues associated with healthcare systems. The proposed
                 model integrates RBAC for role-based categorization,
                 ABAC for fine-grained control based on user attributes
                 and environmental factors, and Risk-Based Access
                 Control (RiBAC) for dynamic risk assessment. The
                 proposed model dynamically adjusts access permissions
                 based on risk values, ensuring accurate and adaptable
                 access control decisions. The experimental results
                 demonstrate the feasibility and effectiveness of the
                 proposed model in granting access to authorized users
                 while denying access to unauthorized users. Through a
                 series of 43 experiments that simulate various
                 scenarios of access control operations in the
                 healthcare system, the proposed model demonstrates
                 significant improvement in the accuracy, precision, and
                 recall of access control decisions compared to
                 traditional models. The proposed model's ability to
                 dynamically assess risk and adjust access permissions
                 based on contextual factors significantly enhances its
                 ability to mitigate threats and protect sensitive
                 medical data.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Baydoun:2025:NCR,
  author =       "Ali Mohammad Baydoun and Ahmed Sherif Zekri",
  title =        "Network-, Cost-, and Renewable-Aware Ant Colony
                 Optimization for Energy-Efficient Virtual Machine
                 Placement in Cloud Datacenters",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "261",
  day =          "14",
  month =        jun,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060261",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/261",
  abstract =     "Virtual machine (VM) placement in cloud datacenters is
                 a complex multi-objective challenge involving
                 trade-offs among energy efficiency, carbon emissions,
                 and network performance. This paper proposes
                 NCRA-DP-ACO (Network-, Cost-, and Renewable-Aware Ant
                 Colony Optimization with Dynamic Power Usage
                 Effectiveness (PUE)), a bio-inspired metaheuristic that
                 optimizes VM placement across geographically
                 distributed datacenters. The approach integrates
                 real-time solar energy availability, dynamic PUE
                 modeling, and multi-criteria decision-making to enable
                 environmentally and cost-efficient resource allocation.
                 The experimental results show that NCRA-DP-ACO reduces
                 power consumption by 13.7\%, carbon emissions by 6.9\%,
                 and live VM migrations by 48.2\% compared to
                 state-of-the-art methods while maintaining Service
                 Level Agreement (SLA) compliance. These results
                 indicate the algorithm's potential to support more
                 environmentally and cost-efficient cloud management
                 across dynamic infrastructure scenarios.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tian:2025:JEP,
  author =       "Hui Tian and Haibao Chen and Yuyan Zhao and Jiawei
                 Zhang",
  title =        "Joint Exploitation of Physical-Layer and Artificial
                 Features for Privacy-Preserving Distributed Source
                 Camera Identification",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "260",
  day =          "13",
  month =        jun,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060260",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/260",
  abstract =     "Identifying the source camera of a digital image is a
                 critical task for ensuring image authenticity. In this
                 paper, we propose a novel privacy-preserving
                 distributed source camera identification scheme that
                 jointly exploits both physical-layer fingerprint
                 features and a carefully designed artificial tag.
                 Specifically, we build a hybrid fingerprint model by
                 combining sensor level hardware fingerprints with
                 artificial tag features to characterize the unique
                 identity of the camera in a digital image. To address
                 privacy concerns, the proposed scheme incorporates a
                 privacy-preserving strategy that encrypts not only the
                 hybrid fingerprint parameters, but also the image
                 content itself. Furthermore, within the distributed
                 framework, the identification task performed by a
                 single secondary user is formulated as a binary
                 hypothesis testing problem. Experimental results
                 demonstrated the effectiveness of the proposed scheme
                 in accurately identifying source cameras, particularly
                 under complex conditions such as those involving images
                 processed by social media platforms. Notably, for
                 social media platform identification, our method
                 achieved average accuracy improvements of 7.19\% on the
                 Vision dataset and 8.87\% on the Forchheim dataset
                 compared to a representative baseline.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lillemets:2025:SRC,
  author =       "Pilleriin Lillemets and Nabaa Bashir Jawad and Joseph
                 Kashi and Ahmad Sabah and Nicola Dragoni",
  title =        "A Systematic Review of Cyber Range Taxonomies: Trends,
                 Gaps, and a Proposed Taxonomy",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "259",
  day =          "12",
  month =        jun,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060259",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/259",
  abstract =     "Cyber ranges have become essential platforms for
                 realistic cybersecurity training, research, and
                 development. Existing taxonomies often describe the
                 functional aspects of cyber ranges---scenario design,
                 team configurations, and evaluation metrics--- focusing
                 less on the underlying technologies that enable modern
                 training. In this paper, we highlight the current
                 trends and persistent gaps in the existing literature
                 and propose a taxonomy that decouples functional
                 capabilities from the enabling infrastructure, adding a
                 dedicated Technology dimension. We derived and refined
                 this taxonomy through an iterative literature mapping
                 process, culminating in a proposed taxonomy that
                 highlights key emerging trends such as cyber--physical
                 integration, federation across multiple sites, and
                 AI-driven orchestration. Key findings include the
                 identification of clear convergences and divergences in
                 existing taxonomies and concrete recommendations for
                 future research directions, such as integrating
                 socio-technical considerations and conducting
                 systematic empirical validation. Our framework aims to
                 guide researchers, developers, and practitioners in
                 designing, implementing, and comparing cyber range
                 solutions. An online Taxonomy Mapping Toolkit is
                 developed to allow the cyber ranges research community
                 to take advantage of the proposed taxonomy and build
                 upon it as new advancements emerge.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Moghaddam:2025:GAT,
  author =       "Pardis Sadatian Moghaddam and Ali Vaziri and Sarvenaz
                 Sadat Khatami and Francisco Hernando-Gallego and Diego
                 Mart{\'\i}n",
  title =        "Generative Adversarial and Transformer Network Synergy
                 for Robust Intrusion Detection in {IoT} Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "258",
  day =          "12",
  month =        jun,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060258",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/258",
  abstract =     "Intrusion detection in the Internet of Things (IoT)
                 environments is increasingly critical due to the rapid
                 proliferation of connected devices and the growing
                 sophistication of cyber threats. Traditional detection
                 methods often fall short in identifying multi-class
                 attacks, particularly in the presence of
                 high-dimensional and imbalanced IoT traffic. To address
                 these challenges, this paper proposes a novel hybrid
                 intrusion detection framework that integrates
                 transformer networks with generative adversarial
                 networks (GANs), aiming to enhance both detection
                 accuracy and robustness. In the proposed architecture,
                 the transformer component effectively models temporal
                 and contextual dependencies within traffic sequences,
                 while the GAN component generates synthetic data to
                 improve feature diversity and mitigate class imbalance.
                 Additionally, an improved non-dominated sorting
                 biogeography-based optimization (INSBBO) algorithm is
                 employed to fine-tune the hyper-parameters of the
                 hybrid model, further enhancing learning stability and
                 detection performance. The model is trained and
                 evaluated on the CIC-IoT-2023 and TON\_IoT dataset,
                 which contains a diverse range of real-world IoT
                 traffic and attack scenarios. Experimental results show
                 that our hybrid framework consistently outperforms
                 baseline methods, in both binary and multi-class
                 intrusion detection tasks. The transformer-GAN achieves
                 a multi-class classification accuracy of 99.67\%, with
                 an F1-score of 99.61\%, and an area under the curve
                 (AUC) of 99.80\% in the CIC-IoT-2023 dataset, and
                 achieves 98.84\% accuracy, 98.79\% F1-score, and
                 99.12\% AUC on the TON\_IoT dataset. The superiority of
                 the proposed model was further validated through
                 statistically significant t -test results, lower
                 execution time compared to baselines, and minimal
                 standard deviation across runs, indicating both
                 efficiency and stability. The proposed framework offers
                 a promising approach for enhancing the security and
                 resilience of next-generation IoT systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ortiz:2025:ATI,
  author =       "Leandro Antonio Pazmi{\~n}o Ortiz and Ivonne Fernanda
                 Maldonado Soliz and Vanessa Katherine Guevara
                 Balarezo",
  title =        "Advancing {TinyML} in {IoT}: a Holistic System-Level
                 Perspective for Resource-Constrained {AI}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "257",
  day =          "11",
  month =        jun,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060257",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/257",
  abstract =     "Resource-constrained devices, including low-power
                 Internet of Things (IoT) nodes, microcontrollers, and
                 edge computing platforms, have increasingly become the
                 focal point for deploying on-device intelligence. By
                 integrating artificial intelligence (AI) closer to data
                 sources, these systems aim to achieve faster responses,
                 reduce bandwidth usage, and preserve privacy.
                 Nevertheless, implementing AI in limited hardware
                 environments poses substantial challenges in terms of
                 computation, energy efficiency, model complexity, and
                 reliability. This paper provides a comprehensive review
                 of state-of-the-art methodologies, examining how recent
                 advances in model compression, TinyML frameworks, and
                 federated learning paradigms are enabling AI in tightly
                 constrained devices. We highlight both established and
                 emergent techniques for optimizing resource usage while
                 addressing security, privacy, and ethical concerns. We
                 then illustrate opportunities in key application
                 domains---such as healthcare, smart cities,
                 agriculture, and environmental monitoring---where
                 localized intelligence on resource-limited devices can
                 have broad societal impact. By exploring architectural
                 co-design strategies, algorithmic innovations, and
                 pressing research gaps, this paper offers a roadmap for
                 future investigations and industrial applications of AI
                 in resource-constrained devices.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lazea:2025:BEW,
  author =       "Dragos Lazea and Anca Hangan and Tudor Cioara",
  title =        "Building Equi-Width Histograms on Homomorphically
                 Encrypted Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "256",
  day =          "10",
  month =        jun,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060256",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/256",
  abstract =     "Histograms are widely used for summarizing data
                 distributions, detecting anomalies, and improving
                 machine learning models' accuracy. However, traditional
                 histogram-based methods require access to raw data,
                 raising privacy concerns, particularly in sensitive IoT
                 applications. Encryption-based techniques offer
                 potential solutions; however, they secure the data in
                 transit or storage, requiring decryption during
                 analysis, which exposes raw data to potential privacy
                 risks. In this paper, we propose a method for
                 constructing privacy-preserving histograms directly on
                 homomorphically encrypted IoT data, leveraging the Fast
                 Fully Homomorphic Encryption over the Torus (TFHE)
                 scheme implemented in the Concrete framework. To
                 overcome the challenges posed by homomorphic
                 encryption, we redesign the traditional histogram
                 construction algorithm, optimizing it for secure
                 computation by addressing constraints related to nested
                 loops and conditional statements. As an evaluation use
                 case, we have considered an outlier detection mechanism
                 based on histogram frequency counts, ensuring that all
                 data and computations remain encrypted throughout the
                 process. Our method achieves results consistent with
                 plaintext-based outlier detection while maintaining
                 reasonable computational overhead compared to those
                 reported in the existing literature.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Cui:2025:EAA,
  author =       "Bowen Cui and Jianwei Zhang",
  title =        "Exact and Approximation Algorithms for Task Offloading
                 with Service Caching and Dependency in Mobile Edge
                 Computing",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "255",
  day =          "10",
  month =        jun,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060255",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/255",
  abstract =     "With the continuous development of the Internet of
                 Things (IoT) and communication technologies, the demand
                 for low latency in practical applications is becoming
                 increasingly significant. Mobile edge computing, as a
                 promising computational model, is receiving growing
                 attention. However, most existing studies fail to
                 consider two critical factors: task dependency and
                 service caching. Additionally, the majority of proposed
                 solutions are not related to the optimal solution. We
                 investigate the task offloading problem in mobile edge
                 computing. Considering the requirements of applications
                 for service caching and task dependency, we define an
                 optimization problem to minimize the delay under the
                 constraint of maximum completion cost and present a
                 (1+\SGMLentity{1013}) -approximation algorithm and an
                 exact algorithm. Specifically, the offloading scheme is
                 determined based on the relationships between tasks as
                 well as the cost and delay incurred by data
                 transmission and task execution. Simulation results
                 demonstrate that in all cases, the offloading schemes
                 obtained by our algorithm consistently outperform other
                 algorithms. Moreover, the approximation ratio to the
                 optimal solution from the approximation algorithm is
                 validated to be less than (1+\SGMLentity{1013}), and
                 the exact algorithm consistently produces the optimal
                 solution.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Begum:2025:ITI,
  author =       "Momotaz Begum and Abm Kamrul Islam Riad and Abdullah
                 {Al Mamun} and Thofazzol Hossen and Salah Uddin and Md
                 Nurul Absur and Hossain Shahriar",
  title =        "{Internet of Things} ({IoT})-Based Solutions for
                 Uneven Roads and Balanced Vehicle Systems Using
                 {YOLOv8}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "254",
  day =          "9",
  month =        jun,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060254",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/254",
  abstract =     "Uneven roads pose significant challenges to vehicle
                 stability, passenger comfort, and safety, especially in
                 snowy and mountainous regions. These problems are often
                 complex and challenging to resolve with traditional
                 detection and stabilization methods. This paper
                 presents a dual-method approach to improving vehicle
                 stability by identifying road irregularities and
                 dynamically adjusting the balance. The proposed
                 solution combines YOLOv8 for real-time road anomaly
                 detection with a GY-521 sensor to track the speed of
                 servo motors, facilitating immediate stabilization.
                 YOLOv8 achieves a peak precision of 0.99 at a
                 confidence threshold of 1.0 rate in surface
                 recognition, surpassing conventional sensor-based
                 detection. The vehicle design is divided into two
                 sections: an upper passenger seating area and a lower
                 section that contains the engine and wheels. The GY-521
                 sensor is strategically placed to monitor road
                 conditions, while the servomotor stabilizes the upper
                 section, ensuring passenger comfort and reducing the
                 risk of accidents. This setup maintains stability even
                 on uneven terrain. Furthermore, the proposed solution
                 significantly reduces collision risk, vehicle wear, and
                 maintenance costs while improving operational
                 efficiency. Its compatibility with various vehicles and
                 capabilities makes it an excellent candidate for
                 enhancing road safety and driving experience in
                 challenging environments. In addition, this work marks
                 a crucial step towards a safer, more sustainable, and
                 more comfortable transportation system.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Niu:2025:TAA,
  author =       "Haixu Niu and Yonghai Li and Shuaixin Hou and Tianfei
                 Chen and Lijun Sun and Mingyang Gu and Muhammad Irsyad
                 Abdullah",
  title =        "Topology-Aware Anchor Node Selection Optimization for
                 Enhanced {DV}-Hop Localization in {IoT}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "253",
  day =          "8",
  month =        jun,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060253",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/253",
  abstract =     "Node localization is a critical challenge in Internet
                 of Things (IoT) applications. The DV-Hop algorithm,
                 which relies on hop counts for localization, assumes
                 that network nodes are uniformly distributed. It
                 estimates actual distances between nodes based on the
                 number of hops. However, in practical IoT networks,
                 node distribution is often non-uniform, leading to
                 complex and irregular topologies that significantly
                 reduce the localization accuracy of the original DV-Hop
                 algorithm. To improve localization performance in
                 non-uniform topologies, we propose an enhanced DV-Hop
                 algorithm using Grey Wolf Optimization (GWO). First,
                 the impact of non-uniform node distribution on hop
                 count and average hop distance is analyzed. A binary
                 Grey Wolf Optimization algorithm (BGWO) is then applied
                 to develop an optimal anchor node selection strategy.
                 This strategy eliminates anchor nodes with high
                 estimation errors and selects a subset of high-quality
                 anchors to improve the localization of unknown nodes.
                 Second, in the multilateration stage, the traditional
                 least square method is replaced by a continuous GWO
                 algorithm to solve the distance equations with higher
                 precision. Simulated experimental results show that the
                 proposed GWO-enhanced DV-Hop algorithm significantly
                 improves localization accuracy in non-uniform
                 topologies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Shehmir:2025:LCS,
  author =       "Sarama Shehmir and Rasha Kashef",
  title =        "{LLM4Rec}: a Comprehensive Survey on the Integration
                 of Large Language Models in Recommender
                 Systems---Approaches, Applications and Challenges",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "252",
  day =          "4",
  month =        jun,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060252",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/252",
  abstract =     "The synthesis of large language models (LLMs) and
                 recommender systems has been a game-changer in tailored
                 content onslaught with applications ranging from
                 e-commerce, social media, and education to health care.
                 This survey covers the usage of LLMs for content
                 recommendations (LLM4Rec). LLM4Rec has opened up a
                 whole set of challenges in terms of scale, real-time
                 processing, and data privacy, all of which we touch
                 upon along with potential future directions for
                 research in areas such as multimodal recommendations
                 and reinforcement learning for long-term engagement.
                 This survey combines existing developments and outlines
                 possible future developments, thus becoming a point of
                 reference for other researchers and practitioners in
                 developing the future of LLM-based recommendation
                 systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ahmed:2025:HMN,
  author =       "Naveed Ahmed and Md Asri Ngadi and Abdulaleem Ali
                 Almazroi and Nouf Atiahallah Alghanmi",
  title =        "Hybrid Model for Novel Attack Detection Using a
                 Cluster-Based Machine Learning Classification Approach
                 for the {Internet of Things} ({IoT})",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "251",
  day =          "31",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060251",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/251",
  abstract =     "To combat the growing danger of zero-day attacks on
                 IoT networks, this study introduces a Cluster-Based
                 Classification (CBC) method. Security vulnerabilities
                 have become more apparent with the growth of IoT
                 devices, calling for new approaches to identify unique
                 threats quickly. The hybrid CBC approach uses optimized
                 k-means clustering to find commonalities across
                 different abnormalities, intending to quickly identify
                 and classify unknown harmful attacks in a varied IoT
                 network. The technique is fine-tuned for eight-class
                 and two-class classifications, supporting different
                 attacks using the IoTCIC2023 dataset and SelectKBest
                 feature selection. Robust analysis is achieved by
                 evaluating and aggregating the performance of machine
                 learning classifiers such as XGBoost, AdaBoost, KNN,
                 and Random Forest. In two-class classification, Random
                 Forest achieves 95.11\% accuracy, while in eight-class
                 classification, KNN tops the charts with 88.24\%. These
                 results demonstrate noteworthy accuracy. The suggested
                 CBC technique is effective, as shown by comparisons
                 with state-of-the-art approaches. Despite several
                 caveats and dataset specifications, this study provides
                 a useful tool for academics and practitioners in the
                 ever-changing field of cybersecurity by suggesting a
                 method to strengthen the security of IoT networks
                 against new threats.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Santana-Cruz:2025:SPE,
  author =       "Rene Francisco Santana-Cruz and Martin Moreno and
                 Daniel Aguilar-Torres and Rom{\'a}n Arturo
                 Valverde-Dom{\'\i}nguez and Rub{\'e}n
                 V{\'a}zquez-Medina",
  title =        "Signal Preprocessing for Enhanced {IoT} Device
                 Identification Using Support Vector Machine",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "250",
  day =          "31",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060250",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/250",
  abstract =     "Device identification based on radio frequency
                 fingerprinting is widely used to improve the security
                 of Internet of Things systems. However, noise and
                 acquisition inconsistencies in raw radio frequency
                 signals can affect the effectiveness of classification,
                 identification and authentication algorithms used to
                 distinguish Bluetooth devices. This study investigates
                 how the RF signal preprocessing techniques affect the
                 performance of a support vector machine classifier
                 based on radio frequency fingerprinting. Four options
                 derived from an RF signal preprocessing technique are
                 evaluated, each of which is applied to the raw radio
                 frequency signals in an attempt to improve the
                 consistency between signals emitted by the same
                 Bluetooth device. Experiments conducted on raw
                 Bluetooth signals from twenty-four smartphone radios
                 from two public databases of RF signals show that
                 selecting an appropriate RF signal preprocessing
                 approach can significantly improve the effectiveness of
                 a support vector machine classifier-based algorithm
                 used to discriminate Bluetooth devices.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Arnaoutoglou:2025:PRC,
  author =       "Dimitrios G. Arnaoutoglou and Tzichat M. Empliouk and
                 Theodoros N. F. Kaifas and Constantinos L. Zekios and
                 George A. Kyriacou",
  title =        "Perspectives and Research Challenges in Wireless
                 Communications Hardware for the Future {Internet} and
                 Its Applications Services",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "249",
  day =          "31",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060249",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/249",
  abstract =     "The transition from 5G to 6G wireless systems
                 introduces new challenges at the physical layer,
                 including the need for higher frequency operations,
                 massive MIMO deployment, advanced beamforming
                 techniques, and sustainable energy harvesting
                 mechanisms. A plethora of feature articles, review and
                 white papers, and roadmaps elaborate on the
                 perspectives and research challenges of wireless
                 systems, in general, including both unified physical
                 and cyber space. Hence, this paper presents a
                 comprehensive review of the technological challenges
                 and recent advancements in wireless communication
                 hardware that underpin the development of
                 next-generation networks, particularly 6G. Emphasizing
                 the physical layer, the study explores critical
                 enabling technologies including beamforming, massive
                 MIMO, reconfigurable intelligent surfaces (RIS),
                 millimeter-wave (mmWave) and terahertz (THz)
                 communications, wireless power transfer, and energy
                 harvesting. These technologies are analyzed in terms of
                 their functional roles, implementation challenges, and
                 integration into future wireless infrastructure. Beyond
                 traditional physical layer components, the paper also
                 discusses the role of reconfigurable RF front-ends,
                 innovative antenna architectures, and user-end devices
                 that contribute to the adaptability and efficiency of
                 emerging communication systems. In addition, the
                 inclusion of application-driven paradigms such as
                 digital twins highlights how new use cases are shaping
                 design requirements and pushing the boundaries of
                 hardware capabilities. By linking foundational
                 physical-layer technologies with evolving application
                 demands, this work provides a holistic perspective
                 aimed at guiding future research directions and
                 informing the design of scalable, energy-efficient, and
                 resilient wireless communication platforms for the
                 Future Internet. Specifically, we first try to identify
                 the demands and, in turn, explore existing or emerging
                 technologies that have the potential to meet these
                 needs. Especially, there will be an extended reference
                 about the state-of-the-art antennas for massive MIMO
                 terrestrial and non-terrestrial networks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Amft:2025:TMN,
  author =       "Tobias Amft and Kalman Graffi",
  title =        "A Tale of Many Networks: Splitting and Merging of
                 Chord-like Overlays in Partitioned Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "248",
  day =          "31",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060248",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/248",
  abstract =     "Peer-to-peer overlays define an approach to operating
                 data management platforms, which are robust against
                 censorship attempts from countries or large
                 enterprises. The robustness of such overlays is
                 endangered in the presence of national Internet
                 isolations, such as was the case in recent years during
                 political revolutions. In this paper, we focus on
                 splits and, with stronger emphasis, on the merging of
                 ring-based overlays in the presence of network
                 partitioning in the underlying Internet due to various
                 reasons. We present a new merging algorithm named the
                 Ring Reunion Algorithm and highlight a method for
                 reducing the number of messages in both separated and
                 united overlay states. The algorithm is parallelized
                 for accelerated merging and is able to automatically
                 detect overlay partitioning and start the corresponding
                 merging processes. Through simulations, we evaluate the
                 new Ring Reunion Algorithm in its simple and
                 parallelized forms in comparison to a plain Chord
                 algorithm, the Chord--Zip algorithm, and two versions
                 of the Ring-Unification Algorithm. The evaluation shows
                 that only our parallelized Ring Reunion Algorithm
                 allows the merging of two, three, and more isolated
                 overlay networks in parallel. Our approach quickly
                 merges the overlays, even under churn, and stabilizes
                 the node contacts in the overlay with small traffic
                 overhead.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Baruah:2025:EPP,
  author =       "Sangita Baruah and Vaskar Deka and Dulumani Das and
                 Utpal Barman and Manob Jyoti Saikia",
  title =        "Enhanced Peer-to-Peer Botnet Detection Using
                 Differential Evolution for Optimized Feature
                 Selection",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "247",
  day =          "30",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060247",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/247",
  abstract =     "With the growing prevalence of cybercrime, botnets
                 have emerged as a significant threat, infiltrating an
                 increasing number of legitimate computers annually.
                 Challenges arising for organizations, educational
                 institutions, and individuals as a result of botnet
                 attacks include distributed denial of service (DDoS)
                 attacks, phishing attacks, and extortion attacks,
                 generation of spam, and identity theft. The stealthy
                 nature of botnets, characterized by constant
                 alterations in network structures, attack
                 methodologies, and data transmission patterns, poses a
                 growing difficulty in their detection. This paper
                 introduces an innovative strategy for mitigating botnet
                 threats. Employing differential evolution, we propose a
                 feature selection approach that enhances the ability to
                 discern peer-to-peer (P2P) botnet traffic amidst
                 evolving cyber threats. Differential evolution is a
                 population-based meta-heuristic technique which can be
                 applied to nonlinear and non-differentiable
                 optimization problems owing to its fast convergence and
                 use of few control parameters. Apart from that, an
                 ensemble learning algorithm is also employed to support
                 and enhance the detection phase, providing a robust
                 defense against the dynamic and sophisticated nature of
                 modern P2P botnets. The results demonstrate that our
                 model achieves 99.99\% accuracy, 99.49\% precision,
                 98.98\% recall, and 99.23\% F1-score, which outperform
                 the state-of-the-art P2P detection approaches.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Elkhodr:2025:ADF,
  author =       "Mahmoud Elkhodr",
  title =        "An {AI}-Driven Framework for Integrated Security and
                 Privacy in {Internet of Things} Using Quantum-Resistant
                 Blockchain",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "246",
  day =          "30",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060246",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/246",
  abstract =     "The growing deployment of the Internet of Things (IoT)
                 across various sectors introduces significant security
                 and privacy challenges. Although numerous individual
                 solutions exist, comprehensive frameworks that
                 effectively combine advanced technologies to address
                 evolving threats are lacking. This paper presents the
                 Integrated Adaptive Security Framework for IoT
                 (IASF-IoT), which integrates artificial intelligence,
                 blockchain technology, and quantum-resistant
                 cryptography into a unified solution tailored for IoT
                 environments. Central to the framework is an adaptive
                 AI-driven security orchestration mechanism,
                 complemented by blockchain-based identity management,
                 lightweight quantum-resistant protocols, and Digital
                 Twins to predict and proactively mitigate threats. A
                 theoretical performance model and large-scale
                 simulation involving 1000 heterogeneous IoT devices
                 were used to evaluate the framework. Results showed
                 that IASF-IoT achieved detection accuracy between 85\%
                 and 99\%, with simulated energy consumption remaining
                 below 1.5 mAh per day and response times averaging
                 around 2 s. These findings suggest that the framework
                 offers strong potential for scalable, low-overhead
                 security in resource-constrained IoT environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fareedi:2025:SFH,
  author =       "Abid Ali Fareedi and Stephane Gagnon and Ahmad
                 Ghazawneh and Raul Valverde",
  title =        "Semantic Fusion of Health Data: Implementing a
                 Federated Virtualized Knowledge Graph Framework
                 Leveraging Ontop System",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "245",
  day =          "30",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060245",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/245",
  abstract =     "Data integration (DI) and semantic interoperability
                 (SI) are critical in healthcare, enabling seamless,
                 patient-centric data sharing across systems to meet the
                 demand for instant, unambiguous access to health
                 information. Federated information systems (FIS)
                 highlight auspicious issues for seamless DI and SI
                 stemming from diverse data sources or models. We
                 present a hybrid ontology-based design science research
                 engineering (ODSRE) methodology that combines design
                 science activities with ontology engineering principles
                 to address the above-mentioned issues. The ODSRE
                 constructs a systematic mechanism leveraging the Ontop
                 virtual paradigm to establish a state-of-the-art
                 federated virtual knowledge graph framework (FVKG)
                 embedded virtualized knowledge graph approach to
                 mitigate the aforementioned challenges effectively. The
                 proposed FVKG helps construct a virtualized data
                 federation leveraging the Ontop semantic query engine
                 that effectively resolves data bottlenecks. Using a
                 virtualized technique, the FVKG helps to reduce data
                 migration, ensures low latency and dynamic freshness,
                 and facilitates real-time access while upholding
                 integrity and coherence throughout the federation
                 system. As a result, we suggest a customized framework
                 for constructing ontological monolithic semantic
                 artifacts, especially in FIS. The proposed FVKG
                 incorporates ontology-based data access (OBDA) to build
                 a monolithic virtualized repository that integrates
                 various ontological-driven artifacts and ensures
                 semantic alignments using schema mapping techniques.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Moccardi:2025:RCF,
  author =       "Alberto Moccardi and Claudia Conte and Rajib Chandra
                 Ghosh and Francesco Moscato",
  title =        "A Robust Conformal Framework for {IoT}-Based
                 Predictive Maintenance",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "244",
  day =          "30",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060244",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/244",
  abstract =     "This study, set within the vast and varied research
                 field of industrial Internet of Things (IoT) systems,
                 proposes a methodology to address uncertainty
                 quantification (UQ) issues in predictive maintenance
                 (PdM) practices. At its core, this paper leverages the
                 commercial modular aero-propulsion system simulation
                 (CMAPSS) dataset to evaluate different artificial
                 intelligence (AI) prognostic algorithms for remaining
                 useful life (RUL) forecasting while supporting the
                 estimation of a robust confidence interval (CI). The
                 methodology primarily involves the comparison of
                 statistical learning (SL), machine learning (ML), and
                 deep learning (DL) techniques for each different
                 scenario of the CMAPSS, evaluating the performances
                 through a tailored metric, the S-score metric, and then
                 benchmarking diverse conformal-based uncertainty
                 estimation techniques, remarkably naive, weighted, and
                 bootstrapping, offering a more suitable and reliable
                 alternative to classical RUL prediction. The results
                 obtained highlight the peculiarities and benefits of
                 the conformal approach, despite probabilistic models
                 favoring the adoption of complex models in cases where
                 the operating conditions of the machine are multiple,
                 and suggest the use of weighted conformal practices in
                 non-exchangeability conditions while recommending
                 bootstrapping alternatives for contexts with a more
                 substantial presence of noise in the data.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhang:2025:RAF,
  author =       "Xubo Zhang and Yang Luo",
  title =        "Resource Allocation for Federated Learning with
                 Heterogeneous Computing Capability in
                 Cloud--Edge--Client {IoT} Architecture",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "243",
  day =          "30",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060243",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/243",
  abstract =     "A federated learning (FL) framework for
                 cloud--edge--client collaboration performs local
                 aggregation of model parameters through edges, reducing
                 communication overhead from clients to the cloud. This
                 framework is particularly suitable for Internet of
                 Things (IoT)-based secure computing scenarios that
                 require extensive computation and frequent parameter
                 updates, as it leverages the distributed nature of IoT
                 devices to enhance data privacy and reduce latency. To
                 address the issue of high-computation-capability
                 clients waiting due to varying computing capabilities
                 under heterogeneous device conditions, this paper
                 proposes an improved resource allocation scheme based
                 on a three-layer FL framework. This scheme optimizes
                 the communication parameter volume from clients to the
                 edge by implementing a method based on random dropout
                 and parameter completion before and after
                 communication, ensuring that local models can be
                 transmitted to the edge simultaneously, regardless of
                 different computation times. This scheme effectively
                 resolves the problem of high-computation-capability
                 clients experiencing long waiting times. Additionally,
                 it optimizes the similarity pairing method, the Shapley
                 Value (SV) aggregation strategy, and the client
                 selection method to better accommodate heterogeneous
                 computing capabilities found in IoT environments.
                 Experiments demonstrate that this improved scheme is
                 more suitable for heterogeneous IoT client scenarios,
                 reducing system latency and energy consumption while
                 enhancing model performance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Huang:2025:IDC,
  author =       "Xiaoying Huang and Jingwei Wang",
  title =        "Inter-Data Center {RDMA}: Challenges, Status, and
                 Future Directions",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "242",
  day =          "29",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060242",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/242",
  abstract =     "Remote Direct Memory Access (RDMA) has been widely
                 implemented in data centers (DCs) due to its
                 high-bandwidth, low-latency, and low-overhead
                 characteristics. In recent years, as various
                 applications relying on inter-DC interconnection have
                 continuously emerged, the demand for deploying RDMA
                 across DCs has been on the rise. Numerous studies have
                 focused on intra-DC RDMA. However, research on inter-DC
                 RDMA is relatively scarce, yet it is showing a growing
                 tendency. Inspired by this trend, this article
                 identifies and discusses specific challenges in
                 inter-DC RDMA deployment, such as congestion control
                 and load balancing. Subsequently, it surveys the recent
                 progress in enhancing the applicability of inter-DC
                 RDMA. Finally, it presents future research directions
                 and opportunities. As the first review article focusing
                 on inter-DC RDMA, this article aims to provide valuable
                 insights and guidance for future research in this
                 emerging field. By systematically reviewing the current
                 state of inter-DC RDMA, we hope to establish a
                 foundation that will inspire and direct subsequent
                 studies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liu:2025:NDC,
  author =       "Qi Liu and Wanjing Ma",
  title =        "Navigating Data Corruption in Machine Learning:
                 Balancing Quality, Quantity, and Imputation
                 Strategies",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "241",
  day =          "29",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060241",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/241",
  abstract =     "Data corruption, including missing and noisy entries,
                 is a common challenge in real-world machine learning.
                 This paper examines its impact and mitigation
                 strategies through two experimental setups: supervised
                 NLP tasks (NLP-SL) and deep reinforcement learning for
                 traffic signal control (Signal-RL). This study analyzes
                 how varying corruption levels affect model performance,
                 evaluate imputation strategies, and assess whether
                 expanding datasets can counteract corruption effects.
                 The results indicate that performance degradation
                 follows a diminishing-return pattern, well modeled by
                 an exponential function. Noisy data harm performance
                 more than missing data, especially in sequential tasks
                 like Signal-RL where errors may compound. Imputation
                 helps recover missing data but can introduce noise,
                 with its effectiveness depending on corruption severity
                 and imputation accuracy. This study identifies clear
                 boundaries between when imputation is beneficial versus
                 harmful, and classifies tasks as either noise-sensitive
                 or noise-insensitive. Larger datasets reduce corruption
                 effects but offer diminishing gains at high corruption
                 levels. These insights guide the design of robust
                 systems, emphasizing smart data collection, imputation
                 decisions, and preprocessing strategies in noisy
                 environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Moreno-Menendez:2025:ECQ,
  author =       "Fabricio Miguel Moreno-Men{\'e}ndez and Victoriano
                 Eusebio Zacar{\'\i}as-Rodr{\'\i}guez and Sara Ricardina
                 Zacar{\'\i}as-Vallejos and Vicente Gonz{\'a}lez-Prida
                 and Pedro Emil Torres-Quillatupa and Hilario
                 Romero-Gir{\'o}n and Jos{\'e} Francisco {V{\'\i}a y
                 Rada-Vittes} and Luis {\'A}ngel Huaynate-Espejo",
  title =        "Enhancing Customer Quality of Experience Through
                 Omnichannel Digital Strategies: Evidence from a Service
                 Environment in an Emerging Context",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "6",
  pages =        "240",
  day =          "29",
  month =        may,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17060240",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/6/240",
  abstract =     "The proliferation of digital platforms and interactive
                 technologies has transformed the way service providers
                 engage with their customers, particularly in emerging
                 economies, where digital inclusion is an ongoing
                 process. This study explores the relationship between
                 omnichannel strategies and customer satisfaction,
                 conceptualized here as a proxy for Quality of
                 Experience (QoE), within a smart service station
                 located in a digitally underserved region. Grounded in
                 customer journey theory and the
                 expectancy--disconfirmation paradigm, the study
                 investigates how data integration, digital payment
                 systems, and logistical flexibility---key components of
                 intelligent e-service systems---influence user
                 perceptions and satisfaction. Based on a correlational
                 design with a non-probabilistic sample of 108
                 customers, the findings reveal a moderate association
                 between overall omnichannel integration and
                 satisfaction ({\rho} = 0.555, p {$<$} 0.01). However, a
                 multiple regression analysis indicates that no
                 individual dimension significantly predicts
                 satisfaction (adjusted R 2 = 0.002). These results
                 suggest that while users value system integration and
                 interaction flexibility, no single technical feature
                 drives satisfaction independently. The study
                 contributes to the growing field of intelligent
                 human-centric service systems by contextualizing QoE
                 and digital inclusion within emerging markets and by
                 emphasizing the importance of perceptual factors in
                 ICT-enabled environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ianculescu:2025:AND,
  author =       "Marilena Ianculescu and Lidia Bajenaru and Ana-Mihaela
                 Vasilevschi and Maria Gheorghe-Moisii and
                 Cristina-Gabriela Gheorghe",
  title =        "Advancing Neurodegenerative Disease Management:
                 Technical, Ethical, and Regulatory Insights from the
                 {NeuroPredict} Platform",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "320",
  day =          "21",
  month =        jul,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070320",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/320",
  abstract =     "On a worldwide scale, neurodegenerative diseases,
                 including multiple sclerosis, Parkinson's, and
                 Alzheimer's, face considerable healthcare challenges
                 demanding the development of novel approaches to early
                 detection and efficient treatment. With its ability to
                 provide real-time patient monitoring, customized
                 medical care, and advanced predictive analytics,
                 artificial intelligence (AI) is fundamentally
                 transforming the way healthcare is provided. Through
                 the integration of wearable physiological sensors,
                 motion sensors, and neurological assessment tools, the
                 NeuroPredict platform harnesses AI and smart sensor
                 technologies to enhance the management of specific
                 neurodegenerative diseases. Machine learning algorithms
                 process these data flows to find patterns that point
                 out disease evolution. This paper covers the design and
                 architecture of the NeuroPredict platform, stressing
                 the ethical and regulatory requirements that guide its
                 development. Initial development of AI algorithms for
                 disease monitoring, technical achievements, and
                 constant enhancements driven by early user feedback are
                 addressed in the discussion section. To ascertain the
                 platform's trustworthiness and data security, it also
                 points towards risk analysis and mitigation approaches.
                 The NeuroPredict platform's capability for achieving
                 AI-driven smart healthcare solutions is highlighted,
                 even though it is currently in the development stage.
                 Subsequent research is expected to focus on boosting
                 data integration, expanding AI models, and providing
                 regulatory compliance for clinical application. The
                 current results are based on incremental laboratory
                 tests using simulated user roles, with no clinical
                 patient data involved so far. This study reports an
                 experimental technology evaluation of modular
                 components of the NeuroPredict platform, integrating
                 multimodal sensors and machine learning pipelines in a
                 laboratory-based setting, with future co-design and
                 clinical validation foreseen for a later project
                 phase.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2025:IAD,
  author =       "Xinyu Li and Xiaoying Wang and Guoqing Yang and Jinsha
                 Zhang and Chunhui Li and Fangfang Cui and Ruize Gu",
  title =        "An Improved Approach to {DNS} Covert Channel Detection
                 Based on {DBM-ENSec}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "319",
  day =          "21",
  month =        jul,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070319",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/319",
  abstract =     "The covert nature of DNS covert channels makes them a
                 widely utilized method for data exfiltration by
                 malicious attackers. In response to this challenge, the
                 present study proposes a detection methodology for DNS
                 covert channels that employs a Deep Boltzmann Machine
                 with Enhanced Security (DBM-ENSec). This approach
                 entails the creation of a dataset through the
                 collection of malicious traffic associated with various
                 DNS covert channel attacks. Time-dependent grouping
                 features are excluded, and feature optimization is
                 conducted on individual traffic data through feature
                 selection and normalization to minimize redundancy,
                 enhancing the differentiation and stability of the
                 features. The result of this process is the extraction
                 of 23-dimensional features for each DNS packet. The
                 extracted features are converted to gray scale images
                 to improve the interpretability of the model and then
                 fed into an improved Deep Boltzmann Machine for further
                 optimization. The optimized features are then processed
                 by an ensemble of classifiers (including Random Forest,
                 XGBoost, LightGBM, and CatBoost) for detection
                 purposes. Experimental results show that the proposed
                 method achieves 99.92\% accuracy in detecting DNS
                 covert channels, with a validation accuracy of up to
                 98.52\% on publicly available datasets.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yaacoub:2025:TSS,
  author =       "Jean Paul A. Yaacoub and Hassan N. Noura and Ola
                 Salman and Khaled Chahine",
  title =        "Toward Secure Smart Grid Systems: Risks, Threats,
                 Challenges, and Future Directions",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "318",
  day =          "21",
  month =        jul,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070318",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/318",
  abstract =     "The evolution of electrical power systems into smart
                 grids has brought about significant advancements in
                 electricity generation, transmission, and utilization.
                 These cutting-edge grids have shown potential as an
                 effective way to maximize energy efficiency, manage
                 resources effectively, and enhance overall reliability
                 and sustainability. However, with the integration of
                 complex technologies and interconnected systems
                 inherent to smart grids comes a new set of safety and
                 security challenges that must be addressed. First, this
                 paper provides an in-depth review of the key
                 considerations surrounding safety and security in smart
                 grid environments, identifying potential risks,
                 vulnerabilities, and challenges associated with
                 deploying smart grid infrastructure within the context
                 of the Internet of Things (IoT). In response, we
                 explore both cryptographic and non-cryptographic
                 countermeasures, emphasizing the need for adaptive,
                 lightweight, and proactive security mechanisms. As a
                 key contribution, we introduce a layered classification
                 framework that maps smart grid attacks to affected
                 components and defense types, providing a clearer
                 structure for analyzing the impact of threats and
                 responses. In addition, we identify current gaps in the
                 literature, particularly in real-time anomaly
                 detection, interoperability, and post-quantum
                 cryptographic protocols, thus offering forward-looking
                 recommendations to guide future research. Finally, we
                 present the Multi-Layer Threat-Defense Alignment
                 Framework, a unique addition that provides a methodical
                 and strategic approach to cybersecurity planning by
                 aligning smart grid threats and defenses across
                 architectural layers.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alharthi:2025:ELA,
  author =       "Manal Alharthi and Faiza Medjek and Djamel Djenouri",
  title =        "Ensemble Learning Approaches for Multi-Class Intrusion
                 Detection Systems for the {Internet of Vehicles}
                 ({IoV}): a Comprehensive Survey",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "317",
  day =          "19",
  month =        jul,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070317",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/317",
  abstract =     "The emergence of the Internet of Vehicles (IoV) has
                 revolutionized intelligent transportation and
                 communication systems. However, IoV presents many
                 complex and ever-changing security challenges and thus
                 requires robust cybersecurity protocols. This paper
                 comprehensively describes and evaluates ensemble
                 learning approaches for multi-class intrusion detection
                 systems in the IoV environment. The study evaluates
                 several approaches, such as stacking, voting, boosting,
                 and bagging. A comprehensive review of the literature
                 spanning 2020 to 2025 reveals important trends and
                 topics that require further investigation and the
                 relative merits of different ensemble approaches. The
                 NSL-KDD, CICIDS2017, and UNSW-NB15 datasets are widely
                 used to evaluate the performance of Ensemble
                 Learning-Based Intrusion Detection Systems (ELIDS).
                 ELIDS evaluation is usually carried out using some
                 popular performance metrics, including Precision,
                 Accuracy, Recall, F1-score, and Area Under Receiver
                 Operating Characteristic Curve (AUC-ROC), which were
                 used to evaluate and measure the effectiveness of
                 different ensemble learning methods. Given the
                 increasing complexity and frequency of cyber threats in
                 IoV environments, ensemble learning methods such as
                 bagging, boosting, and stacking enhance adaptability
                 and robustness. These methods aggregate multiple
                 learners to improve detection rates, reduce false
                 positives, and ensure more resilient intrusion
                 detection models that can evolve alongside emerging
                 attack patterns.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Manriquez:2025:PAB,
  author =       "Manuel Ignacio Manr{\'\i}quez and Veronica Gil-Costa
                 and Mauricio Marin",
  title =        "Parallel Agent-Based Framework for Analyzing Urban
                 Agricultural Supply Chains",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "316",
  day =          "19",
  month =        jul,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070316",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/316",
  abstract =     "This work presents a parallel agent-based framework
                 designed to analyze the dynamics of vegetable trade
                 within a metropolitan area. The system integrates
                 agent-based and discrete event techniques to capture
                 the complex interactions among farmers, vendors, and
                 consumers in urban agricultural supply chains.
                 Decision-making processes are modeled in detail:
                 farmers select crops based on market trends and
                 environmental risks, while vendors and consumers adapt
                 their purchasing behavior according to seasonality,
                 prices, and availability. To efficiently handle the
                 computational demands of large-scale scenarios, we
                 adopt an optimistic approximate parallel execution
                 strategy. Furthermore, we introduce a credit-based load
                 balancing mechanism that mitigates the effects of
                 heterogeneous communication patterns and improves
                 scalability. This framework enables detailed analysis
                 of food distribution systems in urban contexts,
                 offering insights relevant to smart cities and digital
                 agriculture initiatives.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mazloomi:2025:NMS,
  author =       "Fateme Mazloomi and Shahram Shah Heydari and Khalil
                 El-Khatib",
  title =        "A Novel Multi-Server Federated Learning Framework in
                 Vehicular Edge Computing",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "315",
  day =          "19",
  month =        jul,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070315",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/315",
  abstract =     "Federated learning (FL) has emerged as a powerful
                 approach for privacy-preserving model training in
                 autonomous vehicle networks, where real-world
                 deployments rely on multiple roadside units (RSUs)
                 serving heterogeneous clients with intermittent
                 connectivity. While most research focuses on
                 single-server or hierarchical cloud-based FL,
                 multi-server FL can alleviate the communication
                 bottlenecks of traditional setups. To this end, we
                 propose an edge-based, multi-server FL (MS-FL)
                 framework that combines performance-driven aggregation
                 at each server---including statistical weighting of
                 peer updates and outlier mitigation---with an
                 application layer handover protocol that preserves
                 model updates when vehicles move between RSU coverage
                 areas. We evaluate MS-FL on both MNIST and GTSRB
                 benchmarks under shard- and Dirichlet-based non-IID
                 splits, comparing it against single-server FL and a
                 two-layer edge-plus-cloud baseline. Over multiple
                 communication rounds, MS-FL with the Statistical
                 Performance-Aware Aggregation method and Dynamic
                 Weighted Averaging Aggregation achieved up to a
                 20-percentage-point improvement in accuracy and
                 consistent gains in precision, recall, and F1-score
                 (95\% confidence), while matching the low latency of
                 edge-only schemes and avoiding the extra model transfer
                 delays of cloud-based aggregation. These results
                 demonstrate that coordinated cooperation among servers
                 based on model quality and seamless handovers can
                 accelerate convergence, mitigate data heterogeneity,
                 and deliver robust, privacy-aware learning in connected
                 vehicle environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Balaban:2025:TNN,
  author =       "B{\'e}atrix-May Balaban and Ioan Sacala and
                 Alina-Claudia Petrescu-Nita",
  title =        "{TriagE-NLU}: a Natural Language Understanding System
                 for Clinical Triage and Intervention in Multilingual
                 Emergency Dialogues",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "314",
  day =          "18",
  month =        jul,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070314",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/314",
  abstract =     "Telemedicine in emergency contexts presents unique
                 challenges, particularly in multilingual and
                 low-resource settings where accurate, clinical
                 understanding and triage decision support are critical.
                 This paper introduces TriagE-NLU, a novel multilingual
                 natural language understanding system designed to
                 perform both semantic parsing and clinical intervention
                 classification from emergency dialogues. The system is
                 built on a federated learning architecture to ensure
                 data privacy and adaptability across regions and is
                 trained using TriageX, a synthetic, clinically grounded
                 dataset covering five languages (English, Spanish,
                 Romanian, Arabic, and Mandarin). TriagE-NLU integrates
                 fine-tuned multilingual transformers with a hybrid
                 rules-and-policy decision engine, enabling it to parse
                 structured medical information (symptoms, risk factors,
                 temporal markers) and recommend appropriate
                 interventions based on recognized patterns. Evaluation
                 against strong multilingual baselines, including mT5,
                 mBART, and XLM-RoBERTa, demonstrates superior
                 performance by TriagE-NLU, achieving F1 scores of 0.91
                 for semantic parsing and 0.89 for intervention
                 classification, along with 0.92 accuracy and a BLEU
                 score of 0.87. These results validate the system's
                 robustness in multilingual emergency telehealth and its
                 ability to generalize across diverse input scenarios.
                 This paper establishes a new direction for
                 privacy-preserving, AI-assisted triage systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kulkarni:2025:UZT,
  author =       "Shruti Kulkarni and Alexios Mylonas and Stilianos
                 Vidalis",
  title =        "Using the Zero Trust Five-Step Implementation Process
                 with Smart Environments: State-of-the-Art Review and
                 Future Directions",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "313",
  day =          "18",
  month =        jul,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070313",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/313",
  abstract =     "There is a growing pressure on industry to secure
                 environments and demonstrate their commitment in taking
                 right steps to secure their products. This is because
                 of the growing number of security compromises in the IT
                 industry, Operational Technology environment, Internet
                 of Things environment and smart home devices. These
                 compromises are not just about data breaches or data
                 exfiltration, but also about unauthorised access to
                 devices that are not configured correctly and
                 vulnerabilities in software components, which usually
                 lead to insecure authentication and authorisation.
                 Incorrect configurations are usually in the form of
                 devices being made available on the Internet (public
                 domain), reusable credentials, access granted without
                 verifying the requestor, and easily available
                 credentials like default credentials. Organisations
                 seeking to address the dual pressure of demonstrating
                 steps in the right direction and addressing
                 unauthorised access to resources can find a viable
                 approach in the form of the zero trust concept. Zero
                 trust principles are about moving security controls
                 closer to the data, applications, assets and services
                 and are based on the principle of ``never trust, always
                 verify''. As it stands today, zero trust research has
                 advanced far beyond the concept of ``never trust,
                 always verify''. This paper provides the culmination of
                 a literature review of research conducted in the space
                 of smart home devices and IoT and the applicability of
                 the zero trust five-step implementation process to
                 secure them. We discuss the history of zero trust, the
                 tenets of zero trust, the five-step implementation
                 process for zero trust, and its adoption for smart home
                 devices and Internet of Things, and we provide
                 suggestions for future research.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kalodanis:2025:ESF,
  author =       "Konstantinos Kalodanis and Charalampos Papapavlou and
                 Georgios Feretzakis",
  title =        "Enhancing Security in {5G} and Future {6G} Networks:
                 Machine Learning Approaches for Adaptive Intrusion
                 Detection and Prevention",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "312",
  day =          "18",
  month =        jul,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070312",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/312",
  abstract =     "The evolution from 4G to 5G---and eventually to the
                 forthcoming 6G networks---has revolutionized wireless
                 communications by enabling high-speed, low-latency
                 services that support a wide range of applications,
                 including the Internet of Things (IoT), smart cities,
                 and critical infrastructures. However, the unique
                 characteristics of these networks---extensive
                 connectivity, device heterogeneity, and architectural
                 flexibility---impose significant security challenges.
                 This paper introduces a comprehensive framework for
                 enhancing the security of current and emerging wireless
                 networks by integrating state-of-the-art machine
                 learning (ML) techniques into intrusion detection and
                 prevention systems. It also thoroughly explores the key
                 aspects of wireless network security, including
                 architectural vulnerabilities in both 5G and future 6G
                 networks, novel ML algorithms tailored to address
                 evolving threats, privacy-preserving mechanisms, and
                 regulatory compliance with the EU AI Act. Finally, a
                 Wireless Intrusion Detection Algorithm (WIDA) is
                 proposed, demonstrating promising results in improving
                 wireless network security.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gazzan:2025:DLF,
  author =       "Mazen Gazzan and Bader Alobaywi and Mohammed Almutairi
                 and Frederick T. Sheldon",
  title =        "A Deep Learning Framework for Enhanced Detection of
                 Polymorphic Ransomware",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "311",
  day =          "18",
  month =        jul,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070311",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/311",
  abstract =     "Ransomware, a significant cybersecurity threat,
                 encrypts files and causes substantial damage, making
                 early detection crucial yet challenging. This paper
                 introduces a novel multi-phase framework for early
                 ransomware detection, designed to enhance accuracy and
                 minimize false positives. The framework addresses the
                 limitations of existing methods by integrating
                 operational data with situational and threat
                 intelligence, enabling it to dynamically adapt to the
                 evolving ransomware landscape. Key innovations include
                 (1) data augmentation using a Bi-Gradual Minimax
                 Generative Adversarial Network (BGM-GAN) to generate
                 synthetic ransomware attack patterns, addressing data
                 insufficiency; (2) Incremental Mutual Information
                 Selection (IMIS) for dynamically selecting relevant
                 features, adapting to evolving ransomware behaviors and
                 reducing computational overhead; and (3) a Deep Belief
                 Network (DBN) detection architecture, trained on the
                 augmented data and optimized with Uncertainty-Aware
                 Dynamic Early Stopping (UA-DES) to prevent overfitting.
                 The model demonstrates a 4\% improvement in detection
                 accuracy (from 90\% to 94\%) through synthetic data
                 generation and reduces false positives from 15.4\% to
                 14\%. The IMIS technique further increases accuracy to
                 96\% while reducing false positives. The UA-DES
                 optimization boosts accuracy to 98.6\% and lowers false
                 positives to 10\%. Overall, this framework effectively
                 addresses the challenges posed by evolving ransomware,
                 significantly enhancing detection accuracy and
                 reliability.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mahmoudi:2025:TGA,
  author =       "Isra Mahmoudi and Djallel Eddine Boubiche and Samir
                 Athmani and Homero Toral-Cruz and Freddy I. Chan-Puc",
  title =        "Toward Generative {AI}-Based Intrusion Detection
                 Systems for the {Internet of Vehicles} ({IoV})",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "310",
  day =          "17",
  month =        jul,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070310",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/310",
  abstract =     "The increasing complexity and scale of Internet of
                 Vehicles (IoV) networks pose significant security
                 challenges, necessitating the development of advanced
                 intrusion detection systems (IDS). Traditional IDS
                 approaches, such as rule-based and signature-based
                 methods, are often inadequate in detecting novel and
                 sophisticated attacks due to their limited adaptability
                 and dependency on predefined patterns. To overcome
                 these limitations, machine learning (ML) and deep
                 learning (DL)-based IDS have been introduced, offering
                 better generalization and the ability to learn from
                 data. However, these models can still struggle with
                 zero-day attacks, require large volumes of labeled
                 data, and may be vulnerable to adversarial examples. In
                 response to these challenges, Generative AI-based
                 IDS---leveraging models such as Generative Adversarial
                 Networks (GANs), Variational Autoencoders (VAEs), and
                 Transformers---have emerged as promising solutions that
                 offer enhanced adaptability, synthetic data generation
                 for training, and improved detection capabilities for
                 evolving threats. This survey provides an overview of
                 IoV architecture, vulnerabilities, and classical IDS
                 techniques while focusing on the growing role of
                 Generative AI in strengthening IoV security. It
                 discusses the current landscape, highlights the key
                 challenges, and outlines future research directions
                 aimed at building more resilient and intelligent IDS
                 for the IoV ecosystem.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Udokwu:2025:LBE,
  author =       "Chibuzor Udokwu and Roxana Voicu-Dorobantu and Abiodun
                 Afolayan Ogunyemi and Alex Norta and Nata Sturua and
                 Stefan Cra{\ss}",
  title =        "Leveraging Blockchain for Ethical {AI}: Mitigating
                 Digital Threats and Strengthening Societal Resilience",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "309",
  day =          "17",
  month =        jul,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070309",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/309",
  abstract =     "This position paper proposes a conceptual framework
                 (CF-BIAI-SXT) for integrating blockchain with AI to
                 enhance ethical governance, transparency, and privacy
                 in high-risk AI applications that ensure societal
                 resilience through the mitigation of sexual
                 exploitation. Sextortion is a growing form of digital
                 sexual exploitation, and the role of AI in its
                 mitigation and the ethical issues that arise provide a
                 good case for this paper. Through a combination of
                 systematic and narrative literature reviews, the paper
                 first explores the ethical shortcomings of existing AI
                 systems in sextortion prevention and assesses the
                 capacity of blockchain operations to mitigate these
                 limitations. It then develops CF-BIAI-SXT, a framework
                 operationalized through BPMN-modeled components and
                 structured into a three-layer implementation strategy
                 composed of technical enablement, governance alignment,
                 and continuous oversight. The framework is then
                 situated within real-world regulatory constraints,
                 including GDPR and the EU AI Act. This position paper
                 concludes that a resilient society needs ethical,
                 privacy-first, and socially resilient digital
                 infrastructures, and integrating two core technologies,
                 such as AI and blockchain, creates a viable pathway
                 towards this desideratum. Mitigating high-risk
                 environments, such as sextortion, may be a fundamental
                 first step in this pathway, with the potential
                 expansion to other forms of online threats.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhang:2025:RRS,
  author =       "Xing Zhang and Yuexiang Luo and Tianning Li",
  title =        "A Review of Research on Secure Aggregation for
                 Federated Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "308",
  day =          "17",
  month =        jul,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070308",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/308",
  abstract =     "Federated learning (FL) is an advanced distributed
                 machine learning method that effectively solves the
                 data silo problem. With the increasing popularity of
                 federated learning and the growing importance of
                 privacy protection, federated learning methods that can
                 securely aggregate models have received widespread
                 attention. Federated learning enables clients to train
                 models locally and share their model updates with the
                 server. While this approach allows collaborative model
                 training without exposing raw data, it still risks
                 leaking sensitive information. To enhance privacy
                 protection in federated learning, secure aggregation is
                 considered a key enabling technology that requires
                 further in-depth investigation. This paper summarizes
                 the definition, classification, and applications of
                 federated learning; reviews secure aggregation
                 protocols proposed to address privacy and security
                 issues in federated learning; extensively analyzes the
                 selected protocols; and concludes by highlighting the
                 significant challenges and future research directions
                 in applying secure aggregation in federated learning.
                 The purpose of this paper is to review and analyze
                 prior research, evaluate the advantages and
                 disadvantages of various secure aggregation schemes,
                 and propose potential future research directions. This
                 work aims to serve as a valuable reference for
                 researchers studying secure aggregation in federated
                 learning.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rajendran:2025:ECV,
  author =       "Vidhya Prakash Rajendran and Deepalakshmi Perumalsamy
                 and Chinnasamy Ponnusamy and Ezhil Kalaimannan",
  title =        "An Efficient Continuous-Variable Quantum Key
                 Distribution with Parameter Optimization Using Elitist
                 Elk Herd Random Immigrants Optimizer and Adaptive
                 Depthwise Separable Convolutional Neural Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "307",
  day =          "17",
  month =        jul,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070307",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/307",
  abstract =     "Quantum memory is essential for the prolonged storage
                 and retrieval of quantum information. Nevertheless, no
                 current studies have focused on the creation of
                 effective quantum memory for continuous variables while
                 accounting for the decoherence rate. This work presents
                 an effective continuous-variable quantum key
                 distribution method with parameter optimization
                 utilizing the Elitist Elk Herd Random Immigrants
                 Optimizer (2E-HRIO) technique. At the outset of
                 transmission, the quantum device undergoes
                 initialization and authentication via Compressed
                 Hash-based Message Authentication Code with Encoded
                 Post-Quantum Hash (CHMAC-EPQH). The settings are
                 subsequently optimized from the authenticated device
                 via 2E-HRIO, which mitigates the effects of decoherence
                 by adaptively tuning system parameters. Subsequently,
                 quantum bits are produced from the verified device, and
                 pilot insertion is executed within the quantum bits.
                 The pilot-inserted signal is thereafter subjected to
                 pulse shaping using a Gaussian filter. The pulse-shaped
                 signal undergoes modulation. Authenticated
                 post-modulation, the prediction of link failure is
                 conducted through an authenticated channel using Radial
                 Density-Based Spatial Clustering of Applications with
                 Noise. Subsequently, transmission occurs via a
                 non-failure connection. The receiver performs channel
                 equalization on the received signal with Recursive
                 Regularized Least Mean Squares. Subsequently, a dataset
                 for side-channel attack authentication is gathered and
                 preprocessed, followed by feature extraction and
                 classification using Adaptive Depthwise Separable
                 Convolutional Neural Networks (ADS-CNNs), which
                 enhances security against side-channel attacks. The
                 quantum state is evaluated based on the signal
                 received, and raw data are collected. Thereafter, a
                 connection is established between the transmitter and
                 receiver. Both the transmitter and receiver perform the
                 scanning process. Thereafter, the calculation and
                 correction of the error rate are performed based on the
                 sifting results. Ultimately, privacy amplification and
                 key authentication are performed using the repaired key
                 via B-CHMAC-EPQH. The proposed system demonstrated
                 improved resistance to decoherence and side-channel
                 attacks, while achieving a reconciliation efficiency
                 above 90\% and increased key generation rate.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sepulveda-Cervantes:2025:CPS,
  author =       "Gabriel Sep{\'u}lveda-Cervantes and Eduardo
                 Vega-Alvarado and Edgar Alfredo Portilla-Flores and
                 Eduardo Vivanco-Rodr{\'\i}guez",
  title =        "Cyber-Physical System and {3D} Visualization for a
                 {SCADA}-Based Drinking Water Supply: a Case Study in
                 the {Lerma Basin, Mexico City}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "306",
  day =          "17",
  month =        jul,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070306",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/306",
  abstract =     "Cyber-physical systems such as Supervisory Control and
                 Data Acquisition (SCADA) have been applied in
                 industrial automation and infrastructure management for
                 decades. They are hybrid tools for administration,
                 monitoring, and continuous control of real physical
                 systems through their computational representation.
                 SCADA systems have evolved along with computing
                 technology, from their beginnings with low-performance
                 computers, monochrome monitors and communication
                 networks with a range of a few hundred meters, to
                 high-performance systems with advanced 3D graphics and
                 wired and wireless computer networks. This article
                 presents a methodology for the design of a SCADA system
                 with a 3D Visualization for Drinking Water Supply, and
                 its implementation in the Lerma Basin System of Mexico
                 City as a case study. The monitoring of water
                 consumption from the wells is presented, as well as the
                 pressure levels throughout the system. The 3D
                 visualization is generated from the GIS information and
                 the communication is carried out using a hybrid radio
                 frequency transmission system, satellite, and telephone
                 network. The pumps that extract water from each well
                 are teleoperated and monitored in real time. The
                 developed system can be scaled to generate a simulator
                 of water behavior of the Lerma Basin System and perform
                 contingency planning.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rajbhandari:2025:ASS,
  author =       "Yudeep Rajbhandari and Rokin Maharjan and Sakshi
                 Shrestha and Tomas Cerny",
  title =        "Attack Surface Score for Software Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "305",
  day =          "14",
  month =        jul,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070305",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/305",
  abstract =     "Software attack surfaces define the external
                 boundaries---entry points, communication channels, and
                 sensitive data stores through which adversaries may
                 compromise a system. This paper introduces a scoring
                 mechanism that produces a normalized attack-surface
                 metric in the range of 0--1. Building on the
                 established Damage-Potential-to-Effort ratio, our
                 approach further incorporates real-world vulnerability
                 intelligence drawn from MITRE's CVE and CWE
                 repositories. We compute each application's score by
                 ingesting preliminary findings from a static-analysis
                 tool and processing them through our unified model. To
                 assess effectiveness, we validate the scoring system
                 across a spectrum of scenarios, from a simple Java
                 application to complex enterprise applications. The
                 resulting metric offers development and security teams
                 a concise, objective measure to monitor an
                 application's attack surface and hence proactively
                 identify vulnerabilities in their applications. This
                 tool can also be used to benchmark various third-party
                 or dependent applications, enabling both developers and
                 security practitioners to better manage risk.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Varadala:2025:BIC,
  author =       "Sridhar Varadala and Hao Xu",
  title =        "A Biologically Inspired Cost-Efficient Zero-Trust
                 Security Approach for Attacker Detection and
                 Classification in Inter-Satellite Communication
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "304",
  day =          "13",
  month =        jul,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070304",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/304",
  abstract =     "In next-generation Low-Earth-Orbit (LEO) satellite
                 networks, securing inter-satellite communication links
                 (ISLs) through strong authentication is essential due
                 to the network's dynamic and distributed structure.
                 Traditional authentication systems often struggle in
                 these environments, leading to the adoption of
                 Zero-Trust Security (ZTS) models. However, current ZTS
                 protocols typically introduce high computational
                 overhead, especially as the number of satellite nodes
                 grows, which can impact both security and network
                 performance. To overcome these challenges, a new
                 bio-inspired ZTS framework called Manta Ray Foraging
                 Cost-Optimized Zero-Trust Security (MRFCO-ZTS) has been
                 introduced. This approach uses data-driven learning
                 methods to enhance security across satellite
                 communications. It continuously evaluates access
                 requests by applying a cost function that accounts for
                 risk level, likelihood of attack, and computational
                 delay. The Manta Ray Foraging Optimization (MRFO)
                 algorithm is used to minimize this cost, enabling
                 effective classification of nodes as either trusted or
                 malicious based on historical authentication records
                 and real-time behavior. MRFCO-ZTS improves the accuracy
                 of attacker detection while maintaining secure data
                 exchange between authenticated satellites. Its
                 effectiveness has been tested through numerical
                 simulations under different satellite traffic
                 conditions, with performance measured in terms of
                 security accuracy, latency, and operational
                 efficiency.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Maharjan:2025:CSM,
  author =       "Rokin Maharjan and Korn Sooksatra and Tomas Cerny and
                 Yudeep Rajbhandari and Sakshi Shrestha",
  title =        "A Case Study on Monolith to Microservices
                 Decomposition with Variational Autoencoder-Based Graph
                 Neural Network",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "303",
  day =          "13",
  month =        jul,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070303",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/303",
  abstract =     "Microservice is a popular architecture for developing
                 cloud-native applications. However, decomposing a
                 monolithic application into microservices remains a
                 challenging task. This complexity arises from the need
                 to account for factors such as component dependencies,
                 cohesive clusters, and bounded contexts. To address
                 this challenge, we present an automated approach to
                 decomposing monolithic applications into microservices.
                 Our approach uses static code analysis to generate a
                 dependency graph of the monolithic application. Then, a
                 variational autoencoder (VAE) is used to extract
                 features from the components of a monolithic
                 application. Finally, the C-means algorithm is used to
                 cluster the components into possible microservices. We
                 evaluate our approach using a third-party benchmark
                 comprising both monolithic and microservice
                 implementations. Additionally, we compare its
                 performance against two existing decomposition
                 techniques. The results demonstrate the potential of
                 our method as a practical tool for guiding the
                 transition from monolithic to microservice
                 architectures.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mehta:2025:IQM,
  author =       "Vatsal Mehta and Glenford Mapp and Vaibhav Gandhi",
  title =        "The Investigation of Queuing Models to Calculate
                 Journey Times to Develop an Intelligent Transport
                 System for Smart Cities",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "302",
  day =          "7",
  month =        jul,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070302",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/302",
  abstract =     "Intelligent transport systems are a major component of
                 smart cities because their deployment should result in
                 reduced journey times, less traffic congestion and a
                 significant reduction in road deaths, which will
                 greatly improve the quality of life of their citizens.
                 New technologies such as vehicular networks allow more
                 information be available in realtime, and this
                 information can be used with new analytical models to
                 obtain more accurate estimates of journey times. This
                 would be extremely useful to drivers and will also
                 enable transport authorities to optimise the transport
                 network. This paper addresses these issues using a
                 model-based approach to provide a new way of estimating
                 the delay along specified routes. A journey is defined
                 as the traversal of several road links and junctions
                 from source to destination. The delay at the junctions
                 is analysed using the zero-server Markov chain
                 technique. This is then combined with the Jackson
                 network to analyse the delay across multiple junctions.
                 The delay at road links is analysed using an M/M/K/K
                 model. The results were validated using two simulators:
                 SUMO and VISSIM. A real scenario is also examined to
                 determine the best route. The preliminary results of
                 this model-based analysis look promising but more work
                 is needed to make it useful for wide-scale
                 deployment.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mbongo:2025:CGS,
  author =       "Kenan Honore Robacky Mbongo and Kanwal Ahmed and Orken
                 Mamyrbayev and Guanghui Wang and Fang Zuo and Ainur
                 Akhmediyarova and Nurzhan Mukazhanov and Assem
                 Ayapbergenova",
  title =        "{Conv1D-GRU-Self} Attention: an Efficient Deep
                 Learning Framework for Detecting Intrusions in Wireless
                 Sensor Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "301",
  day =          "4",
  month =        jul,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070301",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/301",
  abstract =     "Wireless Sensor Networks (WSNs) consist of distributed
                 sensor nodes that collect and transmit environmental
                 data, often in resource-constrained and unsecured
                 environments. These characteristics make WSNs highly
                 vulnerable to various security threats. To address
                 this, the objective of this research is to design and
                 evaluate a deep learning-based Intrusion Detection
                 System (IDS) that is both accurate and efficient for
                 real-time threat detection in WSNs. This study proposes
                 a hybrid IDS model combining one-dimensional
                 Convolutional Neural Networks (Conv1Ds), Gated
                 Recurrent Units (GRUs), and Self-Attention mechanisms.
                 A Conv1D extracts spatial features from network
                 traffic, GRU captures temporal dependencies, and
                 Self-Attention emphasizes critical sequence components,
                 collectively enhancing detection of subtle and complex
                 intrusion patterns. The model was evaluated using the
                 WSN-DS dataset and demonstrated superior performance
                 compared to traditional machine learning and simpler
                 deep learning models. It achieved an accuracy of
                 98.6\%, precision of 98.63\%, recall of 98.6\%,
                 F1-score of 98.6\%, and an ROC-AUC of 0.9994,
                 indicating strong predictive capability even with
                 imbalanced data. In addition to centralized training,
                 the model was tested under cooperative, node-based
                 learning conditions, where each node independently
                 detects anomalies and contributes to a collective
                 decision-making framework. This distributed approach
                 improves detection efficiency and robustness. The
                 proposed IDS offers a scalable and resilient solution
                 tailored to the unique challenges of WSN security.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zheng:2025:UTO,
  author =       "Yeqiang Zheng and An Li and Yihu Wen and Gaocai Wang",
  title =        "A {UAV} Trajectory Optimization and Task Offloading
                 Strategy Based on Hybrid Metaheuristic Algorithm in
                 Mobile Edge Computing",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "300",
  day =          "3",
  month =        jul,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070300",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/300",
  abstract =     "In the UAV-assisted mobile edge computing (MEC)
                 communication system, the UAV receives the data
                 offloaded by multiple ground user devices as an aerial
                 base station. Among them, due to the limited battery
                 storage of a UAV, energy saving is a key issue in a
                 UAV-assisted MEC system. However, for a low-altitude
                 flying UAV, successful obstacle avoidance is also very
                 necessary. This paper aims to maximize the system
                 energy efficiency (defined as the ratio of the total
                 amount of offloaded data to the energy consumption of
                 the UAV) to meet the maneuverability and
                 three-dimensional obstacle avoidance constraints of a
                 UAV. A joint optimization strategy with maximized
                 energy efficiency for the UAV flight trajectory and
                 user device task offloading rate is proposed. In order
                 to solve this problem, hybrid alternating
                 metaheuristics for energy optimization are given. Due
                 to the non-convexity and fractional structure of the
                 optimization problem, it can be transformed into an
                 equivalent parameter optimization problem using the
                 Dinkelbach method and then divided into two
                 sub-optimization problems that are alternately
                 optimized using metaheuristic algorithms. The
                 experimental results show that the strategy proposed in
                 this paper can enable a UAV to avoid obstacles during
                 flight by detouring or crossing, and the trajectory
                 does not overlap with obstacles, effectively achieving
                 two-dimensional and three-dimensional obstacle
                 avoidance. In addition, compared with related solving
                 methods, the solving method in this paper has
                 significantly higher success than traditional
                 algorithms. In comparison with related optimization
                 strategies, the strategy proposed in this paper can
                 effectively reduce the overall energy consumption of
                 UAV.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Duc:2025:DED,
  author =       "Ma Viet Duc and Pham Minh Dang and Tran Thu Phuong and
                 Truong Duc Truong and Vu Hai and Nguyen Huu Thanh",
  title =        "Detecting Emerging {DGA} Malware in Federated
                 Environments via Variational Autoencoder-Based
                 Clustering and Resource-Aware Client Selection",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "299",
  day =          "3",
  month =        jul,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070299",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/299",
  abstract =     "Domain Generation Algorithms (DGAs) remain a
                 persistent technique used by modern malware to
                 establish stealthy command-and-control (C\&C) channels,
                 thereby evading traditional blacklist-based defenses.
                 Detecting such evolving threats is especially
                 challenging in decentralized environments where raw
                 traffic data cannot be aggregated due to privacy or
                 policy constraints. To address this, we present
                 FedSAGE, a security-aware federated intrusion detection
                 framework that combines Variational Autoencoder
                 (VAE)-based latent representation learning with
                 unsupervised clustering and resource-efficient client
                 selection. Each client encodes its local domain traffic
                 into a semantic latent space using a shared,
                 pre-trained VAE trained solely on benign domains. These
                 embeddings are clustered via affinity propagation to
                 group clients with similar data distributions and
                 identify outliers indicative of novel threats without
                 requiring any labeled DGA samples. Within each cluster,
                 FedSAGE selects only the fastest clients for training,
                 balancing computational constraints with threat
                 visibility. Experimental results from the multi-zones
                 DGA dataset show that FedSAGE improves detection
                 accuracy by up to 11.6\% and reduces energy consumption
                 by up to 93.8\% compared to standard FedAvg under
                 non-IID conditions. Notably, the latent clustering
                 perfectly recovers ground-truth DGA family zones,
                 enabling effective anomaly detection in a fully
                 unsupervised manner while remaining privacy-preserving.
                 These foundations demonstrate that FedSAGE is a
                 practical and lightweight approach for decentralized
                 detection of evasive malware, offering a viable
                 solution for secure and adaptive defense in
                 resource-constrained edge environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Alharbi:2025:HML,
  author =       "Saud Alharbi and Wasan Awad and David Bell",
  title =        "{HECS4MQTT}: a Multi-Layer Security Framework for
                 Lightweight and Robust Encryption in Healthcare {IoT}
                 Communications",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "298",
  day =          "30",
  month =        jun,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070298",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/298",
  abstract =     "Internet of Things (IoT) technology in healthcare has
                 enabled innovative services that enhance patient
                 monitoring, diagnostics and medical data management.
                 However, securing sensitive health data while
                 maintaining system efficiency of resource-constrained
                 IoT devices remains a critical challenge. This work
                 presents a comprehensive end-to-end IoT security
                 framework for healthcare environments, addressing
                 encryption at two key levels: lightweight encryption at
                 the edge for resource-constrained devices and robust
                 end-to-end encryption when transmitting data to the
                 cloud via MQTT cloud brokers. The proposed system
                 leverages multi-broker MQTT architecture to optimize
                 resource utilization and enhance message reliability.
                 At the edge, lightweight cryptographic techniques
                 ensure low-latency encryption before transmitting data
                 via a secure MQTT broker hosted within the hospital
                 infrastructure. To safeguard data as it moves beyond
                 the hospital to the cloud, stronger end-to-end
                 encryption are applied to ensure end-to-end security,
                 such as AES-256 and TLS 1.3, to ensure confidentiality
                 and resilience over untrusted networks. A
                 proof-of-concept Python 3.10 -based MQTT implementation
                 is developed using open-source technologies. Security
                 and performance evaluations demonstrate the feasibility
                 of the multi-layer encryption approach, effectively
                 balancing computational overhead with data protection.
                 Security and performance evaluations demonstrate that
                 our novel HECS4MQTT (Health Edge Cloud Security for
                 MQTT) framework achieves a unique balance between
                 efficiency and security. Unlike existing solutions that
                 either impose high computational overhead at the edge
                 or rely solely on transport-layer protection, HECS4MQTT
                 introduces a layered encryption strategy that decouples
                 edge and cloud security requirements. This design
                 minimizes processing delays on constrained devices
                 while maintaining strong cryptographic protection when
                 data crosses trust boundaries. The framework also
                 introduces a lightweight bridge component for
                 re-encryption and integrity enforcement, thereby
                 reducing broker compromise risk and supporting
                 compliance with healthcare security regulations. Our
                 HECS4MQTT framework offers a scalable, adaptable, and
                 trust-separated security model, ensuring enhanced
                 confidentiality, integrity, and availability of
                 healthcare data while remaining suitable for deployment
                 in real-world, latency-sensitive, and resource-limited
                 medical environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Eghbal:2025:LLS,
  author =       "Nooshin Eghbal and Paul Lu",
  title =        "Lower-Latency Screen Updates over {QUIC} with Forward
                 Error Correction",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "297",
  day =          "30",
  month =        jun,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070297",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/297",
  abstract =     "There are workloads that do not need the total data
                 ordering enforced by the Transmission Control Protocol
                 (TCP). For example, Virtual Network Computing (VNC) has
                 a sequence of pixel-based updates in which the order of
                 rectangles can be relaxed. However, VNC runs over the
                 TCP and can have higher latency due to unnecessary
                 blocking to ensure total ordering. By using Quick UDP
                 Internet Connections (QUIC) as the underlying protocol,
                 we are able to implement a partial order delivery
                 approach, which can be combined with Forward Error
                 Correction (FEC) to reduce data latency. Our earlier
                 work on consistency fences provides a mechanism and
                 semantic foundation for partial ordering. Our new
                 evaluation on the Emulab testbed, with two different
                 synthetic workloads for streaming and non-streaming
                 updates, shows that our partial order and FEC strategy
                 can reduce the blocking time and inter-delivery time of
                 rectangles compared to total delivery. For one
                 workload, partially ordered data with FEC can reduce
                 the 99-percentile message-blocking time to 0.4 ms
                 versus 230 ms with totally ordered data. That workload
                 was with 0.5\% packet loss, 100 ms Round-Trip Time
                 (RTT), and 100 Mbps bandwidth. We study the impact of
                 varying the packet-loss rate, RTT, bandwidth, and CCA
                 and demonstrate that partial order and FEC latency
                 improvements grow as we increase packet loss and RTT,
                 especially with the emerging Bottleneck Bandwidth and
                 Round-Trip propagation time (BBR) congestion control
                 algorithm.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sharifi:2025:OTR,
  author =       "Ashraf Sharifi and Sara Migliorini and Davide
                 Quaglia",
  title =        "Optimizing Trajectories for Rechargeable Agricultural
                 Robots in Greenhouse Climatic Sensing Using Deep
                 Reinforcement Learning with Proximal Policy
                 Optimization Algorithm",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "296",
  day =          "30",
  month =        jun,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070296",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/296",
  abstract =     "The experimentation of agricultural robots has been
                 increasing in recent years, both in greenhouses and
                 open fields. While agricultural robots are inherently
                 useful for automating various farming tasks, their
                 presence can also be leveraged to collect measurements
                 along their paths. This approach enables the creation
                 of a complete and detailed picture of the climate
                 conditions inside a greenhouse, reducing the need to
                 distribute a large number of physical devices among the
                 crops. In this regard, choosing the best visiting
                 sequence of the Points of Interest (PoIs) regarding
                 where to perform the measurements deserves particular
                 attention. This trajectory planning has to carefully
                 combine the amount and significance of the collected
                 data with the energy requirements of the robot. In this
                 paper, we propose a method based on Deep Reinforcement
                 Learning enriched with a Proximal Policy Optimization
                 (PPO) algorithm for determining the best trajectory an
                 agricultural robot must follow to balance the number of
                 measurements and autonomy adequately. The proposed
                 approach has been applied to a real-world case study
                 regarding a greenhouse in Verona (Italy) and compared
                 with other existing state-of-the-art approaches.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ramos-Cruz:2025:FFB,
  author =       "Bruno Ramos-Cruz and Francisco J. Quesada-Real and
                 Javier Andreu-P{\'e}rez and Jessica Zaqueros-Martinez",
  title =        "{FODIT}: a Filter-Based Module for Optimizing Data
                 Storage in {B5G} {IoT} Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "295",
  day =          "30",
  month =        jun,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070295",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/295",
  abstract =     "In the rapidly evolving landscape of the Internet of
                 Things (IoT), managing the vast volumes of data
                 generated by connected devices presents significant
                 challenges, particularly in B5G IoT environments. One
                 key issue is data redundancy, where identical data is
                 stored several times because it is captured by multiple
                 sensors. To address this, we introduce `` FODIT '', a
                 filter-based module designed to optimize data storage
                 in IoT systems. FODIT leverages probabilistic data
                 structures, specifically filters, to improve storage
                 efficiency and query performance. We hypothesize that
                 applying these structures can significantly reduce
                 redundancy and accelerate data access in
                 resource-constrained IoT deployments. We validate our
                 hypothesis through targeted simulations under a
                 specific and rare configuration: high-frequency and
                 high-redundancy environments, with controlled
                 duplication rates between 4\% and 8\%. These
                 experiments involve data storage in local databases,
                 cloud-based systems, and distributed ledger
                 technologies (DLTs). The results demonstrate FODIT's
                 ability to reduce storage requirements and improve
                 query responsiveness under these stress-test
                 conditions. Furthermore, the proposed approach has
                 broader applicability, particularly in DLT-based
                 environments such as blockchain, where efficient
                 querying remains a critical challenge. Nonetheless,
                 some limitations remain, especially regarding the
                 current data structure used to maintain consistency
                 with the DLT, and the need for further adaptation to
                 real-world contexts with dynamic workloads. This
                 research highlights the potential of filter-based
                 techniques to improve data management in IoT and
                 blockchain systems, contributing to the development of
                 more scalable and responsive infrastructures.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Jin:2025:IIC,
  author =       "Yage Jin and Hongming Chen and Rui Ma and Yanhua Wu
                 and Qingxin Li",
  title =        "{ICRSSD}: Identification and Classification for
                 Railway Structured Sensitive Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "294",
  day =          "30",
  month =        jun,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070294",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/294",
  abstract =     "The rapid growth of the railway industry has resulted
                 in the accumulation of large structured data that makes
                 data security a critical component of reliable railway
                 system operations. However, existing methods for
                 identifying and classifying often suffer from
                 limitations such as overly coarse identification
                 granularity and insufficient flexibility in
                 classification. To address these issues, we propose
                 ICRSSD, a two-stage method for identification and
                 classification in terms of the railway domain. The
                 identification stage focuses on obtaining the
                 sensitivity of all attributes. We first divide
                 structured data into canonical data and semi-canonical
                 data at a finer granularity to improve the
                 identification accuracy. For canonical data, we use
                 information entropy to calculate the initial
                 sensitivity. Subsequently, we update the attribute
                 sensitivities through cluster analysis and association
                 rule mining. For semi-canonical data, we calculate
                 attribute sensitivity by using a combination of regular
                 expressions and keyword lists. In the classification
                 stage, to further enhance accuracy, we adopt a dynamic
                 and multi-granularity classified strategy. It considers
                 the relative sensitivity of attributes across different
                 scenarios and classifies them into three levels based
                 on the sensitivity values obtained during the
                 identification stage. Additionally, we design a rule
                 base specifically for the identification and
                 classification of sensitive data in the railway domain.
                 This rule base enables effective data identification
                 and classification, while also supporting the expiry
                 management of sensitive attribute labels. To improve
                 the efficiency of regular expression generation, we
                 developed an auxiliary tool with the help of large
                 language models and a well-designed prompt framework.
                 We conducted experiments on a real-world dataset from
                 the railway domain. The results demonstrate that ICRSSD
                 significantly improves the accuracy and adaptability of
                 sensitive data identification and classification in the
                 railway domain.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Almuzaini:2025:ATP,
  author =       "Talal S. Almuzaini and Andrey V. Savkin",
  title =        "{AUV} Trajectory Planning for Optimized Sensor Data
                 Collection in {Internet of Underwater Things}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "293",
  day =          "30",
  month =        jun,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070293",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/293",
  abstract =     "Efficient and timely data collection in Underwater
                 Acoustic Sensor Networks (UASNs) for Internet of
                 Underwater Things (IoUT) applications remains a
                 significant challenge due to the inherent limitations
                 of the underwater environment. This paper presents a
                 Value of Information (VoI)-based trajectory planning
                 framework for a single Autonomous Underwater Vehicle
                 (AUV) operating in coordination with an Unmanned
                 Surface Vehicle (USV) to collect data from multiple
                 Cluster Heads (CHs) deployed across an uneven seafloor.
                 The proposed approach employs a VoI model that captures
                 both the importance and timeliness of sensed data,
                 guiding the AUV to collect and deliver critical
                 information before its value significantly degrades. A
                 forward Dynamic Programming (DP) algorithm is used to
                 jointly optimize the AUV's trajectory and the USV's
                 start and end positions, with the objective of
                 maximizing the total residual VoI upon mission
                 completion. The trajectory design incorporates the
                 AUV's kinematic constraints into travel time
                 estimation, enabling accurate VoI evaluation throughout
                 the mission. Simulation results show that the proposed
                 strategy consistently outperforms conventional
                 baselines in terms of residual VoI and overall system
                 efficiency. These findings highlight the advantages of
                 VoI-aware planning and AUV--USV collaboration for
                 effective data collection in challenging underwater
                 environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Caturla:2025:TAD,
  author =       "Santiago Iba{\~n}ez Caturla and Juan de Dios Bern{\'a}
                 Mestre and Oscar Martinez Mozos",
  title =        "Towards Automatic Detection of Pneumothorax in
                 Emergency Care with Deep Learning Using Multi-Source
                 Chest {X}-ray Data",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "292",
  day =          "29",
  month =        jun,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070292",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/292",
  abstract =     "Pneumothorax is a potentially life-threatening
                 condition defined as the collapse of the lung due to
                 air leakage into the chest cavity. Delays in the
                 diagnosis of pneumothorax can lead to severe
                 complications and even mortality. A significant
                 challenge in pneumothorax diagnosis is the shortage of
                 radiologists, resulting in the absence of written
                 reports in plain X-rays and, consequently, impacting
                 patient care. In this paper, we propose an automatic
                 triage system for pneumothorax detection in X-ray
                 images based on deep learning. We address this problem
                 from the perspective of multi-source domain adaptation
                 where different datasets available on the Internet are
                 used for training and testing. In particular, we use
                 datasets which contain chest X-ray images corresponding
                 to different conditions (including pneumothorax). A
                 convolutional neural network (CNN) with an EfficientNet
                 architecture is trained and optimized to identify
                 radiographic signs of pneumothorax using those public
                 datasets. We present the results using cross-dataset
                 validation, demonstrating the robustness and
                 generalization capabilities of our multi-source
                 solution across different datasets. The experimental
                 results demonstrate the model's potential to assist
                 clinicians in prioritizing and correctly detecting
                 urgent cases of pneumothorax using different integrated
                 deployment strategies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Huang:2025:EME,
  author =       "Wanwei Huang and Hongchang Liu and Yingying Li and
                 Linlin Ma",
  title =        "{ERA-MADDPG}: an Elastic Routing Algorithm Based on
                 Multi-Agent Deep Deterministic Policy Gradient in
                 {SDN}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "7",
  pages =        "291",
  day =          "29",
  month =        jun,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17070291",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:55 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/7/291",
  abstract =     "To address the fact that changes in network topology
                 can have an impact on the performance of routing, this
                 paper proposes an Elastic Routing Algorithm based on
                 Multi-Agent Deep Deterministic Policy Gradient
                 (ERA-MADDPG), which is implemented within the framework
                 of Multi-Agent Deep Deterministic Policy Gradient
                 (MADDPG) in deep reinforcement learning. The algorithm
                 first builds a three-layer architecture based on
                 Software-Defined Networking (SDN). The top-down layers
                 are the multi-agent layer, the controller layer, and
                 the data layer. The architecture's processing flow,
                 including real-time data layer information collection
                 and dynamic policy generation, enables the ERA-MADDPG
                 algorithm to exhibit strong elasticity by quickly
                 adjusting routing decisions in response to topology
                 changes. The actor-critic framework combined with
                 Convolutional Neural Networks (CNN) to implement the
                 ERA-MADDPG routing algorithm effectively improves
                 training efficiency, enhances learning stability,
                 facilitates collaboration, and improves algorithm
                 generalization and applicability. Finally, simulation
                 experiments demonstrate that the convergence speed of
                 the ERA-MADDPG routing algorithm outperforms that of
                 the Multi-Agent Deep Q-Network (MADQN) algorithm and
                 the Smart Routing based on Deep Reinforcement Learning
                 (SR-DRL) algorithm, and the training speed in the
                 initial phase is improved by approximately 20.9\% and
                 39.1\% compared to the MADQN algorithm and SR-DRL
                 algorithm, respectively. The elasticity performance of
                 ERA-MADDPG is quantified by re-convergence speed: under
                 5--15\% topology node/link changes, its re-convergence
                 speed is over 25\% faster than that of MADQN and
                 SR-DRL, demonstrating superior capability to maintain
                 routing efficiency in dynamic environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lin:2025:HCR,
  author =       "Yijie Lin and Chia-Chen Lin and Zhe-Min Yeh and
                 Ching-Chun Chang and Chin-Chen Chang",
  title =        "A High-Capacity Reversible Data Hiding Scheme for
                 Encrypted Hyperspectral Images Using Multi-Layer {MSB}
                 Block Labeling and {ERLE} Compression",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "378",
  day =          "21",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080378",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/378",
  abstract =     "In the context of secure and efficient data
                 transmission over the future Internet, particularly for
                 remote sensing and geospatial applications, reversible
                 data hiding (RDH) in encrypted hyperspectral images
                 (HSIs) has emerged as a critical technology. This paper
                 proposes a novel RDH scheme specifically designed for
                 encrypted HSIs, offering enhanced embedding capacity
                 without compromising data security or reversibility.
                 The approach introduces a multi-layer block labeling
                 mechanism that leverages the similarity of most
                 significant bits (MSBs) to accurately locate embeddable
                 regions. To minimize auxiliary information overhead, we
                 incorporate an Extended Run-Length Encoding (ERLE)
                 algorithm for effective label map compression. The
                 proposed method achieves embedding rates of up to 3.79
                 bits per pixel per band (bpppb), while ensuring
                 high-fidelity reconstruction, as validated by strong
                 PSNR metrics. Comprehensive security evaluations using
                 NPCR, UACI, and entropy confirm the robustness of the
                 encryption. Extensive experiments across six standard
                 hyperspectral datasets demonstrate the superiority of
                 our method over existing RDH techniques in terms of
                 capacity, embedding rate, and reconstruction quality.
                 These results underline the method's potential for
                 secure data embedding in next-generation Internet-based
                 geospatial and remote sensing systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2025:HAR,
  author =       "Yichuan Wang and Jiazhao Han and Xi Deng and Xinhong
                 Hei",
  title =        "A High-Acceptance-Rate {VxWorks} Fuzzing Framework
                 Based on Protocol Feature Fusion and Memory
                 Extraction",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "377",
  day =          "21",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080377",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/377",
  abstract =     "With the widespread application of Internet of Things
                 (IoT) devices, the security of embedded systems faces
                 severe challenges. As an embedded operating system
                 widely used in critical mission scenarios, the security
                 of the TCP stack in VxWorks directly affects system
                 reliability. However, existing protocol fuzzing methods
                 based on network communication struggle to adapt to the
                 complex state machine and grammatical rules of the TCP.
                 Additionally, the lack of a runtime feedback mechanism
                 for closed-source VxWorks systems leads to low testing
                 efficiency. This paper proposes the vxTcpFuzzer
                 framework, which generates structured test cases by
                 integrating the field features of the TCP.
                 Innovatively, it uses the memory data changes of
                 VxWorks network protocol processing tasks as a coverage
                 metric and combines a dual anomaly detection mechanism
                 (WDB detection and heartbeat detection) to achieve
                 precise anomaly capture. We conducted experimental
                 evaluations on three VxWorks system devices, where
                 vxTcpFuzzer successfully triggered multiple potential
                 vulnerabilities, verifying the framework's
                 effectiveness. Compared with three existing classic
                 fuzzing schemes, vxTcpFuzzer demonstrates significant
                 advantages in test case acceptance rates
                 (44.94--54.92\%) and test system abnormal rates
                 (23.79--34.70\%) across the three VxWorks devices. The
                 study confirms that protocol feature fusion and memory
                 feedback mechanisms can effectively enhance the depth
                 and efficiency of protocol fuzzing for VxWorks systems.
                 Furthermore, this approach offers a practical and
                 effective solution for uncovering TCP vulnerabilities
                 in black-box environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bastardo:2025:POS,
  author =       "Rute Bastardo and Jo{\~a}o Pav{\~a}o and Ana Isabel
                 Martins and Anabela G. Silva and Nelson Pacheco Rocha",
  title =        "Patient-Oriented Smart Applications to Support the
                 Diagnosis, Rehabilitation, and Care of Patients with
                 {Parkinson}'s: an Umbrella Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "376",
  day =          "19",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080376",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/376",
  abstract =     "This umbrella review aimed to identify, analyze, and
                 synthesize the results of existing literature reviews
                 related to patient-oriented smart applications to
                 support healthcare provision for patients with
                 Parkinson's. An electronic search was conducted on
                 Scopus, Web of Science, and PubMed, and, after
                 screening using predefined eligibility criteria, 85
                 reviews were included in the umbrella review. The
                 included studies reported on smart applications
                 integrating wearable devices, smartphones, serious
                 computerized games, and other technologies (e.g.,
                 ambient intelligence, computer-based objective
                 assessments, or online platforms) to support the
                 diagnosis and monitoring of patients with Parkinson's,
                 improve physical and cognitive rehabilitation, and
                 support disease management. Numerous smart applications
                 are potentially useful for patients with Parkinson's,
                 although their full clinical potential has not yet been
                 demonstrated. This is because the quality of their
                 clinical assessments, as well as aspects related to
                 their acceptability and compliance with requirements
                 from regulatory bodies, have not yet been adequately
                 studied. Future research requires more aligned methods
                 and procedures for experimental assessments, as well as
                 collaborative efforts to avoid replication and promote
                 advances on the topic.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Lim:2025:FLA,
  author =       "Le-Hang Lim and Lee-Yeng Ong and Meng-Chew Leow",
  title =        "Federated Learning for Anomaly Detection: a Systematic
                 Review on Scalability, Adaptability, and Benchmarking
                 Framework",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "375",
  day =          "18",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080375",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/375",
  abstract =     "Anomaly detection plays an increasingly important role
                 in maintaining the stability and reliability of modern
                 distributed systems. Federated Learning (FL) is an
                 emerging method that shows strong potential in enabling
                 anomaly detection across decentralised environments.
                 However, there are some crucial and tricky research
                 challenges that remain unresolved, such as ensuring
                 scalability, adaptability to dynamic server clusters,
                 and the development of standardised evaluation
                 frameworks for FL. This review aims to address the
                 research gaps through a comprehensive analysis of
                 existing studies. In this paper, a systematic review is
                 conducted by covering three main aspects of the
                 application of FL in anomaly detection: the impact of
                 communication overhead towards scalability and
                 real-time performance, the adaptability of FL
                 frameworks to dynamic server clusters, and the key
                 components required for a standardised benchmarking
                 framework of FL-based anomaly detection. There are a
                 total of 43 relevant articles, published between 2020
                 and 2025, which were selected from IEEE Xplore, Scopus,
                 and ArXiv. The research findings highlight the
                 potential of asynchronous updates and selective update
                 mechanisms in improving FL's real-time performance and
                 scalability. This review primarily focuses on anomaly
                 detection tasks in distributed system environments,
                 such as network traffic analysis, IoT devices, and
                 industrial monitoring, rather than domains like
                 computer vision or financial fraud detection. While FL
                 frameworks can handle dynamic client changes, the
                 problem of data heterogeneity among the clients remains
                 a significant obstacle that affects the model
                 convergence speed. Moreover, the lack of a unified
                 benchmarking framework to evaluate the performance of
                 FL in anomaly detection poses a challenge to fair
                 comparisons among the experimental results.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Al-Zuhairi:2025:ECS,
  author =       "Yaqoob Al-Zuhairi and Prashanth Kannan and Alberto
                 Baz{\'a}n Guill{\'e}n and Luis J. de la Cruz Llopis and
                 M{\'o}nica Aguilar Igartua",
  title =        "Efficient Charging Station Selection for Minimizing
                 Total Travel Time of Electric Vehicles",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "374",
  day =          "18",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080374",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/374",
  abstract =     "Electric vehicles (EVs) have gained significant
                 attention in recent decades for their environmental
                 benefits. However, their widespread adoption poses
                 challenges due to limited charging infrastructure and
                 long charging times, often resulting in underutilized
                 charging stations (CSs) and unnecessary queues that
                 complicate travel planning. Therefore, selecting the
                 appropriate CS is essential for minimizing the total
                 travel time of EVs, as it depends on both driving time
                 and the required charging duration. This selection
                 process requires estimating the energy required to
                 reach each candidate CS and then continue to the
                 destination, while also checking if the EV's battery
                 level is sufficient for a direct trip. To address this
                 gap, we propose an integrated platform that leverages
                 two ensemble machine learning models: Bi-LSTM + XGBoost
                 to predict energy consumption, and FFNN + XGBoost for
                 identifying the most suitable CS by considering
                 required energy, waiting time at CS, charging speed,
                 and driving time based on varying traffic conditions.
                 This integration forms the core novelty of our system
                 to optimize CS selection to minimize the total trip
                 duration. This approach was validated with SUMO
                 simulations and OpenStreetMap data, demonstrating a
                 mean absolute error (MAE) ranging from 2.29 to 4.5 min,
                 depending on traffic conditions, outperforming
                 conventional approaches that rely on SUMO functions and
                 mathematical calculations, which typically yielded MAEs
                 between 5.1 and 10 min. These findings highlight the
                 proposed system's effectiveness in reducing total
                 travel time, improving charging infrastructure
                 utilization, and enhancing the overall experience for
                 EV drivers.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rusho:2025:SAI,
  author =       "Yonit Rusho and Daphne Ruth Raban and Michal Chalamish
                 and Vered Pnueli",
  title =        "Software Agents as Information-Sharing Enhancers in
                 Security-Sensitive Organizations",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "373",
  day =          "18",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080373",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/373",
  abstract =     "This study examines the influence of software agents
                 on information-sharing behavior within
                 security-sensitive organizations, where confidentiality
                 and hierarchical culture often limit the flow of
                 knowledge. While such organizations aim to collect,
                 analyze, and disseminate information for security
                 purposes, internal sharing dynamics are shaped by
                 competing norms of secrecy and collaboration. To
                 explore this tension, we developed a digital simulation
                 game in which participants from security-sensitive
                 organizations engaged in collaborative tasks over three
                 rounds. In rounds two and three, software agents were
                 introduced to interact with participants by sharing
                 public and classified information. A total of 28
                 participants took part, generating 1626 text-based
                 interactions. Findings indicate that (1)
                 information-sharing patterns in security-sensitive
                 contexts differ significantly from those in
                 non-sensitive environments; (2) when software agents
                 share classified information, participants are more
                 likely to share sensitive data in return; (3) when
                 participants are aware of the agents' presence, they
                 reduce classified sharing and increase public sharing;
                 and (4) agents that share both public and classified
                 information lead to decreased public and increased
                 classified sharing. These results provide insight into
                 the role of artificial agents in shaping communication
                 behaviors in secure environments and inform strategies
                 for training and design in knowledge-sensitive
                 organizational settings.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Eiza:2025:HZT,
  author =       "Max Hashem Eiza and Brian Akwirry and Alessandro
                 Raschella and Michael Mackay and Mukesh Kumar
                 Maheshwari",
  title =        "A Hybrid Zero Trust Deployment Model for Securing
                 {O-RAN} Architecture in {6G} Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "372",
  day =          "18",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080372",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/372",
  abstract =     "The evolution toward sixth generation (6G) wireless
                 networks promises higher performance, greater
                 flexibility, and enhanced intelligence. However, it
                 also introduces a substantially enlarged attack surface
                 driven by open, disaggregated, and multi-vendor Open
                 RAN (O-RAN) architectures that will be utilised in 6G
                 networks. This paper addresses the urgent need for a
                 practical Zero Trust (ZT) deployment model tailored to
                 O-RAN specification. To do so, we introduce a novel
                 hybrid ZT deployment model that establishes the trusted
                 foundation for AI/ML-driven security in O-RAN,
                 integrating macro-level enclave segmentation with
                 micro-level application sandboxing for xApps/rApps. In
                 our model, the Policy Decision Point (PDP) centrally
                 manages dynamic policies, while distributed Policy
                 Enforcement Points (PEPs) reside in logical enclaves,
                 agents, and gateways to enable per-session,
                 least-privilege access control across all O-RAN
                 interfaces. We demonstrate feasibility via a Proof of
                 Concept (PoC) implemented with Kubernetes and Istio and
                 based on the NIST Policy Machine (PM). The PoC
                 illustrates how pods can represent enclaves and sidecar
                 proxies can embody combined agent/gateway functions.
                 Performance discussion indicates that enclave-based
                 deployment adds 1--10 ms of additional per-connection
                 latency while CPU/memory overhead from running a
                 sidecar proxy per enclave is approximately 5--10\%
                 extra utilisation, with each proxy consuming roughly
                 100--200 MB of RAM.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhang:2025:UPR,
  author =       "Shun Zhang and Yaohui Xu and Xuebin Zhang and Boyang
                 Cheng and Ke Wang",
  title =        "Unsupervised Person Re-Identification via Deep
                 Attribute Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "371",
  day =          "15",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080371",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/371",
  abstract =     "Driven by growing public security demands and the
                 advancement of intelligent surveillance systems, person
                 re-identification (ReID) has emerged as a prominent
                 research focus in the field of computer vision.
                 However, this task presents challenges due to its high
                 sensitivity to variations in visual appearance caused
                 by factors such as body pose and camera parameters.
                 Although deep learning-based methods have achieved
                 marked progress in ReID, the high cost of annotation
                 remains a challenge that cannot be overlooked. To
                 address this, we propose an unsupervised attribute
                 learning framework that eliminates the need for costly
                 manual annotations while maintaining high accuracy. The
                 framework learns the mid-level human attributes (such
                 as clothing type and gender) that are robust to
                 substantial visual appearance variations and can hence
                 boost the accuracy of attributes with a small amount of
                 labeled data. To carry out our framework, we present a
                 part-based convolutional neural network (CNN)
                 architecture, which consists of two components for
                 image and body attribute learning on a global level and
                 upper- and lower-body image and attribute learning at a
                 local level. The proposed architecture is trained to
                 learn attribute-semantic and identity-discriminative
                 feature representations simultaneously. For model
                 learning, we first train our part-based network using a
                 supervised approach on a labeled attribute dataset.
                 Then, we apply an unsupervised clustering method to
                 assign pseudo-labels to unlabeled images in a target
                 dataset using our trained network. To improve feature
                 compatibility, we introduce an attribute consistency
                 scheme for unsupervised domain adaptation on this
                 unlabeled target data. During training on the target
                 dataset, we alternately perform three steps: extracting
                 features with the updated model, assigning
                 pseudo-labels to unlabeled images, and fine-tuning the
                 model. Through a unified framework that fuses
                 complementary attribute-label and identity label
                 information, our approach achieves considerable
                 improvements of 10.6\% and 3.91\% mAP on
                 Market-1501{\rightarrow}DukeMTMC-ReID and
                 DukeMTMC-ReID{\rightarrow}Market-1501 unsupervised
                 domain adaptation tasks, respectively.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Khatri:2025:AUF,
  author =       "Manan Khatri and Manmita Sahoo and Sameer Sayyad and
                 Javed Sayyad",
  title =        "Adaptive and User-Friendly Framework for Image
                 Classification with Transfer Learning Models",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "370",
  day =          "15",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080370",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/370",
  abstract =     "The increasing demand for accessible and efficient
                 machine learning solutions has led to the development
                 of the Adaptive Learning Framework (ALF) for
                 multi-class, single-label image classification. Unlike
                 existing low-code tools, ALF integrates multiple
                 transfer learning backbones with a guided, adaptive
                 workflow that empowers non-technical users to create
                 custom classification models without specialized
                 expertise. It employs pre-trained models from
                 TensorFlow Hub to significantly reduce computational
                 costs and training times while maintaining high
                 accuracy. The platform's User Interface (UI), built
                 using Streamlit, enables intuitive operations, such as
                 dataset upload, class definition, and model training,
                 without coding requirements. This research focuses on
                 small-scale image datasets to demonstrate ALF's
                 accessibility and ease of use. Evaluation metrics
                 highlight the superior performance of transfer learning
                 approaches, with the InceptionV2 model architecture
                 achieving the highest accuracy. By bridging the gap
                 between complex deep learning methods and real-world
                 usability, ALF addresses practical needs across fields
                 like education and industry.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Xu:2025:EES,
  author =       "Zongliang Xu and Guicai Yu and Yingcong Luo and Hao
                 Jiang",
  title =        "An Energy-Efficient Scheme for Waking Co-Channel
                 {TDMA} in {LoRa} Networks via the Integration of
                 Bidirectional Timestamp Correction and Address
                 Recognition",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "369",
  day =          "14",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080369",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/369",
  abstract =     "To address the issues of high energy consumption, data
                 collisions, and invalid wake-ups of nontarget nodes in
                 large-scale node-deployment scenarios of long-range
                 (LoRa) star networks, this paper proposes an
                 energy-saving wake-up scheme that combines (i)
                 time-division multiple access (TDMA) slot allocation
                 based on bidirectional timestamp correction with (ii) a
                 sensing and communication integrated (ISAC) scheme
                 proposed for physical address identification of LoRa
                 nodes operating on the same channel. The scheme
                 incorporates parameter estimation of the LoRa channel,
                 which effectively enhances the identification accuracy
                 and improves the system's robustness. The proposed
                 scheme consists of two parts: First, in case nodes
                 briefly lose power, a bidirectional timestamp
                 calibration algorithm and GPS-assisted timing are used
                 to synchronize the gateway and each node with high
                 precision, ensuring the accurate scheduling of the TDMA
                 mechanism. Second, based on time synchronization, a
                 ``slot--LoRa module address'' mapping table is
                 constructed to set the communication time points
                 between the gateway and each node. The gateway can wake
                 the target nodes at specific, precise communication
                 time points. Experimental results show that the
                 proposed method maintains the error range within {\pm}1
                 ms. The significant decrease in the rate of unnecessary
                 node wake-up decreases data collisions and energy waste
                 in the same channel environment. Energy savings scale
                 with network size, thereby significantly extending the
                 network life cycle.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Liang:2025:ITD,
  author =       "Caiping Liang and Xiang Li and Wenxu Niu and Yansong
                 Zhang",
  title =        "{Internet of Things} Driven Digital Twin for
                 Intelligent Manufacturing in Shipbuilding Workshops",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "368",
  day =          "14",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080368",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/368",
  abstract =     "Intelligent manufacturing research has focused on
                 digital twins (DTs) due to the growing integration of
                 physical and cyber systems. This study thoroughly
                 explores the Internet of Things (IoT) as a cornerstone
                 of DTs, showing its promise and limitations in
                 intelligent shipbuilding digital transformation
                 workshops. We analyze the progress of IoT protocols,
                 digital twin frameworks, and intelligent ship
                 manufacturing. A unique bidirectional digital twin
                 system for shipbuilding workshops uses the Internet of
                 Things to communicate data between real and virtual
                 workshops. This research uses a steel-cutting workshop
                 to demonstrate the digital transformation of the
                 production line, including data collection,
                 transmission, storage, and simulation analysis. Then,
                 major hurdles to digital technology application in
                 shipbuilding are comprehensively examined. Critical
                 barriers to DT deployment in shipbuilding environments
                 are systematically analyzed, including technical
                 standard unification, communication security, real-time
                 performance guarantees, cross-workshop collaboration
                 mechanisms, and the deep integration of artificial
                 intelligence. Adaptive solutions include hybrid
                 edge-cloud computing architectures for
                 latency-sensitive tasks and reinforcement
                 learning-based smart scheduling algorithms. The
                 findings suggest that IoT-driven digital transformation
                 may modernize shipbuilding workshops in new ways.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Peng:2025:DDS,
  author =       "Shengmin Peng and Jialin Tian and Xiangyu Zheng and
                 Shuwu Chen and Zhaogang Shu",
  title =        "{DDoS} Defense Strategy Based on Blockchain and
                 Unsupervised Learning Techniques in {SDN}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "367",
  day =          "13",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080367",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/367",
  abstract =     "With the rapid development of technologies such as
                 cloud computing, big data, and the Internet of Things
                 (IoT), Software-Defined Networking (SDN) is emerging as
                 a new network architecture for the modern Internet. SDN
                 separates the control plane from the data plane,
                 allowing a central controller, the SDN controller, to
                 quickly direct the routing devices within the topology
                 to forward data packets, thus providing flexible
                 traffic management for communication between
                 information sources. However, traditional Distributed
                 Denial of Service (DDoS) attacks still significantly
                 impact SDN systems. This paper proposes a novel
                 dual-layer strategy capable of detecting and mitigating
                 DDoS attacks in an SDN network environment. The first
                 layer of the strategy enhances security by using
                 blockchain technology to replace the SDN flow table
                 storage container in the northbound interface of the
                 SDN controller. Smart contracts are then used to
                 process the stored flow table information. We employ
                 the time window algorithm and the token bucket
                 algorithm to construct the first layer strategy to
                 defend against obvious DDoS attacks. To detect and
                 mitigate less obvious DDoS attacks, we design a
                 second-layer strategy that uses a composite data
                 feature correlation coefficient calculation method and
                 the Isolation Forest algorithm from unsupervised
                 learning techniques to perform binary classification,
                 thereby identifying abnormal traffic. We conduct
                 experimental validation using the publicly available
                 DDoS dataset CIC-DDoS2019. The results show that using
                 this strategy in the SDN network reduces the average
                 deviation of round-trip time (RTT) by approximately
                 38.86\% compared with the original SDN network without
                 this strategy. Furthermore, the accuracy of DDoS attack
                 detection reaches 97.66\% and an F1 score of 92.2\%.
                 Compared with other similar methods, under comparable
                 detection accuracy, the deployment of our strategy in
                 small-scale SDN network topologies provides faster
                 detection speeds for DDoS attacks and exhibits less
                 fluctuation in detection time. This indicates that
                 implementing this strategy can effectively identify
                 DDoS attacks without affecting the stability of data
                 transmission in the SDN network environment.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bonilla:2025:FES,
  author =       "Carmen del Rosario Navas Bonilla and Luis Miguel
                 Vi{\~n}an Carrasco and Jhoanna Carolina Gaibor Pupiales
                 and Daniel Eduardo Murillo Noriega",
  title =        "The Future of Education: a Systematic Literature
                 Review of Self-Directed Learning with {AI}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "366",
  day =          "13",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080366",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/366",
  abstract =     "As digital transformation continues to redefine
                 education, understanding how emerging technologies can
                 enhance self-directed learning (SDL) becomes essential
                 for learners, educators, instructional designers, and
                 policymakers, as this approach supports personalized
                 learning, strengthens student autonomy, and responds to
                 the demands of more flexible and dynamic educational
                 environments. This systematic review examines how
                 artificial intelligence (AI) tools enhance SDL by
                 offering personalized, adaptive, and real-time support
                 for learners in online environments. Following the
                 PRISMA 2020 methodology, a literature search was
                 conducted to identify relevant studies published
                 between 2020 and 2025. After applying inclusion,
                 exclusion, and quality criteria, 77 studies were
                 selected for in-depth analysis. The findings indicate
                 that AI-powered tools such as intelligent tutoring
                 systems, chatbots, conversational agents, and natural
                 language processing applications promote learner
                 autonomy, enable self-regulation, provide real-time
                 feedback, and support individualized learning paths.
                 However, several challenges persist, including
                 overreliance on technology, cognitive overload, and
                 diminished human interaction. These insights suggest
                 that, while AI plays a transformative role in the
                 evolution of education, its integration must be guided
                 by thoughtful pedagogical design, ethical
                 considerations, and a learner-centered approach to
                 fully support the future of education through the
                 internet.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ortiz:2025:AEM,
  author =       "Leandro Antonio Pazmi{\~n}o Ortiz and Ivonne Fernanda
                 Maldonado Soliz and Vanessa Katherine Guevara
                 Balarezo",
  title =        "The Adaptive Ecosystem of {MaaS}-Driven Cookie Theft:
                 Dynamics, Anticipatory Analysis Concepts, and Proactive
                 Defenses",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "365",
  day =          "11",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080365",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/365",
  abstract =     "The industrialization of cybercrime, principally
                 through Malware-as-a-Service (MaaS), has elevated HTTP
                 cookie theft to a critical cybersecurity challenge,
                 enabling attackers to bypass multi-factor
                 authentication and perpetrate large-scale account
                 takeovers. Employing a Holistic and Integrative Review
                 methodology, this paper dissects the intricate,
                 adaptive ecosystem of MaaS-driven cookie theft. We
                 systematically characterize the co-evolving arms race
                 between offensive and defensive strategies
                 (2020--2025), revealing a critical strategic asymmetry
                 where attackers optimize for speed and low cost, while
                 effective defenses demand significant resources. To
                 shift security from a reactive to an anticipatory
                 posture, a multi-dimensional predictive framework is
                 not only proposed but is also detailed as a formalized,
                 testable algorithm, integrating technical, economic,
                 and behavioral indicators to forecast emerging threat
                 trajectories. Our findings conclude that long-term
                 security hinges on disrupting the underlying
                 cybercriminal economic model; we therefore reframe
                 proactive countermeasures like Zero-Trust principles
                 and ephemeral tokens as economic weapons designed to
                 devalue the stolen asset. Finally, the paper provides a
                 prioritized, multi-year research roadmap and a
                 practical decision-tree framework to guide the
                 implementation of these advanced, collaborative
                 cybersecurity strategies to counter this pervasive and
                 evolving threat.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Spini:2025:EHC,
  author =       "Gabriele Spini and Stephan Krenn and Erich Teppan and
                 Christina Petschnigg and Elena Wiegelmann",
  title =        "Enabling Horizontal Collaboration in Logistics Through
                 Secure Multi-Party Computation",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "364",
  day =          "8",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080364",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/364",
  abstract =     "The road transport sector is currently facing
                 significant challenges, due in part to CO 2 emissions,
                 high fuel prices, and a shortage of staff. These issues
                 are partially caused by more than 40\% of truck
                 journeys being ``empty runs'' in some member states of
                 the European Union and heavy under-utilization of deck
                 space for non-empty runs. In order to overcome said
                 inefficiency, this paper proposes a decentralized
                 platform to facilitate collaborative transport networks
                 (CTNs), i.e., to enable horizontal collaboration to
                 increase load factors and reduce costs and CO 2
                 emissions. Our solution leverages secure multi-party
                 computation (MPC) to guarantee that no sensitive
                 business information is leaked to competing hauliers.
                 The system optimizes truck assignments by modeling
                 logistics as a weighted graph that considers orders and
                 truck capacities while maintaining strict
                 confidentiality. Our approach addresses key barriers to
                 CTN adoption, such as lack of trust and data privacy.
                 Implemented using MPyC without extensive optimizations,
                 we demonstrate the efficiency and effectiveness in
                 increasing the average load factor, while achieving
                 acceptable running times (in the order of hours) for
                 arguably meaningful instance sizes (up to 1000 orders).
                 After leveraging a rather simplistic modeling inspired
                 by previous work, we finally give an outlook of
                 possible extensions toward more realistic models and
                 estimate their impact on efficiency.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Borghoff:2025:BPC,
  author =       "Uwe M. Borghoff and Paolo Bottoni and Remo Pareschi",
  title =        "Beyond Prompt Chaining: The {TB-CSPN} Architecture for
                 Agentic {AI}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "363",
  day =          "8",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080363",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/363",
  abstract =     "Current agentic AI frameworks such as LangGraph and
                 AutoGen simulate autonomy via sequential prompt
                 chaining but lack true multi-agent coordination
                 architectures. These systems conflate semantic
                 reasoning with orchestration, requiring LLMs at every
                 coordination step and limiting scalability. By
                 contrast, TB-CSPN (Topic-Based Communication Space
                 Petri Net) is a hybrid formal architecture that
                 fundamentally separates semantic processing from
                 coordination logic. Unlike traditional Petri net
                 applications, where the entire system state is encoded
                 within the network structure, TB-CSPN uses Petri nets
                 exclusively for coordination workflow modeling, letting
                 communication and interaction between agents drive
                 semantically rich, topic-based representations. At the
                 same time, unlike first-generation agentic frameworks,
                 here LLMs are confined to topic extraction, with
                 business logic coordination implemented by structured
                 token communication. This hybrid architectural
                 separation preserves human strategic oversight (as
                 supervisors) while delegating consultant and worker
                 roles to LLMs and specialized AI agents, avoiding the
                 state-space explosion typical of monolithic formal
                 systems. Our empirical evaluation shows that TB-CSPN
                 achieves 62.5\% faster processing, 66.7\% fewer LLM API
                 calls, and 167\% higher throughput compared to
                 LangGraph-style orchestration, without sacrificing
                 reliability. Scaling experiments with 10--100 agents
                 reveal sub-linear memory growth (10 $ \times $
                 efficiency improvement), directly contradicting
                 traditional Petri Net scalability concerns through our
                 semantic-coordination-based architectural separation.
                 These performance gains arise from the hybrid design,
                 where coordination patterns remain constant while
                 semantic spaces scale independently. TB-CSPN
                 demonstrates that efficient agentic AI emerges not by
                 over-relying on modern AI components but by embedding
                 them strategically within a hybrid architecture that
                 combines formal coordination guarantees with semantic
                 flexibility. Our implementation and evaluation
                 methodology are openly available, inviting community
                 validation and extension of these principles.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ivanov:2025:PAN,
  author =       "Valeriy Ivanov and Maxim Tereshonok",
  title =        "Parallel Algorithm for {NP}-Hard Problem of Channel
                 Resource Allocation Optimization in Ad Hoc and Sensor
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "362",
  day =          "8",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080362",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/362",
  abstract =     "This paper proposes a technique to estimate the
                 minimal quantity of orthogonal channel resources
                 required for ad hoc and sensor network connectivity.
                 Simultaneously, the resource allocation to each
                 specific line is conducted by grouping lines into
                 concurrent transmission sets. Our proposed technique
                 uses the physical-based interference model assumption,
                 where each node interferes with every other node,
                 turning ad hoc and sensor network performance
                 optimization problems into the NP-hard ones. In
                 contrast to most of the other works with the
                 physical-based interference model assumption, we
                 mitigate the combinatorial explosion of concurrently
                 transmitting line sets considering the global
                 interference instead of localizing the interference
                 with line or space partitioning. We have performed the
                 mitigation, firstly, using pairwise mutually acceptable
                 line sets for each line. Then, based on the limitations
                 of pairwise sets, we construct the tree of mutually
                 acceptable interfering line sets. Then, from the
                 created tree, we find the minimal set cover of
                 concurrently transmitting line sets. The tree
                 construction has the exponential worst-case time and
                 space complexity if all lines in the network can
                 transmit together. By randomly pruning the tree and
                 using the genetic algorithm to find the pruned tree
                 which gives the same minimal set cover as the full
                 tree, we have reduced the worst space and time
                 complexities to the polynomial ones. We have devised
                 our technique with parallelism in mind to speed up the
                 resource allocation optimization even more. Based on an
                 extensive simulation study with random network
                 topologies of sizes up to 250 nodes and the average
                 number of lines up to 2000, we estimated the time and
                 space complexity for different tree pruning and
                 optimization techniques and found the effective ones.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wang:2025:MLS,
  author =       "Qing Wang and Zhijun Wu and Yanrong Lu",
  title =        "A Multi-Layer Secure Sharing Framework for Aviation
                 Big Data Based on Blockchain",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "361",
  day =          "8",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080361",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/361",
  abstract =     "As a new type of production factor, data possesses
                 multidimensional application value, and its pivotal
                 role is becoming increasingly prominent in the aviation
                 sector. Data sharing can significantly enhance the
                 utilization efficiency of data resources and serves as
                 one of the key tasks in building smart civil aviation.
                 However, currently, data silos are pervasive, with vast
                 amounts of data only being utilized and analyzed within
                 limited scopes, leaving their full potential untapped.
                 The challenges in data sharing primarily stem from
                 three aspects: (1) Data owners harbor concerns
                 regarding data security and privacy. (2) The highly
                 dynamic and real-time nature of aviation operations
                 imposes stringent requirements on the timeliness,
                 stability, and reliability of data sharing, thereby
                 constraining its scope and extent. (3) The lack of
                 reasonable incentive mechanisms results in insufficient
                 motivation for data owners to share. Consequently,
                 addressing the issue of aviation big data sharing holds
                 significant importance. Since the release of the
                 Bitcoin whitepaper in 2008, blockchain technology has
                 achieved continuous breakthroughs in the fields of data
                 security and collaborative computing. Its unique
                 characteristics---decentralization, tamper-proofing,
                 traceability, and scalability---lay the foundation for
                 its integration with aviation. Blockchain can deeply
                 integrate with air traffic management (ATM) operations,
                 effectively resolving trust, efficiency, and
                 collaboration challenges in distributed scenarios for
                 ATM data. To address the heterogeneous data usage
                 requirements of different ATM stakeholders, this paper
                 constructs a blockchain-based multi-level data security
                 sharing architecture, enabling fine-grained management
                 and secure collaboration. Furthermore, to meet the
                 stringent timeliness demands of aviation operations and
                 the storage pressure posed by massive data, this paper
                 optimizes blockchain storage deployment and consensus
                 mechanisms, thereby enhancing system scalability and
                 processing efficiency. Additionally, a dual-mode
                 data-sharing solution combining raw data sharing and
                 model sharing is proposed, offering a novel approach to
                 aviation big data sharing. Security and formal analyses
                 demonstrate that the proposed solution is both secure
                 and effective.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Uruqi:2025:NFL,
  author =       "Albin Uruqi and Iosif Viktoratos and Athanasios
                 Tsadiras",
  title =        "A Novel Framework Leveraging Large Language Models to
                 Enhance Cold-Start Advertising Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "360",
  day =          "8",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080360",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/360",
  abstract =     "The cold-start problem remains a critical challenge in
                 personalized advertising, where users with limited or
                 no interaction history often receive suboptimal
                 recommendations. This study introduces a novel,
                 three-stage framework that systematically integrates
                 transformer architectures and large language models
                 (LLMs) to improve recommendation accuracy,
                 transparency, and user experience throughout the entire
                 advertising pipeline. The proposed approach begins with
                 transformer-enhanced feature extraction, leveraging
                 self-attention and learned positional encodings to
                 capture deep semantic relationships among users, ads,
                 and context. It then employs an ensemble integration
                 strategy combining enhanced state-of-the-art models
                 with optimized aggregation for robust prediction.
                 Finally, an LLM-driven enhancement module performs
                 semantic reranking, personalized message refinement,
                 and natural language explanation generation while also
                 addressing cold-start scenarios through pre-trained
                 knowledge. The LLM component further supports
                 diversification, fairness-aware ranking, and sentiment
                 sensitivity in order to ensure more relevant, diverse,
                 and ethically grounded recommendations. Extensive
                 experiments on DigiX and Avazu datasets demonstrate
                 notable gains in click-through rate prediction (CTR),
                 while an in-depth real user evaluation showcases
                 improvements in perceived ad relevance, message
                 quality, transparency, and trust. This work advances
                 the state-of-the-art by combining CTR models with
                 interpretability and contextual reasoning. The
                 strengths of the proposed method, such as its
                 innovative integration of components, empirical
                 validation, multifaceted LLM application, and ethical
                 alignment highlight its potential as a robust,
                 future-ready solution for personalized advertising.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Manolov:2025:CAM,
  author =       "Vladislav Manolov and Daniela Gotseva and Nikolay
                 Hinov",
  title =        "Creating Automated {Microsoft} Bicep Application
                 Infrastructure from {GitHub} in the {Azure Cloud}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "359",
  day =          "7",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080359",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/359",
  abstract =     "Infrastructure as code (IaC) is essential for modern
                 cloud development, enabling teams to define, deploy,
                 and manage infrastructure in a consistent and
                 repeatable manner. As organizations migrate to Azure,
                 selecting the right approach is crucial for managing
                 complexity, minimizing errors, and supporting DevOps
                 practices. This paper examines the use of Azure Bicep
                 with GitHub Actions to automate infrastructure
                 deployment for an application in the Azure cloud. It
                 explains how Bicep improves readability, modularity,
                 and integration compared to traditional ARM templates
                 and other automation tools. The solution utilizes a
                 modular Bicep design to deploy resources, including
                 virtual networks, managed identities, container apps,
                 databases, and AI services, with environment-specific
                 parameters for development, QA, and production. GitHub
                 Actions workflows automate the building, deployment,
                 and tearing down of infrastructure, ensuring consistent
                 deployments across environments. Security
                 considerations include managed identities, private
                 networking, and secret management in continuous
                 integration (CI) and continuous delivery (CD)
                 pipelines. This paper provides a detailed architectural
                 overview, workflow analysis, and implementation
                 guidance to help teams adopt a robust, automated
                 approach to Azure infrastructure deployment. By
                 leveraging automation tooling and modern DevOps
                 practices, organizations can streamline delivery and
                 maintain secure, maintainable cloud environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Miranda:2025:EIP,
  author =       "Alba Miranda and Aracely M. Vallejo and Paulina Ayala
                 and Marcelo V. Garcia and Jose E. Naranjo",
  title =        "Enhancing Industrial Processes Through Augmented
                 Reality: a Scoping Review",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "358",
  day =          "7",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080358",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/358",
  abstract =     "Augmented reality (AR) in industry improves training
                 and technical assistance by overlaying digital
                 information on real environments, facilitating the
                 visualisation and understanding of complex processes.
                 It also enables more effective remote collaboration,
                 optimising problem solving and decision making in real
                 time. This paper proposes a scoping review, using
                 PRISMA guidelines, on the optimisation of industrial
                 processes through the application of AR. The objectives
                 of this study included characterising successful
                 implementations of AR in various industrial processes,
                 comparing different hardware, graphics engines,
                 associated costs, and determining the percentage of
                 optimisation achieved through AR. The databases
                 included were Scopus, SpringerLink, IEEExplore, and
                 MDPI. Eligibility criteria were defined as
                 English-language articles published between 2019 and
                 2024 that provide significant contributions to AR
                 applications in engineering. The Cochrane method was
                 used to assess bias. The rigorous selection process
                 resulted in the inclusion of 38 articles. Key findings
                 indicate that AR reduces errors and execution times,
                 improves efficiency and productivity, and optimises
                 training and maintenance processes, leading to cost
                 savings and quality improvement. Unity 3D is the most
                 widely used graphics engine for AR applications. The
                 main applications of AR are in maintenance, assembly,
                 training and inspection, with maintenance being the
                 most researched area. Challenges include the learning
                 curve, high initial costs, and hardware limitations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ogunbunmi:2025:IFA,
  author =       "Simeon Ogunbunmi and Yu Chen and Qi Zhao and Deeraj
                 Nagothu and Sixiao Wei and Genshe Chen and Erik
                 Blasch",
  title =        "Interest Flooding Attacks in Named Data Networking and
                 Mitigations: Recent Advances and Challenges",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "357",
  day =          "6",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080357",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/357",
  abstract =     "Named Data Networking (NDN) represents a promising
                 Information-Centric Networking architecture that
                 addresses limitations of traditional host-centric
                 Internet protocols by emphasizing content names rather
                 than host addresses for communication. While NDN offers
                 advantages in content distribution, mobility support,
                 and built-in security features, its stateful forwarding
                 plane introduces significant vulnerabilities,
                 particularly Interest Flooding Attacks (IFAs). These
                 IFA attacks exploit the Pending Interest Table (PIT) by
                 injecting malicious interest packets for non-existent
                 or unsatisfiable content, leading to resource
                 exhaustion and denial-of-service attacks against
                 legitimate users. This survey examines research
                 advances in IFA detection and mitigation from 2013 to
                 2024, analyzing seven relevant published detection and
                 mitigation strategies to provide current insights into
                 this evolving security challenge. We establish a
                 taxonomy of attack variants, including Fake Interest,
                 Unsatisfiable Interest, Interest Loop, and Collusive
                 models, while examining their operational
                 characteristics and network performance impacts. Our
                 analysis categorizes defense mechanisms into five
                 primary approaches: rate-limiting strategies, PIT
                 management techniques, machine learning and artificial
                 intelligence methods, reputation-based systems, and
                 blockchain-enabled solutions. These approaches are
                 evaluated for their effectiveness, computational
                 requirements, and deployment feasibility. The survey
                 extends to domain-specific implementations in
                 resource-constrained environments, examining
                 adaptations for Internet of Things deployments,
                 wireless sensor networks, and high-mobility vehicular
                 scenarios. Five critical research directions are
                 proposed: adaptive defense mechanisms against
                 sophisticated attackers, privacy-preserving detection
                 techniques, real-time optimization for edge computing
                 environments, standardized evaluation frameworks, and
                 hybrid approaches combining multiple mitigation
                 strategies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bertolotti:2025:RMU,
  author =       "Ivan Cibrario Bertolotti",
  title =        "Rethinking Modbus-{UDP} for Real-Time {IIoT} Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "356",
  day =          "5",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080356",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/356",
  abstract =     "The original Modbus specification for RS-485 and
                 RS-232 buses supported broadcast transmission. As the
                 protocol evolved into Modbus-TCP, to use the TCP
                 transport, this useful feature was lost, likely due to
                 the point-to-point nature of TCP connections. Later
                 proposals did not restore the broadcast transmission
                 capability, although they used UDP as transport and
                 UDP, by itself, would have supported it. Moreover, they
                 did not address the inherent lack of reliable delivery
                 of UDP, leaving datagram loss detection and recovery to
                 the application layer. This paper describes a novel
                 redesign of Modbus-UDP that addresses the
                 aforementioned shortcomings. It achieves a mean
                 round-trip time of only 38\% with respect to Modbus-TCP
                 and seamlessly supports a previously published protocol
                 based on Modbus broadcast. In addition, the built-in
                 retransmission of Modbus-UDP reacts more efficiently
                 than the equivalent Modbus-TCP mechanism, exhibiting
                 50\% of its round-trip standard deviation when subject
                 to a 1\% two-way IP datagram loss probability. Combined
                 with the lower overhead of UDP versus TCP, this makes
                 the redesigned Modbus-UDP protocol better suited for a
                 variety of Industrial Internet of Things systems with
                 limited computing and communication resources.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Boufaida:2025:TGN,
  author =       "Soundes Oumaima Boufaida and Abdelmadjid Benmachiche
                 and Makhlouf Derdour and Majda Maatallah and Moustafa
                 Sadek Kahil and Mohamed Chahine Ghanem",
  title =        "{TSA-GRU}: a Novel Hybrid Deep Learning Module for
                 Learner Behavior Analytics in {MOOCs}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "355",
  day =          "5",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080355",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/355",
  abstract =     "E-Learning is an emerging dominant phenomenon in
                 education, making the development of robust models that
                 can accurately represent the dynamic behavior of
                 learners in MOOCs even more critical. In this article,
                 we propose the Temporal Sparse Attention-Gated
                 Recurrent Unit (TSA-GRU), a novel deep learning
                 framework that combines TSA with a sequential encoder
                 based on the GRU. This hybrid model effectively
                 reconstructs student response times and learning
                 trajectories with high fidelity by leveraging the
                 temporal embeddings of instructional and feedback
                 activities. By dynamically filtering noise from student
                 interactions, TSA-GRU generates context-aware
                 representations that seamlessly integrate both
                 short-term fluctuations and long-term learning
                 patterns. Empirical evaluation on the 2009--2010
                 ASSISTments dataset demonstrates that TSA-GRU achieved
                 a test accuracy of 95.60\% and a test loss of 0.0209,
                 outperforming Modular Sparse Attention-Gated Recurrent
                 Unit (MSA-GRU), Bayesian Knowledge Tracing (BKT),
                 Performance Factors Analysis (PFA), and TSA in the same
                 experimental design. TSA-GRU converged in five training
                 epochs; thus, while TSA-GRU is demonstrated to have
                 strong predictive performance for knowledge tracing
                 tasks, these findings are specific to the conducted
                 dataset and should not be implicitly regarded as
                 conclusive for all data. More statistical validation
                 through five-fold cross-validation, confidence
                 intervals, and paired t -tests have confirmed the
                 robustness, consistency, and statistically significant
                 superiority of TSA-GRU over the baseline model MSA-GRU.
                 TSA-GRU's scalability and capacity to incorporate a
                 temporal dimension of knowledge can make it acceptably
                 well-positioned to analyze complex learner behaviors
                 and plan interventions for adaptive learning in
                 computerized learning systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Vergara:2025:ESI,
  author =       "Diego Vergara",
  title =        "Editorial for the Special Issue {``Virtual Reality and
                 Metaverse: Impact on the Digital Transformation of
                 Society --- 2nd Edition''}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "354",
  day =          "4",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080354",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/354",
  abstract =     "E-Learning is an emerging dominant phenomenon in
                 education, making the development of robust models that
                 can accurately represent the dynamic behavior of
                 learners in MOOCs even more critical. In this article,
                 we propose the Temporal Sparse Attention-Gated
                 Recurrent Unit (TSA-GRU), a novel deep learning
                 framework that combines TSA with a sequential encoder
                 based on the GRU. This hybrid model effectively
                 reconstructs student response times and learning
                 trajectories with high fidelity by leveraging the
                 emporal embeddings of instructional and feedback
                 activities. By dynamically filtering noise from student
                 interactions, TSA-GRU generates context-aware
                 representations that seamlessly integrate both
                 short-term fluctuations and long-term learning
                 patterns. Empirical evaluation on the 2009--2010
                 ASSISTments dataset demonstrates that TSA-GRU achieved
                 a test accuracy of 95.60\% and a test loss of 0.0209,
                 outperforming Modular Sparse Attention-Gated Recurrent
                 Unit (MSA-GRU), Bayesian Knowledge Tracing (BKT),
                 Performance Factors Analysis (PFA), and TSA in the same
                 experimental design. TSA-GRU converged in five training
                 epochs; thus, while TSA-GRU is demonstrated to have
                 strong predictive performance for knowledge tracing
                 tasks, these findings are specific to the conducted
                 dataset and should not be implicitly regarded as
                 conclusive for all data. More statistical validation
                 through five-fold cross-validation, confidence
                 intervals, and paired t -tests have confirmed the
                 robustness, consistency, and statistically significant
                 superiority of TSA-GRU over the baseline model MSA-GRU.
                 TSA-GRU's scalability and capacity to incorporate a
                 temporal dimension of knowledge can make it acceptably
                 well-positioned to analyze complex learner behaviors
                 and plan interventions for adaptive learning in
                 computerized learning systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Karim:2025:TDA,
  author =       "Md Monjurul Karim and Sangeen Khan and Dong Hoang Van
                 and Xinyue Liu and Chunhui Wang and Qiang Qu",
  title =        "Transforming Data Annotation with {AI} Agents: a
                 Review of Architectures, Reasoning, Applications, and
                 Impact",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "353",
  day =          "2",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080353",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/353",
  abstract =     "Data annotation serves as a critical foundation for
                 artificial intelligence (AI) and machine learning (ML).
                 Recently, AI agents powered by large language models
                 (LLMs) have emerged as effective solutions to
                 longstanding challenges in data annotation, such as
                 scalability, consistency, cost, and limitations in
                 domain expertise. These agents facilitate intelligent
                 automation and adaptive decision-making, thereby
                 enhancing the efficiency and reliability of annotation
                 workflows across various fields. Despite the growing
                 interest in this area, a systematic understanding of
                 the role and capabilities of AI agents in annotation is
                 still underexplored. This paper seeks to fill that gap
                 by providing a comprehensive review of how LLM-driven
                 agents support advanced reasoning strategies, adaptive
                 learning, and collaborative annotation efforts. We
                 analyze agent architectures, integration patterns
                 within workflows, and evaluation methods, along with
                 real-world applications in sectors such as healthcare,
                 finance, technology, and media. Furthermore, we
                 evaluate current tools and platforms that support
                 agent-based annotation, addressing key challenges such
                 as quality assurance, bias mitigation, transparency,
                 and scalability. Lastly, we outline future research
                 directions, highlighting the importance of federated
                 learning, cross-modal reasoning, and responsible system
                 design to advance the development of next-generation
                 annotation ecosystems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Frattolillo:2025:CSC,
  author =       "Franco Frattolillo",
  title =        "Confidential Smart Contracts and Blockchain to
                 Implement a Watermarking Protocol",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "352",
  day =          "1",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080352",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/352",
  abstract =     "Watermarking protocols represent a possible solution
                 to the problem of digital copyright protection of
                 content distributed on the Internet. Their
                 implementations, however, continue to be a complex
                 problem due to the difficulties researchers encounter
                 in proposing secure, easy-to-use and, at the same time,
                 ``trusted third parties'' (TTPs)-free solutions. In
                 this regard, implementations based on blockchain and
                 smart contracts are among the most advanced and
                 promising, even if they are affected by problems
                 regarding the performance and privacy of the
                 information exchanged and processed by smart contracts
                 and managed by blockchains. This paper presents a
                 watermarking protocol implemented by smart contracts
                 and blockchain. The protocol uses a ``layer-2''
                 blockchain execution model and performs the computation
                 in ``trusted execution environments'' (TEEs).
                 Therefore, its implementation can guarantee efficient
                 and confidential execution without compromising ease of
                 use or resorting to TTPs. The protocol and its
                 implementation can, thus, be considered a valid answer
                 to the ``trilemma'' that afflicts the use of
                 blockchains, managing to guarantee decentralization,
                 security, and scalability.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sernandez-Iglesias:2025:ITP,
  author =       "Daniel Sern{\'a}ndez-Iglesias and Llanos Tobarra and
                 Rafael Pastor-Vargas and Antonio Robles-G{\'o}mez and
                 Pedro Vidal-Balboa and Jo{\~a}o Sarraipa",
  title =        "{Internet of Things} Platform for Assessment and
                 Research on Cybersecurity of Smart Rural Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "351",
  day =          "1",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080351",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/351",
  abstract =     "Rural regions face significant barriers to adopting
                 IoT technologies, due to limited connectivity, energy
                 constraints, and poor technical infrastructure. While
                 urban environments benefit from advanced digital
                 systems and cloud services, rural areas often lack the
                 necessary conditions to deploy and evaluate secure and
                 autonomous IoT solutions. To help overcome this gap,
                 this paper presents the Smart Rural IoT Lab, a modular
                 and reproducible testbed designed to replicate the
                 deployment conditions in rural areas using open-source
                 tools and affordable hardware. The laboratory
                 integrates long-range and short-range communication
                 technologies in six experimental scenarios,
                 implementing protocols such as MQTT, HTTP, UDP, and
                 CoAP. These scenarios simulate realistic rural use
                 cases, including environmental monitoring, livestock
                 tracking, infrastructure access control, and heritage
                 site protection. Local data processing is achieved
                 through containerized services like Node-RED, InfluxDB,
                 MongoDB, and Grafana, ensuring complete autonomy,
                 without dependence on cloud services. A key
                 contribution of the laboratory is the generation of
                 structured datasets from real network traffic captured
                 with Tcpdump and preprocessed using Zeek. Unlike
                 simulated datasets, the collected data reflect
                 communication patterns generated from real devices.
                 Although the current dataset only includes benign
                 traffic, the platform is prepared for future
                 incorporation of adversarial scenarios (spoofing, DoS)
                 to support AI-based cybersecurity research. While
                 experiments were conducted in an indoor controlled
                 environment, the testbed architecture is portable and
                 suitable for future outdoor deployment. The Smart Rural
                 IoT Lab addresses a critical gap in current research
                 infrastructure, providing a realistic and flexible
                 foundation for developing secure, cloud-independent IoT
                 solutions, contributing to the digital transformation
                 of rural regions.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Nguyen:2025:SII,
  author =       "Dung T. Nguyen and Mien L. Trinh and Minh T. Nguyen
                 and Thang C. Vu and Tao V. Nguyen and Long Q. Dinh and
                 Mui D. Nguyen",
  title =        "Security Issues in {IoT}-Based Wireless Sensor
                 Networks: Classifications and Solutions",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "350",
  day =          "1",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080350",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/350",
  abstract =     "In recent years, the Internet of Things (IoT) has
                 experienced considerable developments and has played an
                 important role in various domains such as industry,
                 agriculture, healthcare, transportation, and
                 environment, especially for smart cities. Along with
                 that, wireless sensor networks (WSNs) are considered to
                 be important components of the IoT system (WSN-IoT) to
                 create smart applications and automate processes. As
                 the number of connected IoT devices increases, privacy
                 and security issues become more complicated due to
                 their external working environments and limited
                 resources. Hence, solutions need to be updated to
                 ensure that data and user privacy are protected from
                 threats and attacks. To support the safety and
                 reliability of such systems, in this paper, security
                 issues in the WSN-IoT are addressed and classified as
                 identifying security challenges and requirements for
                 different kinds of attacks in either WSNs or IoT
                 systems. In addition, security solutions corresponding
                 to different types of attacks are provided, analyzed,
                 and evaluated. We provide different comparisons and
                 classifications based on specific goals and
                 applications that hopefully can suggest suitable
                 solutions for specific purposes in practical. We also
                 suggest some research directions to support new
                 security mechanisms.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Beschi:2025:ASE,
  author =       "Sara Beschi and Daniela Fogli and Luigi Gargioni and
                 Angela Locoro",
  title =        "{AI}-Supported {EUD} for Data Visualization: an
                 Exploratory Case Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "8",
  pages =        "349",
  day =          "1",
  month =        aug,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17080349",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/8/349",
  abstract =     "Data visualization is a key activity in data-driven
                 decision making and is gaining momentum in many
                 organizational contexts. However, the role and
                 contribution of both end-user development (EUD) and
                 artificial intelligence (AI) technologies for data
                 visualization and analytics are still not clear or
                 systematically studied. This work investigates how
                 effectively AI-supported EUD tools may assist visual
                 analytics tasks in organizations. An exploratory case
                 study with eight interviews with key informants allowed
                 a deep understanding of data analysis and visualization
                 practices in a large Italian company. It aimed at
                 identifying the various professional roles and
                 competencies necessary in the business context,
                 understanding the data sources and data formats
                 exploited in daily activities, and formulating suitable
                 hypotheses to guide the design of AI-supported EUD
                 tools for data analysis and visualization. In
                 particular, the results of interviews with key
                 informants yielded the development of a prototype of an
                 LLM-based EUD environment, which was then used with
                 selected target users to collect their opinions and
                 expectations about this type of intervention in their
                 work practice and organization. All the data collected
                 during the exploratory case study finally led to
                 defining a set of design guidelines for AI-supported
                 EUD for data visualization.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Adam:2025:DLA,
  author =       "Muhammad Adam and Jianchao Song and Wei Yu and
                 Qingqing Li",
  title =        "Deep Learning Approaches for Automatic Livestock
                 Detection in {UAV} Imagery: State-of-the-Art and Future
                 Directions",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "431",
  day =          "21",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090431",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/431",
  abstract =     "Accurate livestock monitoring is critical for
                 precision agriculture, supporting effective farm
                 management, disease prevention, and sustainable
                 resource allocation. Deep learning and remote sensing
                 are recent technological advancements that have created
                 auspicious opportunities for the development of
                 livestock monitoring systems. This paper presents a
                 comprehensive survey of deep learning approaches for
                 automatic livestock detection in unmanned aerial
                 vehicles (UAVs), highlighting key deep learning
                 techniques, livestock detection challenges, and
                 emerging trends. We analyze the innovations of popular
                 deep learning models in the area of object detection,
                 including You Look Only Once (YOLO) versions,
                 Region-based Convolutional Neural Networks (RCNN),
                 Anchor-based networks, and transformer models, to
                 discuss their suitability for scalable and
                 cost-efficient UAV-based livestock detection scenarios.
                 To complement the survey, a case study is conducted on
                 a custom UAV cattle dataset to benchmark representation
                 detection models. Evaluation results demonstrate a
                 trade-off between Precision, Recall, F1 score, IoU,
                 mAP@50, mAP@50-95, inference speed, and model size. The
                 case study results provide a clear understanding of
                 selection and adapting deep learning models for
                 UAV-based livestock monitoring and outline future
                 directions for lightweight, domain-adapted frameworks
                 in precision farming applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fernandez-Miguel:2025:ADT,
  author =       "Andr{\'e}s Fern{\'a}ndez-Miguel and Fernando Enrique
                 Garc{\'\i}a-Mui{\~n}a and Susana Ort{\'\i}z-Marcos and
                 Mariano Jim{\'e}nez-Calzado and Alfonso P.
                 Fern{\'a}ndez del Hoyo and Davide Settembre-Blundo",
  title =        "{AI}-Driven Transformations in Manufacturing: Bridging
                 {Industry 4.0, 5.0, and 6.0} in Sustainable Value
                 Chains",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "430",
  day =          "21",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090430",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/430",
  abstract =     "This study investigates how AI-driven innovations are
                 reshaping manufacturing value chains through the
                 transition from Industry 4.0 to Industry 6.0,
                 particularly in resource-intensive sectors such as
                 ceramics. Addressing a gap in the literature, the
                 research situates the evolution of manufacturing within
                 the broader context of digital transformation,
                 sustainability, and regulatory demands. A mixed-methods
                 approach was employed, combining semi-structured
                 interviews with key industry stakeholders and an
                 extensive review of secondary data, to develop an
                 Industry 6.0 model tailored to the ceramics industry.
                 The findings demonstrate that artificial intelligence,
                 digital twins, and cognitive automation significantly
                 enhance predictive maintenance, real-time supply chain
                 optimization, and regulatory compliance, notably with
                 the Corporate Sustainability Reporting Directive
                 (CSRD). These technological advancements also
                 facilitate circular economy practices and cognitive
                 logistics, thereby fostering greater transparency and
                 sustainability in B2B manufacturing networks. The study
                 concludes that integrating AI-driven automation and
                 cognitive logistics into digital ecosystems and supply
                 chain management serves as a strategic enabler of
                 operational resilience, regulatory alignment, and
                 long-term competitiveness. While the industry-specific
                 focus may limit generalizability, the study underscores
                 the need for further research in diverse manufacturing
                 sectors and longitudinal analyses to fully assess the
                 long-term impact of AI-enabled Industry 6.0
                 frameworks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gomez-Pantoja:2025:BAC,
  author =       "Carlos G{\'o}mez-Pantoja and Daniela Baeza-Rocha and
                 Alonso Inostrosa-Psijas",
  title =        "A Behavior-Aware Caching Architecture for {Web}
                 Applications Using Static, Dynamic, and Burst
                 Segmentation",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "429",
  day =          "20",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090429",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/429",
  abstract =     "This work proposes a behavior-aware caching
                 architecture that improves cache hit rates by up to
                 10.8\% over LRU and 36\% over LFU in large-scale web
                 applications, reducing redundant traffic and
                 alleviating backend server load. The architecture
                 partitions the cache into three sections---static,
                 dynamic, and burst---according to query reuse patterns
                 derived from user behavior. Static queries remain
                 permanently stored, dynamic queries have time-bound
                 validity, and burst queries are detected in real time
                 using a statistical monitoring mechanism to prioritize
                 sudden, high-demand requests. The proposed architecture
                 was evaluated through simulation experiments using
                 real-world query logs (a one-month trace of 1.5 billion
                 queries from a commercial search engine) under multiple
                 cache capacity configurations ranging from 1000 to
                 100,000 entries and in combination with the Least
                 Recently Used (LRU) and Least Frequently Used (LFU)
                 replacement policies. The results show that the
                 proposed architecture consistently achieves higher
                 performance than the baselines, with the largest
                 relative gains in smaller cache configurations and
                 applicability to distributed and hybrid caching
                 environments without fundamental design changes. The
                 integration of user-behavior modeling and burst-aware
                 segmentation delivers a practical and reproducible
                 framework that optimizes cache allocation policies in
                 high-traffic and distributed environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Jia:2025:CFA,
  author =       "Hong Jia and Dalin Qian and Fanghua Chen and Wei
                 Zhou",
  title =        "Collaborative Fusion Attention Mechanism for Vehicle
                 Fault Prediction",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "428",
  day =          "19",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090428",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/428",
  abstract =     "In this study, we investigate a deep learning-based
                 vehicle fault prediction model aimed at achieving
                 accurate prediction of vehicle faults by analyzing the
                 correlations among different faults and the impact of
                 critical faults on future fault development. To this
                 end, we propose a collaborative modeling approach
                 utilizing multiple attention mechanisms. This approach
                 incorporates a graph attention mechanism for the fusion
                 representation of fault correlation information and
                 employs a novel learning method that combines a Long
                 Short-Term Memory (LSTM) network with an attention
                 mechanism to capture the impact of key faults. Based on
                 experimental validation using real-world vehicle fault
                 record data, the model significantly outperforms
                 existing prediction models in terms of fault prediction
                 accuracy.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hakami:2025:EEB,
  author =       "Tahani Ali Hakami and Yasser M. Alginahi and Omar
                 Sabri",
  title =        "Exploring the Evolution of Big Data Technologies: a
                 Systematic Literature Review of Trends, Challenges, and
                 Future Directions",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "427",
  day =          "19",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090427",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/427",
  abstract =     "This study examines the evolution and impact of Big
                 Data technologies across sectors, emphasizing key
                 algorithms, emerging trends, and organizational
                 challenges in their adoption. Special attention is
                 given to ethical concerns related to data privacy,
                 security, and scalability, underscoring the importance
                 of responsible governance frameworks. The review
                 follows the Preferred Reporting Items for Systematic
                 Reviews and Meta-Analyses (PRISMA) 2020 guidelines to
                 ensure transparency and methodological rigor. A
                 comprehensive literature search identified 83
                 peer-reviewed articles from high-indexed journals, and
                 a complementary bibliometric analysis of 1108
                 Scopus-sourced articles (2015--2024) was conducted
                 using R Biblioshiny. This dual-method approach offers
                 both qualitative depth and quantitative insights into
                 major trends, influential sources, and leading
                 countries in Big Data research. Key findings reveal
                 that real-time data processing and AI integration have
                 significantly enhanced data management capabilities,
                 supporting faster and more informed organizational
                 decision-making. This study concludes by highlighting
                 the importance of ethical governance and recommending
                 future research on sector-specific adoption patterns
                 and strategic frameworks that maximize Big Data's value
                 while safeguarding privacy and trust.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Twabi:2025:PAP,
  author =       "Ahmed Twabi and Yepeng Ding and Tohru Kondo",
  title =        "A Platform-Agnostic Publish--Subscribe Architecture
                 with Dynamic Optimization",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "426",
  day =          "19",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090426",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/426",
  abstract =     "Real-time media streaming over publish--subscribe
                 platforms is increasingly vital in scenarios that
                 demand the scalability of event-driven architectures
                 while ensuring timely media delivery. This is
                 especially true in multi-modal and resource-constrained
                 environments, such as IoT, Physical Activity
                 Recognition and Measure (PARM), and Internet of Video
                 Things (IoVT), where integrating sensor data with media
                 streams often leads to complex hybrid setups that
                 compromise consistency and maintainability.
                 Publish--subscribe (pub/sub) platforms like Kafka and
                 MQTT offer scalability and decoupled communication but
                 fall short in supporting real-time video streaming due
                 to platform-dependent design, rigid optimization, and
                 poor sub-second media handling. This paper presents
                 FrameMQ, a layered, platform-agnostic architecture
                 designed to overcome these limitations by decoupling
                 application logic from platform-specific configurations
                 and enabling dynamic real-time optimization. FrameMQ
                 exposes tunable parameters such as compression and
                 segmentation, allowing integration with external
                 optimizers. Using Particle Swarm Optimization (PSO) as
                 an exemplary optimizer, FrameMQ reduces total latency
                 from over 2300 ms to below 400ms under stable
                 conditions (over an 80\% improvement) and maintains up
                 to a 52\% reduction under adverse network conditions.
                 These results demonstrate FrameMQ's ability to meet the
                 demands of latency-sensitive applications, such as
                 real-time streaming, IoT, and surveillance, while
                 offering portability, extensibility, and platform
                 independence without modifying the core application
                 logic.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Korakianitis:2025:DER,
  author =       "Nikolaos S. Korakianitis and Panagiotis Papageorgas
                 and Georgios A. Vokas and Dimitrios D. Piromalis and
                 Stavros D. Kaminaris and George Ch. Ioannidis and Ander
                 Ochoa de Zuazola",
  title =        "Design and Evaluation of a Research-Oriented
                 Open-Source Platform for Smart Grid Metering: a
                 Comprehensive Review and Experimental Intercomparison
                 of Smart Meter Technologies",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "425",
  day =          "19",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090425",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/425",
  abstract =     "Smart meters (SMs) are essential components of modern
                 smart grids, enabling real-time and accurate monitoring
                 of electricity consumption. However, their evaluation
                 is often hindered by proprietary communication
                 protocols and the high cost of commercial testing
                 tools. This study presents a low-cost, open-source
                 experimental platform for smart meter validation, using
                 a microcontroller and light sensor to detect optical
                 pulses emitted by standard SMs. This non-intrusive
                 approach circumvents proprietary restrictions while
                 enabling transparent and reproducible comparisons. A
                 case study was conducted comparing the static meter
                 GAMA 300 model, manufactured by Elgama-Elektronika Ltd.
                 (Vilnius, Lithuania), which is a closed-source
                 commercial meter, with the Texas Instruments
                 EVM430-F67641 evaluation module, manufactured by Texas
                 Instruments Inc. (Dallas, TX, USA), which serves as an
                 open-source reference design. Statistical
                 analyses---based on confidence intervals and
                 ANOVA---revealed a mean deviation of less than 1.5\%
                 between the devices, confirming the platform's
                 reliability. The system supports indirect power
                 monitoring without hardware modification or access to
                 internal data, making it suitable for both educational
                 and applied contexts. Compared to existing tools, it
                 offers enhanced accessibility, modularity, and
                 open-source compatibility. Its scalable design supports
                 IoT and environmental sensor integration, aligning with
                 Internet of Energy (IoE) principles. The platform
                 facilitates transparent, reproducible, and
                 cost-effective smart meter evaluations, supporting the
                 advancement of intelligent energy systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Odeyomi:2025:SII,
  author =       "Olusola T. Odeyomi and Temitayo O. Olowu",
  title =        "Special Issue: Intrusion Detection and Resiliency in
                 Cyber-Physical Systems and Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "424",
  day =          "18",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090424",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/424",
  abstract =     "Smart meters (SMs) are essential components of modern
                 smart grids, enabling real-time and accurate monitoring
                 of electricity consumption. However, their evaluation
                 is often hindered by proprietary communication
                 protocols and the high cost of commercial testing
                 tools. This study presents a low-cost, open-source
                 experimental platform for smart meter validation, using
                 a microcontroller and light sensor to detect optical
                 pulses emitted by standard SMs. This non-intrusive
                 approach circumvents proprietary restrictions while
                 enabling transparent and reproducible comparisons. A
                 case study was conducted comparing the static meter
                 GAMA 300 model, manufactured by Elgama-Elektronika Ltd.
                 (Vilnius, Lithuania), which is a closed-source
                 commercial meter, with the Texas Instruments
                 EVM430-F67641 evaluation module, manufactured by Texas
                 Instruments Inc. (Dallas, TX, USA), which serves as an
                 open-source reference design. Statistical
                 analyses---based on confidence intervals and
                 ANOVA---revealed a mean deviation of less than 1.5\%
                 between the devices, confirming the platform's
                 reliability. The system supports indirect power
                 monitoring without hardware modification or access to
                 internal data, making it suitable for both educational
                 and applied contexts. Compared to existing tools, it
                 offers enhanced accessibility, modularity, and
                 open-source compatibility. Its scalable design supports
                 IoT and environmental sensor integration, aligning with
                 Internet of Energy (IoE) principles. The platform
                 facilitates transparent, reproducible, and
                 cost-effective smart meter evaluations, supporting the
                 advancement of intelligent energy systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ren:2025:GTA,
  author =       "Jiajie Ren and Chang Guo",
  title =        "A Game Theoretic Approach for {D2D} Assisted Uncoded
                 Caching in {IoT} Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "423",
  day =          "18",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090423",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/423",
  abstract =     "Content caching and exchange through device-to-device
                 (D2D) communications can offload data from the
                 centralized base station and improve the quality of
                 users' experience. However, existing studies often
                 overlook the selfish nature of user equipment (UE) and
                 the heterogeneity of content preferences, which limits
                 their practical applicability. In this paper, we
                 propose a novel incentive-driven uncoded caching
                 framework modeled as a Stackelberg game between a base
                 station (BS) and cache-enabled UEs. The BS acts as the
                 leader by determining the unit incentive reward, while
                 UEs jointly optimize their caching strategies as
                 followers. The particular challenge in our formulation
                 is that the uncoded caching decisions make the UEs'
                 total utility maximization problem into a non-convex
                 integer programming problem. To address this, we map
                 the UEs' total utility maximization problem into a
                 potential sub-game and design a potential game-based
                 distributed caching (PGDC) algorithm that guarantees
                 convergence to the optimal joint caching strategy.
                 Building on this, we further develop a dynamic
                 iterative algorithm to derive the Stackelberg
                 equilibrium by jointly optimizing the BS's cost and the
                 total utility of UEs. The simulation results confirm
                 the existence of the Stackelberg Equilibrium and
                 demonstrate that the proposed PGDC algorithm
                 significantly outperforms benchmark caching schemes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Visalom:2025:IMP,
  author =       "Rares-Mihail Visalom and Maria-Elena Mihailescu and
                 Razvan Rughinis and Dinu Turcanu",
  title =        "Intercepting and Monitoring Potentially Malicious
                 Payloads with {Web} Honeypots",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "422",
  day =          "17",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090422",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/422",
  abstract =     "The rapid development of an increasing volume of web
                 apps and the improper testing of the resulting code
                 invariably provide more attack surfaces to potentially
                 exploit. This leads to higher chances of facing
                 cybersecurity breaches that can negatively impact both
                 the users and providers of web services. Moreover,
                 current data leaks resulting from breaches are most
                 probably the fuel of future breaches and social
                 engineering attacks. Given the context, a better
                 analysis and understanding of web attacks are of the
                 utmost priority. Our study provides practical insights
                 into developing, implementing, deploying, and actively
                 monitoring a web application-agnostic honeypot with the
                 objective of improving the odds of defending against
                 web attacks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sasaki:2025:DTA,
  author =       "Nophea Sasaki and Issei Abe",
  title =        "A Digital Twin Architecture for Forest Restoration:
                 Integrating {AI}, {IoT}, and Blockchain for Smart
                 Ecosystem Management",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "421",
  day =          "15",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090421",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/421",
  abstract =     "Meeting global forest restoration targets by 2030
                 requires a transition from labor-intensive and opaque
                 practices to scalable, intelligent, and verifiable
                 systems. This paper introduces a cyber--physical
                 digital twin architecture for forest restoration,
                 structured across four layers: (i) a Physical Layer
                 with drones and IoT-enabled sensors for in situ
                 environmental monitoring; (ii) a Data Layer for secure
                 and structured transmission of spatiotemporal data;
                 (iii) an Intelligence Layer applying AI-driven
                 modeling, simulation, and predictive analytics to
                 forecast biomass, biodiversity, and risk; and (iv) an
                 Application Layer providing stakeholder dashboards,
                 milestone-based smart contracts, and automated climate
                 finance flows. Evidence from Dronecoria, Flash Forest,
                 and AirSeed Technologies shows that digital twins can
                 reduce per-tree planting costs from USD 2.00--3.75 to
                 USD 0.11--1.08, while enhancing accuracy, scalability,
                 and community participation. The paper further outlines
                 policy directions for integrating digital MRV systems
                 into the Enhanced Transparency Framework (ETF) and
                 Article 5 of the Paris Agreement. By embedding
                 simulation, automation, and participatory finance into
                 a unified ecosystem, digital twins offer a resilient,
                 interoperable, and climate-aligned pathway for
                 next-generation forest restoration.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hawa:2025:DCS,
  author =       "Mohammed Hawa and Ramzi Saifan and Talal A. Edwan and
                 Oswa M. Amro",
  title =        "Dynamic Channel Selection for Rendezvous in Cognitive
                 Radio Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "420",
  day =          "15",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090420",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/420",
  abstract =     "In an attempt to improve utilization of the frequency
                 spectrum left vacant by license holders, cognitive
                 radio networks (CRNs) permit secondary users (SUs) to
                 utilize such spectrum when the license holders, known
                 as primary users (PUs), are inactive. When a pair of
                 SUs wants to communicate over the CRN, they need to
                 converge simultaneously on one of the vacant channels,
                 in a process known as rendezvous. In this work, we
                 attempt to reduce the rendezvous time for SUs executing
                 the well-known enhanced jump-stay (EJS) channel hopping
                 procedure. We achieve this by modifying EJS in order to
                 search the vacant spectrum around a specific favorite
                 channel, instead of hopping across the whole spectrum.
                 Moreover, the search process is carefully designed in
                 order to accommodate the dynamic nature of CRNs, where
                 PUs repeatedly become active and inactive, resulting in
                 disturbances to the rendezvous process. A main feature
                 of our proposed technique, named dynamic jump-stay
                 (DJS), is that the SUs do not need any prior
                 coordination over a common control channel (CCC),
                 thereby allowing for scalable and more robust
                 distributed CRNs. Simulations are used to quantify the
                 resulting performance improvement in terms of expected
                 time to rendezvous, maximum time to rendezvous, and
                 interference on PUs.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Qu:2025:SSA,
  author =       "Qian Qu and Yu Chen and Erik Blasch",
  title =        "{SAVE}: Securing Avatars in Virtual Healthcare Through
                 Environmental Fingerprinting for Elder Safety
                 Monitoring",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "419",
  day =          "15",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090419",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/419",
  abstract =     "The rapid adoption of Metaverse technologies in
                 healthcare, particularly for elder safety monitoring,
                 has introduced new security challenges related to the
                 authenticity of virtual representations. As healthcare
                 providers increasingly rely on avatars and digital
                 twins to monitor and interact with elderly patients
                 remotely, ensuring the integrity of these virtual
                 entities becomes paramount. This paper introduces SAVE
                 (Securing Avatars in Virtual Environments), an emerging
                 framework that leverages environmental fingerprinting
                 based on Electric Network Frequency (ENF) signals to
                 authenticate avatars and detect potential deepfake
                 attacks in virtual healthcare settings. Unlike
                 conventional authentication methods that rely solely on
                 digital credentials, SAVE anchors virtual entities to
                 the physical world by utilizing the unique temporal and
                 spatial characteristics of ENF signals. We implement
                 and evaluate SAVE in a Microverse-based nursing home
                 environment designed for monitoring elderly individuals
                 living alone. We evaluated SAVE using a prototype
                 system with Raspberry Pi devices and multiple
                 environmental sensors, demonstrating effectiveness
                 across three attack scenarios in a 30-minute
                 experimental window. Through the experimental
                 evaluation of three distinct attack scenarios,
                 unauthorized device attacks, device ID spoofing, and
                 replay attacks using intercepted data, our system
                 demonstrates high detection accuracy with minimal false
                 positives. Results show that by comparing ENF
                 fingerprints embedded in transmitted data with
                 reference ENF signals, SAVE can effectively identify
                 tampering and ensure the authenticity of avatar updates
                 in real time. The SAVE approach enhances the security
                 of virtual healthcare monitoring without requiring
                 additional user intervention, making it particularly
                 suitable for elderly care applications where ease of
                 use is essential. Our findings highlight the potential
                 of physical environmental fingerprints as a robust
                 security layer for virtual healthcare systems,
                 contributing to safer and more trustworthy remote
                 monitoring solutions for vulnerable populations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Midolo:2025:RLE,
  author =       "Alessandro Midolo and Emiliano Tramontana",
  title =        "Refactoring Loops in the Era of {LLMs}: a
                 Comprehensive Study",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "418",
  day =          "12",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090418",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/418",
  abstract =     "Java 8 brought functional programming to the Java
                 language and library, enabling more expressive and
                 concise code to replace loops by using streams. Despite
                 such advantages, for-loops remain prevalent in current
                 codebases as the transition to the functional paradigm
                 requires a significant shift in the developer mindset.
                 Traditional approaches for assisting refactoring loops
                 into streams check a set of strict preconditions to
                 ensure correct transformation, hence limiting their
                 applicability. Conversely, generative artificial
                 intelligence (AI), particularly ChatGPT, is a promising
                 tool for automating software engineering tasks,
                 including refactoring. While prior studies examined
                 ChatGPT's assistance in various development contexts,
                 none have specifically investigated its ability to
                 refactor for-loops into streams. This paper addresses
                 such a gap by evaluating ChatGPT's effectiveness in
                 transforming loops into streams. We analyzed 2132 loops
                 extracted from four open-source GitHub repositories and
                 classified them according to traditional refactoring
                 templates and preconditions. We then tasked ChatGPT
                 with the refactoring of such loops and evaluated the
                 correctness and quality of the generated code. Our
                 findings revealed that ChatGPT could successfully
                 refactor many more loops than traditional approaches,
                 although it struggled with complex control flows and
                 implicit dependencies. This study provides new insights
                 into the strengths and limitations of ChatGPT in
                 loop-to-stream refactoring and outlines potential
                 improvements for future AI-driven refactoring tools.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ordonez:2025:IEC,
  author =       "Sebasti{\'a}n A. Cajas Ord{\'o}{\~n}ez and Jaydeep
                 Samanta and Andr{\'e}s L. Su{\'a}rez-Cetrulo and
                 Ricardo Sim{\'o}n Carbajo",
  title =        "Intelligent Edge Computing and Machine Learning: a
                 Survey of Optimization and Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "417",
  day =          "11",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090417",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/417",
  abstract =     "Intelligent edge machine learning has emerged as a
                 paradigm for deploying smart applications across
                 resource-constrained devices in next-generation network
                 infrastructures. This survey addresses the critical
                 challenges of implementing machine learning models on
                 edge devices within distributed network environments,
                 including computational limitations, memory
                 constraints, and energy-efficiency requirements for
                 real-time intelligent inference. We provide
                 comprehensive analysis of soft computing optimization
                 strategies essential for intelligent edge deployment,
                 systematically examining model compression techniques
                 including pruning, quantization methods, knowledge
                 distillation, and low-rank decomposition approaches.
                 The survey explores intelligent MLOps frameworks
                 tailored for network edge environments, addressing
                 continuous model adaptation, monitoring under data
                 drift, and federated learning for distributed
                 intelligence while preserving privacy in
                 next-generation networks. Our work covers practical
                 applications across intelligent smart agriculture,
                 energy management, healthcare, and industrial
                 monitoring within network infrastructures, highlighting
                 domain-specific challenges and emerging solutions. We
                 analyze specialized hardware architectures, cloud
                 offloading strategies, and distributed learning
                 approaches that enable intelligent edge computing in
                 heterogeneous network environments. The survey
                 identifies critical research gaps in multimodal model
                 deployment, streaming learning under concept drift, and
                 integration of soft computing techniques with
                 intelligent edge orchestration frameworks for network
                 applications. These gaps directly manifest as open
                 challenges in balancing computational efficiency with
                 model robustness due to limited multimodal optimization
                 techniques, developing sustainable intelligent edge AI
                 systems arising from inadequate streaming learning
                 adaptation, and creating adaptive network applications
                 for dynamic environments resulting from insufficient
                 soft computing integration. This comprehensive roadmap
                 synthesizes current intelligent edge machine learning
                 solutions with emerging soft computing approaches,
                 providing researchers and practitioners with insights
                 for developing next-generation intelligent edge
                 computing systems that leverage machine learning
                 capabilities in distributed network infrastructures.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Beuter:2025:PDK,
  author =       "Niklas Beuter and Andr{\'e} Drews and Nane Kratzke",
  title =        "Prompt-Driven and {Kubernetes} Error Report-Aware
                 Container Orchestration",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "416",
  day =          "11",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090416",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/416",
  abstract =     "Background: Container orchestration systems like
                 Kubernetes rely heavily on declarative manifest files,
                 which serve as orchestration blueprints. However,
                 managing these manifest files is often complex and
                 requires substantial DevOps expertise. Methodology:
                 This study investigates the use of Large Language
                 Models (LLMs) to automate the creation of Kubernetes
                 manifest files from natural language specifications,
                 utilizing prompt engineering techniques within an
                 innovative error- and warning-report--aware refinement
                 process. We assess the capabilities of these LLMs using
                 Zero-Shot, Few-Shot, Prompt-Chaining, and Self-Refine
                 methods to address DevOps needs and support fully
                 automated deployment pipelines. Results: Our findings
                 show that LLMs can generate Kubernetes manifests with
                 varying levels of manual intervention. Notably, GPT-4
                 and GPT-3.5 demonstrate strong potential for deployment
                 automation. Interestingly, smaller models sometimes
                 outperform larger ones, challenging the assumption that
                 larger models always yield better results. Conclusions:
                 This research highlights the crucial impact of prompt
                 engineering on LLM performance for Kubernetes tasks and
                 recommends further exploration of prompt techniques and
                 model comparisons, outlining a promising path for
                 integrating LLMs into automated deployment workflows.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Karthick:2025:TSS,
  author =       "Gayathri Karthick and Glenford Mapp and Jon
                 Crowcroft",
  title =        "Toward Secure {SDN} Infrastructure in Smart Cities:
                 {Kafka}-Enabled Machine Learning Framework for Anomaly
                 Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "415",
  day =          "11",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090415",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/415",
  abstract =     "As smart cities evolve, the demand for real-time,
                 secure, and adaptive network monitoring, continues to
                 grow. Software-Defined Networking (SDN) offers a
                 centralized approach to managing network flows;
                 However, anomaly detection within SDN environments
                 remains a significant challenge, particularly at the
                 intelligent edge. This paper presents a conceptual
                 Kafka-enabled ML framework for scalable, real-time
                 analytics in SDN environments, supported by offline
                 evaluation and a prototype streaming demonstration. A
                 range of supervised ML models covering traditional
                 methods and ensemble approaches (Random Forest, Linear
                 Regression \& XGBoost) were trained and validated using
                 the InSDN intrusion detection dataset. These models
                 were tested against multiple cyber threats, including
                 botnets, dos, ddos, network reconnaissance, brute
                 force, and web attacks, achieving up to 99\% accuracy
                 for ensemble classifiers under offline conditions. A
                 Dockerized prototype demonstrates Kafka's role in
                 offline data ingestion, processing, and visualization
                 through PostgreSQL and Grafana. While full ML pipeline
                 integration into Kafka remains part of future work, the
                 proposed architecture establishes a foundation for
                 secure and intelligent Software-Defined Vehicular
                 Networking (SDVN) infrastructure in smart cities.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Yu:2025:GED,
  author =       "Hui-Hung Yu and Wei-Tsun Lin and Chih-Wei Kuan and
                 Chao-Chi Yang and Kuan-Min Liao",
  title =        "{GraphRAG}-Enhanced Dialogue Engine for
                 Domain-Specific Question Answering: a Case Study on the
                 Civil {IoT} {Taiwan} Platform",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "414",
  day =          "10",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090414",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/414",
  abstract =     "The proliferation of sensor technology has led to an
                 explosion in data volume, making the retrieval of
                 specific information from large repositories
                 increasingly challenging. While Retrieval-Augmented
                 Generation (RAG) can enhance Large Language Models
                 (LLMs), they often lack precision in specialized
                 domains. Taking the Civil IoT Taiwan Data Service
                 Platform as a case study, this study addresses this gap
                 by developing a dialogue engine enhanced with a
                 GraphRAG framework, aiming to provide accurate,
                 context-aware responses to user queries. Our method
                 involves constructing a domain-specific knowledge graph
                 by extracting entities (e.g., `Dataset', `Agency') and
                 their relationships from the platform's documentation.
                 For query processing, the system interprets natural
                 language inputs, identifies corresponding paths within
                 the knowledge graph, and employs a recursive
                 self-reflection mechanism to ensure the final answer
                 aligns with the user's intent. The final answer
                 transformed into natural language by utilizing the
                 TAIDE (Trustworthy AI Dialogue Engine) model. The
                 implemented framework successfully translates complex,
                 multi-constraint questions into executable graph
                 queries, moving beyond keyword matching to navigate
                 semantic pathways. This results in highly accurate and
                 verifiable answers grounded in the source data. In
                 conclusion, this research validates that applying a
                 GraphRAG-enhanced engine is a robust solution for
                 building intelligent dialogue systems for specialized
                 data platforms, significantly improving the precision
                 and usability of information retrieval and offering a
                 replicable model for other knowledge-intensive
                 domains.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Nakamura:2025:IGD,
  author =       "Atomu Nakamura and Homari Matsumoto and Koharu Chiba
                 and Shun Nishide",
  title =        "Improved Generation of Drawing Sequences Using
                 Variational and Skip-Connected Deep Networks for a
                 Drawing Support System",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "413",
  day =          "10",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090413",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/413",
  abstract =     "This study presents a deep generative model designed
                 to predict intermediate stages in the drawing process
                 of character illustrations. To enhance generalization
                 and robustness, the model integrates a variational
                 bottleneck based on the Variational Autoencoder (VAE)
                 and employs Gaussian noise augmentation during
                 training. We also investigate the effect of U-Net-style
                 skip connections, which allow for the direct
                 propagation of low-level features, on autoregressive
                 sequence generation. Comparative experiments with
                 baseline models demonstrate that the proposed VAE with
                 noise augmentation outperforms both CNN- and RNN-based
                 baselines in long-term stability and visual fidelity.
                 While skip connections improve local detail retention,
                 they also introduce instability in extended sequences,
                 suggesting a trade-off between spatial precision and
                 temporal coherence. The findings highlight the
                 advantages of probabilistic modeling and data
                 augmentation for sequential image generation and
                 provide practical insights for designing intelligent
                 drawing support systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fachada:2025:GSS,
  author =       "Nuno Fachada and Daniel Fernandes and Carlos M.
                 Fernandes and Bruno D. Ferreira-Saraiva and Jo{\~a}o P.
                 Matos-Carvalho",
  title =        "{GPT-4.1} Sets the Standard in Automated Experiment
                 Design Using Novel {Python} Libraries",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "412",
  day =          "8",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090412",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib;
                 https://www.math.utah.edu/pub/tex/bib/python.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/412",
  abstract =     "Large language models (LLMs) have advanced rapidly as
                 tools for automating code generation in scientific
                 research, yet their ability to interpret and use
                 unfamiliar Python APIs for complex computational
                 experiments remains poorly characterized. This study
                 systematically benchmarks a selection of
                 state-of-the-art LLMs in generating functional Python
                 code for two increasingly challenging scenarios:
                 conversational data analysis with the ParShift library,
                 and synthetic data generation and clustering using
                 pyclugen and scikit-learn. Both experiments use
                 structured, zero-shot prompts specifying detailed
                 requirements but omitting in-context examples. Model
                 outputs are evaluated quantitatively for functional
                 correctness and prompt compliance over multiple runs,
                 and qualitatively by analyzing the errors produced when
                 code execution fails. Results show that only a small
                 subset of models consistently generate correct,
                 executable code. GPT-4.1 achieved a 100\% success rate
                 across all runs in both experimental tasks, whereas
                 most other models succeeded in fewer than half of the
                 runs, with only Grok-3 and Mistral-Large approaching
                 comparable performance. In addition to benchmarking LLM
                 performance, this approach helps identify shortcomings
                 in third-party libraries, such as unclear documentation
                 or obscure implementation bugs. Overall, these findings
                 highlight current limitations of LLMs for end-to-end
                 scientific automation and emphasize the need for
                 careful prompt design, comprehensive library
                 documentation, and continued advances in language model
                 capabilities.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Luo:2025:DMI,
  author =       "Yu-Yong Luo and Yu-Hsun Chiu and Chia-Hsin Cheng",
  title =        "Detection and Mitigation in {IoT} Ecosystems Using
                 {oneM2M} Architecture and Edge-Based Machine Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "411",
  day =          "8",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090411",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/411",
  abstract =     "Distributed denial-of-service (DDoS) attacks are a
                 prevalent threat to resource-constrained IoT
                 deployments. We present an edge-based detection and
                 mitigation system integrated with the oneM2M
                 architecture. By using a Raspberry Pi 4 client and five
                 Raspberry Pi 3 attack nodes in a smart-home testbed, we
                 collected 200,000 packets with 19 features across four
                 traffic states (normal, SYN/UDP/ICMP floods), trained
                 Decision Tree, 2D-CNN, and LSTM models, and deployed
                 the best model on an edge computer for real-time
                 inference. The edge node classifies traffic and
                 triggers per-attack defenses on the device (SYN
                 cookies, UDP/ICMP iptables rules). On a held-out test
                 set, the 2D-CNN achieved 98.45\% accuracy,
                 outperforming the LSTM (96.14\%) and Decision Tree
                 (93.77\%). In end-to-end trials, the system sustained
                 service during SYN floods (time to capture 200 packets
                 increased from 5.05 s to 5.51 s after enabling SYN
                 cookies), mitigated ICMP floods via rate limiting, and
                 flagged UDP floods for administrator intervention due
                 to residual performance degradation. These results show
                 that lightweight, edge-deployed learning with targeted
                 controls can harden oneM2M-based IoT systems against
                 common DDoS vectors.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{urRahman:2025:FBM,
  author =       "Waqas ur Rahman",
  title =        "Fuzzy-Based {MEC}-Assisted Video Adaptation Framework
                 for {HTTP} Adaptive Streaming",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "410",
  day =          "8",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090410",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/410",
  abstract =     "As the demand for high-quality video streaming
                 applications continues to rise, multi-access edge
                 computing (MEC)-assisted streaming schemes have emerged
                 as a viable solution within the context of HTTP
                 adaptive streaming (HAS). These schemes aim to enhance
                 both quality of experience (QoE) and utilization of
                 network resources. HAS faces a significant challenge
                 when applied to mobile cellular networks. Designing a
                 HAS scheme that fairly allocates bitrates to users
                 ensures a high QoE and optimizes bandwidth utilization
                 remains a challenge. To this end, we designed an MEC-
                 and client-assisted adaptation framework for HAS,
                 facilitating collaboration between the edge and client
                 to enhance users' quality of experience. The proposed
                 framework employs fuzzy logic at the user end to
                 determine the upper limit for the video streaming rate.
                 On the MEC side, we developed an integer nonlinear
                 programming (INLP) optimization model that collectively
                 enhances the QoE of video clients by considering the
                 upper limit set by the client. Due to the NP-hardness
                 of the problem, we utilized a greedy algorithm to
                 efficiently solve the quality adaptation optimization
                 problem. The results demonstrate that the proposed
                 framework, on average, (i) improves users' QoE by 30\%,
                 (ii) achieves a fair allocation of bitrates by 22.6\%,
                 and (iii) enhances network utilization by 4.2\%
                 compared to state-of-the-art approaches. In addition,
                 the proposed approach prevents playback interruptions
                 regardless of the client's buffer size and video
                 segment duration.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tom:2025:SFL,
  author =       "Abin Kumbalapalliyil Tom and Ansam Khraisat and Tony
                 Jan and Md Whaiduzzaman and Thien D. Nguyen and Ammar
                 Alazab",
  title =        "Survey of Federated Learning for Cyber Threat
                 Intelligence in {Industrial IoT}: Techniques,
                 Applications and Deployment Models",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "409",
  day =          "8",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090409",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/409",
  abstract =     "The Industrial Internet of Things (IIoT) is
                 transforming industrial operations through connected
                 devices and real-time automation but also introduces
                 significant cybersecurity risks. Cyber threat
                 intelligence (CTI) is critical for detecting and
                 mitigating such threats, yet traditional centralized
                 CTI approaches face limitations in latency,
                 scalability, and data privacy. Federated learning (FL)
                 offers a privacy-preserving alternative by enabling
                 decentralized model training without sharing raw data.
                 This survey explores how FL can enhance CTI in IIoT
                 environments. It reviews FL architectures,
                 orchestration strategies, and aggregation methods, and
                 maps their applications to domains such as intrusion
                 detection, malware analysis, botnet mitigation, anomaly
                 detection, and trust management. Among its
                 contributions is an empirical synthesis comparing FL
                 aggregation strategies---including FedAvg, FedProx,
                 Krum, ClippedAvg, and Multi-Krum---across accuracy,
                 robustness, and efficiency under IIoT constraints. The
                 paper also presents a taxonomy of FL-based CTI
                 approaches and outlines future research directions to
                 support the development of secure, scalable, and
                 decentralized threat intelligence systems for
                 industrial ecosystems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Andronikos:2025:GBP,
  author =       "Theodore Andronikos and Constantinos Bitsakos and
                 Konstantinos Nikas and Georgios I. Goumas and Nectarios
                 Koziris",
  title =        "A {GHZ}-Based Protocol for the Dining Information
                 Brokers Problem",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "408",
  day =          "6",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090408",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/408",
  abstract =     "This article introduces the innovative Quantum Dining
                 Information Brokers Problem, presenting a novel
                 entanglement-based quantum protocol to address it. The
                 scenario involves n information brokers, all located in
                 distinct geographical regions, engaging in a
                 metaphorical virtual dinner. The objective is for each
                 broker to share a unique piece of information with all
                 the others simultaneously. Unlike previous approaches,
                 this protocol enables a fully parallel, single-step
                 communication exchange among all the brokers,
                 regardless of their physical locations. A key feature
                 of this protocol is its ability to ensure that both the
                 anonymity and privacy of all the participants are
                 preserved, meaning that no broker can discern the
                 identity of the sender of any received information. At
                 its core, the Quantum Dining Information Brokers
                 Problem serves as a conceptual framework for achieving
                 anonymous, untraceable, and massively parallel
                 information exchange in a distributed system. The
                 proposed protocol introduces three significant
                 advancements. First, while quantum protocols for
                 one-to-many simultaneous information transmission have
                 been developed, this is, to the best of our knowledge,
                 one of the first quantum protocols to facilitate
                 many-to-many simultaneous information exchange. Second,
                 it guarantees complete anonymity and untraceability for
                 all senders, a critical improvement over sequential
                 applications of one-to-many protocols, which fail to
                 ensure such robust anonymity. Third, leveraging quantum
                 entanglement, the protocol operates in a fully
                 distributed manner, accommodating brokers in diverse
                 spatial locations. This approach marks a substantial
                 advancement in secure, scalable, and anonymous
                 communication, with potential applications in
                 distributed environments where privacy and parallelism
                 are paramount.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Triantafyllopoulos:2025:DAE,
  author =       "Loukas Triantafyllopoulos and Dimitris Kalles",
  title =        "From Divergence to Alignment: Evaluating the Role of
                 Large Language Models in Facilitating Agreement Through
                 Adaptive Strategies",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "407",
  day =          "6",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090407",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/407",
  abstract =     "Achieving consensus in group decision-making often
                 involves overcoming significant challenges,
                 particularly reconciling diverse perspectives and
                 mitigating biases hindering agreement. Traditional
                 methods relying on human facilitators are usually
                 constrained by scalability and efficiency, especially
                 in large-scale, fast-paced discussions. To address
                 these challenges, this study proposes a novel real-time
                 facilitation framework, employing large language models
                 (LLMs) as automated facilitators within a custom-built
                 multi-user chat system. This framework is distinguished
                 by its real-time adaptive system architecture, which
                 enables dynamic adjustments to facilitation strategies
                 based on ongoing discussion dynamics. Leveraging cosine
                 similarity as a core metric, this approach evaluates
                 the ability of three state-of-the-art LLMs---ChatGPT
                 4.0, Mistral Large 2, and AI21 Jamba-Instruct---to
                 synthesize consensus proposals that align with
                 participants' viewpoints. Unlike conventional
                 techniques, the system integrates adaptive facilitation
                 strategies, including clarifying misunderstandings,
                 summarizing discussions, and proposing compromises,
                 enabling the LLMs to refine consensus proposals based
                 on user feedback iteratively. Experimental results
                 indicate that ChatGPT 4.0 achieved the highest
                 alignment with participant opinions and required fewer
                 iterations to reach consensus. A one-way ANOVA
                 confirmed that differences in performance between
                 models were statistically significant. Moreover,
                 descriptive analyses revealed nuanced differences in
                 model behavior across various sustainability-focused
                 discussion topics, including climate action, quality
                 education, good health and well-being, and access to
                 clean water and sanitation. These findings highlight
                 the promise of LLM-driven facilitation for improving
                 collective decision-making processes and underscore the
                 need for further research into robust evaluation
                 metrics, ethical considerations, and cross-cultural
                 adaptability.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ma:2025:SPP,
  author =       "Junxia Ma and Zixu Yang and Ming Chen",
  title =        "{3D} Spatial Path Planning Based on Improved Particle
                 Swarm Optimization",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "406",
  day =          "5",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090406",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/406",
  abstract =     "Three-dimensional path planning is critical for the
                 successful operation of unmanned aerial vehicles
                 (UAVs), automated guided vehicles (AGVs), and robots in
                 industrial Internet of Things (IIoT) applications. In
                 3D path planning, the standard Particle Swarm
                 Optimization (PSO) algorithm suffers from premature
                 convergence and a tendency to fall into local optima,
                 leading to significant deviations from the optimal
                 path. This paper proposes an improved PSO (IPSO)
                 algorithm that enhances particle diversity and
                 randomness through the introduction of logistic chaotic
                 mapping, while employing dynamic learning factors and
                 nonlinear inertia weights to improve global search
                 capability. Experimental results demonstrate that IPSO
                 outperforms traditional methods in terms of path length
                 and computational efficiency, showing potential for
                 real-time path planning in complex environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Osman:2025:CBP,
  author =       "Radwa Ahmed Osman",
  title =        "{1D-CNN}-Based Performance Prediction in {IRS}-Enabled
                 {IoT} Networks for {6G} Autonomous Vehicle
                 Applications",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "405",
  day =          "5",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090405",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/405",
  abstract =     "To foster the performance of wireless communication
                 while saving energy, the integration of Intelligent
                 Reflecting Surfaces (IRS) into autonomous vehicle (AV)
                 communication networks is considered a powerful
                 technique. This paper proposes a novel IRS-assisted
                 vehicular communication model that combines Lagrange
                 optimization and Gradient-Based Phase Optimization to
                 determine the optimal transmission power, optimal
                 interference transmission power, and IRS phase shifts.
                 Additionally, the proposed model help increase the
                 Signal-to-Interference-plus-Noise Ratio (SINR) by
                 utilizing IRS, which leads to maximizes energy
                 efficiency and the achievable data rate under a variety
                 of environmental conditions, while guaranteeing that
                 resource limits are satisfied. In order to represent
                 dense vehicular environments, practical constraints for
                 the system model, such as IRS reflection efficiency and
                 interference, have been incorporated from multiple
                 sources, namely, Device-to-Device (D2D),
                 Vehicle-to-Vehicle (V2V), Vehicle-to-Base Station
                 (V2B), and Cellular User Equipment (CUE). A Lagrangian
                 optimization approach has been implemented to determine
                 the required transmission interference power and the
                 best IRS phase designs in order to enhance the system
                 performance. Consequently, a one-dimensional
                 convolutional neural network has been implemented for
                 the optimized data provided by this framework as
                 training input. This deep learning algorithm learns to
                 predict the required optimal IRS settings quickly,
                 allowing for real-time adaptation in dynamic wireless
                 environments. The obtained results from the simulation
                 show that the combined optimization and prediction
                 strategy considerably enhances the system reliability
                 and energy efficiency over baseline techniques. This
                 study lays a solid foundation for implementing
                 IRS-assisted AV networks in real-world settings, hence
                 facilitating the development of next-generation
                 vehicular communication systems that are both
                 performance-driven and energy-efficient.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bandi:2025:RAA,
  author =       "Ajay Bandi and Bhavani Kongari and Roshini Naguru and
                 Sahitya Pasnoor and Sri Vidya Vilipala",
  title =        "The Rise of Agentic {AI}: a Review of Definitions,
                 Frameworks, Architectures, Applications, Evaluation
                 Metrics, and Challenges",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "404",
  day =          "4",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090404",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/404",
  abstract =     "Agentic AI systems are a recently emerged and
                 important approach that goes beyond traditional AI,
                 generative AI, and autonomous systems by focusing on
                 autonomy, adaptability, and goal-driven reasoning. This
                 study provides a clear review of agentic AI systems by
                 bringing together their definitions, frameworks, and
                 architectures, and by comparing them with related areas
                 like generative AI, autonomic computing, and
                 multi-agent systems. To do this, we reviewed 143
                 primary studies on current LLM-based and non-LLM-driven
                 agentic systems and examined how they support planning,
                 memory, reflection, and goal pursuit. Furthermore, we
                 classified architectural models, input--output
                 mechanisms, and applications based on their task
                 domains where agentic AI is applied, supported using
                 tabular summaries that highlight real-world case
                 studies. Evaluation metrics were classified as
                 qualitative and quantitative measures, along with
                 available testing methods of agentic AI systems to
                 check the system's performance and reliability. This
                 study also highlights the main challenges and
                 limitations of agentic AI, covering technical,
                 architectural, coordination, ethical, and security
                 issues. We organized the conceptual foundations,
                 available tools, architectures, and evaluation metrics
                 in this research, which defines a structured foundation
                 for understanding and advancing agentic AI. These
                 findings aim to help researchers and developers build
                 better, clearer, and more adaptable systems that
                 support responsible deployment in different domains.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Xin:2025:CSB,
  author =       "Ran Xin and Yapeng Wang and Xiaohong Huang and Xu Yang
                 and Sio Kei Im",
  title =        "Cell-Sequence-Based Covert Signal for {Tor}
                 De-Anonymization Attacks",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "403",
  day =          "4",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090403",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/403",
  abstract =     "This research introduces a novel de-anonymization
                 technique targeting the Tor network, addressing
                 limitations in prior attack models, particularly
                 concerning router positioning following the
                 introduction of bridge relays. Our method exploits two
                 specific, inherent protocol-level vulnerabilities: the
                 absence of a continuity check for circuit-level cells
                 and anomalous residual values in RELAY\_EARLY cell
                 counters, working by manipulating cell headers to embed
                 a covert signal. This signal is composed of reserved
                 fields, start and end delimiters, and a payload that
                 encodes target identifiers. Using this signal,
                 malicious routers can effectively mark data flows for
                 later identification. These routers employ a finite
                 state machine (FSM) to adaptively switch between signal
                 injection and detection. Experimental evaluations,
                 conducted within a controlled environment using
                 attacker-controlled onion routers, demonstrated that
                 the embedded signals are undetectable by standard Tor
                 routers, cause no noticeable performance degradation,
                 and allow reliable correlation of Tor users with public
                 services and deanonymization of hidden service IP
                 addresses. This work reveals a fundamental design
                 trade-off in Tor: the decision to conceal circuit
                 length inadvertently exposes cell transmission
                 characteristics. This creates a bidirectional vector
                 for stealthy, protocol-level de-anonymization attacks,
                 even though Tor payloads remain encrypted.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Shaji:2025:DRM,
  author =       "Krishnapriya V. Shaji and Srilakshmi S. Rethy and Simi
                 Surendran and Livya George and Namita Suresh and
                 Hrishika Dayan",
  title =        "Dynamic Resource Management in {5G}-Enabled Smart
                 Elderly Care Using Deep Reinforcement Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "9",
  pages =        "402",
  day =          "2",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17090402",
  ISSN =         "1999-5903",
  bibdate =      "Thu Oct 2 09:27:56 MDT 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/9/402",
  abstract =     "The increasing elderly population presents major
                 challenges to traditional healthcare due to the need
                 for continuous care, a shortage of skilled
                 professionals, and increasing medical costs. To address
                 this, smart elderly care homes where multiple residents
                 live with the support of caregivers and IoT-based
                 assistive technologies have emerged as a promising
                 solution. For their effective operation, a reliable
                 high speed network like 5G is essential, along with
                 intelligent resource allocation to ensure efficient
                 service delivery. This study proposes a deep
                 reinforcement learning (DRL)-based resource management
                 framework for smart elderly homes, formulated as a
                 Markov decision process. The framework dynamically
                 allocates computing and network resources in response
                 to real-time application demands and system
                 constraints. We implement and compare two DRL
                 algorithms, emphasizing their strengths in optimizing
                 edge utilization and throughput. System performance is
                 evaluated across balanced, high-demand, and
                 resource-constrained scenarios. The results demonstrate
                 that the proposed DRL approach effectively learns
                 adaptive resource management policies, making it a
                 promising solution for next-generation intelligent
                 elderly care environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Morsidi:2025:RBS,
  author =       "Mahran Morsidi and Sharul Tajuddin and S. H. Shah
                 Newaz and Ravi Kumar Patchmuthu and Gyu Myoung Lee",
  title =        "A Review on Blockchain Sharding for Improving
                 Scalability",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "481",
  day =          "21",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100481",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/481",
  abstract =     "Blockchain technology, originally designed as a secure
                 and immutable ledger, has expanded its applications
                 across various domains. However, its scalability
                 remains a fundamental bottleneck, limiting throughput,
                 specifically Transactions Per Second (TPS) and
                 increasing confirmation latency. Among the many
                 proposed solutions, sharding has emerged as a promising
                 Layer 1 approach by partitioning blockchain networks
                 into smaller, parallelized components, significantly
                 enhancing processing efficiency while maintaining
                 decentralization and security. In this paper, we have
                 conducted a systematic literature review, resulting in
                 a comprehensive review of sharding. We provide a
                 detailed comparative analysis of various sharding
                 approaches and emerging AI-assisted sharding
                 approaches, assessing their effectiveness in improving
                 TPS and reducing latency. Notably, our review is the
                 first to incorporate and examine the standardization
                 efforts of the ITU-T and ETSI, with a particular focus
                 on activities related to blockchain sharding.
                 Integrating these standardization activities allows us
                 to bridge the gap between academic research and
                 practical standardization in blockchain sharding,
                 thereby enhancing the relevance and applicability of
                 our review. Additionally, we highlight the existing
                 research gaps, discuss critical challenges such as
                 security risks and inter-shard communication
                 inefficiencies, and provide insightful future research
                 directions. Our work serves as a foundational reference
                 for researchers and practitioners aiming to optimize
                 blockchain scalability through sharding, contributing
                 to the development of more efficient, secure, and
                 high-performance decentralized networks. Our
                 comparative synthesis further highlights that while
                 Bitcoin and Ethereum remain limited to 7-15 TPS with
                 long confirmation delays, sharding-based systems such
                 as Elastico and OmniLedger have reported significant
                 throughput improvements, demonstrating sharding's clear
                 advantage over traditional Layer 1 enhancements. In
                 contrast to other state-of-the-art scalability
                 techniques such as block size modification, consensus
                 optimization, and DAG-based architectures, sharding
                 consistently achieves higher transaction throughput and
                 lower latency, indicating its position as one of the
                 most effective Layer 1 solutions for improving
                 blockchain scalability.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chevaphatrakul:2025:MMB,
  author =       "Thananont Chevaphatrakul and Han Wang and Sukhpal
                 Singh Gill",
  title =        "{MambaNet0}: {Mamba}-Based Sustainable Cloud Resource
                 Prediction Framework Towards Net Zero Goals",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "480",
  day =          "21",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100480",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/480",
  abstract =     "With the ever-growing reliance on cloud computing,
                 efficient resource allocation is crucial for maximising
                 the effective use of provisioned resources from cloud
                 service providers. Proactive resource management is
                 therefore critical for minimising costs and striving
                 for net zero emission goals. One of the most promising
                 methods involves the use of Artificial Intelligence
                 (AI) techniques to analyse and predict resource demand,
                 such as cloud CPU utilisation. This paper presents
                 MambaNet0, a Mamba-based cloud resource prediction
                 framework. The model is implemented on Google's Vertex
                 AI workbench and uses the real-world Bitbrains Grid
                 Workload Archive-T-12 dataset, which contains the
                 resource usage metrics of 1750 virtual machines. The
                 Mamba model's performance is then evaluated against
                 established baseline models, including Autoregressive
                 Integrated Moving Average (ARIMA), Long Short-Term
                 Memory (LSTM), and Amazon Chronos, to demonstrate its
                 potential for accurate prediction of CPU utilisation.
                 The MambaNet0 model achieved a 29\% improvement in
                 Symmetric Mean Absolute Percentage Error (SMAPE)
                 compared to the best-performing baseline Amazon
                 Chronos. These findings reinforce the Mamba model's
                 ability to forecast accurate CPU utilisation,
                 highlighting its potential for optimising cloud
                 resource allocation in contribution to net zero
                 goals.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wu:2025:PAK,
  author =       "Jing Wu and Yaoyi Cai",
  title =        "The Paradox of {AI} Knowledge: a Blockchain-Based
                 Approach to Decentralized Governance in {Chinese} New
                 Media Industry",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "479",
  day =          "20",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100479",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/479",
  abstract =     "AI text-to-video systems, such as OpenAI's Sora,
                 promise substantial efficiency gains in media
                 production but also pose risks of biased outputs,
                 opaque optimization, and deceptive content. Using the
                 Orientation-Stimulus-Orientation-Response (O-S-O-R)
                 model, we conduct an empirical study with 209 Chinese
                 new media professionals and employ structural equation
                 modeling to examine how information elaboration relates
                 to AI knowledge, perceptions, and adoption intentions.
                 Our findings reveal a knowledge paradox: higher
                 objective AI knowledge negatively moderates
                 elaboration, suggesting that centralized information
                 ecosystems can misguide even well-informed
                 practitioners. Building on these behavioral insights,
                 we propose a blockchain-based governance framework that
                 operationalizes five mechanisms to enhance oversight
                 and trust while maintaining efficiency: Expert
                 Assessment DAOs, Community Validation DAOs, real-time
                 algorithm monitoring, professional integrity
                 protection, and cross-border coordination. While our
                 study focuses on China's substantial new media market,
                 the observed patterns and design principles generalize
                 to global contexts. This work contributes empirical
                 grounding for Web3-enabled AI governance, specifies
                 implementable smart-contract patterns for
                 multi-stakeholder validation and incentives, and
                 outlines a research agenda spanning longitudinal,
                 cross-cultural, and implementation studies.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rotuna:2025:TPD,
  author =       "Carmen Ionela Rotuna and Ioan Stefan Sacala and
                 Adriana Alexandru",
  title =        "Towards Proactive Domain Name Security: an Adaptive
                 System for {\tt .r}o domains Reputation Analysis",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "478",
  day =          "18",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100478",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/478",
  abstract =     "In a digital landscape marked by the exponential
                 growth of cyber threats, the development of automated
                 domain reputation systems is extremely important.
                 Emerging technologies such as artificial intelligence
                 and machine learning now enable proactive and scalable
                 approaches to early identification of malicious or
                 suspicious domains. This paper presents an adaptive
                 domain name reputation system that integrates advanced
                 machine learning to enhance cybersecurity resilience.
                 The proposed framework uses domain data from .ro domain
                 Registry and several other sources (blacklists,
                 whitelists, DNS, SSL certificate), detects anomalies
                 using machine learning techniques, and scores domain
                 security risk levels. A supervised XGBoost model is
                 trained and assessed through five-fold stratified
                 cross-validation and a held-out 80/20 split. On an
                 example dataset of 25,000 domains, the system attains
                 accuracy 0.993 and F1 0.993 and is exposed through a
                 lightweight Flask service that performs asynchronous
                 feature collection for near real-time scoring. The
                 contribution is a blueprint that links list supervision
                 with registry/DNS/TLS features and deployable inference
                 to support proactive domain abuse mitigation in ccTLD
                 environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Sokhansanj:2025:UAW,
  author =       "Bahrad A. Sokhansanj",
  title =        "Uncensored {AI} in the Wild: Tracking Publicly
                 Available and Locally Deployable {LLMs}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "477",
  day =          "18",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100477",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/477",
  abstract =     "Open-weight generative large language models (LLMs)
                 can be freely downloaded and modified. Yet, little
                 empirical evidence exists on how these models are
                 systematically altered and redistributed. This study
                 provides a large-scale empirical analysis of
                 safety-modified open-weight LLMs, drawing on 8608 model
                 repositories and evaluating 20 representative modified
                 models on unsafe prompts designed to elicit, for
                 example, election disinformation, criminal instruction,
                 and regulatory evasion. This study demonstrates that
                 modified models exhibit substantially higher
                 compliance: while an average of unmodified models
                 complied with only 19.2\% of unsafe requests, modified
                 variants complied at an average rate of 80.0\%.
                 Modification effectiveness was independent of model
                 size, with smaller, 14-billion-parameter variants
                 sometimes matching or exceeding the compliance levels
                 of 70B parameter versions. The ecosystem is highly
                 concentrated yet structurally decentralized; for
                 example, the top 5\% of providers account for over 60\%
                 of downloads and the top 20 for nearly 86\%. Moreover,
                 more than half of the identified models use GGUF
                 packaging, optimized for consumer hardware, and 4-bit
                 quantization methods proliferate widely, though
                 full-precision and lossless 16-bit models remain the
                 most downloaded. These findings demonstrate how locally
                 deployable, modified LLMs represent a paradigm shift
                 for Internet safety governance, calling for new
                 regulatory approaches suited to decentralized AI.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Iznaga:2025:ILL,
  author =       "Yanet S{\'a}ez Iznaga and Lu{\'\i}s Rato and Pedro
                 Salgueiro and Javier Lamar Le{\'o}n",
  title =        "Integrating Large Language Models into Automated
                 Software Testing",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "476",
  day =          "18",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100476",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/476",
  abstract =     "This work investigates the use of LLMs to enhance
                 automation in software testing, with a particular focus
                 on generating high-quality, context-aware test scripts
                 from natural language descriptions, while addressing
                 both text-to-code and text+code-to-code generation
                 tasks. The Codestral Mamba model was fine-tuned by
                 proposing a way to integrate LoRA matrices into its
                 architecture, enabling efficient domain-specific
                 adaptation and positioning Mamba as a viable
                 alternative to Transformer-based models. The model was
                 trained and evaluated on two benchmark datasets:
                 CONCODE/CodeXGLUE and the proprietary TestCase2Code
                 dataset. Through structured prompt engineering, the
                 system was optimized to generate syntactically valid
                 and semantically meaningful code for test cases.
                 Experimental results demonstrate that the proposed
                 methodology successfully enables the automatic
                 generation of code-based test cases using large
                 language models. In addition, this work reports
                 secondary benefits, including improvements in test
                 coverage, automation efficiency, and defect detection
                 when compared to traditional manual approaches. The
                 integration of LLMs into the software testing pipeline
                 also showed potential for reducing time and cost while
                 enhancing developer productivity and software quality.
                 The findings suggest that LLM-driven approaches can be
                 effectively aligned with continuous integration and
                 deployment workflows. This work contributes to the
                 growing body of research on AI-assisted software
                 engineering and offers practical insights into the
                 capabilities and limitations of current LLM
                 technologies for testing automation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Asiri:2025:DFL,
  author =       "Mohammed Asiri and Maher A. Khemakhem and Reemah M.
                 Alhebshi and Bassma S. Alsulami and Fathy E. Eassa",
  title =        "Decentralized Federated Learning for {IoT} Malware
                 Detection at the Multi-Access Edge: a Two-Tier,
                 Privacy-Preserving Design",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "475",
  day =          "17",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100475",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/475",
  abstract =     "Botnet attacks on Internet of Things (IoT) devices are
                 escalating at the 5G/6G multi-access edge, yet most
                 federated learning frameworks for IoT malware detection
                 (FL-IMD) still hinge on a central aggregator, enlarging
                 the attack surface, weakening privacy, and creating a
                 single point of failure. We propose a two-tier, fully
                 decentralized FL architecture aligned with MEC's
                 Proximal Edge Server (PES)/Supplementary Edge Server
                 (SES) hierarchy. PES nodes train locally and encrypt
                 updates with the Cheon-Kim-Kim-Song (CKKS) scheme; SES
                 nodes verify ECDSA-signed provenance, homomorphically
                 aggregate ciphertexts, and finalize each round via an
                 Algorand-style committee that writes a compact,
                 tamper-evident record (update digests/URIs and a
                 global-model hash) to an append-only ledger. Using the
                 N-BaIoT benchmark with an unsupervised autoencoder, we
                 evaluate known-device and leave-one-device-out regimes
                 against a classical centralized baseline and a
                 cryptographically hardened but server-centric variant.
                 With the heavier CKKS profile, attack sensitivity is
                 preserved (TPR >=0.99 {$>$}=0.99 >=0.99 ), and
                 specificity (TNR) declines by only 0.20 percentage
                 points relative to plaintext in both regimes; a lighter
                 profile maintains TPR while trading 3.5-4.8 percentage
                 points of TNR for about 71\% smaller payloads.
                 Decentralization adds only a negligible per-round
                 overhead for committee finality, while homomorphic
                 aggregation dominates latency. Overall, our FL-IMD
                 design removes the trusted aggregator and provides
                 verifiable, ledger-backed provenance suitable for
                 trustless MEC deployments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Aich:2025:BSM,
  author =       "Nassim Aich and Zakarya Oubrahim and Hachem Ait
                 Talount and Ahmed Abbou",
  title =        "Bi-Scale {Mahalanobis} Detection for Reactive Jamming
                 in {UAV} {OFDM} Links",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "474",
  day =          "17",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100474",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/474",
  abstract =     "Reactive jamming remains a critical threat to
                 low-latency telemetry of Unmanned Aerial Vehicles
                 (UAVs) using Orthogonal Frequency Division Multiplexing
                 (OFDM). In this paper, a Bi-scale Mahalanobis approach
                 is proposed to detect and classify reactive jamming
                 attacks on UAVs; it jointly exploits window-level
                 energy and the Sevcik fractal dimension and employs
                 self-adapting thresholds to detect any drift in
                 additive white Gaussian noise (AWGN), fading effects,
                 or Radio Frequency (RF) gain. The simulations were
                 conducted on 5000 frames of OFDM signals, which were
                 distorted by Rayleigh fading, a \pm 10 kHz frequency
                 drift, and log-normal power shadowing. The simulation
                 results achieved a precision of 99.4\%, a recall of
                 100\%, an F1 score of 99.7\%, an area under the
                 receiver operating characteristic curve (AUC) of
                 0.9997, and a mean alarm latency of 80 $ \mu $ s. The
                 method used reinforces jam resilience in low-power
                 commercial UAVs, yet it needs no extra RF hardware and
                 avoids heavy deep learning computation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ateya:2025:QAQ,
  author =       "Abdelhamied A. Ateya and Nguyen Duc Tu and Ammar
                 Muthanna and Andrey Koucheryavy and Dmitry Kozyrev and
                 J{\'a}nos Sztrik",
  title =        "{QL-AODV}: {Q}-Learning-Enhanced Multi-Path Routing
                 Protocol for {6G}-Enabled Autonomous Aerial Vehicle
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "473",
  day =          "16",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100473",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/473",
  abstract =     "With the arrival of sixth-generation (6G) wireless
                 systems comes radical potential for the deployment of
                 autonomous aerial vehicle (AAV) swarms in
                 mission-critical applications, ranging from disaster
                 rescue to intelligent transportation. However,
                 6G-supporting AAV environments present challenges such
                 as dynamic three-dimensional topologies, highly
                 restrictive energy constraints, and extremely low
                 latency demands, which substantially degrade the
                 efficiency of conventional routing protocols. To this
                 end, this work presents a Q-learning-enhanced ad hoc
                 on-demand distance vector (QL-AODV). This intelligent
                 routing protocol uses reinforcement learning within the
                 AODV protocol to support adaptive, data-driven route
                 selection in highly dynamic aerial networks. QL-AODV
                 offers four novelties, including a multipath route set
                 collection methodology that retains up to ten candidate
                 routes for each destination using an extended route
                 reply (RREP) waiting mechanism, a more detailed RREP
                 message format with cumulative node buffer usage,
                 enabling informed decision-making, a normalized 3D
                 state space model recording hop count, average buffer
                 occupancy, and peak buffer saturation, optimized to
                 adhere to aerial network dynamics, and a light-weighted
                 distributed Q-learning approach at the source node that
                 uses an $ \epsilon $-greedy policy to balance
                 exploration and exploitation. Large-scale simulations
                 conducted with NS-3.34 for various node densities and
                 mobility conditions confirm the better performance of
                 QL-AODV compared to conventional AODV. In high-mobility
                 environments, QL-AODV offers up to 9.8\% improvement in
                 packet delivery ratio and up to 12.1\% increase in
                 throughput, while remaining persistently scalable for
                 various network sizes. The results prove that QL-AODV
                 is a reliable, scalable, and intelligent routing method
                 for next-generation AAV networks that will operate in
                 intensive environments that are expected for 6G.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Rajendran:2025:SAD,
  author =       "Mani Rajendran and Dharminder Chaudhary and S. A.
                 Lakshmanan and Cheng-Chi Lee",
  title =        "Security Analysis and Designing Advanced Two-Party
                 Lattice-Based Authenticated Key Establishment and Key
                 Transport Protocols for Mobile Communication",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "472",
  day =          "16",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100472",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/472",
  abstract =     "In this paper, we have proposed a two-party
                 authenticated key establishment (AKE), and
                 authenticated key transport protocols based on
                 lattice-based cryptography, aiming to provide security
                 against quantum attacks for secure communication. This
                 protocol enables two parties, who may share long-term
                 public keys, to securely establish a shared session
                 key, and transportation of the session key from the
                 server while achieving mutual authentication. Our
                 construction leverages the hardness of lattice problems
                 Ring Learning With Errors (Ring-LWE), ensuring
                 robustness against quantum and classical adversaries.
                 Unlike traditional schemes whose security depends upon
                 number-theoretic assumptions being vulnerable to
                 quantum attacks, our protocol ensures security in the
                 post-quantum era. The proposed protocol ensures forward
                 secrecy, and provides security even if the long-term
                 key is compromised. This protocol also provides
                 essential property key freshness and resistance against
                 man-in-the-middle attacks, impersonation attacks,
                 replay attacks, and key mismatch attacks. On the other
                 hand, the proposed key transport protocol provides
                 essential property key freshness, anonymity, and
                 resistance against man-in-the-middle attacks,
                 impersonation attacks, replay attacks, and key mismatch
                 attacks. A two-party key transport protocol is a
                 cryptographic protocol in which one party (typically a
                 trusted key distribution center or sender) securely
                 generates and sends a session key to another party.
                 Unlike key exchange protocols (where both parties
                 contribute to key generation), key transport protocols
                 rely on one party to generate the key and deliver it
                 securely. The protocol possesses a minimum number of
                 exchanged messages and can reduce the number of
                 communication rounds to help minimize the communication
                 overhead.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mushtaq:2025:EAB,
  author =       "Sameer Mushtaq and Marcello Trovati and Nik Bessis",
  title =        "Explainable {AI}-Based Semantic Retrieval from an
                 Expert-Curated Oncology Knowledge Graph for Clinical
                 Decision Support",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "471",
  day =          "16",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100471",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/471",
  abstract =     "The modern oncology landscape is characterised by a
                 deluge of high-dimensional data from genomic
                 sequencing, medical imaging, and electronic health
                 records, negatively impacting the analytical capacity
                 of clinicians and health practitioners. This field is
                 not new and it has drawn significant attention from the
                 research community. However, one of the main limiting
                 issues is the data itself. Despite the vast amount of
                 available data, most of it lacks scalability, quality,
                 and semantic information. This work is motivated by the
                 data platform provided by OncoProAI, an AI-driven
                 clinical decision support platform designed to address
                 this challenge by enabling highly personalised,
                 precision cancer care. The platform is built on a
                 comprehensive knowledge graph, formally modelled as a
                 directed acyclic graph, which has been manually
                 populated, assessed and maintained to provide a unique
                 data ecosystem. This enables targeted and bespoke
                 information extraction and assessment.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Drozdz:2025:MSD,
  author =       "Stanis{\l}aw Drozdz and Robert Kluszczy{\'n}ski and
                 Jaros{\l}aw Kwapie{\'n} and Marcin Watorek",
  title =        "Multifractality and Its Sources in the Digital
                 Currency Market",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "470",
  day =          "13",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100470",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/470",
  abstract =     "Multifractality in time series analysis characterizes
                 the presence of multiple scaling exponents, indicating
                 heterogeneous temporal structures and complex dynamical
                 behaviors beyond simple monofractal models. In the
                 context of digital currency markets, multifractal
                 properties arise due to the interplay of long-range
                 temporal correlations and heavy-tailed distributions of
                 returns, reflecting intricate market microstructure and
                 trader interactions. Incorporating multifractal
                 analysis into the modeling of cryptocurrency price
                 dynamics enhances the understanding of market
                 inefficiencies. It may also improve volatility
                 forecasting and facilitate the detection of critical
                 transitions or regime shifts. Based on the multifractal
                 cross-correlation analysis (MFCCA) whose spacial case
                 is the multifractal detrended fluctuation analysis
                 (MFDFA), as the most commonly used practical tools for
                 quantifying multifractality, we applied a recently
                 proposed method of disentangling sources of
                 multifractality in time series to the most
                 representative instruments from the digital market.
                 They include Bitcoin (BTC), Ethereum (ETH),
                 decentralized exchanges (DEX) and non-fungible tokens
                 (NFT). The results indicate the significant role of
                 heavy tails in generating a broad multifractal
                 spectrum. However, they also clearly demonstrate that
                 the primary source of multifractality encompasses the
                 temporal correlations in the series, and without them,
                 multifractality fades out. It appears characteristic
                 that these temporal correlations, to a large extent, do
                 not depend on the thickness of the tails of the
                 fluctuation distribution. These observations, made here
                 in the context of the digital currency market, provide
                 a further strong argument for the validity of the
                 proposed methodology of disentangling sources of
                 multifractality in time series.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Raposo:2025:MMA,
  author =       "Adriano N. Raposo and Vasco N. G. J. Soares",
  title =        "Modular Microservices Architecture for Generative
                 Music Integration in Digital Audio Workstations via
                 {VST} Plugin",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "469",
  day =          "12",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100469",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/469",
  abstract =     "This paper presents the design and implementation of a
                 modular cloud-based architecture that enables
                 generative music capabilities in Digital Audio
                 Workstations through a MIDI microservices backend and a
                 user-friendly VST plugin frontend. The system comprises
                 a generative harmony engine deployed as a standalone
                 service, a microservice layer that orchestrates
                 communication and exposes an API, and a VST plugin that
                 interacts with the backend to retrieve harmonic
                 sequences and MIDI data. Among the microservices is a
                 dedicated component that converts textual chord
                 sequences into MIDI files. The VST plugin allows the
                 user to drag and drop the generated chord progressions
                 directly into a DAW's MIDI track timeline. This
                 architecture prioritizes modularity, cloud scalability,
                 and seamless integration into existing music production
                 workflows, while abstracting away technical complexity
                 from end users. The proposed system demonstrates how
                 microservice-based design and cross-platform plugin
                 development can be effectively combined to support
                 generative music workflows, offering both researchers
                 and practitioners a replicable and extensible
                 framework.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Francuz:2025:ICA,
  author =       "{\'A}d{\'a}m Francuz and Tam{\'a}s B{\'a}nyai",
  title =        "Intelligent Control Approaches for Warehouse
                 Performance Optimisation in {Industry 4.0} Using
                 Machine Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "468",
  day =          "11",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100468",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/468",
  abstract =     "In conventional logistics optimization problems, an
                 objective function describes the relationship between
                 parameters. However, in many industrial practices, such
                 a relationship is unknown, and only observational data
                 is available. The objective of the research is to use
                 machine learning-based regression models to uncover
                 patterns in the warehousing dataset and use them to
                 generate an accurate objective function. The models are
                 not only suitable for prediction, but also for
                 interpreting the effect of input variables. This
                 data-driven approach is consistent with the automated,
                 intelligent systems of Industry 4.0, while Industry 5.0
                 provides opportunities for sustainable, flexible, and
                 collaborative development. In this research, machine
                 learning (ML) models were tested on a fictional dataset
                 using Automated Machine Learning (AutoML), through
                 which Light Gradient Boosting Machine (LightGBM) was
                 selected as the best method (R 2 = 0.994). Feature
                 Importance and Partial Dependence Plots revealed the
                 key factors influencing storage performance and their
                 functional relationships. Defining performance as a
                 cost indicator allowed us to interpret optimization as
                 cost minimization, demonstrating that ML-based methods
                 can uncover hidden patterns and support efficiency
                 improvements in warehousing. The proposed approach not
                 only achieves outstanding predictive accuracy, but also
                 transforms model outputs into actionable, interpretable
                 insights for warehouse optimization. By combining
                 automation, interpretability, and optimization, this
                 research advances the practical realization of
                 intelligent warehouse systems in the era of Industry
                 4.0.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Mavridou:2025:BAB,
  author =       "Efthimia Mavridou and Eleni Vrochidou and Michail
                 Selvesakis and George A. Papakostas",
  title =        "Beyond Accuracy: Benchmarking Machine Learning Models
                 for Efficient and Sustainable {SaaS} Decision Support",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "467",
  day =          "11",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100467",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/467",
  abstract =     "Machine learning (ML) methods have been successfully
                 employed to support decision-making for Software as a
                 Service (SaaS) providers. While most of the published
                 research primarily emphasizes prediction accuracy,
                 other important aspects, such as cloud deployment
                 efficiency and environmental impact, have received
                 comparatively less attention. It is also critical to
                 effectively use factors such as training time,
                 prediction time and carbon footprint in production.
                 SaaS decision support systems use the output of ML
                 models to provide actionable recommendations, such as
                 running reactivation campaigns for users who are likely
                 to churn. To this end, in this paper, we present a
                 benchmarking comparison of 17 different ML models for
                 churn prediction in SaaS, which include cloud
                 deployment efficiency metrics (e.g., latency,
                 prediction time, etc.) and sustainability metrics
                 (e.g., CO 2 emissions, consumed energy, etc.) along
                 with predictive performance metrics (e.g., AUC, Log
                 Loss, etc.). Two public datasets are employed,
                 experiments are repeated on four different machines,
                 locally and on the cloud, while a new weighted Green
                 Efficiency Weighted Score (GEWS) is introduced, as
                 steps towards choosing the simpler, greener and more
                 efficient ML model. Experimental results indicated
                 XGBoost and LightGBM as the models capable of offering
                 a good balance on predictive performance, fast
                 training, inference times, and limited emissions, while
                 the importance of region selection towards minimizing
                 the carbon footprint of the ML models was confirmed.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ahmad:2025:BTA,
  author =       "Sagir Muhammad Ahmad and Mohammad Samie and Barmak
                 Honarvar Shakibaei Asli",
  title =        "Building Trust in Autonomous Aerial Systems: a Review
                 of Hardware-Rooted Trust Mechanisms",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "466",
  day =          "10",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100466",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/466",
  abstract =     "Unmanned aerial vehicles (UAVs) are redefining both
                 civilian and defense operations, with swarm-based
                 architectures unlocking unprecedented scalability and
                 autonomy. However, these advancements introduce
                 critical security challenges, particularly in location
                 verification and authentication. This review provides a
                 comprehensive synthesis of hardware security primitives
                 (HSPs)-including Physical Unclonable Functions (PUFs),
                 Trusted Platform Modules (TPMs), and
                 blockchain-integrated frameworks-as foundational
                 enablers of trust in UAV ecosystems. We systematically
                 analyze communication architectures, cybersecurity
                 vulnerabilities, and deployment constraints, followed
                 by a comparative evaluation of HSP-based techniques in
                 terms of energy efficiency, scalability, and
                 operational resilience. The review further identifies
                 unresolved research gaps and highlights transformative
                 trends such as AI-augmented environmental PUFs,
                 post-quantum secure primitives, and RISC-V-based secure
                 control systems. By bridging current limitations with
                 emerging innovations, this work underscores the pivotal
                 role of hardware-rooted security in shaping the next
                 generation of autonomous aerial networks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Andrade:2025:OWS,
  author =       "Rodrigo de Albuquerque Pacheco Andrade and Helder Eiki
                 Oshiro and Gabriel Augusto Ginja and Eduardo Colombari
                 and Maria Celeste Dias and Jos{\'e} A. Afonso and
                 Jo{\~a}o Paulo Pereira do Carmo",
  title =        "{OptoBrain}: a Wireless Sensory Interface for
                 Optogenetics",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "465",
  day =          "9",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100465",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/465",
  abstract =     "Optogenetics leverages light to control neural
                 circuits, but traditional systems are often bulky and
                 tethered, limiting their use. This work introduces
                 OptoBrain, a novel, portable wireless system for
                 optogenetics designed to overcome these challenges. The
                 system integrates modules for multichannel data
                 acquisition, smart neurostimulation, and continuous
                 processing, with a focus on low-power and low-voltage
                 operation. OptoBrain features up to eight neuronal
                 acquisition channels with a low input-referred noise
                 (e.g., 0.99 \micro VRMS at 250 sps with 1 V/V gain),
                 and reliably streams data via a Bluetooth 5.0 link at a
                 measured throughput of up to 400 kbps. Experimental
                 results demonstrate robust performance, highlighting
                 its potential as a simple, practical, and low-cost
                 solution for emerging optogenetics research centers and
                 enabling new avenues in neuroscience.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Farooq:2025:ACD,
  author =       "Muhammad Omer Farooq",
  title =        "Adaptive Cyber Defense Through Hybrid Learning: From
                 Specialization to Generalization",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "464",
  day =          "9",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100464",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/464",
  abstract =     "This paper introduces a hybrid learning framework that
                 synergistically combines Reinforcement Learning (RL)
                 and Supervised Learning (SL) to train autonomous
                 cyber-defense agents capable of operating effectively
                 in dynamic and adversarial environments. The proposed
                 approach leverages RL for strategic exploration and
                 policy development, while incorporating SL to distill
                 high-reward trajectories into refined policy updates,
                 enhancing sample efficiency, learning stability, and
                 robustness. The framework first targets specialized
                 agent training, where each agent is optimized against a
                 specific adversarial behavior. Subsequently, it is
                 extended to enable the training of a generalized agent
                 that learns to counter multiple, diverse attack
                 strategies through multi-task and curriculum learning
                 techniques. Comprehensive experiments conducted in the
                 CybORG simulation environment demonstrate that the
                 hybrid RL-SL framework consistently outperforms pure RL
                 baselines across both specialized and generalized
                 settings, achieving higher cumulative rewards.
                 Specifically, hybrid-trained agents achieve up to 23\%
                 higher cumulative rewards in specialized defense tasks
                 and approximately 18\% improvements in generalized
                 defense scenarios compared to RL-only agents. Moreover,
                 incorporating temporal context into the observation
                 space yields a further 4-6\% performance gain in policy
                 robustness. Furthermore, we investigate the impact of
                 augmenting the observation space with historical
                 actions and rewards, revealing consistent, albeit
                 incremental, gains in SL-based learning performance.
                 Key contributions of this work include: (i) (i) (i) a
                 novel hybrid learning paradigm that integrates RL and
                 SL for effective cyber-defense policy learning, (ii)
                 (ii) (ii) a scalable extension for training generalized
                 agents across heterogeneous threat models, and (iii)
                 (iii) (iii) empirical analysis on the role of temporal
                 context in agent observability and decision-making.
                 Collectively, the results highlight the promise of
                 hybrid learning strategies for building intelligent,
                 resilient, and adaptable cyber-defense systems in
                 evolving threat landscapes.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fragkiadakis:2025:QWP,
  author =       "Ioannis Fragkiadakis and Stefanos Gritzalis and Costas
                 Lambrinoudakis",
  title =        "Quantifying {Website} Privacy Posture Through
                 Technical and Policy-Based Assessment",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "463",
  day =          "9",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100463",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/463",
  abstract =     "With the rapid growth of digital interactions,
                 safeguarding user privacy on websites has become a
                 critical concern. This paper introduces a comprehensive
                 framework that integrates both technical and
                 policy-based factors to assess a website's level of
                 privacy protection. The framework employs a scoring
                 system that evaluates key technical elements, such as
                 HTTP security headers, email authentication protocols
                 (SPF, DKIM, DMARC), SSL/TLS certificate usage, domain
                 reputation, DNSSEC, and cookie practices. In parallel,
                 it examines the clarity and GDPR compliance of privacy
                 policies. The resulting score reflects not only the
                 technical strength of a website's defenses but also the
                 transparency with which data processing practices are
                 communicated to users. To demonstrate its
                 effectiveness, the framework was applied to two
                 similarly sized private hospitals, generating
                 comparative privacy scores under a unified metric. The
                 results confirm the framework's value in producing
                 measurable insights that enable cross-organizational
                 privacy benchmarking. By combining policy evaluation
                 with technical analysis, this work addresses a
                 significant gap in existing research and offers a
                 reproducible, extensible methodology for assessing
                 website privacy posture from a visitor's perspective.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Moiseeva:2025:PMC,
  author =       "Svetlana Moiseeva and Evgeny Polin and Alexander
                 Moiseev and Janos Sztrik",
  title =        "Performance Modeling of Cloud Systems by an
                 Infinite-Server Queue Operating in Rarely Changing
                 Random Environment",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "462",
  day =          "8",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100462",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/462",
  abstract =     "This paper considers a heterogeneous queuing system
                 with an unlimited number of servers, where the
                 parameters are determined by a random environment. A
                 distinctive feature is that the parameters of the
                 exponential distribution of the request processing time
                 do not change their values until the end of service.
                 Thus, the devices in the system under consideration are
                 heterogeneous. For the study, a method of asymptotic
                 analysis is proposed under the condition of extremely
                 rare changes in the states of the random environment.
                 We consider the following problem. Cloud node accepts
                 requests of one type that have a similar intensity of
                 arrival and duration of processing. Sometimes an input
                 scheduler switches to accept requests of another type
                 with other intensity and duration of processing. We
                 model the system as an infinite-server queue in a
                 random environment, which influences the arrival
                 intensity and service time of new requests. The random
                 environment is modeled by a Markov chain with a finite
                 number of states. Arrivals are modeled as a Poisson
                 process with intensity dependent on the state of the
                 random environment. Service times are exponentially
                 distributed with rates also dependent on the state of
                 the random environment at the time moment when the
                 request arrived. When the environment changes its
                 state, requests that are already in the system do not
                 change their service times. So, we have requests of
                 different types (serviced with different rates) present
                 in the system at the same time. For the study, we
                 consider a situation where changes of the random
                 environment are made rarely. The method of asymptotic
                 analysis is used for the study. The asymptotic
                 condition of a rarely changing random environment
                 (entries of the generator of the corresponding Markov
                 chain tend to zero) is used. A multi-dimensional joint
                 steady-state probability distribution of the number of
                 requests of different types present in the system is
                 obtained. Several numerical examples illustrate the
                 comparisons of asymptotic results to simulations.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Chizari:2025:MIB,
  author =       "Nikzad Chizari and Keywan Tajfar and Mar{\'\i}a N.
                 Moreno-Garc{\'\i}a",
  title =        "Measuring Inter-Bias Effects and Fairness-Accuracy
                 Trade-Offs in {GNN}-Based Recommender Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "461",
  day =          "8",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100461",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/461",
  abstract =     "Bias in artificial intelligence is a critical issue
                 because these technologies increasingly influence
                 decision-making in a wide range of areas. The
                 recommender system field is one of them, where biases
                 can lead to unfair or skewed outcomes. The origin
                 usually lies in data biases coming from historical
                 inequalities or irregular sampling. Recommendation
                 algorithms using such data contribute to a greater or
                 lesser extent to amplify and perpetuate those
                 imbalances. On the other hand, different types of
                 biases can be found in the outputs of recommender
                 systems, and they can be evaluated by a variety of
                 metrics specific to each of them. However, biases
                 should not be treated independently, as they are
                 interrelated and can potentiate or mask each other.
                 Properly assessing the biases is crucial for ensuring
                 fair and equitable recommendations. This work focuses
                 on analyzing the interrelationship between different
                 types of biases and proposes metrics designed to
                 jointly evaluate multiple interrelated biases, with
                 particular emphasis on those biases that tend to mask
                 or obscure discriminatory treatment against minority or
                 protected demographic groups, evaluated in terms of
                 disparities in recommendation quality outcomes. This
                 approach enables a more comprehensive assessment of
                 algorithmic performance in terms of both fairness and
                 predictive accuracy. Special attention is given to
                 Graph Neural Network-based recommender systems, due to
                 their strong performance in this application domain.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fourkiotis:2025:FIA,
  author =       "Konstantinos P. Fourkiotis and Athanasios Tsadiras",
  title =        "Future {Internet} Applications in Healthcare: Big
                 Data-Driven Fraud Detection with Machine Learning",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "460",
  day =          "8",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100460",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/460",
  abstract =     "Hospital fraud detection has often relied on periodic
                 audits that miss evolving, internet-mediated patterns
                 in electronic claims. An artificial intelligence and
                 machine learning pipeline is being developed that is
                 leakage-safe, imbalance aware, and aligned with
                 operational capacity for large healthcare datasets. The
                 preprocessing stack integrates four tables, engineers
                 13 features, applies imputation, categorical encoding,
                 Power transformation, Boruta selection, and denoising
                 autoencoder representations, with class balancing via
                 SMOTE-ENN evaluated inside cross-validation folds.
                 Eight algorithms are compared under a fraud-oriented
                 composite productivity index that weighs recall,
                 precision, MCC, F1, ROC-AUC, and G-Mean, with per-fold
                 threshold calibration and explicit reporting of Type I
                 and Type II errors. Multilayer perceptron attains the
                 highest composite index, while CatBoost offers the
                 strongest control of false positives with high
                 accuracy. SMOTE-ENN provides limited gains once
                 representations regularize class geometry. The
                 calibrated scores support prepayment triage,
                 postpayment audit, and provider-level profiling,
                 linking alert volume to expected recovery and
                 protecting investigator workload. Situated in the
                 Future Internet context, this work targets
                 internet-mediated claim flows and web-accessible
                 provider registries. Governance procedures for drift
                 monitoring, fairness assessment, and change control
                 complete an internet-ready deployment path. The results
                 indicate that disciplined preprocessing and evaluation,
                 more than classifier choice alone, translate AI
                 improvements into measurable economic value and
                 sustainable fraud prevention in digital health
                 ecosystems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Li:2025:ARE,
  author =       "Min Li and Yuansong Qiao and Brian Lee",
  title =        "Adversarial Robustness Evaluation for Multi-View Deep
                 Learning Cybersecurity Anomaly Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "459",
  day =          "8",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100459",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/459",
  abstract =     "In the evolving cyberthreat landscape, a critical
                 challenge for intrusion detection systems (IDSs) lies
                 in defending against meticulously crafted adversarial
                 attacks. Traditional single-view detection frameworks,
                 constrained by their reliance on limited and
                 unidimensional feature representations, are often
                 inadequate for identifying maliciously manipulated
                 samples. To address these limitations, this study
                 proposes a key hypothesis: a detection architecture
                 that adopts a multi-view fusion strategy can
                 significantly enhance the system's resilience to
                 attacks. To validate the proposed hypothesis, this
                 study developed a multi-view fusion architecture and
                 conducted a series of comparative experiments. A
                 two-pronged validation framework was employed. First,
                 we examined whether the multi-view fusion model
                 demonstrates superior robustness compared to a
                 single-view model in intrusion detection tasks, thereby
                 providing empirical evidence for the effectiveness of
                 multi-view strategies. Second, we evaluated the
                 generalization capability of the multi-view model under
                 varying levels of attack intensity and coverage,
                 assessing its stability in complex adversarial
                 scenarios. Methodologically, a dual-axis training
                 assessment scheme was introduced, comprising (i)
                 continuous gradient testing of perturbation intensity,
                 with the $ \epsilon $ parameter increasing from 0.01 to
                 0.2, and (ii) variation in attack density, with sample
                 contamination rates ranging from 80\% to 90\%.
                 Adversarial test samples were generated using the Fast
                 Gradient Sign Method (FGSM) on the TON_IoT and
                 UNSW-NB15 datasets. Furthermore, we propose a
                 validation mechanism that integrates both performance
                 and robustness testing. The model is evaluated on clean
                 and adversarial test sets, respectively. By analyzing
                 performance retention and adversarial robustness, we
                 provide a comprehensive assessment of the stability of
                 the multi-view model under varying evaluation
                 conditions. The experimental results provide clear
                 support for the research hypothesis: The multi-view
                 fusion model is more robust than the single-view model
                 under adversarial scenarios. Even under high-intensity
                 attack scenarios, the multi-view model consistently
                 demonstrates superior robustness and stability. More
                 importantly, the multi-view model, through its
                 architectural feature diversity, effectively resists
                 targeted attacks to which the single-view model is
                 vulnerable, confirming the critical role of feature
                 space redundancy in enhancing adversarial robustness.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Tsai:2025:LBI,
  author =       "Kuo-Yu Tsai and Ying-Hsuan Yang",
  title =        "Lattice-Based Identity Authentication Protocol with
                 Enhanced Privacy and Scalability for Vehicular Ad Hoc
                 Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "458",
  day =          "7",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100458",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/458",
  abstract =     "Vehicular ad hoc networks (VANETs) demand
                 authentication mechanisms that are both secure and
                 privacy-preserving, particularly in light of emerging
                 quantum-era threats. In this work, we propose a
                 lattice-based identity authentication protocol that
                 leverages pseudo-IDs to safeguard user privacy, while
                 allowing the Trusted Authority (TA) to trace
                 misbehaving vehicles when necessary. Compared with
                 existing approaches, the proposed scheme strengthens
                 accountability, improves scalability, and offers
                 resistance against quantum attacks. A comprehensive
                 complexity analysis is presented, addressing
                 computational, communication, and storage overhead.
                 Analysis results under practical parameter settings
                 demonstrate that the protocol delivers robust security
                 with manageable overhead, maintaining authentication
                 latency within the real-time requirements of VANET
                 applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Reis:2025:IAS,
  author =       "Manuel J. C. S. Reis and Frederico Branco and Nishu
                 Gupta and Carlos Ser{\^o}dio",
  title =        "An {IoT} Architecture for Sustainable Urban Mobility:
                 Towards Energy-Aware and Low-Emission Smart Cities",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "457",
  day =          "4",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100457",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/457",
  abstract =     "The rapid growth of urban populations intensifies
                 congestion, air pollution, and energy demand. Green
                 mobility is central to sustainable smart cities, and
                 the Internet of Things (IoT) offers a means to monitor,
                 coordinate, and optimize transport systems in real
                 time. This paper presents an Internet of Things
                 (IoT)-based architecture integrating heterogeneous
                 sensing with edge-cloud orchestration and AI-driven
                 control for green routing and coordinated Electric
                 Vehicle (EV) charging. The framework supports adaptive
                 traffic management, energy-aware charging, and
                 multimodal integration through standards-aware
                 interfaces and auditable Key Performance Indicators
                 (KPIs). We hypothesize that, relative to a static
                 shortest-path baseline, the integrated green routing
                 and EV-charging coordination reduce (H1) mean travel
                 time per trip by {$>$}=7\%, (H2) CO 2 intensity (g/km)
                 by {$>$}=6\%, and (H3) station peak load by {$>$}=20\%
                 under moderate-to-high demand conditions. These
                 hypotheses are tested in Simulation of Urban MObility
                 (SUMO) with Handbook Emission Factors for Road
                 Transport (HBEFA) emission classes, using 10
                 independent random seeds and reporting means with 95\%
                 confidence intervals and formal significance testing.
                 The results confirm the hypotheses: average travel time
                 decreases by approximately 9.8\%, CO 2 intensity by
                 approximately 8\%, and peak load by approximately 25\%
                 under demand multipliers {$>$}=1.2 and EV shares
                 {$>$}=20\%. Gains are attenuated under light demand,
                 where congestion effects are weaker. We further discuss
                 scalability, interoperability, privacy/security, and
                 the simulation-to-deployment gap, and outline
                 priorities for reproducible field pilots. In summary, a
                 pragmatic edge-cloud IoT stack has the potential to
                 lower congestion, reduce per-kilometer emissions, and
                 smooth charging demand, provided it is supported by
                 reliable data integration, resilient edge services, and
                 standards-compliant interoperability, thereby
                 contributing to sustainable urban mobility in line with
                 the objectives of SDG 11 (Sustainable Cities and
                 Communities).",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Guo:2025:CLI,
  author =       "Chaoqun Guo and Xihan Li and Jubao Cheng and Shunjie
                 Yang and Huiquan Gong",
  title =        "Continual Learning for Intrusion Detection Under
                 Evolving Network Threats",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "456",
  day =          "4",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100456",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/456",
  abstract =     "In the face of ever-evolving cyber threats, modern
                 intrusion detection systems (IDS) must achieve
                 long-term adaptability without sacrificing performance
                 on previously encountered attacks. Traditional IDS
                 approaches often rely on static training assumptions,
                 making them prone to forgetting old patterns,
                 underperforming in label-scarce conditions, and
                 struggling with imbalanced class distributions as new
                 attacks emerge. To overcome these limitations, we
                 present a continual learning framework tailored for
                 adaptive intrusion detection. Unlike prior methods, our
                 approach is designed to operate under real-world
                 network conditions characterized by high-dimensional,
                 sparse traffic data and task-agnostic learning
                 sequences. The framework combines three core
                 components: a clustering-based memory strategy that
                 selectively retains informative historical samples
                 using DP-Means; multi-level knowledge distillation that
                 aligns current and previous model states at output and
                 intermediate feature levels; and a meta-learning-driven
                 class reweighting mechanism that dynamically adjusts to
                 shifting attack distributions. Empirical evaluations on
                 benchmark intrusion detection datasets demonstrate the
                 framework's ability to maintain high detection accuracy
                 while effectively mitigating forgetting. Notably, it
                 delivers reliable performance in continually changing
                 environments where the availability of labeled data is
                 limited, making it well-suited for real-world
                 cybersecurity systems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Fernandez-Miguel:2025:TTF,
  author =       "Andr{\'e}s Fern{\'a}ndez-Miguel and Susana
                 Ort{\'\i}z-Marcos and Mariano Jim{\'e}nez-Calzado and
                 Alfonso P. Fern{\'a}ndez del Hoyo and Fernando E.
                 Garc{\'\i}a-Mui{\~n}a and Davide Settembre-Blundo",
  title =        "Toward the Theoretical Foundations of {Industry 6.0}:
                 a Framework for {AI}-Driven Decentralized Manufacturing
                 Control",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "455",
  day =          "3",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100455",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/455",
  abstract =     "This study advances toward establishing the
                 theoretical foundations of Industry 6.0 by developing a
                 comprehensive framework that integrates artificial
                 intelligence (AI), decentralized control systems, and
                 cyber-physical production environments for intelligent,
                 sustainable, and adaptive manufacturing. The research
                 employs a tri-modal methodology (deductive, inductive,
                 and abductive reasoning) to construct a theoretical
                 architecture grounded in five interdependent
                 constructs: advanced technology integration,
                 decentralized organizational structures, mass
                 customization and sustainability strategies, cultural
                 transformation, and innovation enhancement. Unlike
                 prior conceptualizations of Industry 6.0, the proposed
                 framework explicitly emphasizes the cyclical feedback
                 between innovation and organizational design, as well
                 as the role of cultural transformation as a binding
                 element across technological, organizational, and
                 strategic domains. The resulting framework demonstrates
                 that AI-driven decentralized control systems constitute
                 the cornerstone of Industry 6.0, enabling autonomous
                 real-time decision-making, predictive zero-defect
                 manufacturing, and strategic organizational agility
                 through distributed intelligent control architectures.
                 This work contributes foundational theory and
                 actionable guidance for transitioning from centralized
                 control paradigms to AI-driven distributed intelligent
                 manufacturing control systems, establishing a
                 conceptual foundation for the emerging Industry 6.0
                 paradigm.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Dong:2025:ETS,
  author =       "Jiajie Dong and Yong Wang and Qingsong Zhao and
                 Ruiqian Ma and Jiaxiong Yang",
  title =        "Enhancing Two-Step Random Access in {LEO} Satellite
                 {Internet} an Attack-Aware Adaptive Backoff Indicator
                 ({AA-BI})",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "454",
  day =          "1",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100454",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/454",
  abstract =     "Low-Earth-Orbit Satellite Internet (LEO SI), with its
                 capability for seamless global coverage, is a key
                 solution for connecting IoT devices in areas beyond
                 terrestrial network reach, playing a vital role in
                 building a future ubiquitous IoT system. Inspired by
                 the IEEE 802.15.4 Improved Adaptive Backoff Algorithm
                 (I-ABA), this paper proposes an Attack-Aware Adaptive
                 Backoff Indicator (AA-BI) mechanism to enhance the
                 security and robustness of the two-step random access
                 process in LEO SI. The mechanism constructs a composite
                 threat intensity indicator that incorporates collision
                 probability, Denial-of-Service (DoS) attack strength,
                 and replay attack intensity. This quantified threat
                 level is smoothly mapped to a dynamic backoff window to
                 achieve adaptive backoff adjustment. Simulation results
                 demonstrate that, with 200 pieces of user equipment
                 (UE), the AA-BI mechanism significantly improves the
                 access success rate ( ASR ) and jamming resistance rate
                 (JRR) under various attack scenarios compared to the
                 I-ABA and Binary Exponential Backoff (BEB) algorithms.
                 Notably, under high-attack conditions, AA-BI improves
                 ASR by up to 25.1\% and 56.6\% over I-ABA and BEB,
                 respectively. Moreover, under high-load conditions with
                 800 users, AA-BI still maintains superior performance,
                 achieving an ASR of 0.42 and a JRR of 0.68, thereby
                 effectively ensuring the access performance and
                 reliability of satellite Internet in malicious
                 environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ahmed:2025:ASE,
  author =       "Abbirah Ahmed and Martin J. Hayes and Arash
                 Joorabchi",
  title =        "Assessing Student Engagement: a Machine Learning
                 Approach to Qualitative Analysis of Institutional
                 Effectiveness",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "453",
  day =          "1",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100453",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/453",
  abstract =     "In higher education, institutional quality is
                 traditionally assessed through metrics such as academic
                 programs, research output, educational resources, and
                 community services. However, it is important that their
                 activities align with student expectations,
                 particularly in relation to interactive learning
                 environments, learning management system interaction,
                 curricular and co-curricular activities, accessibility,
                 support services and other learning resources that
                 ensure academic success and, jointly, career readiness.
                 The growing popularity of student engagement metrics as
                 one of the key measures to evaluate institutional
                 efficacy is now a feature across higher education. By
                 monitoring student engagement, institutions assess the
                 impact of existing resources and make necessary
                 improvements or interventions to ensure student
                 success. This study presents a comprehensive analysis
                 of student feedback from the StudentSurvey.ie dataset
                 (2016-2022), which consists of approximately 275,000
                 student responses, focusing on student self-perception
                 of engagement in the learning process. By using
                 classical topic modelling techniques such as Latent
                 Dirichlet Allocation (LDA) and Bi-term Topic Modelling
                 (BTM), along with the advanced transformer-based
                 BERTopic model, we identify key themes in student
                 responses that can impact institutional strength
                 performance metrics. BTM proved more effective than LDA
                 for short text analysis, whereas BERTopic offered
                 greater semantic coherence and uncovered hidden themes
                 using deep learning embeddings. Moreover, a custom
                 Named Entity Recognition (NER) model successfully
                 extracted entities such as university personnel,
                 digital tools, and educational resources, with improved
                 performance as the training data size increased. To
                 enable students to offer actionable feedback,
                 suggesting areas of improvement, an n-gram and bigram
                 network analysis was used to focus on common modifiers
                 such as ``more'' and ``better'' and trends across
                 student groups. This study introduces a fully
                 automated, scalable pipeline that integrates topic
                 modelling, NER, and n-gram analysis to interpret
                 student feedback, offering reportable insights and
                 supporting structured enhancements to the student
                 learning experience.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Zhu:2025:ROI,
  author =       "Xu Zhu and Litian Kang and Ming Zhao",
  title =        "Robust Optimization for {IRS}-Assisted {SAGIN} Under
                 Channel Uncertainty",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "452",
  day =          "1",
  month =        oct,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100452",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/452",
  abstract =     "With the widespread adoption of space-air-ground
                 integrated networks (SAGINs) in next-generation
                 wireless communications, intelligent reflecting
                 surfaces (IRSs) have emerged as a key technology for
                 enhancing system performance through passive link
                 reinforcement. This paper addresses the prevalent issue
                 of channel state information (CSI) uncertainty in
                 practical systems by constructing an IRS-assisted
                 multi-hop SAGIN communication model. To capture the
                 performance degradation caused by channel estimation
                 errors, a norm-bounded uncertainty model is introduced.
                 A simulated annealing (SA)-based phase optimization
                 algorithm is proposed to enhance system robustness and
                 improve worst-case communication quality. Simulation
                 results demonstrate that the proposed method
                 significantly outperforms traditional multiple access
                 strategies (SDMA and NOMA) under various user densities
                 and perturbation levels, highlighting its stability and
                 scalability in complex environments.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Skepetari:2025:TSA,
  author =       "Eugenia Skepetari and Sotiris Pelekis and Hercules
                 Koutalidis and Alexandros Menelaos Tzortzis and
                 Georgios Kormpakis and Christos Ntanos and Dimitris
                 Askounis",
  title =        "{TwinP2G}: a Software Application for Optimal
                 Power-to-Gas Planning",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "451",
  day =          "30",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100451",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/451",
  abstract =     "This paper presents TwinP2G, a software application
                 for optimal planning of investments in power-to-gas
                 (PtG) systems. TwinP2G provides simulation and
                 optimization services for the techno-economic analysis
                 of user-customized energy networks. The core of TwinP2G
                 is based on power flow simulation; however it supports
                 energy sector coupling, including electricity, green
                 hydrogen, natural gas, and synthetic methane. The
                 framework provides a user-friendly user interface (UI)
                 suitable for various user roles, including data
                 scientists and energy experts, using visualizations and
                 metrics on the assessed investments. An identity and
                 access management mechanism also serves the security
                 and authorization needs of the framework. Finally,
                 TwinP2G revolutionizes the concept of data availability
                 and data sharing by granting its users access to
                 distributed energy datasets available in the EnerShare
                 Data Space. These data are available to TwinP2G users
                 for conducting their experiments and extracting useful
                 insights on optimal PtG investments for the energy
                 grid.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kira:2025:TFR,
  author =       "Mostafa Kira and Zeyad Alajamy and Ahmed Soliman and
                 Yusuf Mesbah and Manuel Mazzara",
  title =        "Trustworthy Face Recognition as a Service: a
                 Multi-Layered Approach for Mitigating Spoofing and
                 Ensuring System Integrity",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "450",
  day =          "30",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100450",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/450",
  abstract =     "Facial recognition systems are increasingly used for
                 authentication across domains such as finance,
                 e-commerce, and public services, but their growing
                 adoption raises significant concerns about spoofing
                 attacks enabled by printed photos, replayed videos, or
                 AI-generated deepfakes. To address this gap, we
                 introduce a multi-layered Face Recognition-as-a-Service
                 (FRaaS) platform that integrates passive liveness
                 detection with active challenge-response mechanisms,
                 thereby defending against both low-effort and
                 sophisticated presentation attacks. The platform is
                 designed as a scalable cloud-based solution,
                 complemented by an open-source SDK for seamless
                 third-party integration, and guided by ethical AI
                 principles of fairness, transparency, and privacy. A
                 comprehensive evaluation validates the system's logic
                 and implementation: (i) Frontend audits using
                 Lighthouse consistently scored above 96\% in
                 performance, accessibility, and best practices; (ii)
                 SDK testing achieved over 91\% code coverage with
                 reliable OAuth flow and error resilience; (iii) Passive
                 liveness layer employed the DeepPixBiS model, which
                 achieves an Average Classification Error Rate (ACER) of
                 0.4 on the OULU-NPU benchmark, outperforming prior
                 state-of-the-art methods; and (iv) Load simulations
                 confirmed high throughput (276 req/s), low latency
                 (95th percentile at 1.51 ms), and zero error rates.
                 Together, these results demonstrate that the proposed
                 platform is robust, scalable, and trustworthy for
                 security-critical applications.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{AlFaia:2025:ELS,
  author =       "Dalal {Al Faia} and Khalid Alomar",
  title =        "Evaluating Learning Success, Engagement, and Usability
                 of Moalemy: an {Arabic} Rule-Based Chatbot",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "449",
  day =          "30",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100449",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/449",
  abstract =     "A rule-based chatbot is a type of chatbot that
                 responds by matching users' queries with pre-defined
                 rules. In e-learning, chatbots can enhance the learning
                 experience by assisting teachers in delivering learning
                 materials pleasantly. This research introduces Moalemy,
                 an Arabic rule-based chatbot designed to provide a
                 personalized learning experience by tailoring
                 educational content to each learner's prior knowledge.
                 This empirical study evaluates learning outcomes, user
                 engagement, and system usability using both subjective
                 and objective metrics. It compares the effectiveness of
                 a proposed Arabic rule-based chatbot with adaptive
                 personalization to that of a static, non-personalized
                 chatbot. The comparison was conducted across three
                 levels of task difficulty (easy, medium, and hard)
                 using a $ 2 \times 3 $ within-subject experimental
                 design with 34 participants. Descriptive statistics
                 revealed higher mean values of usability and engagement
                 in the adaptive method. Although the analysis revealed
                 no significant variations in learning outcomes and SUS
                 scores, it showed statistically significant differences
                 in user satisfaction in favor of the adaptive method, p
                 = 0.003. Analyses showed no significant differences
                 between the two learning methods in terms of
                 effectiveness, efficiency, and engagement. Across
                 difficulty levels, the adaptive method outperforms the
                 static method in terms of efficiency and effectiveness
                 at the medium level, and in engagement at the easy
                 level.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Farhan:2025:SSI,
  author =       "Maruf Farhan and Usman Butt and Rejwan {Bin Sulaiman}
                 and Mansour Alraja",
  title =        "Self-Sovereign Identities and Content Provenance:
                 {VeriTrust} --- a Blockchain-Based Framework for Fake
                 News Detection",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "448",
  day =          "30",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100448",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/448",
  abstract =     "The widespread circulation of digital misinformation
                 exposes a critical shortcoming in prevailing detection
                 strategies, namely, the absence of robust mechanisms to
                 confirm the origin and authenticity of online content.
                 This study addresses this by introducing VeriTrust, a
                 conceptual and provenance-centric framework designed to
                 establish content-level trust by integrating
                 Self-Sovereign Identity (SSI), blockchain-based
                 anchoring, and AI-assisted decentralized verification.
                 The proposed system is designed to operate through
                 three key components: (1) issuing Decentralized
                 Identifiers (DIDs) and Verifiable Credentials (VCs)
                 through Hyperledger Aries and Indy; (2) anchoring
                 cryptographic hashes of content metadata to an
                 Ethereum-compatible blockchain using Merkle trees and
                 smart contracts; and (3) enabling a community-led
                 verification model enhanced by federated learning with
                 future extensibility toward zero-knowledge proof
                 techniques. Theoretical projections, derived from
                 established performance benchmarks, suggest the
                 framework offers low latency and high scalability for
                 content anchoring and minimal on-chain transaction
                 fees. It also prioritizes user privacy by ensuring no
                 on-chain exposure of personal data. VeriTrust redefines
                 misinformation mitigation by shifting from reactive
                 content-based classification to proactive
                 provenance-based verification, forming a verifiable
                 link between digital content and its creator.
                 VeriTrust, while currently at the conceptual and
                 theoretical validation stage, holds promise for
                 enhancing transparency, accountability, and resilience
                 against misinformation attacks across journalism,
                 academia, and online platforms.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Jayawardena:2025:NCE,
  author =       "Chathura Jayawardena and George Ntavazlis Katsaros and
                 Konstantinos Nikitopoulos",
  title =        "{NL-COMM}: Enabling High-Performing Next-Generation
                 Networks via Advanced Non-Linear Processing",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "447",
  day =          "30",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100447",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/447",
  abstract =     "Future wireless networks are expected to deliver
                 enhanced spectral efficiency while being energy
                 efficient. MIMO and other non-orthogonal transmission
                 schemes, such as non-orthogonal multiple access (NOMA),
                 offer substantial theoretical spectral efficiency
                 gains. However, these gains have yet to translate into
                 practical deployments, largely due to limitations in
                 current signal processing methods. Linear transceiver
                 processing, though widely adopted, fails to fully
                 exploit non-orthogonal transmissions, forcing massive
                 MIMO systems to use a disproportionately large number
                 of RF chains for relatively few streams, increasing
                 power consumption. Non-linear processing can unlock the
                 full potential of non-orthogonal schemes but is
                 hindered by high computational complexity and
                 integration challenges. Moreover, existing
                 message-passing receivers for NOMA depend on specially
                 designed sparse signals, limiting resource allocation
                 flexibility and efficiency. This work presents NL-COMM,
                 an efficient non-linear processing framework that
                 translates the theoretical gains of non-orthogonal
                 transmissions into practical benefits for both the
                 uplink and downlink. NL-COMM delivers over 200\%
                 spectral efficiency gains, enables 50\% reductions in
                 antennas and RF chains (and thus base station power
                 consumption), and increases concurrently supported
                 users by 450\%. In distributed MIMO deployments, the
                 antenna reduction halves fronthaul bandwidth
                 requirements, mitigating a key system bottleneck.
                 Furthermore, NL-COMM offers the flexibility to unlock
                 new NOMA schemes. Finally, we present both hardware and
                 software architectures for NL-COMM that support
                 massively parallel execution, demonstrating how
                 advanced non-linear processing can be realized in
                 practice to meet the demands of next-generation
                 networks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Nagesh:2025:DAT,
  author =       "Sanjay Segu Nagesh and Niroshinie Fernando and Seng W.
                 Loke and Azadeh Ghari Neiat and Pubudu N. Pathirana",
  title =        "A Dependency-Aware Task Stealing Framework for Mobile
                 Crowd Computing",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "446",
  day =          "29",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100446",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/446",
  abstract =     "Mobile crowd computing (MCdC) leverages the collective
                 computational resources of nearby mobile devices to
                 execute complex tasks without relying on remote cloud
                 infrastructure. However, existing MCdC systems struggle
                 with device heterogeneity and complex application
                 dependencies, often leading to inefficient resource
                 utilization and poor scalability. This paper presents
                 Honeybee-Tx, a novel dependency-aware work stealing
                 framework designed for heterogeneous mobile device
                 clusters. The framework introduces three key
                 contributions: (1) capability-aware job selection that
                 matches computational tasks to device capabilities
                 through lightweight profiling and dynamic scoring, (2)
                 static dependency-aware work stealing that respects
                 predefined task dependencies while maintaining
                 decentralized execution, and (3) staged result
                 transfers that minimize communication overhead by
                 selectively transmitting intermediate results. We
                 evaluate Honeybee-Tx using two applications: Human
                 Activity Recognition (HAR) for sensor analytics and
                 multi-camera video processing for compute-intensive
                 workflows. The experimental results on five
                 heterogeneous Android devices (OnePlus 5T, Pixel 6 Pro,
                 and Pixel 7) demonstrate performance improvements over
                 monolithic execution. For HAR workloads, Honeybee-Tx
                 achieves up to 4.72$ \times $ speed-up while reducing
                 per-device energy consumption by 63\% (from 1.5\% to
                 0.56\% battery usage). For video processing tasks, the
                 framework delivers 2.06$ \times $ speed-up compared to
                 monolithic execution, with 51.4\% energy reduction and
                 71.6\% memory savings, while generating 42\% less
                 network traffic than non-dependency-aware approaches.
                 These results demonstrate that Honeybee-Tx successfully
                 addresses key challenges in heterogeneous MCdC
                 environments, enabling efficient execution of
                 dependency-aware applications across diverse mobile
                 device capabilities. The framework provides a practical
                 foundation for collaborative mobile computing
                 applications in scenarios where cloud connectivity is
                 limited or unavailable.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Bernal-Beltran:2025:SAM,
  author =       "Tom{\'a}s Bernal-Beltr{\'a}n and Mario Andr{\'e}s
                 Paredes-Valverde and Mar{\'\i}a del Pilar
                 Salas-Z{\'a}rate and Jos{\'e} Antonio
                 Garc{\'\i}a-D{\'\i}az and Rafael Valencia-Garc{\'\i}a",
  title =        "Sentiment Analysis in {Mexican Spanish}: a Comparison
                 Between Fine-Tuning and In-Context Learning with Large
                 Language Models",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "445",
  day =          "29",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100445",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/445",
  abstract =     "The proliferation of social media has made Sentiment
                 Analysis an essential tool for understanding user
                 opinions, particularly in underrepresented language
                 variants such as Mexican Spanish. Recent advances in
                 Large Language Models have made effective sentiment
                 analysis through in-context learning techniques,
                 reducing the need for supervised training. This study
                 compares the performance of zero and few-shot with
                 traditional fine-tuning approaches of tourism-related
                 texts in Mexican Spanish. Two annotated datasets from
                 the REST-MEX 2022 and 2023 shared tasks were used for
                 this purpose. Results show that fine-tuning,
                 particularly with the MarIA model, achieves the best
                 overall performance. However, modern LLMs that use
                 in-context learning strategies, such as Mixtral 8x7B
                 for zero-shot and Mistral 7B for few-shot, demonstrate
                 strong potential in low-resource settings by closely
                 approximating the accuracy of fine-tuned models,
                 suggesting that in-context learning is a viable
                 alternative to fine-tuning for sentiment analysis in
                 Mexican Spanish when labeled data is limited. These
                 approaches can enable intelligent, data-driven digital
                 services with applications in tourism platforms and
                 urban information systems that enhance user experience
                 and trust in large-scale socio-technical ecosystems.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Al-Humaimeedy:2025:IPP,
  author =       "Abeer S. Al-Humaimeedy",
  title =        "Intellectual Property Protection Through Blockchain:
                 Introducing the Novel {SmartRegistry-IP} for Secure
                 Digital Ownership",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "444",
  day =          "29",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100444",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/444",
  abstract =     "The rise of digital content has made the need for
                 reliable and practical intellectual property (IP)
                 management systems more critical than ever. Most
                 traditional IP systems are prone to issues such as
                 delays, inefficiency, and data security breaches. This
                 paper introduces SmartRegistry-IP, a system developed
                 to simplify the registration, licensing, and transfer
                 of intellectual property assets in a secure and
                 scalable decentralized environment. By utilizing the
                 InterPlanetary File System (IPFS) for decentralized
                 storage, SmartRegistry-IP achieves a low storage
                 latency of 300 milliseconds, outperforming both cloud
                 storage (500 ms) and local storage (700 ms). The system
                 also supports a high transaction throughput of 120
                 transactions per second. Through the use of smart
                 contracts, licensing agreements are automatically and
                 securely enforced, reducing the need for intermediaries
                 and lowering operational costs. Additionally, the
                 proof-of-work process verifies all transactions,
                 ensuring higher security and maintaining data
                 consistency. The platform integrates an intuitive
                 graphical user interface that enables seamless asset
                 uploads, license management, and analytics
                 visualization in real time. SmartRegistry-IP
                 demonstrates superior efficiency compared to
                 traditional systems, achieving a blockchain delay of
                 300 ms, which is half the latency of standard systems,
                 averaging 600 ms. According to this study, adopting
                 SmartRegistry-IP provides IP organizations with
                 enhanced security and transparent management, ensuring
                 they can overcome operational challenges regardless of
                 their size. As a result, the use of blockchain for
                 intellectual property management is expected to
                 increase, helping maintain precise records and reducing
                 time spent on online copyright registration.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Panagiotopoulos:2025:CSI,
  author =       "Apostolos Panagiotopoulos and Vasileios Karyotis",
  title =        "Commercial Off-the-Shelf {IoT}-Based Infant Car Seat
                 Application for Preventing the Forgotten Baby
                 Syndrome",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "443",
  day =          "29",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100443",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/443",
  abstract =     "The Forgotten Baby Syndrome (FBS), the accidental
                 abandonment of infants in vehicles, continues to result
                 in otherwise preventable tragedies worldwide. This work
                 presents a prototype system called SafeCuddle, designed
                 to mitigate the risks associated with FBS. The proposed
                 solution utilizes an Arduino UNO R4 WiFi
                 microcontroller integrated with low-cost IoT sensors
                 for real-time data acquisition and processing.
                 Processed signals are visualized via a Python-based
                 desktop application. A key feature of the system is its
                 ability to issue immediate alerts to the driver upon
                 detecting their departure from the vehicle while an
                 infant remains seated in the vehicle. An extensive
                 review of the syndrome's etiology identifies disrupted
                 routines and the high demands of modern life as primary
                 contributing factors. In response, the proposed system
                 can be easily implemented with commercial off-the-shelf
                 components and aims to support caregivers by acting as
                 a fail-safe mechanism. The paper is structured into two
                 primary sections: (i) an analytical overview of FBS and
                 its contributing factors and (ii) a detailed account of
                 the system's design, implementation, operational
                 workflow, and evaluation results. The unique
                 contribution of this work lies in the integration of a
                 low-cost, real-time alert system within a modular and
                 easily deployable architecture that can be integrated
                 in existing infant car seats as an aftermarket
                 solution, if properly commercialized, specifically
                 tailored to prevent FBS through immediate driver
                 feedback at the critical moment of risk.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Kozina:2025:OAD,
  author =       "Olha Kozina and Jos{\'e} Machado and Maksym Volk and
                 Hennadii Heiko and Volodymyr Panchenko and Mykyta Kozin
                 and Maryna Ivanova",
  title =        "Opportunities for Adapting Data Write Latency in
                 Geo-Distributed Replicas of Multicloud Systems",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "442",
  day =          "28",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100442",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/442",
  abstract =     "This paper proposes an AI-based approach to adapting
                 the data write latency in multicloud systems (MCSs)
                 that supports data consistency across geo-distributed
                 replicas of cloud service providers (CSPs). The
                 proposed approach allows for dynamically forming
                 adaptation scenarios based on the proposed model of
                 multi-criteria optimization of data write latency. The
                 generated adaptation scenarios are aimed at maintaining
                 the required data write latency under changes in the
                 intensity of the incoming request flow and network
                 transmission time between replicas in CSPs. To generate
                 adaptation scenarios, the features of the algorithmic
                 Latord method of data consistency, are used. To
                 determine the threshold values and predict the external
                 parameters affecting the data write latency, we propose
                 using learning AI models. An artificial neural network
                 is used to form rules for changing the parameters of
                 the Latord method when the external operating
                 conditions of MCSs change. The features of the Latord
                 method that influence data write latency are
                 demonstrated by the results of simulation experiments
                 on three MCSs with different configurations. To confirm
                 the effectiveness of the developed approach, an
                 adaptation scenario was considered that allows reducing
                 the data write latency by 13\% when changing the
                 standard deviation of network transmission time between
                 DCs of MCS.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Charilogis:2025:HIB,
  author =       "Vasileios Charilogis and Ioannis G. Tsoulos",
  title =        "Healing Intelligence: a Bio-Inspired Metaheuristic
                 Optimization Method Using Recovery Dynamics",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "441",
  day =          "27",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100441",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/441",
  abstract =     "BioHealing Optimization (BHO) is a bio-inspired
                 metaheuristic that operationalizes the injury-recovery
                 paradigm through an iterative loop of recombination,
                 stochastic injury, and guided healing. The algorithm is
                 further enhanced by adaptive mechanisms, including scar
                 map, hot-dimension focusing, RAGE/hyper-RAGE bursts
                 (Rapid Aggressive Global Exploration), and healing-rate
                 modulation, enabling a dynamic balance between
                 exploration and exploitation. Across 17 benchmark
                 problems with 30 runs, each under a fixed budget of
                 1.5$ \cdot $105 function evaluations, BHO achieves the
                 lowest overall rank in both the ``best-of-runs'' (47)
                 and the ``mean-of-runs'' (48), giving an overall rank
                 sum of 95 and an average rank of 2.794. Representative
                 first-place results include Frequency-Modulated Sound
                 Waves, the Lennard-Jones potential, and Electricity
                 Transmission Pricing. In contrast to prior
                 healing-inspired optimizers such as Wound Healing
                 Optimization (WHO) and Synergistic Fibroblast
                 Optimization (SFO), BHO uniquely integrates (i) an
                 explicit tri-phasic architecture (DE/best/1/bin
                 recombination -{$>$} Gaussian/L{\'e}vy injury -{$>$}
                 guided healing), (ii) per-dimension stateful adaptation
                 (scar map, hot-dims), and (iii) stagnation-triggered
                 bursts (RAGE/hyper-RAGE). These features provide a
                 principled exploration-exploitation separation that is
                 absent in WHO/SFO.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Qian:2025:EPE,
  author =       "Jingshi Qian and Nobuyoshi Komuro and Won-Suk Kim and
                 Younghwan Yoo",
  title =        "Enhanced Position Estimation via {RSSI} Offset
                 Correction in {BLE} Fingerprinting-Based Indoor
                 Positioning",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "440",
  day =          "26",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100440",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/440",
  abstract =     "Since GPS (Global Positioning System) cannot meet
                 accuracy requirements indoors, indoor Location-Based
                 Services (LBSs) have become increasingly important. BLE
                 (Bluetooth Low Energy) offers cost and accuracy
                 advantages. Typically, the position fingerprinting
                 method is used for indoor positioning. However, due to
                 irregular reflection and absorption, the indoor
                 environment introduces various offsets in Bluetooth
                 RSSI (Received Signal Strength Indicator). This study
                 analyzed the RSSI space and proposed a pre-processing
                 workflow to improve position estimation accuracy by
                 correcting offsets in RSSI space for BLE fingerprinting
                 methods using machine learning. Experiments performed
                 using different position estimation methods showed that
                 the corrected data achieved a 6\% improvement over the
                 filter-only result. This study also evaluated the
                 effects of different pre-processing and post-processing
                 filters on positioning accuracy. Experiments were also
                 conducted using a published dataset and showed similar
                 results.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Almalki:2025:LJP,
  author =       "Ashwaq Almalki and Safa Alsafari and Noura M.
                 Alotaibi",
  title =        "Legal Judgment Prediction in the {Saudi Arabian}
                 Commercial Court",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "439",
  day =          "26",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100439",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/439",
  abstract =     "Legal judgment prediction is an emerging application
                 of artificial intelligence in the legal domain,
                 offering significant potential to enhance legal
                 decision support systems. Such systems can improve
                 judicial efficiency, reduce burdens on legal
                 professionals, and assist in early-stage case
                 assessment. This study focused on predicting whether a
                 legal case would be Accepted or Rejected using only the
                 Fact section of court rulings. A key challenge lay in
                 processing long legal documents, which often exceeded
                 the input length limitations of transformer-based
                 models. To address this, we proposed a two-step
                 methodology: first, each document was segmented into
                 sentence-level inputs compatible with AraBERT-a
                 pretrained Arabic transformer model-to generate
                 sentence-level predictions; second, these predictions
                 were aggregated to produce a document-level decision
                 using several methods, including Mean, Max,
                 Confidence-Weighted, and Positional aggregation. We
                 evaluated the approach on a dataset of 19,822
                 real-world cases collected from the Saudi Arabian
                 Commercial Court. Among all aggregation methods, the
                 Confidence-Weighted method applied to the AraBERT-based
                 classifier achieved the highest performance, with an
                 overall accuracy of 85.62\%. The results demonstrated
                 that combining sentence-level modeling with effective
                 aggregation methods provides a scalable and accurate
                 solution for Arabic legal judgment prediction, enabling
                 full-length document processing without truncation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Wu:2025:RDP,
  author =       "Liang Wu and Xiang Li and Ping Ma and Yicheng Cai",
  title =        "Research on a Dense Pedestrian-Detection Algorithm
                 Based on an Improved {YOLO11}",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "438",
  day =          "26",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100438",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/438",
  abstract =     "Pedestrian detection, as a core function of an
                 intelligent vision system, plays a key role in obstacle
                 avoidance during driverless navigation, intelligent
                 traffic monitoring, and other fields. In this paper, we
                 optimize the YOLO11 detection algorithm to solve the
                 problem of insufficient accuracy of pedestrian
                 detection in complex scenes. The C3K2-lighter module is
                 constructed by replacing the Bottleneck in the C3K2
                 module with the FasterNet Block, which significantly
                 enhances feature extraction for long-distance
                 pedestrians in dense scenes. In addition, it
                 incorporates the Triplet Attention Module to establish
                 correlations between local features and the global
                 context, thereby effectively mitigating omission
                 problems caused by occlusion. The Variable Focus Loss
                 Function (VFL) is additionally introduced to optimize
                 target classification by quantifying the variance in
                 features between the predicted frame and the
                 ground-truth frame. The improved model,
                 YOLO11-Improved, achieves a synergistic optimization of
                 detection accuracy and computational efficiency,
                 increasing the AP value by 3.7\% and the precision by
                 2.8\% and reducing the parameter volume by 0.5 M while
                 maintaining real-time performance.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Ferreira:2025:DRL,
  author =       "Henrique C. Ferreira and Ramiro S. Barbosa",
  title =        "Deep Reinforcement Learning for Adaptive Robotic
                 Grasping and Post-Grasp Manipulation in Simulated
                 Dynamic Environments",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "437",
  day =          "26",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100437",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/437",
  abstract =     "This article presents a deep reinforcement learning
                 (DRL) approach for adaptive robotic grasping in dynamic
                 environments. We developed UR5GraspingEnv, a
                 PyBullet-based simulation environment integrated with
                 OpenAI Gym, to train a UR5 robotic arm with a Robotiq
                 2F-85 gripper. Soft Actor-Critic (SAC) and Proximal
                 Policy Optimization (PPO) were implemented to learn
                 robust grasping policies for randomly positioned
                 objects. A tailored reward function, combining distance
                 penalties, grasp, and pose rewards, optimizes grasping
                 and post-grasping tasks, enhanced by domain
                 randomization. SAC achieves an 87\% grasp success rate
                 and 75\% post-grasp success, outperforming PPO 82\% and
                 68\%, with stable convergence over 100,000 timesteps.
                 The system addresses post-grasping manipulation and
                 sim-to-real transfer challenges, advancing industrial
                 and assistive applications. Results demonstrate the
                 feasibility of learning stable and goal-driven policies
                 for single-arm robotic manipulation using minimal
                 supervision. Both PPO and SAC yield competitive
                 performance, with SAC exhibiting superior adaptability
                 in cluttered or edge cases. These findings suggest that
                 DRL, when carefully designed and monitored, can support
                 scalable learning in manipulation tasks.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Gurrola-Mijares:2025:ESP,
  author =       "Luis-Dagoberto Gurrola-Mijares and Jos{\'e}-Manuel
                 Mej{\'\i}a-Mu{\~n}oz and Oliverio Cruz-Mej{\'\i}a and
                 Abraham-Leonel L{\'o}pez-Le{\'o}n and Leticia
                 Ortega-M{\'a}ynez",
  title =        "Evaluation Study of Pavement Condition Using Digital
                 Twins and Deep Learning on {IMU} Signals",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "436",
  day =          "26",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100436",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/436",
  abstract =     "Traditional road asset management relies on periodic,
                 often inefficient, inspections. Digital Twins offer a
                 paradigm shift towards proactive, data-driven
                 maintenance by creating a real-time virtual replica of
                 physical infrastructure. This paper proposes a
                 comprehensive, formalized framework for a highway
                 Digital Twin, structured into three integrated
                 components: a Physical Space, which defines key
                 performance indicators through mathematical state
                 vectors; a Data Interconnection layer for real-time
                 data processing; and a Virtual Space equipped with
                 hybrid models. We provide a formal definition of these
                 state vectors and a dynamic synchronization mechanism
                 between the physical and virtual spaces. In this study,
                 we focused on pavement condition assessment by using a
                 data-driven component using accessible technology. This
                 study show the synergy between the Digital Twin and
                 deep learning, specifically by integrating advanced
                 analytical models within the Virtual Space for
                 intelligent pavement condition assessment. To validate
                 this approach, a case study was conducted to classify
                 road surface anomalies using low-cost Inertial
                 Measurement Unit (IMU) data. We evaluated several
                 machine learning classifiers and introduced a novel
                 parallel Gated Recurrent Unit network. The results
                 demonstrate that our proposed architecture achieved
                 superior performance, with an accuracy of 89.5\% and an
                 F1-score of 0.875, significantly outperforming
                 traditional methods. The findings validate the
                 viability of the proposed Digital Twin framework and
                 highlight its potential to achieve high-precision
                 pavement monitoring using low-cost sensor data, a
                 critical step towards intelligent road infrastructure
                 management.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Emil:2025:RAF,
  author =       "Repede Stefan Emil and Brad Remus",
  title =        "A Review of Automatic Fake News Detection: From
                 Traditional Methods to Large Language Models",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "435",
  day =          "25",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100435",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/435",
  abstract =     "In the current digital era, the spread of fake news
                 presents serious difficulties. This study offers a
                 thorough analysis of recent developments in false news
                 automatic detection techniques, from traditional
                 methods to the most recent developed models like large
                 language models. The review identifies four
                 perspectives on automatic detection of fake news that
                 are oriented towards knowledge, style, propagation, and
                 source of the misinformation. This paper describes how
                 automatic detection methods use data science techniques
                 such as deep learning, large language models, and
                 traditional machine learning. In addition to discussing
                 the shortcomings of existing approaches, such as the
                 absence of datasets, this paper emphasizes the
                 multidimensional function of large language models in
                 creating and identifying fake news while underlining
                 the necessity for textual, visual, and audio common
                 analysis, multidisciplinary collaboration, and greater
                 model transparency.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Angelis:2025:OLS,
  author =       "Apostolos Angelis and George Kousiouris",
  title =        "An Overview on the Landscape of Self-Adaptive Cloud
                 Design and Operation Patterns: Goals, Strategies,
                 Tooling, Evaluation, and Dataset Perspectives",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "434",
  day =          "24",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100434",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/434",
  abstract =     "Cloud-native applications have significantly advanced
                 the development and scalability of online services
                 through the use of microservices and modular
                 architectures. However, achieving adaptability,
                 resilience, and efficient performance management within
                 cloud environments remains a key challenge. This work
                 systematically reviews 111 publications from the last
                 eight years on self-adaptive cloud design and
                 operations patterns, classifying them by objectives,
                 control scope, decision-making approach, automation
                 level, and validation methods. Our analysis reveals
                 that performance optimization dominates research goals,
                 followed by cost reduction and security enhancement,
                 with availability and reliability underexplored.
                 Reactive feedback loops prevail, while proactive
                 approaches-often leveraging machine learning-are
                 increasingly applied to predictive resource
                 provisioning and application management.
                 Resource-oriented adaptation strategies are common, but
                 direct application-level reconfiguration remains
                 scarce, representing a promising research gap. We
                 further catalog tools, platforms, and more than 30
                 publicly accessible datasets used in validation, and
                 that dataset usage is fragmented without a de facto
                 standard. Finally, we map the research findings on a
                 generic application and system-level design for
                 self-adaptive applications, including a proposal for a
                 federated learning approach for SaaS application
                 Agents. This blueprint aims to guide future work toward
                 more intelligent, context-aware cloud automation.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Hamdi:2025:DLB,
  author =       "Ahmed Hamdi and Hassan N. Noura and Joseph Azar",
  title =        "Deep Learning-Based Approach to Automated Monitoring
                 of Defects and Soiling on Solar Panels",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "433",
  day =          "23",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100433",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/433",
  abstract =     "The reliable operation of photovoltaic (PV) systems is
                 often compromised by surface soiling and structural
                 damage, which reduce energy efficiency and complicate
                 large-scale monitoring. To address this challenge, we
                 propose a two-tiered image-classification framework
                 that combines Vision Transformer (ViT) models,
                 lightweight convolutional neural networks (CNNs), and
                 knowledge distillation (KD). In Tier 1, a DINOv2
                 ViT-Base model is fine-tuned to provide robust
                 high-level categorization of solar-panel images into
                 three classes: Normal, Soiled, and Damaged. In Tier 2,
                 two enhanced EfficientNetB0 models are introduced: (i)
                 a KD-based student model distilled from a DINOv2
                 ViT-S/14 teacher, which improves accuracy from 96.7\%
                 to 98.67\% for damage classification and from 90.7\% to
                 92.38\% for soiling classification, and (ii) an
                 EfficientNetB0 augmented with Multi-Head Self-Attention
                 (MHSA), which achieves 98.73\% accuracy for damage and
                 93.33\% accuracy for soiling. These results demonstrate
                 that integrating transformer-based representations with
                 compact CNN architectures yields a scalable and
                 efficient solution for automated monitoring of the
                 condition of PV systems, offering high accuracy and
                 real-time applicability in inspections on solar
                 farms.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}

@Article{Reed:2025:MOM,
  author =       "Andy Reed and Laurence S. Dooley and Soraya Kouadri
                 Mostefaoui",
  title =        "Minimal Overhead Modelling of Slow {DoS} Attack
                 Detection for Resource-Constrained {IoT} Networks",
  journal =      j-FUTURE-INTERNET,
  volume =       "17",
  number =       "10",
  pages =        "432",
  day =          "23",
  month =        sep,
  year =         "2025",
  CODEN =        "????",
  DOI =          "https://doi.org/10.3390/fi17100432",
  ISSN =         "1999-5903",
  bibdate =      "Tue Nov 4 11:31:15 MST 2025",
  bibsource =    "https://www.math.utah.edu/pub/tex/bib/future-internet.bib",
  URL =          "https://www.mdpi.com/1999-5903/17/10/432",
  abstract =     "The increasing deployment of internet of things(IoT)
                 systems across critical domains has broadened the
                 threat landscape, and being the catalyst for a variety
                 of security concerns, including very stealthy slow
                 denial of service (slow DoS) attacks. These exploit the
                 hypertext transfer protocol's (HTTP) application-layer
                 protocol to either close down service requests or
                 degrade responsiveness while closely mimicking
                 legitimate traffic. Current available datasets fail to
                 capture the more stealthy operational profiles of slow
                 DoS attacks or account for the presence of genuine slow
                 nodes (SN), which are devices experiencing high
                 latency. These can significantly degrade detection
                 accuracy since slow DoS attacks closely emulate SN.
                 This paper addresses these problems by synthesising a
                 realistic HTTP slow DoS dataset derived from a live IoT
                 network, that incorporates both stealth-tuned slow DoS
                 traffic and legitimate SN traffic, with the three main
                 slow DoS variants of slow GET, slow Read, and slow POST
                 being critically evaluated under these network
                 conditions. A limited packet capture (LPC) strategy is
                 adopted which focuses on just two metadata attributes,
                 namely packet length (lp) and packet inter-arrival time
                 ($ \Delta t $). Using a resource lightweight decision
                 tree classifier, the proposed model achieves over 96\%
                 accuracy while incurring minimal computational
                 overheads. Experimental results in a live IoT network
                 reveal the negative classification impact of including
                 SN traffic, thereby underscoring the importance of
                 modelling stealthy attacks and SN latency in any slow
                 DoS detection framework. Finally, a MPerf (Modelling
                 Performance) is presented which quantifies and balances
                 detection accuracy against processing costs to
                 facilitate scalable deployment of low-cost detection
                 models in resource-constrained IoT networks. This
                 represents a practical solution to improving IoT
                 resilience against stealthy slow DoS attacks whilst
                 pragmatically balancing the resource-constraints of IoT
                 nodes. By analysing the impact of SN on detection
                 performance, a robust reliable model has been developed
                 which can both measure and fine tune the
                 accuracy-efficiency nexus.",
  acknowledgement = ack-nhfb,
  journal-URL =  "https://www.mdpi.com/journal/futureinternet",
}